Ambient air pollution: A global assessment

of exposure and burden of disease

ContentList of tables 7

List of figures 7

List of annexes 9

Preface 11

Abbreviations 13

Summary 15

1. Introduction 19

2. Exposure to ambient air pollution 23

2.1. Exposure : ground measurements of PM10 and PM2.5 23 2.1.1. Methods 23 2.1.2. Results 25 2.1.3. Discussion 31

2.2 Exposure : modelled estimates of PM2.5 32 2.2.1. Methods 32 2.2.2. Results 32 2.2.3. Discussion 37

3. Burden of disease attributable to ambient air pollution 39

3.1. Methods 39 3.1.1. Source of datas 39 3.1.2. Estimation of the disease burden 39 3.1.3. Uncertainty analysis 40

3.2. Results 40

3.3. Discussion 47

4. Conclusion and way forward 49

References 51

Acknowledgment 55

Annex 1. Modelled population exposure to particulate matter (PM2.5), by country 57

Annex 2. Deaths, YLL’s and DALY’S Attributable to Ambient Air Pollution, by country 63

7

Table 1 : Ambient air pollution database : Proportion of settlements by population size

Table 2 : Total number of towns and cities in AAP database, 2016 version, by region

Table 3 : Number of cities included for the PM2.5 and PM10 comparison over a five-year period (mostly 2008-2013), by region

Table 4 : Trend for the five-year period (mostly 2008-2013) in PM2.5 or PM10 based on cities available in several versions of the database, by region

Table 5 : Deaths attributable to AAP in 2012, by disease, age and sex

Table 6 : Disability-adjusted life years (DALYs) attributable to AAP in 2012, by disease, age and sex

Table 7 : Population attributable fraction for disability-adjusted life years attributable to AAP in 2012, by disease, age, sex and region

Table A1 : Annual median concentration of particulate matter of an aerodynamic diameter of 2.5 μm or less (PM2.5) with lower and upper bound, population-weighted and modelled, by area and country

Table A2.1 : Deaths attributable to AAP in 2012 in both sex, by disease and country

Table A2.2 : Deaths attributable to AAP in 2012 in women, by disease and country

Table A2.3 : Deaths attributable to AAP in 2012 in men, by disease and country

Table A2.4 : Years of life lost (YLLs) attributable to AAP in 2012 in both sex, by disease and country

Table A2.5 : Years of life lost (YLLs) attributable to AAP in 2012 in women, by disease and country

Table A2.6 : Years of life lost (YLLs) attributable to AAP in 2012 in men, by disease and country

Table A2.7 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in both sex, by disease and country

Table A2.8 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in women, by disease and country

Table A2.9 : Disability-adjusted life years (DALY) attributable to AAP in 2012 in men, by disease and country

Figure 1 : Number of towns and cities with accessible PM10 and PM2.5 data in 2016 per urban population

Figure 2 : Location of the monitoring stations and PM2.5 concentration in nearly 3 000 human settlements, 2008-2015

List of tables

List of figures

9

Figure 3 : PM10 levels by region and city size, for available cities and towns latest year in the period 2008-2015

Figure 4 : PM10 levels for selected cities by region, for the last available year in the period 2011-2015

Figure 5 : PM10 levels for available mega-cities of more than 14 million habitants for the last available year in the period 2011-2015

Figure 6 : Annual mean particulate matter concentration of the assessed towns and cities compared to the WHO Air Quality Guidelines a

Figure 7 : Percentage of cities with increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region

Figure 8 : Percentage of city population experiencing increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region

Figure 9 : Global map of modelled annual median concentration of PM2.5, in μg / m3

Figure 10 : Annual median exposure to ambient (outdoor) PM2.5 in μg / m3, by region - urban and rural population, 2014

Figure 11 : Annual median exposure to ambient (outdoor) PM2.5 in μg / m3, by region - urban population only, 2014

Figure 12 : Median PM2.5 concentration, by geographic region – urban and rural areas combined, 2014

Figure 13 : Modelled annual median particulate matter concentration compared to the WHO Air Quality Guidelines (AQG)

Figure 14 : Deaths attributable to AAP in 2012, by disease and region

Figure 15 : Age-standardized deaths per capita attributable to AAP in 2012, by disease and region

Figure 16 : Deaths attributable to AAP in 2012, by country

Figure 17 : DALYs attributable to AAP in 2012, by country

Figure 18 : Age-standardized deaths per 100 000 capita attributable to AAP in 2012, by country

Figure 19 : Age-standardized DALYs per 100 000 capita attributable to AAP in 2012, by country

Figure 20 : Deaths attributable to AAP in 2012, by disease

List of annexesAnnex 1 : Modelled population exposure to particulate matter of PM2.5, by country

Annex 2 : Deaths, YLLs and DALYs attributable to ambient air pollution, by country

11

This report presents a summary of methods and results of the latest World Health Organi-zation (WHO) global assessment of ambient air pollution exposure and the resulting burden of disease.

Air pollution has become a growing concern in the past few years, with an increasing number of acute air pollution episodes in many cities worldwide. As a result, data on air quality is becoming increasingly available and the science underlying the related health impacts is also evolving rapidly.

To date, air pollution – both ambient (outdoor) and household (indoor) – is the biggest envi-ronmental risk to health, carrying responsibility for about one in every nine deaths annually. Ambient (outdoor) air pollution alone kills around 3 million people each year, mainly from noncommunicable diseases. Only one person in ten lives in a city that complies with the WHO Air quality guidelines. Air pollution continues to rise at an alarming rate, and affects econo-mies and people’s quality of life ; it is a public health emergency.

Interventions and policies for tackling air pollu-tion issues exist and have been proven to be effective. The implementation of WHO resolution WHA68.8, which maps out a road map for en-hanced global responses to the adverse effects of air pollution, provides an essential framework for decision-makers to choose and implement the most efficient policies.

Air pollution has also been identified as a global health priority in the sustainable development agenda. WHO has responsibility for stewarding three air pollution-related indicators for monito-ring progress against the Sustainable Develop-ment Goals (SDGs) : in health (Goal 3), in cities (Goal 11) and in energy (Goal 7).

Air pollution affects practically all countries in the world and all parts of society.

The role of the health sector is crucial, and there is a need to engage with other sectors to maxi-mize the co-benefits of health, climate, environ-ment, social and development. Saving people’s lives is the overarching aim to implement policies aiming at tackling air pollution in the health, trans-port, energy, and urban development sectors.

Dr Maria Neira Director of Public Health, Environmental and Social Determinants of Health

World Health Organization

Preface

13

AbbreviationsAAP ambient air pollution

AFR Africa Region

ALRI acute lower respiratory disease

AMR Americas Region

AQG Air quality guidelines

BoD burden of disease

COPD chronic obstructive pulmonary disease

DALY disability-adjusted life year

DIMAQ data integration model for air quality

EMR Eastern Mediterranean Region

EUR European Region

GBD global burden of disease

HAP household air pollution

HIC high-income countries

IER integrated exposure risk

IHD ischeamic heart disease

LMIC low-and middle-income countries

PAF population attributable fraction

PM2.5 particulate matter of diameter of less than 2.5 μm in μg / m3

PM10 particulate matter of diameter of less than 10 μm in μg / m3

RR relative risk

SDGs Sustainable Development Goals

SEAR South East Asia Region

UN United Nations

YLD year lived with disability

YLL year of life lost

WHO World Health Organization

WPR Western Pacific Region

15

Air pollution represents the biggest environ-mental risk to health. In 2012, one out of every nine deaths was the result of air pollution-rela-ted conditions. Of those deaths, around 3 mil-lion are attributable solely to ambient (outdoor) air pollution. Air pollution affects all regions, settings, socioeconomic groups, and age groups. While all people living in a given area breathe from the same air, there are never-theless important geographical differences in exposure to air pollution. Citizens in Africa, Asia or the Middle East breathe much higher levels of air pollutants that those in living other parts of the world. Some places have air pollution levels that are several times higher than those consi-dered safe by the World Health Organization (WHO) Air quality guidelines.

Air pollution is used as a marker of sustai-nable development, as sources of air pollu-tion also produce climate-modifying pollutants (e.g. CO2 or black carbon). Policies to address air pollution also generate a range of bene-fits to human health, not only through air quality improvements but also other health benefits, such as injury prevention or enabling physical activity.

Consequently, concerns about air pollution are reflected in the Sustainable Development Goals (SDGs) : Air pollution levels in cities is cited as an indicator for urban sustainable development (SDG 11) ; access to clean energy – particular-ly clean household fuels and technologies – is highlighted as an indicator for sustainable en-ergy (SDG 7) ; and mortality due to air pollution (ambient and household) is used an indicator for the health SDG goal (SDG 3). Reliable estimates of exposure to and impacts from air pollutants are key to better inform policy-makers, as well as development partners. These figures are neces-sary to track progress in air quality improvements and to help evaluate the effectiveness of policies aiming at reducing air pollution, as well as as-sessment of how much they are contributing to protect health.

In 2015, to respond to this major global public health threat, the 194 WHO Member States adop-ted the first World Health Assembly resolution to “ address the adverse health effects of air pollu-tion ”. The following year, Member States agreed on a road map for “ an enhanced global response to the adverse health effects of air pollution ”.

Among the main elements of this road map are the monitoring and reporting of air pollution, and enhanced systems, structures and processes for monitoring and reporting health trends asso-ciated with air pollution and its sources.

The current report presents methods and data for two of the SDG indicators reported by WHO :

· SDG Indicator 11.6.2 : Annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted) ; and

· SDG Indicator 3.9.1 : Mortality rate attribu-ted to household and ambient air pollution.

This report presents the updated results of morta-lity and morbidity attributed to ambient air pollu-tion (also known as ‘ burden of disease due to air pollution ’). It includes information on the sources of data on air pollution available to the WHO, on the methodology used to estimate human exposure to air pollution and related burden of disease, as well as the actual estimates of human exposure to particulate matter of a diameter less than 2.5 micrometres (PM2.5) for countries and for the globe ; and the related national burden of disease attributable to long-term exposure to ambient (outdoor) air pollution for the year 2012.

The global exposure assessment to air pollu-tion consists of modelled data of population-weighted annual mean PM2.5 concentrations. Data are modelled through combining remote satellite sensing data with ground measure-ments from the 2016 WHO ambient (outdoor) air quality database, which serves for calibration of the satellite data.

Summary

17

This database compiles information on PM2.5 and PM10

1 from measurements for about 3000 cities and towns worldwide. The modelled estimates indicate that in 2014 only about one in ten people breathe clean air, as defined by the WHO Air quality guidelines.

The burden of disease attributed to ambient air pollution was estimated using methodology developed for the Comparative Risk Assessment study. This methodology is based on combi-ning estimates of exposure to air pollution and its distribution in the population, with results from epidemiological studies that indicate the additio-nal disease burden from different levels of expo-sure to air pollution, after adjusting for other risk factors (e.g. tobacco smoke).

The results are refered to by epidemiologists as exposure-risk estimates at each level of expo-sure. Health outcomes, for which there is enough epidemiological evidence to be included in the analysis, comprise acute lower respiratory, chronic obstructive pulmonary disease, stroke, ischeamic heart disease and lung cancer. Many other diseases have been associated with air pollution, but are not included in this assess-ment because the evidence was not considered sufficiently robust.

The actual impact of air pollution on health pre-sented here is a conservative figure, as it does not include the separate impacts of health from other air pollutants such as nitrogen oxides (NOx) or ozone (O3), and excludes health impacts where evidence is still limited (e.g. pre-term birth or low birth weight).

Through this combined approach, the current report summarizes three sets of data and the interrelationship between them : 1) The compi-lation of the PM2.5 and PM10 measurements data in the 2016 WHO ambient (outdoor) air quality database ; 2) the modelled estimates of PM2.5 ; and 3) the associated burden of disease.

1 Particulate matter of a diameter less than 25 and 10 micrometres respectively.

19

This document summarizes the methods and the results of the latest WHO global assessment of air pollution exposure and related burden of disease.

Exposure to air pollutants can affect human health in various ways, leading to increased mor-tality and morbidity (1). Epidemiological evidence on the health effects of air pollution is growing and evolving quickly. Today, air pollution is the largest environmental risk factor (2).

Reliable estimates of exposure to air pollu-tants and related impacts on health are key to better inform policy-makers, as well as other health and development partners. Such infor-mation is essential to implementing, monitoring and evaluating policies that help to tackle air pollution while also protecting health.

The 194 WHO Member States recently adop-ted a resolution to respond to the adverse health effects of air pollution (3), as well as a road map for an enhanced global response (4). The road map outlines goals and approaches for monitoring and reporting of air pollution, as well as enhancing systems, structures and processes necessary to support monitoring and reporting on health trends associated with air pollution and its sources.

Air pollution is a clear marker for sustainable deve-lopment, as sources of air pollution also produce climate pollutants (like CO2 or black carbon).

Policies to address air pollution generate a num-ber of benefits to human health, not only through air quality improvements but also other health benefits, such as injury prevention or enabling physical activity. Adressing air pollution there-fore features highly in the global agenda.

In September 2015, the United Nations (UN) General Assembly adopted Transforming our world : The 2030 Agenda for sustainable deve-lopment, which paves the way for a renewed global commitment to combat the world’s most persistent development issues over the next 15

years (5). A framework of indicators for the 17 SDGs and 169 SDG-related targets has been developed, and includes three air pollution-rela-ted indicators, which fall under WHO’s reporting responsibility :

· SDG Indicator 3.9.1 : Mortality rate attri-buted to household and ambient air pollution for the health goal (SDG 3).

· SDG Indicator 11.6.2 : Annual mean levels of fine particulate matter (PM2.5) in cities (population-weighted) for the urban sus-tainable development goal (SDG 11).

· SDG Indicator 7.1.2 : Proportion of popu-lation with primary reliance on clean fuels and technologies for the sustainable energy goal (SDG 3).

Reporting for Indicators 3.9.1 and 11.6.2 are based on the methods and results presented in the current document, while the methods for estimating SDG Indicator 7.1.2. are presented elsewhere (6).

While a number of air pollutants are associa-ted with significant excess mortality or morbi-dity, including NOx, ozone, carbon monoxide and sulfur dioxides in particular, PM2.5 is the air pollutant that has been most closely studied and is most commonly used as proxy indicator of exposure to air pollution more generally (1).

Particulate matter consists of a complex mixture of solid and liquid particles of organic and inor-ganic substances suspended in the air. The ma-jor components of PM are sulphates, nitrates, ammonia, sodium chloride, black carbon, mine-ral dust and water. The most health-damaging particles are those with a diameter of 10 μm or less, which can penetrate and lodge deep in-side the lungs. Both short- and long-term expo-sure to air pollutants have been associated with health impacts.

1. Introduction

21

Small particle pollution has health impacts even at very low concentrations – indeed no threshold has been identified below which no damage to health is observed. Therefore, the WHO Air quality guidelines (AQGs) recommend aiming for, and achieving, the lowest concentrations of PM possible (1). The guideline values are :

PM2.5 PM10 10 µg / m3 annual mean 20 µ / m3 annual mean 25 µg / m3 24-hour mean 50 µg / m3 24-hour mean

Reflecting the rising number of air pollution episodes in cities worldwide – and the resulting increased awareness about its impacts on health - PM2.5 is increasingly measured and monitored by national air quality monitoring networks. WHO has been compiling annual mean concentrations for PM2.5 and PM10 in cities since 2011 (7,8).

A summary of a recent update of the WHO ambient (outdoor) air quality database (9) containing average annual estimates for PM2.5 exposure globally, by region and for 3 000 spe-cific human settlements is presented as part of this report.

The present work on global exposure modelling further develops recent innovations in global exposure estimates for PM2.5 (10,11), as used to model global burden of disease attributable to ambient air pollution (2, 12–14).

It was also presented and reviewed at the Global Platform on Air Quality and Health, ini-tiatied by WHO and other partners in 2014 (15).

Academic researchers, scientists and interna-tional organizations have combined efforts to harmonize in developing comprehensive and reliable models of population exposure to PM2.5, which can be used for health impact estimation.

Coverage of the entire exposure range for long-term exposure to PM2.5 has been achieved through the development of the integrated ex-posure risk (IER) functions (16) that have been developed for the Global Burden of Disease Study (17).

This allows for the integration of available rela-tive risks information from studies of ambient air pollution, household air pollution, second-hand smoke and active smoking. The IERs have been used to derive estimates for both household- and ambient air pollution-attributable burden of disease for the GBD Project (12, 14, 18) and by the WHO (2, 6).

They currently cover cause-specific mortality such as acute lower respiratory in children under five years of age, and chronic obstructive pulmo-nary disease (COPD), ischeaemic heart disease (IHD), stroke and lung cancers in adults.

Other health outcomes have been associated with long-term exposure to particulate matter, such as adverse birth outcomes, childhood respiratory disease, diabetes, atherosclerosis, and neurodevelopment and cognitive function, but are not considered here (19).

The current report presents the latest national mortality and morbidity estimates attributable to ambient air pollution.

23

2.1.1. MethodsDescription of methods

The database compiles ground measurements of annual mean concentrations of particulate matter of a diameter of less than 10 μm (PM10) or 2.5 μm (PM2.5) and aims to compile an ave-rage for each city / town. Years of measurements range from 2010 to 2015, unless the latest avai-lable data precede these times, in which case the most recent was used.

Scope of data

The database covers 3 000 human settlements ranging in size from a few hundred to more than 10 million inhabitants. Most of these are urban areas of 20 000 inhabitants or more – hence reference to an “ urban air quality data base ”. However, about 25 % of settlements in the data-base are smaller areas of up to 20 000 residents, and a limited proportion (mostly in Europe) are settlements of only a few hundred to a few thou-sand inhabitants - although these may also be located in proximity to larger urban agglomera-tions (see Table 1).

Table 1. Ambient air pollution database : Proportion of settlements by population size

Percentages of observations

Settlement size

1 % 05 % 1 24010 % 4 17325 % 20 00041 % 50 00050 % 80 75675 % 314 71990 % 1 150 15395 % 2 313 32899 % 8 741 365Mean settlement size 543 664Number of settlements 2977

Data sources

Primary sources of data include official repor-ting from countries to WHO, official national /sub-national reports and national/sub-national web sites containing measurements of PM10 or PM2.5. Furthermore, measurements reported by the following regional networks were used : Clean Air Asia for Asia (20), and the Air quality e-reporting database (21) from the European Environment Agency for Europe. In the absence of the above-mentioned data, data from UN agen-cies, development agencies, articles from peer reviewed journals and ground measurements compiled in the framework of the Global Burden of Disease Project (17) were used. 2

The data was compiled between Septem-ber–November 2015 from the above-mentio-ned sources / partners, or from web searches when not availbable. The web search strategy included the following approaches :

1. Screening of the web sites of respective minis-tries of environment, health, and statistics offices.

2. Web searches with the terms « air quality », « air pollution », « suspended particles », « moni-toring », « PM10 », « PM2.5 ».

Language variations used included English, French, Spanish, Portuguese, Italian, and German.

Type of data used

The database incorporated annual mean concentrations of particulate matter (PM10 or PM2.5) based on daily measurements, or other data that could be aggregated into annual mean values. In the absence of annual means, mea-surements covering a more limited period of the year were exceptionally used and extrapolated.

2 For the full list of references, please refer to the online version of the WHO database (9).

2. Exposure to ambient air pollution2.1. Exposure : ground measurements of PM10 and PM2.5

24

In order to derive air quality that is largely repre-sentative of human exposure in urban contexts, mainly data from urban background readings, residential areas, and commercial (or mixed) area measurements were used. Air quality sta-tions characterized as covering particular ‘ hot spots ’ or exclusively industrial areas were not included, unless they were contained in repor-ted city means and could not be disaggregated.

This selection is in accordance with the aim of capturing representative values for average human exposure. In contrast, measurements from hot spots and industrial areas are often captured for the purpose of identifying the highest exposure areas, and were deemed to be less representative of mean exposures for most of the urban population. Hot spots were either designated as such by the original reports, or were qualified as such due to their exceptional nature (e.g. exceptionally busy roads etc.). Omitting these, may, however, have led to an underestimation of the mean air pollu-tion levels of a given city.

Where the data from various sources were available, only the latest data and most reliable sources were used. Only data measured since 2008 were included in the database.

It was not always possible to retrieve or use all publicly available data of interest. Reasons included language barriers, or incomplete infor-mation on data or data quality (e.g. missing year of reference). Data were used as presented in original sources. The indicated numbers of monitors do not necessarily correspond to the total number of existing or operational stations in the cities, but to the numbers of stations used for deriving the indicated city data.

Data processing and reporting

Where available, urban means reported by the original sources are included in the data-base. Where no urban means were available, the eligible city data were averaged using appropriate denominators.

Population data - used for weighting and for estimating the share of urban population co-vered - were either based on : UN population statistics when available for all human settle-ments covered (22), or census data from national statistical offices (23).

For completeness, cities with only PM10 (or resp. PM2.5) reported, PM2.5 (or PM10) concentration was calculated from PM10 (resp. PM2.5) using national conversion factors (PM2.5 / PM10 ratio) either provided by the country or estimated as population-weighted averages of urban-speci-fic conversion factors for the country. Urban-specific conversion factors were estimated as the mean ratio of PM2.5 to PM10 of stations for the same year. If national conversion factors were not available, regional ones were used, which were obtained by averaging country-specific conversion factors.

As exposure to PM2.5 serves as indicator for burden of disease calculation, PM2.5 data were converted from PM10 in the absence of their measurement because they were used to cali-brate the model described below.

As the conversion factor PM2.5 / PM10 may vary according to location (generally between 0.4 and 0.8), the converted PM10 value for individual sett-lements may deviate from the actual value, and should only be considered as approximations.

The temporal coverage represents the number of days per year covered by measurements, or any alternative qualification (as provided in the original sources). If data from several moni-toring stations in one city or town were available, their average temporal coverage was used for the overall average. Information on temporal coverage was not always available ; however reporting agencies often respect a specific reporting threshold for the number of days cove-red before reporting on a given measurement va-lue, or using it for estimating the city annual mean.

25

2.1.2. ResultsData availability

The 2016 version of the WHO ambient (outdoor) air quality database consists mainly of urban air quality data - annual means for PM10 and / or PM2.5 - covering about 3 000 human settlements in 103 countries, for the years 2008-2015 (9). The regional distribution and the number of settlements, and correspon-ding accessible data are described in Table 2 and Figure 1, respectively.

Table 2 : Total number of towns and cities in AAP database, 2016 version, by region

Region

Number of towns / cities

Number of countries with data

Total number of countries in region

Africa (Sub-Saharan) (LMIC) 39 10 47Americas (LMIC) 102 13 24

Americas (HIC) 524 6 11Eastern Mediterranean (LMIC) 53 8 15Eastern Mediterranean (HIC) 31 6 6Europe (LMIC) 165 9 19

Europe (HIC) 1 549 33 34South-East Asia (LMIC) 175 9 11Western Pacific (LMIC) 225 4 21Western Pacific (HIC) 109 5 6Global 2 972 103 194

AAP : Ambient air pollution database ; LMIC : Low-and middle-income countries ; HIC : high-income countries.

Figure 1 : Number of towns and cities with accessible PM10 and PM2.5 data in 2016 per urban population.

PM10 / 2.5 : Fine particulate matter of 10 / 2.5 microns or less ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr: Western Pacific; LMIC : low- and middle-income countries ; HIC : high-income countries.

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Nr of towns and cities per 1 million urban inhabitants

26

PM2.5 measurements can be directly linked to estimates of health risks, and are therefore of particular interest. In high-income countries, PM2.5 measurements are conducted widely. In low- and middle-income countries (LMICs), PM2.5 measures are not readily available in many countries but there have been large improve-ments since in the past three years.

Annual mean PM2.5 measurements were avai-lable for 339 cities, or almost five times more than in the 2014 version of the database.

Annual mean PM10 measurements could be accessed in as many as 586 cities in LMICs.

In high-income countries (HIC), 1 241 cities and towns with PM2.5 measures could be accessed, compared to 1639 cities and towns with PM10 measurements.

The 3 000 cities and towns currently covered by the WHO database represent about 1.6 billion people, or 43 % of the global urban population.

Ground measurements of annual mean concen-tration of PM2.5 for the 3000 towns and cities is shown in Figure 2.

Figure 2 : Location of the monitoring stations and PM2.5 concentration in nearly 3 000 human settlements, 2008-2015

PM2.5 : Fine particulate matter of 2.5 microns or less.

27

Data summary

An overview of PM10 levels for the WHO regions and selected cities is presented in Figures 3, 4 and 5.

Figure 3 : PM10 levels by region and city size, for available cities and towns latest year in the period 2008–2015

PM10 : Particulate matter of 10 microns or less ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. PM10 values for the world are regional urban population-weighted.

Figure 4 : PM10 levels for selected 3 cities by region, for the last available year in the period 2011-2015

PM10 : Particulate matter of 10 microns or less; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries.

3 Selection criteria : For year of measurement (2011 or more recent), the largest city or capital for each country within a region (or two cities for one country if only two countries available in the region. City size ranges from 140 000 to 26 million habitants.

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28

Figure 5 : PM10 levels for available mega-cities of more than 14 million habitants for the last available year in the period 2011-2015

PM10 : Particulate matter of 10 microns or less.

Compliance with Air Quality Guidelines

Figure 6 shows the regional percentages of the assessed towns and cities with PM measurements expe-riencing PM10 or PM2.5 air pollution levels that meet or exceed the WHO Air Quality Guidelines (AQG) (i.e. annual mean values of 20 µg / m3 (for PM10) and 10 µg / m3 (for PM2.5)).4 Globally, according to the currently available data, only 16 % of the assessed population is exposed to PM10or PM2.5 annual mean levels complying with AQG levels. This increases to 27 % for the interim target 3 (i.e. IT-3 : 30 µg / m3 for PM10 and 15 µg / m3 for PM2.5) of the AQG, 46 % for interim target 2 (i.e. IT-2 : 50 µg / m3 for PM10 and 25 µg / m3 for PM2.5), and 56 % for interim target 1 (IT-1 : 70 µg / m3 for PM10 and 35 µg / m3 for PM2.5).

Figure 6 : Annual mean particulate matter concentration of the assessed towns and cities, compared to the WHO Air Quality Guidelinesa

Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific; LMIC: low- and middle-income countries; HIC : high-income countries ; AQG : WHO Air Quality Guidelines. a Annual mean PM10 : 20 µg / m3 ; Annual mean PM2.5 : 10 µg / m3. 4 For town and cities with both PM10 and PM2.5 values, PM2.5 were used.

0

50

100

150

200

250

IstanbulKolkata

Buenos AiresDhaka

CairoBeijing

Mexico cityMumbai

Sao PauloShanghai

Delhi

PM10 (μg/m3)

0%

20%

40%

60%

80%

100%

1.2

Emr (HIC)

WPr (LMIC)

SearEmr (LMIC)

AfrEur (LMIC)

Amr (LMIC)

Eur (HIC)

Wpr (HIC)

Amr (HIC)

% of cities assessedbelow AQG

exceed AQG

29

Table 3 : Number of cities included for the PM2.5 and PM10 comparison over a five-year period (mostly 2008-2013), by regionRegion Number of town and cities Number of countriesAfrica (Sub-Saharan) 1 2 2America (LMIC) 13 7America (HIC) 343 6Eastern Mediterranean (LMIC) 16 6Eastern Mediterranean (HIC) 6 2Europe (LMIC) 32 5Europe (HIC) 277 30South-East Asia 53 5Western Pacific (LMIC) 33 2Western Pacific (HIC) 21 3Global 796 68

LMIC : Low- and middle-income countries ; HIC : High-income countries. 1 Regions with less than five cities were not included in the analysis, due to poor representation.

Figure 7 shows the percentage of towns and cities with decreasing levels of annual mean PM2.5 or PM10 (in green), increasing levels (in red), and levels with changes of ≤10 % over a five-year period (in blue), by region.

The variation in population living in cities with increasing or decreasing population levels is represented in Figure 8.

Table 4 : Trend for the five-year period (mostly 2008-2013) in PM2.5 or PM10 based on cities available in several versions of the database, by region 1

Region Trend over the mean period 2008-2013 2

Africa (Sub-Saharan) NA

America (LMIC) America (HIC)

Eastern Mediterranean (LMIC)Eastern Mediterranean (HIC)Europe (LMIC)Europe (HIC)

South-East Asia Western Pacific (LMIC)Western Pacific (HIC)Global 3

1 Criteria for inclusion : cities with measured PM2.5 or PM10 values in the three database versions covering a period of three years or more, or in two versions and covering a period of four years or more. 2 : No more than 5 % change over the five-year period ; : More than 5 % decrease over the five-year period ; : More than 5 % increase over the five-year period.3 Based on weighting by regional urban population.LMIC : Low- and middle-income countries ; HIC : high-income countries ; NA : not available. Results are based on 795 cities and are to be interpreted with caution, as : a) cities included might not ensure representativeness ; a) yearly variations due for example to climatic changes can be important ; and c) a five-year comparison does not necessarily represent trends, in particular when changes are limited.

30

Figure 7 : Percentage of cities 1 with increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008–2013), by region

Amr : Americas ; Emr : Eastern Mediterranean; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries. 1 The number of cities is indicated in bracket. * The world figure is regional population-weighted.

Figure 8 : Percentage of city population experiencing increasing and decreasing PM2.5 or PM10 annual means over a five-year period (mostly 2008-2013), by region

Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries.

0%

20%

40%

60%

80%

100%

1.2

World* (792)

WPr (LMIC) (32)

Emr (HIC) (6)

Sear (53)

Emr (LMIC) (15)

Amr (HIC) (343)

Wpr (HIC) (21)

Eur (HIC)

(277)

Amr (LMIC) (13)

Eur(LMIC)(30)

% cities decreasing

Limited change (≤10% over 5 years)

% cities increasing

0%

20%

40%

60%

80%

100%

1.2

WorldEmr (HIC)

WPr (LMIC)

SearEmr (LMIC)

Eur (HIC)

Amr (LMIC)

Wpr (HIC)

Amr (HIC)

Eur (LMIC)

with decreasing air pollution

Limited change (≤10% over 5 years) in air pollution

with increasing air pollution

31

The WHO urban ambient air quality database presents data on annual mean concentration of particulate matter (PM) for almost 3 000 human settlements, mostly cities, in 103 countries and is the most comprehensive database of its kind to date. The number of cities and towns repor-ting on PM measurements has nearly doubled since the previous version of the database was published in 2014 (1 600 cities) (8) and nearly tripled since the first 2011 version (1 100 cities) (7), which indicates an increased awareness of the risks posed by air pollution. In the past two years, the number of ground measurements available in high-income countries has doubled, while there has been a 50 % increase in low-and middle-income countries.

Monitoring the air quality is the first, but key, step to be taken by public authorities, both at the national and city levels, to tackle the mul-tisectoral challenge of addressing air pollution. However, there are still huge monitoring and reporting gaps between high-income countries and low- and middle-income counterparts. Most air quality data still comes from Europe and the Americas, with regions such as Africa, South East Asia, and Eastern Mediterranean lagging behind.

The data presented in the latest database reflects a number of important limitations. The ground measurements are of limited compara-bility because of various reasons : a) Differing locations of measurement stations ; b) varying measurement methods ; c) different temporal coverage of certain measurements (i.e. if only part of the year was covered, the measurement may significantly deviate from the annual mean due to seasonal variability) ; d) possible inclu-sion of data that should not have been eligible for this database due to insufficient information to ensure compliance ; e) differences in sizes of urban areas covered (i.e. for certain countries, only measurements for larger cities were found, whereas for others also cities with just a few thou-sand inhabitants were available) ; and f) varying quality of measurements.

In addition, some existing data may have been omitted, either because it could not yet be accessed due to language issues or limited ac-cessibility. Finally, the city means presented in the database may differ from the ones calculated by the cities or municipalities themselves because they are averaged from multiple station data.

The comparison of air pollution levels for a given set of cities over the five-year period 2008-2013 shows a global increase of 8% in annual mean concentrations of PM2.5. High-income regions of the Americas, Europe and Western Pacific demonstrate decreasing air pollution, while the other regions have increasing levels.

However, such a comparison of air pollution levels has a number of limitations. First of all, when PM2.5 measurements were not available, PM10 values (converted into PM2.5) were used for the compari-son, which may have influenced the results.

Second, the period of comparison is relatively short. Yearly variations may for example be in-fluenced by weather patterns and data within a five-year period may not be sufficient to reflect a longer-term trend. A longer time period of com-parison would be required to confirm any trends.

Third, although sampling locations are reaso-nably stable over time, they may have changed within the period of comparison, and variations in annual mean PM levels for a given city may reflect different sampling locations rather than a genuine trend. As the data collected is used for calibrating the model that derives global PM2.5 estimates, data quality is crucial, as well as loca-tion details and the type of monitoring stations : information that is also used in the modeling exer-cise. Efforts and investments should be made to encourage cities and countries to monitor air quality closely, using standard, good quality and comparable methods and instruments, as well as making this information widely available.

To date, only particulate matter concentrations have been compiled in the database. Additional pollutants – such as nitreous oxide (NO2), ozone (O3) or others – might be added to the database in the future.

2.1.3. Discussion

32

Assessment of the global effects of air pollution requires a comprehensive set of estimates of exposure for all populations. Ground monito-ring networks have provided the primary source of this information but, although coverage has increased, there remain regions in which there is no or very little monitoring.

Ground measurement data therefore need to be supplemented with information from other sources, such as estimates from satellite retrie-vals of aerosol optical depth and chemical transport models. The recently developed Data Integration Model for Air Quality (DIMAQ) incor-porates data from multiple sources in order to provide estimates of exposures to PM2.5 at high spatial resolution (0.1o × 0.1o) globally.

Sources of data include : Ground measurements from 6 003 monitoring locations around the world (9,10), satellite remote sensing ; population estimates ; topography ; and information on local monitoring networks and measures of specific contributors of air pollution from chemical trans-port models. The DIMAQ model calibrates data from these sources with ground measurements. The relationships between the various sources of data may be complex and will vary between regions due to differences in the composition of PM2.5, and other factors.

DIMAQ has a hierarchical structure within which calibration equations are produced for indivi-dual countries using, as a priority, data from that country where available. Where data within a country is insufficient to produce accurate estimates, it is supplemented with regional information. When calibration equations have been established and tested, the model is used to estimate exposures, together with associa-ted measures of uncertainty across the globe. These high-resolution estimates can be used to produce air quality profiles for individual countries, regions and globally.

A full description of the model development and evaluation is available separately (24).

Global exposure to PM2.5 has been modelled for the year 2014 in order to provide a com-prehensive global coverage of estimates of air quality. The key parameter is the annual median concentration of PM2.5, which is highly relevant for estimating health impacts. Modelled exposure to ambient PM2.5 levels provides more comprehensive information for countries than measured data, which only provide data for a selection of towns and cities. A comprehensive set of estimated exposures such as this will be required, when estimating the health impacts of ambient air pollution for a given country.

Estimates of exposure are required for all areas, including those that may not be covered by ground monitoring networks. Estimates of air quality, expressed in terms of median concen-trations of PM2.5 are now available for all regions of the world, including areas in which PM2.5 monitoring is not available (Figure 9) . It can be viewed on an interactive map at www.who.int/phe/health_topics/outdoorair/databases/en. Estimates of exposure, by country, are pre-sented in Table A1 of Annex 1.

2.2. Exposure : modelled estimates of PM2.5

2.2.1. Methods 2.2.2. Results

33

In the majority of regions of the world, annual median concentrations of air pollution are higher than the WHO guideline levels of 10 μg / m3 (Figures 10 and 11). Exposures are particularly high in the Eastern Mediterranean, South-East Asian and Western Pacific Regions. Air pollution does not exclusively originate from human activity, and can be greatly influenced by dust storms, for example, particularly in areas close to deserts. This is partially illustra-ted in Figure 12, where modelled annual median PM2.5 concentration by area (rural / urban) is pre-sented and where rural areas in the African and Eastern Mediterranean Regions show greater concentrations than urban ones.

Based on the modelled data, 92 % of the world population are exposed to PM2.5 air pollution concentrations tha are above the annual mean WHO AQG levels of 10 μg / m3 (Figure 13). With the exception of the region of the Americas, all regions – both HIC and LMIC – have less than 20 % of the population living in places in com-pliance with the WHO AQG.

Figure 9 : Global map of modelled annual median concentration of PM2.5, in µg / m3

PM2.5 : Fine particulate matter of 2.5 microns or less.

34

Figure 10 : Annual median exposure to ambient (outdoor) mean annual concentration of PM2.5 in µg / m3, by region - urban and rural population population, 2014

Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur: Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC: low- and middle-income countries ; HIC : high-income countries ; PM2.5 : particulate matter with an aerodynamic diameter of 2.5 µm or less. WHO AQG : WHO Air Quality Guidelines.

Figure 11 : Annual median exposure to ambient (outdoor) PM2.5 in µg / m3, by region - urban population only, 2014

Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. PM2.5 : particulate matter with an aerodynamic diameter of 2.5 µPM2.5 : pa. WHO AQG : WHO Air Quality Guidelines.

WHO AQG for PM2.5: 10 μg/m3

PM2.5 (μg/m3)

37

18

9

104

59

15

28

59

16

54

43

0

20

40

60

80

100

120

WorldWPr (LMIC)

WPr (HIC)

SearEUR (LMIC)

Eur (HIC)

Emr (LMIC)

Emr (HIC)

Amr (LMIC)

Amr (HIC)

Afr

WHO AQG for PM2.5: 10 μg/m3

PM2.5 (μg/m3)

32

9

17

91

55

14

25

55

49

39

15

0

20

40

60

80

100

WorldWPr (LMIC)

Wpr (HIC)

SearEur (LMIC)

Eur (HIC)

Emr (LMIC)

Emr (HIC)

Amr (LMIC)

Amr (HIC)

Afr

35

Figure 12 : Median PM2.5 concentration, by geographic region - urban and rural areas combined, 2014

Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia, Wpr : Western Pacific ; LMIC : low- and middle-income countries ; HIC : high-income countries. Note : This graph represents the median PM2.5 of regional urban and rural areas. These estimates are not in relation to the number of people exposed to those levels.

Figure 13 : Modelled annual median particulate matter concentration compared to the WHO Air Quality Guidelines (AQG) a

Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : high-income countries ; AQG : WHO Air Quality Guidelines.a Annual mean PM10 : 20 µg / m3 ; Annual mean PM2.5 : 10 µg / m3.

0

20

40

60

80

100

WPr (LMIC).

Wpr (HIC)

SearEur (LMIC)

Eur (HIC)

Eur (LMIC)

Emr (HIC)

Amr (LMIC)

Amr (HIC)

Afr

PM2.5 (μg/m3)

2937

86

15 14

8992

5249

13

7

25

19

46

35

128

49

30

rural

urban

0%

20%

40%

60%

80%

100%

1.2

WorldEmr (LMIC)

Emr (HIC)

WPr (LMIC)

Afr (LMIC)

Eur (LMIC)

SearWpr (HIC)

Eur (HIC)

Amr (LMIC)

Amr (HIC)

below AQG

exceed AQG

76

20 1816

2 1.0 0.7 0.5 0.0 0.0 8%

37

Global population exposure to PM2.5 matter has been modelled for the year 2014 to provide a comprehensive global coverage of estimates of air quality. Annual mean concentration of PM2.5 is highly relevant for estimating health impacts and is used as an exposure indicator for calculating the burden of disease attributable to ambient air pollution.

The model used for this study currently has several limitations, however. The first limitation relates to population data. While the quality of estimates of population data and population density, used to calculate the average esti-mates of PM2.5 for urban and rural areas is gene-rally good for high-income countries, it can be relatively poor for some low- and middle-income areas. Furthermore, the definition of urban / rural may greatly vary by country.

The second limitation relates to resolution : The grid size is 0.1° x 0.1° (11 x 11 km close to the equator, but smaller towards the poles). This resolution may cause limitations when considering local situations. However, finer resolutions are planned for future studies. Regarding lack of monitoring data in countries, the model produces a calibration equation for each country using country level data as a prio-rity, with regional data being used to supple-ment local information for countries with sparse, or no, ground monitoring data. It is acknowle-dged that the estimates for data-poor countries may be relatively imprecise and that this may re-sult in apparent changes in levels of air pollution at borders with data-poor countries. In order to achiever reduced uncertainty in modelled data it is important that countries continue and / or improve ground measurement programmes.

Finally, where measurements of PM2.5 are not avai-lable, PM10 measurements are used after conver-sion to PM2.5 using either city, country or regional conversion factors. Conversion factors typically range between 0.4 - 0.8 depending on location. Localised conversion factors are likely to be more accurate, but the ability to calculate them relies on availability of localised data. The potential for inaccuracies in conversion factors means that model outputs for areas using large numbers of converted values may be less accurate than those based on measurements of PM2.5 and extra cau-tion should be taken in their interpretation.

Wherever possible, estimates of PM2.5 have been computed using standardized categories and methods in order to enhance cross-natio-nal comparability. This approach may result in some cases in differences between the esti-mates presented here and the official national statistics prepared and endorsed by indivi-dual WHO Member States. These differences between WHO and national statistics may be larger in countries with small cities and settle-ments which may not be fully represented by the resolution of the WHO model. This may be compounded for isolated regions where air pollution is primarily from local sources and is experienced at very local levels.

2.2.3. Discussion

39

3.1. Methods

3. Burden of disease attributable to ambient air pollution

The burden of disease attributable to ambient air pollution was estimated for the year 2012 based on Comparative Risk Assessment methods (25) and in consultation with expert groups for the Global Burden of Disease (GBD) study (12, 14).This methodology is based on combining expo-sure to air pollution and its distribution in the population with exposure-risk estimates at each level of exposure. This results in a population attributable fraction of disease burden, which is then applied to the health outcome of interest.

3.1.1. Source of the dataHealth data

The total number of deaths, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) by disease, country, sex and age group have been deve-loped by the World Health Organization (26).

Exposure data

Annual mean concentration of PM2.5 were modelled according to the description in the section Exposure : modelled estimates of PM2.5. The model output provided the percentage of the population exposed to PM2.5 by country, in increments of 1 µg / m3.

Exposure-risk relationship

The integrated exposure-response (IER) func-tions, developed for the GBD 2010 study (16) and further updated for the GBD 2013 study (14 ; 27), were used for acute lower respiratory infections (ALRI), lung cancer, chronic obstruc-tive pulmonary disease (COPD), stroke and ischaemic heart disease (IHD) and can be des-cribed with the following formula (16) :

where z is the annual mean concentration of PM2.5, zcf is the counterfactual PM2.5 concentra-tion, α, γ and δ are the parameter estimates. The IERs are age-specific for both IHD and stroke.

Demographic data

Population data from the UN Population Division (21) were used.

3.1.2. Estimation of disease burden The percentage of the population exposed to PM2.5 was provided by country, in incre-ments of 1 µg / m3 ; relative risks were calcu-lated for each PM2.5 increment, based on the integrated exposure-response functions (IER). The counterfactual concentration was selec-ted to be a uniform distribution with lower and upper limits of 5.9 and 8.7 µg / m3 respectively, given by the average of the minimum and and 5th percentiles of outdoor air pollution cohort exposure distribution, as described elsewhere (14, 16). The country population attributable fractions (PAF) for ALRI, COPD, lung can-cer, stroke and IHD were calculated using the following formula, for each sex and age group :

where i is the level of PM2.5 in µg / m3, and Pi is the percentage of the population exposed to that level of air pollution, and RR is the relative risk.

40

The attributable burden is calculated by multi-plying the population-attributable fraction (PAF) by the health outcome, for each health outcome, sex and age group :

AB = PAF x health outcome

where AB is the attributable burden, PAF is the population-attributable fraction and the health out-come of interest, e.g. deaths, DALYs, YLLs, etc. DALYs are calculated by adding the years of life lived with disability (YLDs) and the YLLs. The relative risks (RRs) for YLDs were adjus-ted by a scalar of 1 for ALRI, lung cancer, and COPD ; of 0.141 for IHD and of 0.553 for stroke (27). The age groups included in the analysis were children less than five years of age for ALRI, and adults above 25 years for the other diseases as previously reported (2, 6).

3.1.3. Uncertainty analysisThe uncertainty intervals are based on the fol-lowing sources of uncertainty : (a) Uncertainty around the exposure to air pollution; and (b) uncertainty around relative risks of the integra-ted exposure-function. To account for uncer-tainty in exposure, the upper and lower expo-sure was obtained from the model (24) for each country, i.e. upper and lower credible limits for the estimate of the percentage of the population exposed to PM2.5.

Alternative burden of disease estimates were calculated for each of these exposures. For the integrated exposure-response function, 1 000 draws of each parameter of the function were obtained (27) and population attributable frac-tions were calculated for each draw.

The final uncertainty intervals were obtained as the 2.5 and 97.5 percentiles of the draws for the alternative burden of disease calculations. As uncertainty for total mortality by cause was not taken into account, this is a partial accounting of uncertainty, and is likely to be underestimated.

3.2. Results Globally, 3 million deaths were attributable to ambient air pollution (AAP) in 2012. About 87 % of these deaths occur in LMICs , which repre-sent 82 % of the world population.

The WHO Western Pacific and South East Asian regions bear most of the burden with 1.1 mil-lion and 799 000 deaths, respectively. In other regions, about 211 000 deaths occur in Sub-Saharan Africa, 194 000 in the Eastern Mediter-ranean region, 190 000 in Europe, and 93 000 in the Americas. The remaining deaths occur in high-income countries of Europe (289 000), the Americas (44 000), Western Pacific (44 000), and Eastern Mediterranean (10 000) (Figure 14).

Age-standardized deaths and DALYs are shown in Figures 15 to 19. Age-standardized measures of deaths and disease are often used to compare countries, as they adjust for age distribution differences by applying age-specific mortality rates for each population. Country estimates of deaths, YLLs and DALYs are provided by disease and sex in Annex 2. The methods for exposure assessment and burden of disease estimation have been slight-ly updated compared with the previous esti-mate of 3.7 million deaths from AAP (2012), as released in 2014 (2).

The variation is thought to be due to : 1) Addi-tional evidence that has become available on the relationship between exposure and health outcomes, and the use of an updated version of the integrated exposure-response functions leading to modified estimates depending on the disease ; and 2) revised population exposure to air pollution leading to modified estimates according to the region.

41

Figure 14 : Deaths attributable to AAP in 2012, by disease and region

AAP : ambient air pollution ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries

Figure 15 : Age-standardized deaths per capita attributable to AAP in 2012, by disease and region

AAP : ambient air pollution ; Afr : Africa ; Amr : Americas ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Wes-tern Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries.

0

250

500

750

1000

1250

1500

Emr (HIC)

Wpr (HIC)

Amr (HIC)

Amr (LMIC)

Eur (LMIC)

Emr (LMIC)

AfrEur (HIC)

SearWpr (LMIC)

1 102

799

289211 194 190

9344 44

10

Number of deaths (000s)

Stroke

IHD

COPD

Lung cancer

ALRI

0

10

20

30

40

50

60

70

80

Amr (HIC)

Wpr (HIC)

Amr (LMIC)

Eur (HIC)

AfrWorldEmr (HIC)

Emr (LMIC)

Eur (LMIC)

SearWpr (LMIC)

Age-standardized deaths per 100 000 capita

Stroke

IHD

COPD

Lung cancer

ALRI

65

59 5955

54

47

39

25

18

10 7

42

Figure 16 : Deaths attributable to AAP in 2012, by country

Figure 17 : DALYs attributable to AAP in 2012, by country

AAP : Ambient air pollution

AAP : Ambient air pollution

43

Figure 18 : Age-standardized deaths per 100 000 capita attributable to AAP in 2012, by country

Figure 19 : Age-standardized DALYs per 100 000 capita attributable to AAP in 2012, by country

AAP : Ambient air pollution

AAP : Ambient air pollution

44

Almost 94 % of deaths worldwide are due to noncommunicable diseases in adults, such as cardiovas-cular diseases (stroke and ischaemic heart disease), chronic obstructive pulmonary disease and lung cancers. The remaining deaths occur in children under five years of age due to acute lower respiratory infections (Figure 20 and Tables 5 and 6).

Figure 20 : Deaths attributable to AAP in 2012, by disease

Percentage represents percentage of total AAP burden. AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease.

Table 5 : Deaths attributable to AAP in 2012, by disease, age and sex

DeathsDisease Children < 5 years Men Women TotalALRI 169 250 - - 169 250COPD - 135 900 106 350 242 250Lung cancer - 285 900 116 450 402 350IHD - 606 350 472 450 1 078 800Stroke - 540 600 542 150 1 082 750Total 169 250 1 568 750 1 237 400 2 975 400

AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease. Men and women are adults of 25 years and above.

Table 6 : Disability-adjusted life years (DALYs) attributable to AAP in 2012, by disease, age and sex

DALYs (‘000s)Disease Children < 5 years Men Women TotalALRI 15 478 - - 15 478COPD - 3 758 2 862 6 620Lung cancer - 7 076 2 736 9 812IHD - 16 782 10 105 26 887Stroke - 13 927 12 210 26 137Total 15 478 41 544 27 913 84 934

DALYs : disability-adjusted life years; AAP : ambient air pollution ; ALRI : acute lower respiratory disease ; COPD : chronic obstructive pulmonary disease ; IHD : ischaemic heart disease. Men and women are adults of 25 years and above.

The fraction of each individual disease attributable to ambient air pollution is presented in Table 7 for DALYs, and ranges from 8 % for COPD to 25 % for lung cancers. ALRI, stroke and IHD lie in the middle with population attributable fraction of around 16 %.

STROKE

COPD

ALRILUNG CANCER

IHD

402 350

242 250

169 250

14%

8%6%

1 078 80036%

1 082 750

36%

45

Tabl

e 7 :

Pop

ulat

ion

attri

buta

ble

fract

ion

(PAF

) for

the

Dis

abilit

y-ad

just

ed li

fe y

ears

(DAL

Y) a

ttrib

utab

le A

AP in

201

2, b

y di

seas

e, a

ge, s

ex a

nd re

gion

.

ALR

IC

OPD

Lung

can

cer

IHD

Stro

ke

Chi

ldre

nM

enW

omen

Both

Men

Wom

enBo

thM

enW

omen

Both

Men

Wom

enBo

th

< 5

year

s≥ 2

5 ye

ars

≥ 25

year

s≥ 2

5 ye

ars

≥ 25

year

s

Afr

16 %

5 %5 %

5 %26

%27

%27

%18

%16

%17

%18

%17

%18

%

Amr (

HIC

)6 %

1 %0 %

1 %5 %

5 %5 %

6 %5 %

6 %5 %

5 %5 %

Amr (

LMIC

)12

%2 %

2 %2 %

15 %

16 %

15 %

12 %

11 %

12 %

11 %

10 %

11 %

Emr (

HIC

)23

%14

%14

%14

%47

%47

%47

%23

%20

%22

%25

%22

%24

%

Emr (

LMIC

)18

%9 %

9 %9 %

35 %

36 %

36 %

19 %

18 %

18 %

20 %

19 %

20 %

Eur (

HIC

)10

%2 %

2 %2 %

15 %

15 %

15 %

12 %

10 %

11 %

11 %

9 %10

%

Eur (

LMIC

)15

%4 %

4 %4 %

24 %

23 %

23 %

14 %

12 %

13 %

14 %

12 %

13 %

Sear

19 %

10 %

10 %

10 %

33 %

32 %

33 %

20 %

18 %

19 %

20 %

18 %

19 %

Wpr

(HIC

)8 %

2 %2 %

2 %15

%14

%15

%10

%8 %

9 %10

%8 %

9 %

Wpr

(LM

IC)

17 %

9 %9 %

9 %38

%38

%38

%17

%16

%17

%19

%18

%19

%

HIC

10 %

2 %1 %

1 %13

%11

%12

%10

%9 %

10 %

10%

9 %9 %

LMIC

17%

9 %9 %

9 %34

%34

%34

%18

%16

%17

%19

%17

%18

%

Wor

ld17

%8 %

8 %8 %

26 %

24 %

25 %

16 %

14 %

15 %

17 %

16 %

16 %

DAL

Y : D

isab

ility-

adju

sted

life

year

s ; P

AF: p

opul

atio

n at

tribu

tabl

e fra

ctio

n ; A

AP : A

mbi

ent a

ir po

llutio

n ; A

LRI :

Acut

e lo

wer

resp

irato

ry d

isea

se ; C

OPD

: Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; IH

D: I

scha

emic

he

art d

isea

se. A

fr : A

frica

; Am

r : A

mer

ica ;

Em

r : E

aste

rn M

edite

rrane

an ; E

ur : E

urop

e ; S

ear:

Sout

h-Ea

st A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

.

47

In 2012, ambient air pollution from particu-late matter was responsible for about 3 million deaths and 85 million DALYs. Burden of disease calculation is based on : 1) Population exposure assessment ; 2) exposure-response functions ; and 3) underlying health data. As data on air quality and epidemiological evidence is accu-mulating rapidly, and methodolodies for both points 1) and 2) are being revised on a regular basis, and these figures are evolving.

Decision-makers and researchers need accurate and reliable estimates of air pollution exposure and the related health impacts. Differing needs (cause-specific vs all-cause mortality, national or regional assessment), publication schedules and audience may lead to different approaches and data use, and therefore different results (28–31). The methods used in this report were developed for global reporting and using the latest available evidence and health data that complied with WHO standards ; they may therefore differ from official national statistics prepared and endorsed by individual WHO Member States.

Some regions, such as the Eastern Mediterra-nean and Africa are highly affected by natural desert dust particles. This results in high health burden according to the current methods, which assume natural dust affects health the same way as PM2.5 from other sources.

The health impacts associated with exposure to dust are not yet fully understood, and are current-ly treated the same way as those from air pollu-tion in industrialized countries where most of the epidemiological studies have been performed.

There is a need to for a better assessment of the health impacts from natural dust, as it could result in much lower burden than those from antropogenic particulate matter (32, 33).

The actual impact of air pollution on health presented here is a conservative figure. Many other diseases have been associated with air pollution but are not included in this assessment, because the evidence was not considered to be sufficiently robust, such as pre-term birth or low birth weight. Also, it does not include the separate impacts of health from other air pollutants such as nitrogen oxides (NOx) or ozone (O3).

As data on air pollutants, methods to assess population exposure and epidemiological evidence accumulates, health effects of additio-nal pollutants should be taken into account in the future as it has already been done for ozone (14). In addition, assessments of the health im-pacts from interventions to reduce air pollution using rigorous epidemiological methodology are much needed. These would be able to take account of context, of intervention packages and provide a stronger basis for assessing real-life impacts of air quality improvement efforts.

3.3. Discussion

49

Ambient air pollution kills about 3 million people annually and is affecting all regions of the world, although Western Pacific and South East Asia are the most affected. About 90 % of people breathe air that does not comply with the WHO Air Quality Guidelines.

The data presented here carry significant uncertainties but constitute the best evidence available to date. Air quality data and epidemio-logical evidence on the effects of air pollutants on health are growing quickly. They will conti-nue to improve exposure assessment to parti-culate matter and other pollutants, as well as for burden of disease estimation.

More epidemiological studies of the long-term effects of exposure to air pollution in low-income settings, where air pollution reaches unaccep-table levels, are urgently needed to better inform the exposure-response relationships. Additional evidence on health outcomes cur-rently not assessed in the analysis, because of lack of knowledge, is also crucial.

In terms of monitoring and reporting, there is a huge gap in monitoring and reporting air pollutants in low and middle-income regions, especially in Africa and Asia but also other regions. Strengthening capacities of cities to monitor their air quality with standardized methods, reliable and good quality instrumenta-tion, and sustainable structures is key.

4. Conclusion and way forward

51

1. Air quality guidelines : Global update 2005. Copenhagen : WHO Regional Office for Europe ; 2005.

2. Methods for burden of disease attributable to ambient air pollution for the year 2012. Geneva : World Health Organization ; 2014. (http:/ /www.who.int /phe/health_topics/outdoorair/databases/AAP_BoD_methods_March2014.pdf?ua=1, accessed May 2016).

3. Health and the environment : addressing the health impact of air pollution (resolution A68.8). Geneva : World Health Organization ; 2015. (http://apps.who.int/gb/ebwha/pdf_files/WHA68/A68_R8-en.pdf, accessed May 2016).

4. Health and the environment : Draft road map for an enhanced global response to the ad-verse health effects of air pollution (resolution A68.18). Geneva : World Health Organization ; 2016. (http://apps.who.int/gb/ebwha/pdf_files/WHA69/A69_18-en.pdf, accessed July 2016).

5. Transforming our world : The 2030 Agenda for Sustainable Development (resolution A/RES/70/1). New York : United Nations ; 2015.

6. Methods for burden of disease attribu-table to household air pollution for the year 2012. Geneva : World Health Organization ; 2014. (http://www.who.int/phe/health_topics/outdoorair/databases/HAP_BoD_methods_March2014.pdf?ua=1, accessed May 2016).

7. WHO Outdoor Air Pollution Database. Geneva : World Health Organization ; 2011. (http://www.who.int/phe/health_topics/outdoo-rair/databases/cities-2011/en/, accessed 26 May 2016).

8. WHO Ambient (Outdoor) Air Quality Data-base 2014. Geneva : World Health Organiza-tion ; 2014. (http://www.who.int/phe/health_topics/outdoorair/databases/cities-2014/en/accessed 26 May 2016).

9. WHO Urban Ambient (Outdoor) Air Qua-lity Database (update 2016). Geneva : World Health Organization; 2016. (http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/, accessed 19 May 2016).

10. Brauer M et al. Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environmental Science & Technology. 2012 ; 46(2):652–60. (doi: 10.1021/es2025752).

11. Brauer M et al. Ambient air pollution exposure estimation for the Global Burden of Disease 2013. Environmental Science & Tech-nology. 2015 ; 50:79–88.

12. Lim SS et al. The Lancet. 2012 ; 380(9859):2224–60. (doi:10.1016/S0140-6736(12)61766-8).

13. Apte J et al (2015). Addressing Global Mortality from Ambient PM2.5. Environmental Science & Technology. 2015 ; 49:8057–8066.

14. Forouzanfar et al (2015). Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupatio-nal, and metabolic risks or clusters of risks in 188 countries, 1990–2013 : a systematic ana-lysis for the Global Burden of Disease Study 2013. The Lancet. 2015 ; 386:2287–323.

15. WHO Global Platform on Air Quality and Health. Geneva : World Health Organization ; 2016. (www.who.int/phe/health_topics/outdoo-rair/global_plateform/en, accessed June 2016).

16. Burnett R et al. An Integrated Risk Func-tion for Estimating the Global Burden of Disease Attributable to Ambient Fine Particu-late Matter Exposure. Environmental Health Perspectives. 2014 ; 122, Issue 4:397–403.

17.Global burden of disease. Seattle : Institute for Health Metrics and Evaluation ; 2015.(www.healthdata.org/gbd, accessed October 2015).

18. Smith KR et al. Millions dead: how do we know and what does it mean ? Methods used in the Comparative risk assessment of house-hold air pollution. Annual Review of Public Health. 2014; 35:185–206.

19. Review of evience on health aspects of air pollution – REVIHAAP Project. Technical Report. Copenhagen : WHO Regional Office for Europe ; 2013.

20. Clean Air Asia. Manila : Clean Air Asia ; 2015. (http://cleanairasia.org/, accessed October 2015).

21. Air quality e-reporting database. Copen-hagen : European Environment Agency ; 2015. (http://www.eea.europa.eu/data-and-maps/data/aqereporting, accessed November 2015).

References

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22. World population prospects : 2015 revi-sion. New York : United Nations Population Division ; 2015.

23. Citypopulation (2016). (http://www.citypo-pulation.de, accessed February 2016).

24. Shaddick G. et al. Data Integration Model for Air Quality : A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution (2016, submitted). http://arxiv.org/abs/1609.00141, accessed September 2016.

25. Ezzati M. et al. Selected major risk factors and global and regional burden of disease. The Lancet. 2002; 360(9343):1347-60.

26. Global health estimates 2013 : Deaths by cause, age and sex, by Country, 2000-2012. Geneva : World Health Organization ; 2014.

27. Institute for Health Metrics and Evalua-tion. Seattle : Institute for Health Metrics and Evaluation ; 2016. (https://cloud.ihme.washing-ton.edu/index.php/s/mQiX0vGIaBTbaT7, accessed September 2016).

28. Health risks of air pollution in Europe - HRA-PIE Project : Recommandations for concentra-tion-response functions for cost-benefit analy-sis of particulate matter, ozone and nitrogen dioxide. Copenhagen : WHO Regional Office for Europe ; 2013.

29. Economic cost of the health impact of air pollution in Europe : Clean air, health and wealth. Copenhagen : WHO Regional Office for Europe; 2015.

30. Air quality in Europe - 2015 report. Copen-hagen : European Environement Agency ; 2015.

31. The economic consequences of outdoor air pollution. Paris : OECD Publishing ; 2016.(http://dx.doi.org/10.1787/9789264257474-en, accessed July 2016).

32. Giannadaki et al. Modeled global effects of airborne desert dust. Atmospheric Chemistry and Physics. 2014 ; 14, 957–968.

33. Lelieveld et al. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature. 2015; 525: 367.

55

This document was prepared by Sophie Gumy, and Annette Prüss-Üstün (WHO Geneva), with inputs and comments from Heather Adair-Ro-hani, Carlos Dora and Elaine Fletcher (WHO Geneva), Gavin Shaddick and Matthew Tho-mas (University of Bath, United Kingdom). The interactive map and the static map of expo-sure to air pollution were prepared by Ravi San-thana Gopala Krishnan (WHO Geneva) ; all other maps were prepared by Florence Rusciano (WHO Geneva).

Exposure : ground measurements of PM10 and PM2.5

The database was compiled during 2015 with some updates in the first quarter of 2016 by Sophie Gumy, Tara Neville, Kristina Dushaj and Annette Prüss-Ustün (WHO Geneva) with contributions from Mazen Malkawi (WHO CEHA, Amman), Christian Gapp (WHO ECEH, Bonn), Alberto González Ortiz (European Environment Agency), Kaye Patdu and Candy Tong (Clean Air Asia), Michael Brauer (School of Population and Public Health, University of British Colum-bia, Canada), and several national institutions.

Exposure : modelled estimates of PM2.5

The model to produce the estimates was deve-loped under the leadership of WHO and the University of Bath, United Kingdom, with the input and review of an expert group of 12 lea-ding scientists in the area. The scientist leading the work was Gavin Shaddick (University of Bath) who was assisted by Matthew Thomas and Amelia Jobling (University of Bath). The expert group consisted of Gavin Shaddick, Michael Brauer (University of British Columbia), Aaron van Donkelaar (Dalhousie University), Rick Burnett (Health Canada), Howard Chang

(Emory University), Aaron Cohen (Health Effects Institute), Rita van Dingenen (Joint Research Centre, European Commission), Yang Liu (Emo-ry University), Randall Martin (Dalhousie), Lance Waller (Emory University), Jason West (North Carolina) and Jim Zidek (University of British Columbia), in addition to Annette Prüss-Us-tün, Sophie Gumy and Carlos Dora of WHO. The model was presented and reviewed at the WHO Global Platform on Air Quality, Geneva, in August 2015.

Burden of disease attributable to ambient air pollution

The burden of disease was calculated by Sophie Gumy and Annette Prüss-Ustün (WHO Geneva).

Acknowledgment

57

Annex 1 : Modelled population exposure to particulate matter (PM2.5 ), by country Country income grouping is based on the World Bank analytical income classification of economies 1 corresponding to the year of the data.

Table A1 : Annual median concentration of particulate matter of an aerodynamic diameter of 2.5 mm or less (PM2.5) with lower and upper bound, population-weighted and modelled, by area and country

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Emr (LMIC) Afghanistan 46 26 80 63 41 98

Eur (LMIC) Albania 16 9 29 17 10 30

Afr Algeria 27 9 74 25 8 73

Eur (HIC) Andorra 10 6 18 11 6 17

Afr Angola 27 8 95 42 9 182

Amr (HIC) Antigua and Barbuda 13 6 28 13 6 28

Amr (LMIC) Argentina 13 8 22 14 9 24

Eur (LMIC) Armenia 21 7 66 25 7 87

Wpr (HIC) Australia 6 4 8 6 4 9

Eur (HIC) Austria 16 11 23 17 12 24

Eur (LMIC) Azerbaijan 24 8 73 26 8 86

Amr (HIC) Bahamas 13 6 28 13 6 28

Emr (HIC) Bahrain 60 43 82 60 44 82

Sear Bangladesh 84 53 131 89 58 134

Amr (HIC) Barbados 14 6 31 14 6 31

Eur (LMIC) Belarus 17 6 48 18 6 54

Eur (HIC) Belgium 15 11 22 16 11 23

Amr (LMIC) Belize 22 7 64 21 7 62

Afr Benin 31 9 107 28 7 106

Sear Bhutan 48 30 79 39 30 50

Amr (LMIC) Bolivia, Plurinational States of 27 17 45 32 20 49

Eur (LMIC) Bosnia and Herzegovina 42 23 76 55 30 100

Afr Botswana 16 6 42 19 6 57

Amr (LMIC) Brazil 10 7 16 11 8 17

Wpr HIC Brunei Darussalam 5 3 9 5 3 9

Eur (LMIC) Bulgaria 27 18 40 30 21 42

Afr Burkina Faso 37 12 119 37 10 132

1 For more information, see : Country classification. Washington (DC): World Bank (https://datahelpdesk.worldbank.org/knowledgebase/topics/19280-country-classification, accessed February 2016).

58

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Afr Burundi 38 11 136 49 12 198

Afr Cabo Verde 36 14 96

Wpr (LMIC) Cambodia 23 7 75 25 6 99

Afr Cameroon 65 38 111 64 39 104

Amr (HIC) Canada 7 5 10 7 5 10

Afr Central African Republic 39 12 129 56 15 217

Afr Chad 39 14 115 61 18 207

Amr (HIC) Chile 20 13 30 25 18 36

Wpr (LMIC) China 54 37 80 59 42 84

Amr (LMIC) Colombia 17 11 25 18 13 26

Afr Comoros 16 8 32 16 8 32

Afr Congo 40 11 143 57 13 236

Wpr (LMIC) Cook Islands NA NA NA NA NA NA

Amr (LMIC) Costa Rica 18 12 27 19 13 27

Eur (HIC) Croatia 19 12 31 20 13 32

Amr (LMIC) Cuba 17 7 38 16 7 38

Eur (HIC) Cyprus 17 11 26 17 11 26

Eur (HIC) Czech Republic 20 14 29 21 15 29

Afr Côte d’Ivoire 22 7 71 19 5 71

Sear Democratic People’s Republic of Korea 27 8 92 31 8 118

Afr Democratic Republic of the Congo 38 12 121 61 16 225

Eur (HIC) Denmark 10 7 16 11 7 17

Emr (LMIC) Djibouti 39 9 159 46 10 211

Amr (LMIC) Dominica 13 6 28 13 6 28

Amr (LMIC) Dominican Republic 16 7 37 17 7 40

Amr (LMIC) Ecuador 13 9 20 13 9 20

Emr (LMIC) Egypt 93 50 171 101 54 188

Amr (LMIC) El Salvador 35 20 62 37 22 64

Afr Equatorial Guinea 33 7 153 32 8 128

Afr Eritrea 35 10 126 36 9 138

Eur (HIC) Estonia 8 5 13 8 5 13

Afr Ethiopia 30 9 94 36 10 132

Wpr (LMIC) Fiji 6 2 22 6 2 22

Eur (HIC) Finland 7 5 11 7 5 11

Eur (HIC) France 12 8 17 13 9 18

Afr Gabon 30 8 115 36 7 169

Afr Gambia 39 7 234 43 6 306

Eur (LMIC) Georgia 19 11 33 23 13 40

NANA NA

59

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Eur (HIC) Germany 14 9 20 14 10 21

Afr Ghana 24 12 46 22 10 46

Eur (HIC) Greece 12 8 18 13 9 18

Amr (LMIC) Grenada 14 6 31 14 6 32

Amr (LMIC) Guatemala 32 20 51 33 23 49

Afr Guinea 21 7 66 19 5 68

Afr Guinea-Bissau 27 7 103 29 6 138

Amr (LMIC) Guyana 15 5 45 16 5 54

Amr (LMIC) Haiti 22 7 63 25 8 79

Amr (LMIC) Honduras 35 20 60 40 23 68

Eur (LMIC) Hungary 21 14 32 23 16 33

Eur (HIC) Iceland 8 5 12 8 5 12

Sear India 62 41 95 66 45 97

Sear Indonesia 14 9 23 18 11 28

Emr (LMIC) Iran (Islamic Republic of) 42 27 63 40 28 58

Emr (LMIC) Iraq 50 18 141 51 17 154

Eur (HIC) Ireland 9 6 14 10 7 14

Eur (HIC) Israel 19 13 28 19 14 27

Eur (HIC) Italy 17 12 25 18 13 26

Amr (LMIC) Jamaica 16 11 25 17 12 25

Wpr (HIC) Japan 13 8 19 13 9 19

Emr (LMIC) Jordan 36 24 53 38 27 52

Eur (LMIC) Kazakhstan 15 6 43 21 7 67

Afr Kenya 16 9 28 17 10 29

Wpr (LMIC) Kiribati 5 1 20

Emr (HIC) Kuwait 75 50 112 78 53 116

Eur (LMIC) Kyrgyzstan 15 8 27 15 8 28

Wpr (LMIC) Lao People’s DemocraticRepublic 27 9 76 34 10 106

Eur (HIC) Latvia 19 12 29 20 13 31

Emr (LMIC) Lebanon 30 19 45 31 21 45

Afr Lesotho 18 4 76 22 4 113

Afr Liberia 8 4 17 6 3 15

Emr (LMIC) Libya 61 22 171 58 19 175

Eur (HIC) Lithuania 18 12 28 19 13 28

Eur (HIC) Luxembourg 16 11 24 17 12 23

Afr Madagascar 17 9 33 32 19 54

Afr Malawi 22 7 72 26 7 95

Wpr (LMIC) Malaysia 15 9 24 17 10 26

Sear Maldives 16 8 29

NA NA NA

NA NA NA

60

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Afr Mali 39 13 124 35 10 120

Eur (HIC) Malta 14 9 21 14 10 20

Wpr (LMIC) Marshall Islands NA NA NA NA NA NA

Afr Mauritania 65 19 230 86 21 368

Afr Mauritius 14 9 23 14 8 24

Amr (LMIC) Mexico 20 13 30 20 13 31

Wpr (LMIC) Micronesia (FederatedStates of) 6 2 22 6 2 23

Eur (HIC) Monaco 9 6 18 9 6 18

Wpr (LMIC) Mongolia 20 13 32 32 20 51

Eur (LMIC) Montenegro 22 14 35 24 15 38

Emr (LMIC) Morocco 20 13 32 19 12 29

Afr Mozambique 17 6 47 22 7 69

Sear Myanmar 51 32 80 57 35 90

Afr Namibia 18 6 51 18 6 57

Wpr (LMIC) Nauru NA NA NA NA NA NA

Sear Nepal 64 33 123 74 39 140

Eur (HIC) Netherlands 15 10 22 15 10 22

Wpr (HIC) New Zealand 5 4 8 5 4 8

Amr (LMIC) Nicaragua 24 8 74 26 7 95

Afr Niger 59 19 191 51 15 177

Afr Nigeria 39 25 61 38 24 58

Wpr (LMIC) Niue NA NA NA NA NA NA

Eur (HIC) Norway 9 6 13 9 6 14

Emr (HIC) Oman 48 18 132 47 15 145

Emr (LMIC) Pakistan 60 37 97 68 43 107

Wpr (LMIC) Palau NA NA NA NA NA NA

Amr (LMIC) Panama 12 7 20 13 7 23

Wpr (LMIC) Papua New Guinea 10 2 45 12 2 71

Amr (LMIC) Paraguay 15 9 25 17 10 28

Amr (LMIC) Peru 26 16 42 36 23 54

Wpr (LMIC) Philippines 22 14 35 27 17 43

Eur (HIC) Poland 24 16 35 25 18 36

Eur (HIC) Portugal 9 6 14 10 6 14

Emr (HIC) Qatar 103 67 160 105 69 159

Wpr (HIC) Republic of Korea 27 18 39 28 19 40

Eur (LMIC) Republic of Moldova 17 5 59 17 4 68

Eur (LMIC) Romania 19 13 28 20 14 29

Eur (HIC) Russian Federation 15 8 27 17 9 31

Afr Rwanda 43 13 143 51 14 185

61

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Amr (HIC) Saint Kitts and Nevis NA NA NA NA NA NA

Amr (LMIC) Saint Lucia 15 7 31 15 7 32

Amr (LMIC) Saint Vincent and theGrenadines 13 6 28

Wpr (LMIC) Samoa NA NA NA NA NA NA

Eur (HIC) San Marino NA NA NA NA NA NA

Afr Sao Tome and Principe 13 5 29

Emr (HIC) Saudi Arabia 108 67 174 127 79 205

Afr Senegal 34 21 55 43 29 64

Eur (LMIC) Serbia 19 12 31 21 14 33

Afr Seychelles 13 7 27 13 7 27

Afr Sierra Leone 17 4 69 17 3 86

Wpr (HIC) Singapore 17 9 31 17 9 31

Eur (HIC) Slovakia 19 13 29 20 14 29

Eur (HIC) Slovenia 18 12 27 19 14 28

Wpr (LMIC) Solomon Islands 5 1 18 5 1 19

Emr (LMIC) Somalia 16 5 49 17 4 66

Afr South Africa 27 18 42 31 21 48

Emr (LMIC) South Sudan 29 11 81 32 12 91

Eur (HIC) Spain 9 7 14 10 7 14

Sear Sri Lanka 27 14 51 28 15 55

Emr (LMIC) Sudan 44 14 137 53 16 178

Amr (LMIC) Suriname 16 5 51 16 4 63

Afr Swaziland 18 5 59 20 5 72

Eur (HIC) Sweden 6 4 9 6 4 9

Eur (HIC) Switzerland 12 8 18 13 8 18

Emr (LMIC) Syrian Arab Republic 34 12 98 34 11 105

Eur (LMIC) Tajikistan 41 12 138 51 14 187

Sear Thailand 25 16 37 27 19 38

Eur (LMIC) The former Yugoslav Republic of Macedonia 37 23 59 43 28 65

Sear Timor-Leste 15 3 65 15 3 69

Afr Togo 28 8 107 26 6 113

Wpr (LMIC) Tonga NA NA NA NA NA NA

Amr (HIC) Trinidad and Tobago 13 6 28 13 6 28

Emr (LMIC) Tunisia 36 22 61 35 21 59

Eur (LMIC) Turkey 34 22 50 35 24 51

Eur (LMIC) Turkmenistan 25 8 76 26 7 95

Wpr (LMIC) Tuvalu NA NA NA NA NA NA

Afr Uganda 57 30 108 80 46 138

Eur (LMIC) Ukraine 16 6 44 17 6 48

NA NA NA

NA NA NA

62

PM2.5 [µg/m3], urban and rural areas PM2.5 [µg/m3], urban areas

Region Country Median Lower Upper Median Lower Upper

Emr (HIC) United Arab Emirates 64 39 104 64 39 106

Eur (HIC) United Kingdom 12 8 18 12 8 18

Afr United Republic of Tanzania 22 11 42 24 12 47

Amr (HIC) United States of America 8 5 12 8 6 12

Amr (HIC) Uruguay 11 8 17 11 8 17

Eur (LMIC) Uzbekistan 32 10 102 38 12 128

Wpr (LMIC) Vanuatu 6 2 23 7 2 26

Amr (LMIC) Venezuela, Bolivarian Republic of 22 13 39 24 14 41

Wpr (LMIC) Viet Nam 26 15 43 28 17 45

Emr (LMIC) Yemen 43 11 173 42 9 208

Afr Zambia 23 9 64 29 10 90

Afr Zimbabwe 20 7 55 24 8 75

PM2.5 : Particulate matter of a diameter of 2.5 mm or less ; ALRI : Acute lower respiratory disease ; COPD : Chronic obs-tructive pulmonary disease ; IHD : Ischaemic heart disease. Afr : Africa ; Amr : America ; Emr : Eastern Mediterranean ; Eur : Europe ; Sear : South-East Asia ; Wpr : Western Pacific ; LMIC : Low- and middle-income countries ; HIC : High-income countries ; NA : Not available.

Wherever possible, estimates of PM2.5 have been computed using standardized categories and methods in order to enhance cross-national comparability. This approach may result in some cases in differences between the estimates presented here and the official national statistics prepared and endorsed by individual WHO Member States.

These differences between WHO and national statistics may be larger for occur in countries with small cities and settlements which may not be fully represented by the resolution of the WHO model. This may be compounded for isolated regions where air pollution is primarily from local sources and is experienced at very local levels.

63

Annex 2 : Deaths, YLLs and DALYs attributable to ambient air pollution, by country

65

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n3

772

188

301

3 81

33

071

11 1

45(8

961,

135

70)

3781

Eur (

LMIC

)Al

bani

a8

2018

485

078

01

842

(744

, 245

2)64

47

Afr

Alge

ria34

113

163

35

087

5 23

111

424

(457

7, 1

6150

)31

41

Eur (

HIC

) An

dorra

00

313

622

(0, 3

3)27

12

Afr

Ango

la3

687

131

391

491

1 71

07

058

(137

7, 1

1428

)31

51

Amr (

HIC

)An

tigua

and

Bar

buda

00

110

617

(0, 2

5)19

20

Amr (

LMIC

)Ar

gent

ina

8519

21

500

5 25

62

723

9 75

6(2

660,

133

85)

2318

Eur (

LMIC

)Ar

men

ia8

5337

01

643

676

2 75

0(1

07, 4

229)

9267

Wpr

(HIC

)Au

stra

lia0

114

5820

93(1

, 282

9)0.

40.

2

Eur (

HIC

)Au

stria

163

687

1 64

249

62

890

(201

0, 3

587)

3415

Eur (

LMIC

)Az

erba

ijan

135

4523

82

656

1 22

24

297

(954

, 622

0)46

57

Amr (

HIC

)Ba

ham

as3

05

3119

57(0

, 86)

1517

Emr (

HIC

)Ba

hrai

n2

725

7639

148

(132

, 165

)11

33

Sear

Bang

lade

sh3

850

8 31

64

375

10 2

9110

617

37 4

49(3

0245

, 460

36)

2438

Amr (

HIC

)Ba

rbad

os1

04

2217

44(0

, 64)

1510

Eur (

LMIC

)Be

laru

s4

5756

36

680

2 14

69

450

(159

, 137

17)

100

58

Eur (

HIC

)Be

lgiu

m1

115

1 23

21

276

718

3 34

3(2

135,

429

4)30

14

Amr (

LMIC

)Be

lize

11

318

1336

(5, 5

4)11

21

Afr

Beni

n71

441

1976

71

065

2 60

6(9

09, 3

972)

2652

Sear

Bhut

an20

2914

7653

192

(154

, 237

)26

40

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

265

6888

1 12

697

32

521

(198

3, 3

045)

2531

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na2

100

583

1 39

81

454

3 53

8(2

753,

437

3)92

53

Afr

Bots

wan

a35

310

8913

627

3(2

, 423

)13

26

Amr (

LMIC

)Br

azil

198

539

2 90

112

987

9 61

626

241

(112

92, 3

9983

)13

14

Wpr

HIC

Brun

ei D

arus

sala

m0

00

00

1(0

, 40)

0.2

0.3

Eur (

LMIC

)Bu

lgar

ia20

195

960

4 03

13

428

8 63

4(7

033,

102

10)

118

55

Afr

Burk

ina

Faso

1 65

172

451

120

1 73

54

623

(238

1, 6

922)

2858

66

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Buru

ndi

1 37

845

2153

21

025

3 00

1(1

348,

468

9)30

48

Afr

Cab

o Ve

rde

315

6223

01

249

1 07

82

934

(222

, 451

0)20

37

Wpr

(LM

IC)

Cam

bodi

a2

621

169

621

736

2 41

37

000

(575

5, 8

463)

3254

Afr

Cam

eroo

n1

2350

31

060

300

1 88

6(2

9, 6

607)

53

Amr (

HIC

)C

anad

a5

71

3778

128

(79,

181

)25

37

Afr

Cen

tral A

frica

n Re

publ

ic45

264

1230

638

11

215

(610

, 188

9)26

40

Afr

Cha

d2

426

6120

731

1 10

14

340

(241

0, 6

438)

3452

Amr (

HIC

)C

hile

1789

587

1 08

71

042

2 82

2(2

064,

346

5)16

13

Wpr

(LM

IC)

Chi

na6

716

90 6

2622

8 47

925

7 63

844

9 37

31

032

833

(869

033,

121

2034

)76

70

Amr (

LMIC

)C

olom

bia

158

270

748

3 68

81

638

6 50

2(4

499,

806

3)14

17

Afr

Com

oros

322

131

5912

5(2

9, 1

74)

1734

Afr

Con

go32

443

838

648

41

244

(605

, 191

0)29

50

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a2

2665

380

172

644

(469

, 786

)14

14

Eur (

HIC

)C

roat

ia0

4958

31

404

806

2 84

2(2

028,

355

6)66

31

Amr (

LMIC

)C

uba

771

975

1 98

91

086

4 12

7(3

38, 6

115)

3623

Eur (

HIC

)C

ypru

s0

356

120

4522

3(1

50, 2

81)

2014

Eur (

HIC

)C

zech

Rep

ublic

383

1 21

03

620

1 19

46

110

(478

8, 7

314)

5829

Afr

Côt

e d’

Ivoi

re1

431

6442

1 39

42

038

4 97

0(6

88, 7

767)

2443

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

230

1 21

03

334

3 91

06

911

15 5

96(2

047,

263

52)

6362

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

10 5

2047

387

4 82

87

124

23 0

34(1

1528

, 350

80)

3352

Eur (

HIC

)D

enm

ark

039

402

434

263

1 13

8(5

2, 1

845)

2010

Emr (

LMIC

)D

jibou

ti54

55

5792

212

(82,

336

)25

42

Amr (

LMIC

)D

omin

ica

00

16

513

(1, 1

9)18

16

Amr (

LMIC

)D

omin

ican

Rep

ublic

8520

164

1 09

864

12

008

(173

, 286

4)20

24

Amr (

LMIC

)Ec

uado

r86

4315

287

561

51

771

(860

, 230

8)11

14

Emr (

LMIC

)Eg

ypt

951

1 96

82

079

22 3

2716

206

43 5

31(3

6017

, 518

17)

5177

Amr (

LMIC

)El

Sal

vado

r46

7697

953

326

1 49

8(1

189,

182

8)25

27

67

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Equa

toria

l Gui

nea

628

575

7722

8(1

8, 3

84)

2950

Afr

Eritr

ea36

222

1730

753

41

243

(543

, 190

4)25

56

Eur (

HIC

)Es

toni

a0

136

233

4831

9(4

, 624

)24

11

Afr

Ethi

opia

5 56

540

037

62

320

4 59

513

257

(489

0, 2

0742

)14

23

Wpr

(LM

IC)

Fiji

00

02

02

(0, 3

02)

0.2

0.3

Eur (

HIC

)Fi

nlan

d0

131

233

6232

7(1

, 160

9)6

3

Eur (

HIC

)Fr

ance

412

64

256

3 79

32

774

10 9

54(3

825,

152

04)

178

Afr

Gab

on58

1816

138

155

385

(76,

622

)24

34

Afr

Gam

bia

114

75

100

160

386

(24,

675

)21

46

Eur (

LMIC

)G

eorg

ia12

5219

22

127

1 35

83

741

(234

1, 4

741)

9051

Eur (

HIC

)G

erm

any

556

96

821

13 3

925

372

26 1

60(1

2729

, 342

29)

3313

Afr

Gha

na96

872

751

810

2 80

45

728

(381

6, 7

407)

2241

Eur (

HIC

)G

reec

e1

7084

42

388

1 70

55

008

(171

7, 6

683)

4519

Amr (

LMIC

)G

rena

da0

01

119

22(0

, 32)

2123

Amr (

LMIC

)G

uate

mal

a39

669

162

880

473

1 98

0(1

598,

237

8)13

19

Afr

Gui

nea

690

3216

723

1 00

62

466

(273

, 383

2)21

38

Afr

Gui

nea-

Biss

au15

97

412

017

446

4(3

8, 7

55)

2747

Amr (

LMIC

)G

uyan

a3

14

123

9923

0(0

, 352

)30

43

Amr (

LMIC

)H

aiti

574

1498

801

1 53

53

022

(381

, 453

2)29

46

Amr (

LMIC

)H

ondu

ras

9981

9380

949

31

575

(124

2, 1

927)

2032

Eur (

LMIC

)H

unga

ry4

160

2 00

04

324

1 65

98

147

(627

9, 9

881)

8242

Eur (

HIC

)Ic

elan

d0

04

124

21(0

, 64)

64

Sear

Indi

a39

914

110

500

26 3

3424

9 38

819

5 00

162

1 13

8(5

1524

2, 7

4441

6)49

68

Sear

Indo

nesi

a2

534

1 00

04

951

16 7

8136

527

61 7

92(3

2783

, 818

76)

2538

Emr (

LMIC

)Ira

n

(Isla

mic

Rep

ublic

of)

600

434

1 46

016

484

7 29

026

267

(225

83, 3

0064

)34

50

Emr (

LMIC

)Ira

q1

010

173

728

4 97

43

200

10 0

85(6

690,

136

84)

3168

Eur (

HIC

)Ire

land

012

142

403

124

681

(43,

107

1)15

10

Eur (

HIC

)Is

rael

135

411

509

262

1 21

9(9

12, 1

501)

1611

Eur (

HIC

)Ita

ly2

558

6 39

18

292

5 81

421

057

(142

91, 2

6531

)35

13

68

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)Ja

mai

ca8

882

246

349

693

(484

, 869

)25

22

Wpr

(HIC

)Ja

pan

1828

19

743

10 2

8610

463

30 7

90(1

1488

, 419

45)

249

Emr (

LMIC

)Jo

rdan

6334

159

743

484

1 48

3(1

269,

170

4)21

43

Eur (

LMIC

)Ka

zakh

stan

8911

766

96

307

3 11

110

293

(132

2, 1

5858

)61

69

Afr

Keny

a2

021

3179

1 19

21

780

5 10

2(1

993,

697

1)12

21

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 2

2)0.

00.

0

Emr (

HIC

)Ku

wai

t12

335

319

117

487

(433

, 544

)14

45

Eur (

LMIC

)Ky

rgyz

stan

4833

731

357

617

2 12

9(8

50, 2

784)

3859

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

399

4812

266

862

01

857

(758

, 273

0)29

52

Eur (

HIC

)La

tvia

07

199

1 15

649

61

859

(136

3, 2

268)

9142

Emr (

LMIC

)Le

bano

n6

2520

992

127

41

434

(118

3, 1

679)

2930

Afr

Leso

tho

8216

689

195

387

(0, 7

19)

1931

Afr

Libe

ria63

42

7591

236

(0, 6

21)

611

Emr (

LMIC

)Li

bya

3060

251

1 03

867

42

054

(140

8, 2

758)

3358

Eur (

HIC

)Li

thua

nia

116

223

1 42

455

32

216

(167

1, 2

678)

7335

Eur (

HIC

)Lu

xem

bour

g0

437

3530

106

(69,

135

)20

11

Afr

Mad

agas

car

914

4713

61

135

1 98

44

215

(195

3, 5

715)

1939

Afr

Mal

awi

747

4213

697

1 20

72

706

(87,

427

3)17

35

Wpr

(LM

IC)

Mal

aysi

a29

148

670

3 63

01

773

6 25

1(3

548,

803

6)22

32

Sear

Mal

dive

s1

13

2320

48(1

2, 6

5)14

23

Afr

Mal

i2

291

154

491

122

1 60

15

218

(279

4, 7

902)

3260

Eur (

HIC

)M

alta

01

2776

2512

9(6

6, 1

64)

3116

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia34

023

1023

736

997

8(5

97, 1

453)

2646

Afr

Mau

ritiu

s2

223

144

8225

2(1

09, 3

26)

2018

Amr (

LMIC

)M

exic

o46

774

21

336

9 98

34

269

16 7

98(1

2475

, 205

28)

1417

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

00

0(0

, 19)

0.1

0.2

Eur (

HIC

)M

onac

o0

01

42

8(0

, 14)

209

69

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Wpr

(LM

IC)

Mon

golia

3918

6057

243

41

123

(779

, 138

9)40

70

Eur (

LMIC

)M

onte

negr

o0

177

160

145

382

(284

, 472

)61

39

Emr (

LMIC

)M

oroc

co36

984

767

3 37

93

535

8 13

4(6

109,

990

7)25

31

Afr

Moz

ambi

que

1 35

058

5859

81

278

3 34

3(1

32, 5

360)

1321

Sear

Mya

nmar

1 53

01

561

2 78

05

476

11 3

1622

664

(187

44, 2

6942

)43

61

Afr

Nam

ibia

3410

992

162

306

(40,

481

)13

27

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al74

01

770

923

3 32

83

183

9 94

3(7

426,

130

57)

3656

Eur (

HIC

)N

ethe

rland

s1

137

1 83

91

203

836

4 01

7(2

176,

539

4)24

12

Wpr

(HIC

)N

ew Z

eala

nd0

03

134

20(0

, 463

)0.

50.

3

Amr (

LMIC

)N

icar

agua

7240

6467

139

91

247

(196

, 187

4)21

31

Afr

Nig

er3

168

997

1 07

31

835

6 18

3(3

802,

914

6)35

57

Afr

Nig

eria

22 2

3365

226

49

618

13 9

8346

750

(380

31, 5

6243

)28

44

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay0

1213

733

015

663

6(2

4, 1

226)

136

Emr (

HIC

)O

man

106

2525

718

047

7(3

26, 6

34)

1336

Emr (

LMIC

)Pa

kist

an13

683

5 68

82

394

20 7

7216

705

59 2

41(4

8757

, 713

40)

3352

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a15

536

227

142

425

(54,

615

)11

12

Wpr

(LM

IC)

Papu

a N

ew G

uine

a16

510

2618

613

251

9(0

, 120

8)7

12

Amr (

LMIC

)Pa

ragu

ay42

1610

852

946

51

159

(534

, 152

3)18

25

Amr (

LMIC

)Pe

ru16

312

865

11

949

1 34

84

239

(327

7, 5

148)

1417

Wpr

(LM

IC)

Philip

pine

s1

666

599

2 24

014

067

10 1

2428

696

(220

37, 3

4736

)30

47

Eur (

HIC

)Po

land

1248

35

731

11 9

878

376

26 5

89(2

1327

, 316

70)

6939

Eur (

HIC

)Po

rtuga

l1

2032

364

777

91

769

(66,

289

4)17

7

Emr (

HIC

)Q

atar

12

3410

436

179

(158

, 200

)9

31

Wpr

(HIC

)Re

publ

ic o

f Kor

ea7

284

4 69

52

638

3 89

911

523

(905

4, 1

3963

)23

16

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

1626

188

1 96

781

13

008

(0, 4

776)

7457

Eur (

LMIC

)Ro

man

ia88

164

2 11

56

794

5 33

614

497

(110

01, 1

7576

)73

39

70

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

133

723

9 84

083

938

46 2

1614

0 85

1(5

9079

, 192

348)

9861

Afr

Rwan

da73

834

1949

694

02

227

(122

0, 3

320)

2140

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

10

315

1838

(6, 5

5)21

19

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s0

01

128

21(0

, 31)

1921

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe5

11

612

25(0

, 40)

1426

Emr (

HIC

)Sa

udi A

rabi

a59

236

362

4 12

83

335

8 11

9(7

027,

929

3)28

67

Afr

Sene

gal

613

6732

529

764

2 00

5(1

592,

244

0)15

28

Eur (

LMIC

)Se

rbia

488

1 34

12

049

1 95

25

435

(382

1, 6

858)

6134

Afr

Seyc

helle

s0

02

105

18(1

, 26)

1919

Afr

Sier

ra L

eone

745

158

398

617

1 78

3(0

, 319

6)30

50

Wpr

(HIC

)Si

ngap

ore

116

285

544

248

1 09

4(5

43, 1

479)

2116

Eur (

HIC

)Sl

ovak

ia5

2141

62

210

813

3 46

5(2

681,

415

6)64

40

Eur (

HIC

)Sl

oven

ia0

1021

726

524

073

2(5

22, 9

15)

3517

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 8

1)0.

00.

0

Emr (

LMIC

)So

mal

ia1

362

1622

273

471

2 14

4(1

22, 3

734)

2127

Afr

Sout

h Af

rica

1 16

046

41

638

4 60

86

486

14 3

56(1

1397

, 172

06)

2739

Emr (

LMIC

)So

uth

Suda

n1

200

4332

493

864

2 63

2(1

271,

389

5)24

36

Eur (

HIC

)Sp

ain

312

51

834

3 13

41

765

6 86

0(1

210,

110

62)

157

Sear

Sri L

anka

3327

536

54

846

2 27

37

792

(567

5, 9

843)

3838

Emr (

LMIC

)Su

dan

2 87

819

911

81

738

3 16

18

093

(464

4, 1

1955

)21

36

Amr (

LMIC

)Su

rinam

e2

08

3133

74(0

, 122

)14

16

Afr

Swaz

iland

527

447

7818

8(0

, 318

)15

28

Eur (

HIC

)Sw

eden

00

426

940

(0, 1

886)

0.4

0.2

Eur (

HIC

)Sw

itzer

land

028

408

750

295

1 48

2(3

96, 2

031)

188

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

116

6653

83

779

1 49

65

994

(354

2, 8

251)

3060

Eur (

LMIC

)Ta

jikis

tan

501

8695

1 74

31

189

3 61

5(2

044,

524

6)46

89

71

AAP:

Am

bien

t air

pollu

tion;

ALR

I: Ac

ute

low

er re

spira

tory

dis

ease

; CO

PD: C

hron

ic o

bstru

ctiv

e pu

lmon

ary

dise

ase;

IHD

: Isc

haem

ic h

eart

dise

ase.

Afr:

Afri

ca; A

mr:

Amer

ica;

Em

r: Ea

ster

n M

edite

rrane

an; E

ur:

Euro

pe; S

ear:

Sout

h-Ea

st A

sia;

Wpr

: Wes

tern

Pac

ific;

LM

IC: L

ow- a

nd m

iddl

e-in

com

e co

untri

es; H

IC: H

igh-

inco

me

coun

tries

; NA:

Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Sear

Thai

land

104

976

4 32

39

669

7 30

222

375

(177

90, 2

6921

)33

28

Eur (

LMIC

)Th

e fo

rmer

Yug

oslav

Re

publ

ic of

Mac

edon

ia1

2329

239

066

01

366

(110

7, 1

635)

6647

Sear

Tim

or-L

este

502

2673

5821

0(0

, 403

)19

31

Afr

Togo

484

1912

372

566

1 45

4(2

87, 2

322)

2242

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o3

228

223

9635

1(0

, 515

)26

24

Emr (

LMIC

)Tu

nisi

a45

102

492

2 46

51

527

4 63

1(3

739,

554

0)43

44

Eur (

LMIC

)Tu

rkey

240

1 06

56

498

14 8

1310

053

32 6

68(2

7197

, 382

89)

4448

Eur (

LMIC

)Tu

rkm

enis

tan

130

5511

42

425

944

3 66

7(1

134,

519

7)71

108

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

3 14

119

212

61

624

2 90

57

989

(623

9, 1

0044

)23

45

Eur (

LMIC

)U

krai

ne63

268

2 64

438

707

12 8

2454

507

(673

, 791

37)

120

65

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

913

6239

917

265

5(5

64, 7

49)

728

Eur (

HIC

)U

nite

d Ki

ngdo

m12

424

4 80

37

366

3 74

916

355

(538

7, 2

2534

)26

13

Afr

Uni

ted

Repu

blic

of

Tanz

ania

1 91

211

036

1 59

92

108

5 76

5(3

513,

764

5)12

21

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

3372

18

836

22 5

605

893

38 0

43(1

539,

808

04)

127

Amr (

HIC

)U

rugu

ay4

1416

930

821

771

3(1

94, 9

96)

2113

Eur (

LMIC

)U

zbek

ista

n72

219

544

49

984

4 93

616

282

(793

7, 2

3064

)57

85

Wpr

(LM

IC)

Vanu

atu

00

01

12

(0, 4

1)1

2

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

125

126

814

3 46

61

582

6 11

3(4

424,

761

2)20

27

Wpr

(LM

IC)

Viet

Nam

591

1 12

74

897

5 08

115

644

27 3

40(1

9758

, 348

35)

3033

Emr (

LMIC

)Ye

men

1 41

513

512

22

849

2 14

46

667

(302

8, 1

0148

)27

58

Afr

Zam

bia

997

1824

519

854

2 41

1(6

79, 3

600)

1630

Afr

Zim

babw

e70

051

123

366

616

1 85

6(1

37, 2

949)

1323

73

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n1

798

8877

1 82

81

752

5 54

4(4

463,

673

9)38

81

Eur (

LMIC

)Al

bani

a3

963

400

440

915

(352

, 121

7)64

42

Afr

Alge

ria14

947

118

2 00

02

537

4 85

1(1

930,

686

2)26

34

Eur (

HIC

)An

dorra

00

16

310

(0, 1

4)24

8

Afr

Ango

la1

452

5414

653

924

3 09

6(6

25, 4

980)

2747

Amr (

HIC

)An

tigua

and

Bar

buda

00

05

38

(0, 1

2)17

17

Amr (

LMIC

)Ar

gent

ina

3681

443

2 37

51

359

4 29

4(1

094,

583

1)20

13

Eur (

LMIC

)Ar

men

ia3

2165

721

351

1 16

1(3

4, 1

756)

7745

Wpr

(HIC

)Au

stra

lia0

06

2412

43(0

, 131

2)0.

40.

2

Eur (

HIC

)Au

stria

127

250

797

296

1 37

2(9

60, 1

694)

3211

Eur (

LMIC

)Az

erba

ijan

6019

521

176

656

1 96

2(4

07, 2

839)

4246

Amr (

HIC

)Ba

ham

as1

01

139

25(0

, 37)

1312

Emr (

HIC

)Ba

hrai

n1

37

2517

52(4

6, 5

8)10

27

Sear

Bang

lade

sh1

728

3 72

985

93

345

5 42

215

084

(120

74, 1

8726

)20

31

Amr (

HIC

)Ba

rbad

os0

01

109

20(0

, 28)

137

Eur (

LMIC

)Be

laru

s1

1270

3 28

91

206

4 57

8(4

4, 6

579)

9038

Eur (

HIC

)Be

lgiu

m1

4231

949

939

81

258

(832

, 159

4)22

9

Amr (

LMIC

)Be

lize

10

19

717

(2, 2

5)10

21

Afr

Beni

n32

314

738

755

31

284

(450

, 194

4)25

49

Sear

Bhut

an9

117

3129

86(6

9, 1

05)

2540

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

120

3545

509

454

1 16

4(9

13, 1

410)

2327

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na1

4412

462

383

01

623

(126

8, 2

005)

8441

Afr

Bots

wan

a17

12

4990

160

(1, 2

46)

1528

Amr (

LMIC

)Br

azil

9022

31

144

5 11

04

634

11 2

01(4

747,

171

19)

1111

Wpr

HIC

Brun

ei D

arus

sala

m0

00

00

0(0

, 17)

0.1

0.2

Eur (

LMIC

)Bu

lgar

ia8

8316

91

896

1 85

04

006

(327

1, 4

734)

107

40

Afr

Burk

ina

Faso

763

3321

579

873

2 26

9(1

179,

338

7)27

52

74

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Buru

ndi

625

2211

210

455

1 32

3(5

89, 2

082)

2642

Afr

Cab

o Ve

rde

133

2883

615

557

1 41

6(1

02, 2

163)

1932

Wpr

(LM

IC)

Cam

bodi

a1

165

6222

824

1 24

93

322

(273

7, 4

005)

3151

Afr

Cam

eroo

n1

1123

442

117

183

8(9

, 299

6)5

2

Amr (

HIC

)C

anad

a2

21

1438

57(3

5, 8

1)23

28

Afr

Cen

tral A

frica

n Re

publ

ic18

630

414

620

557

0(2

89, 8

82)

2436

Afr

Cha

d1

028

298

344

536

1 94

5(1

086,

287

7)31

47

Amr (

HIC

)C

hile

739

237

385

500

1 16

8(8

45, 1

444)

139

Wpr

(LM

IC)

Chi

na2

831

42 9

0367

281

129

846

219

575

462

436

(389

791,

542

399)

7060

Amr (

LMIC

)C

olom

bia

6612

629

91

555

886

2 93

2(2

017,

364

3)12

14

Afr

Com

oros

141

014

2756

(12,

78)

1529

Afr

Con

go12

316

217

325

556

8(2

79, 8

63)

2645

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a1

1322

147

8727

0(1

94, 3

31)

1211

Eur (

HIC

)C

roat

ia0

1814

669

344

01

297

(941

, 160

5)58

21

Amr (

LMIC

)C

uba

331

353

863

540

1 79

1(1

32, 2

638)

3218

Eur (

HIC

)C

ypru

s0

112

4025

78(5

3, 9

8)14

8

Eur (

HIC

)C

zech

Rep

ublic

133

364

1 70

268

52

786

(219

4, 3

323)

5220

Afr

Côt

e d’

Ivoi

re65

219

1658

088

12

147

(293

, 335

1)21

40

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

114

571

1 56

11

830

3 21

17

288

(890

, 123

33)

5846

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

4 66

519

925

2 22

63

836

10 9

52(5

520,

166

14)

3150

Eur (

HIC

)D

enm

ark

021

199

180

145

546

(19,

896

)19

8

Emr (

LMIC

)D

jibou

ti23

32

2541

94(3

6, 1

50)

2236

Amr (

LMIC

)D

omin

ica

00

03

36

(0, 9

)17

14

Amr (

LMIC

)D

omin

ican

Rep

ublic

3510

6457

535

01

035

(82,

147

0)20

23

Amr (

LMIC

)Ec

uado

r38

1861

380

299

797

(378

, 104

1)10

11

Emr (

LMIC

)Eg

ypt

490

868

564

10 0

187

743

19 6

82(1

6245

, 234

95)

4664

Amr (

LMIC

)El

Sal

vado

r20

4445

478

180

767

(607

, 941

)24

24

75

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Equa

toria

l Gui

nea

233

126

3588

(7, 1

48)

2342

Afr

Eritr

ea15

211

913

024

554

7(2

39, 8

40)

2246

Eur (

HIC

)Es

toni

a0

09

116

2715

2(1

, 292

)22

7

Afr

Ethi

opia

2 04

951

196

911

2 05

55

263

(197

3, 8

087)

1119

Wpr

(LM

IC)

Fiji

00

00

01

(0, 9

5)0.

10.

2

Eur (

HIC

)Fi

nlan

d0

010

100

3514

6(0

, 722

)5

2

Eur (

HIC

)Fr

ance

146

1 15

31

547

1 60

24

349

(151

4, 5

912)

135

Afr

Gab

on21

85

6487

185

(36,

295

)23

30

Afr

Gam

bia

502

145

7217

1(1

1, 2

96)

1942

Eur (

LMIC

)G

eorg

ia4

2333

1 04

476

41

868

(115

6, 2

365)

8638

Eur (

HIC

)G

erm

any

224

62

238

6 03

33

133

11 6

52(5

497,

151

13)

289

Afr

Gha

na45

033

1685

31

676

3 02

8(2

013,

392

3)23

41

Eur (

HIC

)G

reec

e0

3314

91

039

957

2 17

8(7

07, 2

867)

3813

Amr (

LMIC

)G

rena

da0

00

54

9(0

, 13)

1716

Amr (

LMIC

)G

uate

mal

a17

832

6839

823

691

2(7

36, 1

096)

1216

Afr

Gui

nea

313

125

373

515

1 21

9(1

37, 1

882)

2138

Afr

Gui

nea-

Biss

au69

22

6186

220

(18,

355

)26

44

Amr (

LMIC

)G

uyan

a2

01

5347

104

(0, 1

60)

2740

Amr (

LMIC

)H

aiti

264

652

408

815

1 54

4(1

96, 2

313)

3044

Amr (

LMIC

)H

ondu

ras

4535

3733

422

767

8(5

33, 8

32)

1826

Eur (

LMIC

)H

unga

ry2

6671

42

164

878

3 82

4(2

973,

461

8)73

29

Eur (

HIC

)Ic

elan

d0

02

52

10(0

, 32)

63

Sear

Indi

a20

455

47 2

106

202

89 7

2796

383

259

977

(214

832,

312

709)

4357

Sear

Indo

nesi

a1

081

297

1 34

15

875

18 3

4726

941

(141

14, 3

5705

)22

31

Emr (

LMIC

)Ira

n (Is

lam

ic

Repu

blic

of)

289

177

469

6 85

83

513

11 3

06(9

706,

129

63)

3046

Emr (

LMIC

)Ira

q46

669

204

1 88

41

394

4 01

6(2

657,

548

1)25

51

Eur (

HIC

)Ire

land

06

5916

971

305

(15,

480

)13

7

Eur (

HIC

)Is

rael

014

139

209

139

501

(378

, 615

)13

7

Eur (

HIC

)Ita

ly2

224

1 66

13

808

3 43

49

128

(629

7, 1

1395

)30

8

76

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)Ja

mai

ca3

218

114

184

322

(225

, 402

)23

18

Wpr

(HIC

)Ja

pan

963

2 67

04

089

5 05

211

883

(438

3, 1

5975

)18

5

Emr (

LMIC

)Jo

rdan

289

2127

623

957

3(4

92, 6

56)

1733

Eur (

LMIC

)Ka

zakh

stan

3843

121

2 94

81

744

4 89

5(5

99, 7

483)

5653

Afr

Keny

a89

214

3147

781

52

229

(865

, 305

2)10

18

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 7

)0.

00.

0

Emr (

HIC

)Ku

wai

t5

19

7542

131

(116

, 147

)9

34

Eur (

LMIC

)Ky

rgyz

stan

2114

1863

929

198

3(3

80, 1

283)

3447

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

167

2435

325

305

856

(353

, 125

3)26

45

Eur (

HIC

)La

tvia

02

3459

129

692

3(6

77, 1

121)

8327

Emr (

LMIC

)Le

bano

n3

1062

274

160

508

(417

, 599

)21

21

Afr

Leso

tho

386

148

120

213

(0, 3

87)

2029

Afr

Libe

ria31

21

3747

117

(0, 3

07)

611

Emr (

LMIC

)Li

bya

1323

3143

333

183

1(5

78, 1

113)

2745

Eur (

HIC

)Li

thua

nia

04

3476

534

21

146

(865

, 137

9)70

24

Eur (

HIC

)Lu

xem

bour

g0

212

1417

45(3

0, 5

7)17

8

Afr

Mad

agas

car

410

2324

489

1 01

51

961

(910

, 265

9)18

36

Afr

Mal

awi

383

175

371

664

1 44

1(4

4, 2

267)

1835

Wpr

(LM

IC)

Mal

aysi

a13

4222

01

342

820

2 43

6(1

379,

312

4)17

27

Sear

Mal

dive

s0

10

95

16(4

, 22)

917

Afr

Mal

i1

046

4720

647

924

2 68

5(1

469,

399

8)34

62

Eur (

HIC

)M

alta

00

632

1251

(26,

64)

2511

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia12

910

412

319

445

9(2

84, 6

74)

2444

Afr

Mau

ritiu

s1

06

5335

95(3

9, 1

22)

1512

Amr (

LMIC

)M

exic

o20

534

850

54

307

2 25

57

620

(562

0, 9

341)

1214

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

00

0(0

, 7)

0.1

0.1

Eur (

HIC

)M

onac

o0

00

21

4(0

, 6)

186

77

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Wpr

(LM

IC)

Mon

golia

157

1322

419

845

8(3

16, 5

67)

3253

Eur (

LMIC

)M

onte

negr

o0

019

4763

130

(97,

161

)41

22

Emr (

LMIC

)M

oroc

co15

928

851

506

1 99

13

769

(285

1, 4

570)

2327

Afr

Moz

ambi

que

567

3321

313

636

1 56

9(6

4, 2

509)

1219

Sear

Mya

nmar

644

893

1 20

83

257

5 49

111

493

(951

1, 1

3676

)43

56

Afr

Nam

ibia

165

350

103

177

(22,

275

)15

28

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al35

490

243

81

446

1 58

84

728

(350

5, 6

257)

3351

Eur (

HIC

)N

ethe

rland

s1

6469

247

549

41

726

(953

, 230

7)20

9

Wpr

(HIC

)N

ew Z

eala

nd0

02

53

10(0

, 230

)0.

40.

2

Amr (

LMIC

)N

icar

agua

3019

2529

019

055

4(8

1, 8

37)

1925

Afr

Nig

er1

313

431

559

942

2 85

9(1

773,

419

3)33

58

Afr

Nig

eria

9 51

927

613

24

347

7 00

821

283

(173

47, 2

5554

)26

42

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay0

659

146

9130

2(1

0, 5

83)

125

Emr (

HIC

)O

man

52

688

6616

7(1

14, 2

23)

1329

Emr (

LMIC

)Pa

kist

an5

883

1 31

336

19

764

9 06

826

390

(220

64, 3

1251

)31

49

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a8

311

8469

174

(21,

253

)9

9

Wpr

(LM

IC)

Papu

a N

ew G

uine

a75

39

8542

214

(0, 4

88)

610

Amr (

LMIC

)Pa

ragu

ay18

522

200

204

450

(206

, 588

)14

19

Amr (

LMIC

)Pe

ru72

6631

284

765

11

948

(149

8, 2

377)

1314

Wpr

(LM

IC)

Philip

pine

s75

616

063

65

226

4 29

711

074

(852

0, 1

3378

)23

34

Eur (

HIC

)Po

land

517

11

678

5 28

44

514

11 6

51(9

373,

138

62)

5825

Eur (

HIC

)Po

rtuga

l0

667

273

415

762

(25,

121

1)14

5

Emr (

HIC

)Q

atar

11

521

734

(30,

38)

728

Wpr

(HIC

)Re

publ

ic o

f Kor

ea3

891

326

1 10

01

914

4 43

1(3

523,

533

8)18

10

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

79

381

024

433

1 51

2(0

, 236

6)71

45

Eur (

LMIC

)Ro

man

ia40

5143

23

037

2 76

76

327

(483

0, 7

618)

6226

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

6219

21

682

39 3

1326

465

67 7

14(2

7433

, 922

71)

8841

78

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Rwan

da32

916

722

245

21

026

(562

, 153

1)18

33

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

00

16

916

(2, 2

4)18

15

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s0

00

64

11(0

, 15)

2019

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe2

00

47

13(0

, 20)

1526

Emr (

HIC

)Sa

udi A

rabi

a29

9092

1 42

91

559

3 19

9(2

746,

369

5)25

56

Afr

Sene

gal

265

2412

263

398

962

(768

, 116

5)14

26

Eur (

LMIC

)Se

rbia

133

363

829

1 08

02

306

(164

9, 2

892)

5024

Afr

Seyc

helle

s0

00

42

7(0

, 10)

1512

Afr

Sier

ra L

eone

353

63

203

323

887

(0, 1

582)

2951

Wpr

(HIC

)Si

ngap

ore

14

9519

812

242

0(2

08, 5

66)

1611

Eur (

HIC

)Sl

ovak

ia2

611

11

072

421

1 61

2(1

250,

192

8)58

28

Eur (

HIC

)Sl

oven

ia0

463

112

134

313

(227

, 389

)30

11

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 2

7)0.

00.

0

Emr (

LMIC

)So

mal

ia62

710

1011

321

997

9(5

5, 1

714)

1924

Afr

Sout

h Af

rica

509

162

579

1 98

73

690

6 92

8(5

511,

828

1)26

31

Emr (

LMIC

)So

uth

Suda

n52

416

1421

542

01

190

(577

, 175

7)22

32

Eur (

HIC

)Sp

ain

126

324

1 24

998

02

581

(426

, 398

1)11

4

Sear

Sri L

anka

1396

100

1 74

596

12

915

(211

7, 3

689)

2826

Emr (

LMIC

)Su

dan

1 22

475

4075

91

537

3 63

5(2

095,

535

0)19

32

Amr (

LMIC

)Su

rinam

e0

02

1316

32(0

, 52)

1213

Afr

Swaz

iland

234

127

5511

0(0

, 183

)18

30

Eur (

HIC

)Sw

eden

00

212

619

(0, 9

26)

0.4

0.1

Eur (

HIC

)Sw

itzer

land

012

148

328

172

660

(160

, 899

)16

6

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

4822

961

418

513

2 09

7(1

261,

286

2)21

41

Eur (

LMIC

)Ta

jikis

tan

214

4736

893

700

1 88

9(1

070,

274

1)48

92

79

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Sear

Thai

land

4221

91

424

4 32

03

406

9 41

2(7

563,

112

00)

2821

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

18

5314

134

254

3(4

42, 6

50)

5233

Sear

Tim

or-L

este

231

938

2999

(0, 1

87)

1829

Afr

Togo

231

74

189

296

727

(145

, 115

4)21

40

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o1

08

8344

137

(0, 2

00)

2017

Emr (

LMIC

)Tu

nisi

a19

4329

1 01

073

21

833

(148

9, 2

188)

3332

Eur (

LMIC

)Tu

rkey

101

411

862

6 27

35

054

12 7

01(1

0666

, 148

18)

3333

Eur (

LMIC

)Tu

rkm

enis

tan

5326

261

037

482

1 62

4(4

83, 2

310)

6289

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

1 33

597

6666

01

393

3 55

2(2

767,

447

3)20

39

Eur (

LMIC

)U

krai

ne26

7643

920

654

7 47

928

673

(245

, 413

29)

118

48

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

34

1359

3911

8(1

00, 1

37)

526

Eur (

HIC

)U

nite

d Ki

ngdo

m6

207

2 16

62

843

2 20

77

429

(222

2, 1

0324

)23

9

Afr

Uni

ted

Repu

blic

of

Tanz

ania

841

4715

692

980

2 57

5(1

568,

341

6)11

19

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1537

84

004

9 35

53

362

17 1

13(6

08, 3

6782

)11

5

Amr (

HIC

)U

rugu

ay2

436

117

120

278

(74,

380

)16

8

Eur (

LMIC

)U

zbek

ista

n30

390

111

4 62

22

560

7 68

5(3

717,

109

05)

5371

Wpr

(LM

IC)

Vanu

atu

00

00

01

(0, 1

4)1

1

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

5462

344

1 25

374

82

461

(176

3, 3

091)

1620

Wpr

(LM

IC)

Viet

Nam

230

557

1 24

52

177

7 29

211

502

(831

2, 1

4709

)25

21

Emr (

LMIC

)Ye

men

631

6429

1 06

099

72

781

(124

2, 4

274)

2349

Afr

Zam

bia

473

1310

210

379

1 08

4(2

95, 1

633)

1524

Afr

Zim

babw

e34

523

4119

436

596

8(7

0, 1

524)

1322

AAP

: Am

bien

t air

pollu

tion ;

ALR

I : Ac

ute

low

er re

spira

tory

dis

ease

; CO

PD : C

hron

ic o

bstru

ctiv

e pu

lmon

ary

dise

ase ;

IHD

: Isc

haem

ic h

eart

dise

ase.

Afr

: Afri

ca ; A

mr :

Am

eric

a ; E

mr :

Eas

tern

Med

iterra

nean

; Eu

r : E

urop

e ; S

ear:

Sout

h-Ea

st A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

; NA

: Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

81

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n1

974

100

224

1 98

51

318

5 60

1(4

497,

682

9)37

80

Eur (

LMIC

)Al

bani

a5

1112

145

134

092

8(3

79, 1

237)

6451

Afr

Alge

ria19

284

515

3 08

82

694

6 57

3(2

638,

929

3)35

48

Eur (

HIC

)An

dorra

00

28

312

(0, 1

8)31

17

Afr

Ango

la2

235

7726

838

786

3 96

2(7

50, 6

449)

3556

Amr (

HIC

)An

tigua

and

Bar

buda

00

15

39

(0, 1

3)22

24

Amr (

LMIC

)Ar

gent

ina

4911

11

057

2 88

01

364

5 46

2(1

548,

754

7)27

26

Eur (

LMIC

)Ar

men

ia5

3230

692

232

41

589

(67,

247

4)10

795

Wpr

(HIC

)Au

stra

lia0

09

348

51(1

, 152

0)0.

40.

3

Eur (

HIC

)Au

stria

035

437

845

200

1 51

8(1

047,

189

0)37

20

Eur (

LMIC

)Az

erba

ijan

7526

186

1 48

156

62

334

(540

, 338

2)50

69

Amr (

HIC

)Ba

ham

as2

03

189

32(0

, 48)

1823

Emr (

HIC

)Ba

hrai

n1

418

5122

96(8

6, 1

07)

1237

Sear

Bang

lade

sh2

121

4 58

73

516

6 94

65

195

22 3

65(1

8175

, 273

11)

2945

Amr (

HIC

)Ba

rbad

os0

03

129

24(0

, 35)

1813

Eur (

LMIC

)Be

laru

s3

4649

33

392

940

4 87

3(1

00, 7

150)

110

88

Eur (

HIC

)Be

lgiu

m1

7491

377

732

02

085

(130

1, 2

703)

3821

Amr (

LMIC

)Be

lize

01

29

619

(3, 2

9)11

22

Afr

Beni

n39

226

1238

051

21

322

(455

, 202

8)26

56

Sear

Bhut

an12

187

4524

106

(84,

132

)27

39

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

145

3343

617

518

1 35

7(1

070,

163

5)26

35

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na1

5645

877

562

41

915

(148

0, 2

370)

100

67

Afr

Bots

wan

a18

28

3946

113

(1, 1

77)

1124

Amr (

LMIC

)Br

azil

108

317

1 75

77

877

4 98

215

041

(648

6, 2

2871

)15

18

Wpr

HIC

Brun

ei D

arus

sala

m0

00

00

0(0

, 24)

0.2

0.3

Eur (

LMIC

)Bu

lgar

ia12

112

791

2 13

51

578

4 62

8(3

756,

548

3)13

073

Afr

Burk

ina

Faso

888

3924

541

862

2 35

4(1

202,

353

6)29

65

Afr

Buru

ndi

753

2310

322

570

1 67

7(7

59, 2

607)

3455

82

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Cab

o Ve

rde

182

3514

763

452

11

519

(116

, 234

8)21

44

Wpr

(LM

IC)

Cam

bodi

a1

456

107

4091

11

163

3 67

7(3

017,

445

7)34

58

Afr

Cam

eroo

n0

1226

963

912

91

049

(17,

361

2)6

4

Amr (

HIC

)C

anad

a3

51

2339

70(4

4, 1

00)

2849

Afr

Cen

tral A

frica

n Re

publ

ic26

634

816

017

664

4(3

20, 1

007)

2844

Afr

Cha

d1

398

3312

388

564

2 39

5(1

324,

356

1)38

56

Amr (

HIC

)C

hile

1149

350

702

542

1 65

4(1

216,

202

4)19

18

Wpr

(LM

IC)

Chi

na3

885

47 7

2416

1 19

812

7 79

122

9 79

857

0 39

6(4

7890

4, 6

6994

9)81

81

Amr (

LMIC

)C

olom

bia

9214

444

92

133

752

3 57

1(2

479,

442

2)15

20

Afr

Com

oros

171

118

3369

(16,

96)

1939

Afr

Con

go20

127

621

322

967

6(3

25, 1

046)

3255

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a1

1343

233

8437

4(2

73, 4

55)

1617

Eur (

HIC

)C

roat

ia0

3143

771

136

61

546

(107

8, 1

953)

7543

Amr (

LMIC

)C

uba

440

622

1 12

654

52

337

(191

, 348

0)41

28

Eur (

HIC

)C

ypru

s0

244

8020

145

(96,

184

)25

20

Eur (

HIC

)C

zech

Rep

ublic

250

846

1 91

750

93

324

(258

2, 3

990)

6440

Afr

Côt

e d’

Ivoi

re77

945

2681

41

157

2 82

3(3

92, 4

417)

2645

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

117

639

1 77

22

080

3 70

08

308

(108

1, 1

4021

)69

87

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

5 85

527

462

2 60

23

289

12 0

82(6

010,

184

71)

3455

Eur (

HIC

)D

enm

ark

018

203

253

119

593

(32,

949

)21

12

Emr (

LMIC

)D

jibou

ti31

22

3250

118

(45,

186

)28

48

Amr (

LMIC

)D

omin

ica

00

13

26

(0, 1

0)18

18

Amr (

LMIC

)D

omin

ican

Rep

ublic

5010

101

523

291

974

(88,

139

5)19

24

Amr (

LMIC

)Ec

uado

r49

2491

495

316

975

(480

, 126

9)13

16

Emr (

LMIC

)Eg

ypt

461

1 10

01

515

12 3

108

463

23 8

49(1

9760

, 283

30)

5593

Amr (

LMIC

)El

Sal

vado

r26

3253

475

146

731

(582

, 888

)26

30

Afr

Equa

toria

l Gui

nea

395

449

4214

0(1

1, 2

36)

3557

83

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Eritr

ea21

111

817

728

969

7(3

04, 1

065)

2868

Eur (

HIC

)Es

toni

a0

127

118

2116

7(2

, 334

)27

18

Afr

Ethi

opia

3 51

634

918

01

409

2 54

07

994

(290

2, 1

2647

)17

28

Wpr

(LM

IC)

Fiji

00

01

01

(0, 2

08)

0.3

0.4

Eur (

HIC

)Fi

nlan

d0

121

133

2718

1(1

, 892

)7

4

Eur (

HIC

)Fr

ance

380

3 10

32

246

1 17

26

605

(228

2, 9

311)

2112

Afr

Gab

on38

1111

7368

200

(40,

328

)25

38

Afr

Gam

bia

645

455

8721

5(1

3, 3

79)

2450

Eur (

LMIC

)G

eorg

ia8

3015

91

083

594

1 87

3(1

176,

237

9)95

68

Eur (

HIC

)G

erm

any

332

34

583

7 35

92

240

14 5

08(6

932,

191

42)

3718

Afr

Gha

na51

739

5995

71

128

2 70

0(1

801,

348

9)21

42

Eur (

HIC

)G

reec

e1

3869

41

349

748

2 82

9(9

88, 3

824)

5226

Amr (

LMIC

)G

rena

da0

01

75

13(0

, 19)

2432

Amr (

LMIC

)G

uate

mal

a21

837

9448

223

71

068

(862

, 128

3)14

23

Afr

Gui

nea

376

1911

350

491

1 24

7(1

36, 1

950)

2138

Afr

Gui

nea-

Biss

au90

42

5988

243

(19,

399

)29

49

Amr (

LMIC

)G

uyan

a2

12

7052

126

(0, 1

93)

3347

Amr (

LMIC

)H

aiti

310

846

393

720

1 47

8(1

84, 2

220)

2948

Amr (

LMIC

)H

ondu

ras

5446

5647

526

689

6(7

09, 1

095)

2339

Eur (

LMIC

)H

unga

ry2

931

286

2 16

178

24

324

(330

0, 5

271)

9159

Eur (

HIC

)Ic

elan

d0

02

72

11(0

, 32)

74

Sear

Indi

a19

459

63 2

9120

132

159

661

98 6

1836

1 16

1(3

0041

8, 4

3187

3)55

80

Sear

Indo

nesi

a1

453

703

3 60

910

906

18 1

7934

851

(185

54, 4

6214

)28

45

Emr (

LMIC

)Ira

n (Is

lam

ic

Repu

blic

of)

311

257

991

9 62

63

776

14 9

61(1

2870

, 171

01)

3954

Emr (

LMIC

)Ira

q54

410

452

43

090

1 80

76

069

(403

2, 8

209)

3689

Eur (

HIC

)Ire

land

06

8423

453

377

(26,

591

)16

13

Eur (

HIC

)Is

rael

121

273

300

123

718

(533

, 887

)19

16

Eur (

HIC

)Ita

ly1

335

4 73

04

484

2 38

011

929

(793

4, 1

5165

)41

18

Amr (

LMIC

)Ja

mai

ca5

664

132

164

371

(257

, 468

)27

26

84

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Wpr

(HIC

)Ja

pan

921

87

072

6 19

75

410

18 9

07(7

055,

260

40)

3113

Emr (

LMIC

)Jo

rdan

3525

138

468

244

910

(776

, 104

9)25

54

Eur (

LMIC

)Ka

zakh

stan

5074

548

3 35

81

367

5 39

8(6

97, 8

392)

6791

Afr

Keny

a1

129

1747

715

965

2 87

3(1

130,

392

0)14

25

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 1

5)0.

00.

0

Emr (

HIC

)Ku

wai

t8

226

245

7535

6(3

17, 3

97)

1952

Eur (

LMIC

)Ky

rgyz

stan

2819

5571

832

61

145

(468

, 150

2)41

75

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

232

2487

344

315

1 00

1(4

04, 1

477)

3160

Eur (

HIC

)La

tvia

05

165

565

200

937

(678

, 115

0)10

165

Emr (

LMIC

)Le

bano

n3

1514

764

711

492

6(7

66, 1

080)

3739

Afr

Leso

tho

449

541

7517

5(0

, 332

)17

33

Afr

Libe

ria33

21

3845

119

(0, 3

14)

611

Emr (

LMIC

)Li

bya

1837

220

605

343

1 22

2(8

29, 1

646)

3873

Eur (

HIC

)Li

thua

nia

012

189

659

210

1 07

0(7

96, 1

302)

7751

Eur (

HIC

)Lu

xem

bour

g0

225

2212

61(3

9, 7

8)23

15

Afr

Mad

agas

car

504

2311

164

696

82

253

(104

7, 3

058)

2042

Afr

Mal

awi

364

248

326

542

1 26

4(4

2, 2

006)

1635

Wpr

(LM

IC)

Mal

aysi

a16

106

450

2 28

895

43

814

(216

6, 4

914)

2737

Sear

Mal

dive

s0

13

1415

32(8

, 43)

1929

Afr

Mal

i1

245

107

2947

567

72

533

(132

6, 3

904)

3157

Eur (

HIC

)M

alta

01

2144

1378

(39,

100

)38

22

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia21

113

611

417

551

9(3

14, 7

79)

2749

Afr

Mau

ritiu

s1

117

9247

158

(68,

204

)25

26

Amr (

LMIC

)M

exic

o26

239

383

15

677

2 01

49

178

(683

7, 1

1188

)15

20

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

00

0(0

, 12)

0.1

0.2

Eur (

HIC

)M

onac

o0

01

21

4(0

, 8)

2312

Wpr

(LM

IC)

Mon

golia

2411

4734

723

666

5(4

62, 8

22)

4889

Eur (

LMIC

)M

onte

negr

o0

158

112

8125

2(1

87, 3

11)

8259

85

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)M

oroc

co21

056

683

1 87

31

544

4 36

6(3

247,

534

4)27

34

Afr

Moz

ambi

que

784

2537

285

642

1 77

3(6

7, 2

850)

1424

Sear

Mya

nmar

887

669

1 57

22

219

5 82

511

171

(923

4, 1

3274

)44

68

Afr

Nam

ibia

186

642

5813

0(1

6, 2

06)

1226

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al38

586

948

41

882

1 59

55

216

(392

2, 6

802)

3961

Eur (

HIC

)N

ethe

rland

s1

741

147

727

342

2 29

1(1

220,

308

9)28

16

Wpr

(HIC

)N

ew Z

eala

nd0

02

72

11(0

, 235

)0.

50.

3

Amr (

LMIC

)N

icar

agua

4221

3938

120

969

2(1

11, 1

037)

2439

Afr

Nig

er1

855

557

514

894

3 32

5(2

028,

495

0)37

56

Afr

Nig

eria

12 7

1437

613

25

271

6 97

525

467

(206

92, 3

0689

)30

46

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay0

679

184

6633

4(1

4, 6

44)

138

Emr (

HIC

)O

man

54

1916

811

431

0(2

12, 4

11)

1442

Emr (

LMIC

)Pa

kist

an7

800

4 37

52

032

11 0

087

637

32 8

52(2

6659

, 401

54)

3656

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a7

325

143

7325

0(3

3, 3

62)

1315

Wpr

(LM

IC)

Papu

a N

ew G

uine

a91

617

101

9030

5(0

, 721

)8

15

Amr (

LMIC

)Pa

ragu

ay24

1087

329

260

709

(327

, 936

)22

32

Amr (

LMIC

)Pe

ru91

6233

91

103

697

2 29

1(1

779,

277

2)15

20

Wpr

(LM

IC)

Philip

pine

s91

043

91

605

8 84

15

827

17 6

22(1

3500

, 213

70)

3661

Eur (

HIC

)Po

land

731

24

053

6 70

43

863

14 9

38(1

1904

, 178

34)

8056

Eur (

HIC

)Po

rtuga

l0

1325

637

436

41

007

(42,

168

5)20

10

Emr (

HIC

)Q

atar

11

3084

2914

5(1

28, 1

62)

1032

Wpr

(HIC

)Re

publ

ic o

f Kor

ea5

195

3 36

91

538

1 98

57

092

(552

0, 8

637)

2925

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

817

150

943

378

1 49

6(0

, 241

2)76

72

Eur (

LMIC

)Ro

man

ia48

113

1 68

33

757

2 56

98

170

(613

7, 9

965)

8454

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

7253

18

158

44 6

2419

752

73 1

37(3

1229

, 100

241)

110

91

Afr

Rwan

da40

918

1227

448

81

201

(657

, 179

0)23

48

86

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

10

29

921

(3, 3

1)24

24

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s0

01

64

10(0

, 15)

1923

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe3

01

35

12(0

, 19)

1327

Emr (

HIC

)Sa

udi A

rabi

a30

145

270

2 69

91

776

4 92

1(4

282,

560

4)30

78

Afr

Sene

gal

348

4320

266

366

1 04

3(8

25, 1

274)

1531

Eur (

LMIC

)Se

rbia

355

978

1 22

187

23

128

(216

4, 3

974)

7145

Afr

Seyc

helle

s0

01

63

11(1

, 16)

2227

Afr

Sier

ra L

eone

392

95

195

294

895

(0, 1

614)

3049

Wpr

(HIC

)Si

ngap

ore

112

190

346

126

674

(336

, 914

)26

22

Eur (

HIC

)Sl

ovak

ia2

1530

41

139

392

1 85

2(1

422,

222

8)71

55

Eur (

HIC

)Sl

oven

ia0

715

315

310

641

9(2

94, 5

27)

4125

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 5

4)0.

00.

0

Emr (

LMIC

)So

mal

ia73

66

1216

025

21

165

(67,

202

0)23

30

Afr

Sout

h Af

rica

651

302

1 05

92

622

2 79

67

429

(587

6, 8

928)

2953

Emr (

LMIC

)So

uth

Suda

n67

627

1827

844

41

442

(693

, 213

8)26

40

Eur (

HIC

)Sp

ain

298

1 51

01

885

785

4 27

9(7

59, 7

106)

1910

Sear

Sri L

anka

1917

826

63

101

1 31

24

877

(355

5, 6

154)

4954

Emr (

LMIC

)Su

dan

1 65

412

478

979

1 62

44

458

(254

9, 6

608)

2440

Amr (

LMIC

)Su

rinam

e2

06

1816

42(0

, 70)

1620

Afr

Swaz

iland

293

319

2478

(0, 1

35)

1325

Eur (

HIC

)Sw

eden

00

215

421

(0, 9

61)

0.4

0.2

Eur (

HIC

)Sw

itzer

land

016

260

422

123

821

(227

, 113

2)21

11

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

6744

442

2 36

198

33

898

(227

8, 5

388)

3980

Eur (

LMIC

)Ta

jikis

tan

287

3959

850

489

1 72

6(9

75, 2

507)

4386

Sear

Thai

land

6175

72

899

5 34

93

896

12 9

62(1

0209

, 157

31)

3935

87

Num

ber o

f dea

ths

Dea

ths

per 1

00 0

00 c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

115

239

249

319

823

(663

, 986

)80

64

Sear

Tim

or-L

este

271

1835

2911

0(0

, 216

)20

33

Afr

Togo

252

129

184

270

727

(142

, 116

8)22

43

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o1

219

140

5221

4(0

, 316

)32

32

Emr (

LMIC

)Tu

nisi

a25

5946

31

454

795

2 79

8(2

246,

335

4)52

57

Eur (

LMIC

)Tu

rkey

139

653

5 63

68

540

4 99

919

967

(164

80, 2

3516

)54

68

Eur (

LMIC

)Tu

rkm

enis

tan

7729

881

388

462

2 04

3(6

32, 2

888)

8013

1

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

1 80

695

6096

31

512

4 43

6(3

471,

556

8)25

53

Eur (

LMIC

)U

krai

ne37

192

2 20

518

054

5 34

625

834

(366

, 378

75)

123

89

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

69

4934

013

453

7(4

64, 6

12)

828

Eur (

HIC

)U

nite

d Ki

ngdo

m7

217

2 63

74

523

1 54

28

926

(300

6, 1

2230

)29

16

Afr

Uni

ted

Repu

blic

of

Tanz

ania

1 07

263

2190

71

128

3 19

0(1

942,

422

7)13

24

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1834

34

833

13 2

052

531

20 9

30(8

82, 4

4069

)13

9

Amr (

HIC

)U

rugu

ay2

1013

419

297

434

(118

, 617

)27

20

Eur (

LMIC

)U

zbek

ista

n41

910

633

35

362

2 37

68

597

(422

1, 1

2158

)61

103

Wpr

(LM

IC)

Vanu

atu

00

01

12

(0, 2

8)1

2

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

7164

470

2 21

383

43

652

(266

2, 4

521)

2535

Wpr

(LM

IC)

Viet

Nam

361

570

3 65

12

903

8 35

215

838

(114

14, 2

0146

)35

48

Emr (

LMIC

)Ye

men

785

7194

1 78

91

147

3 88

6(1

779,

587

6)31

69

Afr

Zam

bia

523

514

309

475

1 32

7(3

82, 1

968)

1836

Afr

Zim

babw

e35

528

8217

225

188

8(6

4, 1

425)

1223

AAP

: Am

bien

t air

pollu

tion ;

ALR

I : Ac

ute

low

er r

espi

rato

ry d

isea

se ;

CO

PD :

Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; IH

D :

Isch

aem

ic h

eart

dise

ase.

Afr

: Afri

ca ;

Amr :

Am

eric

a ; E

mr :

Eas

tern

Med

iterra

nean

; Eu

r : E

urop

e; S

ear :

Sou

th-E

ast A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

; NA

: Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

89

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n34

2 27

84

660

9 76

212

0 81

388

567

566

080

(445

478,

704

450)

1 90

42

456

Eur (

LMIC

)Al

bani

a73

634

64

553

16 5

7514

364

36 5

75(1

5359

, 487

21)

1 27

097

9

Afr

Alge

ria30

968

2 78

819

267

136

594

134

408

324

026

(130

976,

457

620)

865

1 07

2

Eur (

HIC

)An

dorra

04

5723

085

377

(11,

564

)47

526

1

Afr

Ango

la33

4 71

63

243

1 14

746

867

53 6

1443

9 58

7(6

7634

, 731

631)

1 93

81

794

Amr (

HIC

)An

tigua

and

Bar

buda

71

2225

215

944

0(0

, 637

)49

450

8

Amr (

LMIC

)Ar

gent

ina

7 71

03

240

37 2

2310

9 17

857

557

214

908

(633

34, 2

9534

5)51

145

1

Eur (

LMIC

)Ar

men

ia75

092

59

666

30 9

6512

773

55 0

79(2

607,

851

84)

1 84

91

467

Wpr

(HIC

)Au

stra

lia6

1130

01

026

288

1 63

1(2

5, 4

8436

)7

5

Eur (

HIC

)Au

stria

791

023

16 4

2626

617

7 77

451

919

(355

31, 6

4880

)61

433

4

Eur (

LMIC

)Az

erba

ijan

12 2

5393

67

393

60 8

1528

109

109

506

(256

10, 1

6002

5)1

170

1 34

8

Amr (

HIC

)Ba

ham

as27

13

125

627

367

1 39

3(5

, 212

7)37

439

0

Emr (

HIC

)Ba

hrai

n14

614

561

42

221

1 08

04

207

(376

9, 4

651)

315

659

Sear

Bang

lade

sh34

9 66

316

7 79

712

0 66

126

4 73

623

9 16

71

142

024

(938

727,

138

2416

)73

61

007

Amr (

HIC

)Ba

rbad

os58

492

457

361

972

(0, 1

428)

345

254

Eur (

LMIC

)Be

laru

s34

11

195

15 1

4414

4 98

542

857

204

523

(452

8, 2

9617

5)2

155

1 39

9

Eur (

HIC

)Be

lgiu

m12

31

839

27 7

5523

954

11 3

5565

026

(409

25, 8

3926

)58

733

3

Amr (

LMIC

)Be

lize

8419

7835

726

880

6(1

33, 1

216)

239

424

Afr

Beni

n64

834

1 04

556

422

852

31 7

2912

1 02

4(3

7122

, 190

585)

1 20

41

547

Sear

Bhut

an1

854

645

463

2 30

71

412

6 68

2(5

402,

814

0)89

81

195

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

24 0

911

356

2 22

331

861

28 9

0788

439

(688

06, 1

0734

0)86

41

010

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na21

21

875

14 8

4929

104

28 2

6374

303

(577

91, 9

1575

)1

941

1 18

3

Afr

Bots

wan

a3

222

6327

12

245

3 55

19

353

(51,

147

94)

439

657

Amr (

LMIC

)Br

azil

17 9

5310

115

74 3

6035

4 71

623

9 36

769

6 51

1(3

0181

3, 1

0530

85)

344

363

Wpr

HIC

Brun

ei D

arus

sala

m0

01

145

21(0

, 116

0)5

7

Eur (

LMIC

)Bu

lgar

ia1

810

3 46

226

434

79 4

5363

521

174

680

(142

448,

206

211)

2 39

21

302

Afr

Burk

ina

Faso

149

811

1 86

91

412

34 0

0052

792

239

884

(114

860,

370

840)

1 44

61

764

90

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Buru

ndi

125

078

1 26

469

217

513

30 9

4717

5 49

4(7

2493

, 282

653)

1 73

31

684

Afr

Cab

o Ve

rde

28 6

051

172

6 85

035

272

29 6

9710

1 59

6(7

214,

157

893)

685

938

Wpr

(LM

IC)

Cam

bodi

a23

7 84

14

061

2 36

950

212

69 5

1536

3 99

9(2

9447

7, 4

4962

1)1

681

1 79

7

Afr

Cam

eroo

n91

342

10 8

3620

685

4 82

836

782

(667

, 128

437)

105

64

Amr (

HIC

)C

anad

a46

112

041

792

1 62

23

037

(188

3, 4

261)

606

868

Afr

Cen

tral A

frica

n Re

publ

ic41

024

1 38

636

68

325

10 2

3361

334

(287

45, 9

7338

)1

328

1 35

6

Afr

Cha

d22

0 18

41

545

688

21 8

6532

829

277

111

(146

456,

422

581)

2 17

91

906

Amr (

HIC

)C

hile

1 55

01

341

13 4

1626

362

22 2

4364

913

(479

70, 7

9146

)37

331

8

Wpr

(LM

IC)

Chi

na61

1 12

11

487

398

5 19

2 60

55

586

044

10 1

74 9

6423

052

132

(195

4371

6,

2680

7904

)1

691

1 50

7

Amr (

LMIC

)C

olom

bia

14 3

824

440

18 3

7589

424

41 9

8316

8 60

4(1

1775

6, 2

0785

9)36

040

8

Afr

Com

oros

2 87

040

2995

31

691

5 58

3(9

34, 7

945)

761

1 00

8

Afr

Con

go29

392

925

205

10 8

0513

452

54 7

79(2

4516

, 864

06)

1 27

81

490

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a16

736

11

489

9 16

23

710

14 8

89(1

0973

, 179

78)

320

319

Eur (

HIC

)C

roat

ia34

821

14 6

1426

245

14 5

3956

253

(396

13, 7

0634

)1

312

706

Amr (

LMIC

)C

uba

593

1 28

823

280

42 3

5422

408

89 9

23(8

044,

133

450)

793

555

Eur (

HIC

)C

ypru

s13

391

327

2 78

472

94

892

(329

1, 6

130)

433

329

Eur (

HIC

)C

zech

Rep

ublic

257

1 58

929

092

65 2

9220

142

116

373

(905

11, 1

3952

2)1

104

618

Afr

Côt

e d’

Ivoi

re12

9 98

21

756

1 29

245

243

66 0

2224

4 29

5(2

6116

, 393

384)

1 15

81

396

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

20 9

0723

675

88 1

9096

799

169

397

398

968

(548

84, 6

6268

1)1

611

1 52

8

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

955

030

11 3

642

589

144

887

212

525

1 32

6 39

6(6

1663

6, 2

0801

28)

1 88

71

809

Eur (

HIC

)D

enm

ark

1363

48

768

7 77

14

463

21 6

50(1

208,

355

99)

387

217

Emr (

LMIC

)D

jibou

ti4

895

116

135

1 57

62

398

9 12

0(3

063,

149

57)

1 06

91

296

Amr (

LMIC

)D

omin

ica

73

2714

613

131

4(1

7, 4

60)

439

423

Amr (

LMIC

)D

omin

ican

Rep

ublic

7 68

434

93

958

25 1

5114

794

51 9

36(4

994,

744

10)

511

603

Amr (

LMIC

)Ec

uado

r7

813

634

3 43

818

890

13 9

8144

756

(223

13, 5

8308

)29

033

2

Emr (

LMIC

)Eg

ypt

86 4

3241

035

61 1

7657

9 45

940

5 95

61

174

059

(977

014,

138

9703

)1

371

1 87

6

Amr (

LMIC

)El

Sal

vado

r4

155

1 22

12

280

22 3

937

739

37 7

87(3

0163

, 457

49)

622

694

91

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Equa

toria

l Gui

nea

5 63

618

318

22

279

2 28

110

561

(553

, 183

43)

1 36

51

545

Afr

Eritr

ea32

875

619

588

9 64

415

798

59 5

24(2

3614

, 941

05)

1 21

71

685

Eur (

HIC

)Es

toni

a15

1683

24

190

926

5 97

9(9

4, 1

1818

)45

225

1

Afr

Ethi

opia

505

240

9 51

912

822

64 0

4511

7 45

870

9 08

4(2

3159

4, 1

1343

57)

769

781

Wpr

(LM

IC)

Fiji

20

052

963

(0, 9

613)

79

Eur (

HIC

)Fi

nlan

d11

2068

53

903

983

5 60

1(3

2, 2

7740

)10

352

Eur (

HIC

)Fr

ance

354

1 84

310

4 13

267

410

43 1

6921

6 90

7(7

6667

, 306

566)

341

203

Afr

Gab

on5

279

340

497

3 14

63

452

12 7

14(2

213,

208

86)

788

921

Afr

Gam

bia

10 3

4718

116

13

180

5 07

018

938

(790

, 343

69)

1 04

81

400

Eur (

LMIC

)G

eorg

ia1

109

925

5 10

240

220

25 9

2573

280

(464

65, 9

2862

)1

771

1 15

9

Eur (

HIC

)G

erm

any

462

9 48

215

6 41

822

6 87

884

821

478

060

(230

550,

632

146)

594

292

Afr

Gha

na87

880

1 71

82

304

52 6

1080

135

224

647

(143

698,

295

100)

879

1 18

8

Eur (

HIC

)G

reec

e92

1 03

018

944

43 0

8426

883

90 0

33(3

3231

, 120

529)

810

426

Amr (

LMIC

)G

rena

da3

229

258

204

496

(0, 7

20)

470

554

Amr (

LMIC

)G

uate

mal

a35

958

1 13

14

319

21 1

9211

548

74 1

47(5

8770

, 902

13)

482

570

Afr

Gui

nea

62 6

3082

960

022

249

30 9

7911

7 28

7(1

0043

, 187

988)

1 00

91

211

Afr

Gui

nea-

Biss

au14

444

167

115

3 47

25

041

23 2

39(1

203,

392

55)

1 35

51

493

Amr (

LMIC

)G

uyan

a30

020

120

3 84

53

057

7 34

1(2

, 112

67)

968

1 18

4

Amr (

LMIC

)H

aiti

52 0

2429

32

571

21 3

0040

672

116

861

(110

65, 1

8008

9)1

136

1 38

6

Amr (

LMIC

)H

ondu

ras

8 98

01

326

2 43

720

015

12 2

8645

045

(355

58, 5

4901

)58

283

3

Eur (

LMIC

)H

unga

ry32

33

224

53 1

9182

644

31 8

0617

1 18

8(1

3035

7, 2

0882

4)1

719

1 00

8

Eur (

HIC

)Ic

elan

d0

595

182

6434

6(2

, 109

5)10

772

Sear

Indi

a3

624

190

2 51

6 69

980

5 53

07

412

934

5 23

0 65

119

590

004

(164

6907

1,

2317

9478

)1

550

1 89

9

Sear

Indo

nesi

a22

9 87

019

399

137

053

439

333

905

691

1 73

1 34

6(9

1844

9, 2

2950

02)

698

905

Emr (

LMIC

)Ira

n (Is

lam

ic

Repu

blic

of)

54 4

258

513

37 8

9442

2 10

518

0 27

070

3 20

7(6

0643

7, 8

0205

2)92

31

203

Emr (

LMIC

)Ira

q91

681

3 60

019

790

131

867

80 6

5932

7 59

6(2

1309

0, 4

5221

4)99

41

690

Eur (

HIC

)Ire

land

4117

93

110

7 59

42

016

12 9

41(9

97, 2

0463

)27

720

5

Eur (

HIC

)Is

rael

9252

89

349

8 47

34

408

22 8

50(1

6838

, 282

99)

297

245

Eur (

HIC

)Ita

ly20

96

796

130

442

131

513

79 3

7234

8 33

3(2

3411

0, 4

3969

3)58

327

1

92

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)Ja

mai

ca71

812

52

131

4 81

76

809

14 5

99(1

0198

, 182

71)

528

524

Wpr

(HIC

)Ja

pan

1 64

83

516

178

246

193

571

178

114

555

095

(219

824,

753

378)

437

206

Emr (

LMIC

)Jo

rdan

5 72

675

74

326

20 8

1013

027

44 6

46(3

8246

, 512

07)

638

1 08

4

Eur (

LMIC

)Ka

zakh

stan

8 04

72

713

19 0

5015

8 91

877

917

266

644

(352

23, 4

1130

7)1

585

1 69

9

Afr

Keny

a18

3 43

678

42

293

36 0

5549

073

271

641

(896

98, 3

8012

5)63

969

6

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 8

20)

00

Emr (

HIC

)Ku

wai

t1

112

7485

610

165

3 15

715

363

(136

99, 1

7117

)44

997

0

Eur (

LMIC

)Ky

rgyz

stan

4 39

967

32

148

31 3

2517

023

55 5

69(2

2858

, 730

35)

984

1 39

8

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

36 1

6193

03

593

16 9

9715

521

73 2

03(2

6356

, 110

316)

1 13

11

458

Eur (

HIC

)La

tvia

3815

04

812

21 9

649

136

36 1

00(2

6497

, 440

09)

1 77

295

5

Emr (

LMIC

)Le

bano

n51

941

85

274

18 7

655

021

29 9

97(2

4739

, 350

54)

609

631

Afr

Leso

tho

7 45

832

016

32

248

5 16

515

355

(10,

288

99)

746

949

Afr

Libe

ria5

755

107

522

180

2 61

410

708

(2, 2

9331

)25

632

6

Emr (

LMIC

)Li

bya

2 76

11

153

6 88

625

039

15 4

7151

310

(352

43, 6

8435

)81

71

285

Eur (

HIC

)Li

thua

nia

6730

35

763

27 5

1310

720

44 3

67(3

3458

, 535

73)

1 47

185

5

Eur (

HIC

)Lu

xem

bour

g2

5585

471

248

52

109

(136

1, 2

703)

396

259

Afr

Mad

agas

car

82 9

141

179

3 97

533

857

54 7

5117

6 67

7(7

6607

, 243

779)

792

1 11

6

Afr

Mal

awi

67 8

1894

941

318

014

29 5

3811

6 73

2(2

564,

190

738)

743

962

Wpr

(LM

IC)

Mal

aysi

a2

670

2 89

718

812

92 6

5543

660

160

693

(917

43, 2

0624

3)55

473

0

Sear

Mal

dive

s63

2696

515

437

1 13

8(2

90, 1

520)

330

514

Afr

Mal

i20

8 01

63

651

1 70

131

393

45 0

3428

9 79

5(1

4607

5, 4

5053

0)1

799

1 85

6

Eur (

HIC

)M

alta

019

635

1 50

944

12

605

(134

2, 3

308)

627

361

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia30

826

525

332

6 35

39

893

47 9

30(2

8099

, 738

26)

1 26

91

414

Afr

Mau

ritiu

s18

131

577

3 84

62

071

6 70

7(2

957,

864

4)53

347

7

Amr (

LMIC

)M

exic

o42

444

11 8

4831

617

234

186

102

089

422

185

(315

925,

512

238)

346

419

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)1

00

21

3(0

, 642

)3

4

Eur (

HIC

)M

onac

o0

131

7226

130

(0, 2

47)

346

193

93

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Wpr

(LM

IC)

Mon

golia

3 56

746

31

690

16 5

3712

529

34 7

87(2

4192

, 429

89)

1 23

91

764

Eur (

LMIC

)M

onte

negr

o30

142

392

3 34

32

758

8 53

7(6

237,

106

02)

1 36

893

7

Emr (

LMIC

)M

oroc

co33

467

1 78

123

822

90 8

7089

658

239

598

(178

845,

291

920)

726

830

Afr

Moz

ambi

que

122

599

1 40

21

609

16 7

1833

533

175

861

(383

0, 2

8909

7)68

368

3

Sear

Mya

nmar

138

885

31 5

2176

488

144

488

299

332

690

714

(574

461,

817

291)

1 31

51

627

Afr

Nam

ibia

3 08

021

924

72

372

4 35

810

276

(117

7, 1

6247

)44

870

0

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al67

160

37 9

4927

843

87 5

6475

614

296

130

(224

082,

383

002)

1 07

71

438

Eur (

HIC

)N

ethe

rland

s11

92

151

41 7

7923

421

13 8

3081

300

(429

01, 1

0977

3)48

527

9

Wpr

(HIC

)N

ew Z

eala

nd3

470

233

6937

9(2

, 815

5)9

6

Amr (

LMIC

)N

icar

agua

6 56

971

71

679

18 1

8610

835

37 9

86(6

041,

569

39)

646

871

Afr

Nig

er28

7 40

42

457

299

30 7

0552

736

373

601

(221

491,

569

811)

2 11

81

879

Afr

Nig

eria

2 01

8 55

117

656

8 85

330

3 54

943

9 41

92

788

027

(222

6669

, 34

1596

4)1

657

1 58

5

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay16

185

2 94

75

653

2 26

311

065

(473

, 216

55)

220

132

Emr (

HIC

)O

man

889

128

722

6 96

84

887

13 5

94(9

288,

179

27)

383

750

Emr (

LMIC

)Pa

kist

an1

242

440

115

082

70 5

0753

4 58

338

2 74

82

345

359

(192

3609

, 28

4857

7)1

322

1 51

8

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a1

364

8782

45

199

2 96

710

442

(142

6, 1

5150

)27

930

3

Wpr

(LM

IC)

Papu

a N

ew G

uine

a14

990

244

783

6 05

54

354

26 4

28(0

, 632

61)

369

427

Amr (

LMIC

)Pa

ragu

ay3

819

301

2 75

914

263

11 9

0233

044

(154

60, 4

3378

)51

867

2

Amr (

LMIC

)Pe

ru14

797

2 17

215

470

47 7

8734

847

115

073

(891

77, 1

3909

3)38

243

9

Wpr

(LM

IC)

Philip

pine

s15

1 16

413

981

65 4

4544

5 70

831

2 14

698

8 44

3(7

5525

5, 1

1959

18)

1 02

91

356

Eur (

HIC

)Po

land

1 08

98

840

144

742

247

551

157

769

559

991

(447

950,

666

269)

1 45

091

0

Eur (

HIC

)Po

rtuga

l56

280

7 99

012

011

12 4

8632

822

(154

8, 5

4610

)31

216

6

Emr (

HIC

)Q

atar

126

641

211

3 87

51

366

6 64

2(5

902,

740

3)33

069

9

Wpr

(HIC

)Re

publ

ic o

f Kor

ea67

64

051

99 2

1857

125

80 0

2024

1 09

0(1

9013

4, 2

9058

6)48

634

5

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

1 42

449

85

388

40 3

3618

514

66 1

60(0

, 105

853)

1 62

41

298

Eur (

LMIC

)Ro

man

ia7

962

3 26

757

942

142

088

103

680

314

939

(237

754,

382

435)

1 57

998

9

94

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

12 1

1615

103

264

830

1 93

9 66

696

2 21

73

193

932

(138

7484

, 349

265)

2 22

91

511

Afr

Rwan

da66

948

843

622

14 6

2125

587

108

622

(561

63, 1

6732

6)1

004

1 19

5

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

848

7833

440

190

5(1

47, 1

308)

500

495

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s9

121

273

177

482

(0, 6

99)

441

477

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe45

113

2416

931

897

5(0

, 157

7)54

676

4

Emr (

HIC

)Sa

udi A

rabi

a5

322

4 57

810

690

105

918

80 1

8820

6 69

7(1

8063

7, 2

3407

9)70

11

373

Afr

Sene

gal

55 7

111

566

1 14

514

426

20 7

6393

611

(727

49, 1

1574

6)67

983

1

Eur (

LMIC

)Se

rbia

366

1 71

137

806

47 8

9938

856

126

637

(879

89, 1

6038

2)1

410

870

Afr

Seyc

helle

s7

553

266

126

458

(37,

668

)48

450

1

Afr

Sier

ra L

eone

67 6

6242

528

413

264

20 5

0210

2 13

6(0

, 190

034)

1 69

01

782

Wpr

(HIC

)Si

ngap

ore

131

280

6 52

013

343

5 65

725

931

(132

25, 3

4817

)48

937

4

Eur (

HIC

)Sl

ovak

ia41

143

010

779

42 7

9916

506

70 9

25(5

4710

, 850

63)

1 31

087

6

Eur (

HIC

)Sl

oven

ia11

162

5 14

75

133

3 88

614

338

(100

98, 1

7970

)69

538

2

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 3

022)

00

Emr (

LMIC

)So

mal

ia12

3 65

240

072

98

353

13 2

4214

6 37

6(6

893,

261

160)

1 45

91

089

Afr

Sout

h Af

rica

105

342

10 1

8644

936

120

850

173

456

454

770

(359

039,

545

313)

861

1 11

6

Emr (

LMIC

)So

uth

Suda

n10

8 89

51

113

983

14 7

5123

942

149

684

(659

42, 2

2753

5)1

363

1 28

7

Eur (

HIC

)Sp

ain

237

1 69

142

769

56 7

2526

621

128

043

(238

35, 2

1005

6)27

515

6

Sear

Sri L

anka

2 98

14

972

10 0

3411

7 18

952

962

188

138

(137

899,

235

835)

921

893

Emr (

LMIC

)Su

dan

261

209

5 12

23

569

52 2

7588

336

410

512

(224

919,

623

811)

1 08

91

190

Amr (

LMIC

)Su

rinam

e15

910

210

948

851

2 17

7(1

, 357

3)41

244

8

Afr

Swaz

iland

4 71

815

810

31

277

2 26

38

520

(0, 1

4612

)69

287

1

Eur (

HIC

)Sw

eden

13

8241

812

562

9(0

, 294

79)

73

Eur (

HIC

)Sw

itzer

land

3341

39

276

12 0

404

266

26 0

28(7

270,

362

08)

324

177

95

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

10 5

331

328

14 5

6895

816

36 7

0515

8 95

0(9

3603

, 218

308)

796

1 39

2

Eur (

LMIC

)Ta

jikis

tan

45 4

941

955

3 00

443

109

30 3

0912

3 87

1(6

6432

, 185

137)

1 56

22

346

Sear

Thai

land

9 44

217

204

114

602

216

933

160

335

518

516

(411

912,

622

205)

772

643

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

101

434

8 10

39

960

13 7

0932

306

(262

26, 3

8493

)1

561

1 14

8

Sear

Tim

or-L

este

4 57

347

795

1 91

11

487

8 81

4(0

, 175

45)

800

926

Afr

Togo

43 9

2450

139

911

519

17 5

2373

867

(116

08, 1

2218

2)1

095

1 30

9

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o25

838

733

5 54

82

284

8 86

2(0

, 130

46)

661

594

Emr (

LMIC

)Tu

nisi

a4

057

1 98

714

135

61 3

2636

037

117

542

(951

77, 1

3994

6)1

080

1 10

6

Eur (

LMIC

)Tu

rkey

21 8

0520

007

196

101

368

778

239

376

846

068

(704

766,

988

251)

1 13

01

208

Eur (

LMIC

)Tu

rkm

enis

tan

11 7

661

531

4 04

674

229

28 6

2112

0 19

3(3

6834

, 171

202)

2 32

33

120

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

285

051

4 87

84

194

48 9

8680

384

423

492

(324

787,

543

839)

1 19

61

402

Eur (

LMIC

)U

krai

ne5

734

5 41

173

112

796

790

247

172

1 12

8 21

9(1

7925

, 163

8357

)2

489

1 51

2

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

829

393

2 08

516

984

7 43

227

723

(239

71, 3

1545

)31

059

5

Eur (

HIC

)U

nite

d Ki

ngdo

m1

135

6 76

097

796

139

234

56 0

5930

0 98

5(1

0383

9, 4

1553

1)47

327

7

Afr

Uni

ted

Repu

blic

of

Tanz

ania

173

615

2 66

71

009

45 5

1655

715

278

521

(158

205,

377

239)

573

651

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

2 95

912

278

192

562

465

743

110

472

784

015

(353

95, 1

6601

76)

249

168

Amr (

HIC

)U

rugu

ay32

426

14

196

6 47

33

844

15 0

99(4

262,

212

61)

444

326

Eur (

LMIC

)U

zbek

ista

n65

481

4 49

114

596

249

788

125

646

460

001

(221

078,

657

777)

1 60

92

196

Wpr

(LM

IC)

Vanu

atu

80

330

2666

(0, 1

225)

2743

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

11 4

072

395

21 6

4594

773

40 1

5317

0 37

3(1

2368

2, 2

1121

2)57

168

9

Wpr

(LM

IC)

Viet

Nam

53 7

6217

575

147

882

111

775

328

906

659

901

(476

947,

835

297)

730

811

Emr (

LMIC

)Ye

men

128

485

3 37

83

389

89 7

0866

717

291

678

(121

702,

458

316)

1 17

21

720

Afr

Zam

bia

90 4

7741

768

314

882

22 4

9012

8 94

9(2

8321

, 198

935)

872

935

Afr

Zim

babw

e63

624

986

2 54

98

822

15 7

9391

774

(380

0, 1

4816

4)63

069

2

YLL :

yea

r of

life

lost

; AA

P :

Ambi

ent

air

pollu

tion ;

ALR

I : Ac

ute

low

er r

espi

rato

ry d

isea

se ;

CO

PD :

Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; I

HD

: Is

chae

mic

hea

rt di

seas

e. A

fr :

Afric

a ; A

mr :

Am

eric

a ;

Emr :

Eas

tern

Med

iterra

nean

; Eur

: Eur

ope ;

Sea

r : S

outh

-Eas

t Asi

a ; W

pr : W

este

rn P

acifi

c ; L

MIC

: Low

- and

mid

dle-

inco

me

coun

tries

; HIC

: Hig

h-in

com

e co

untri

es ; N

A : N

ot a

vaila

ble.

a Age

gro

up in

clud

es le

ss th

an 5

yea

rs o

ld.

b Age

gro

up in

clud

es 2

5 ye

ars

and

abov

e.

96

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n16

3 09

92

231

2 64

856

435

50 5

7027

4 98

3(2

1665

3, 3

4178

1)1

905

2 41

1

Eur (

LMIC

)Al

bani

a31

115

21

506

6 70

37

540

16 2

13(6

722,

215

86)

1 12

981

7

Afr

Alge

ria13

523

945

3 64

148

877

60 9

4012

7 92

5(5

1571

, 180

805)

688

835

Eur (

HIC

)An

dorra

01

1375

4213

2(3

, 196

)32

814

5

Afr

Ango

la13

1 79

71

326

412

18 6

4327

801

179

980

(283

57, 2

9856

1)1

573

1 53

0

Amr (

HIC

)An

tigua

and

Bar

buda

20

710

275

187

(0, 2

70)

401

392

Amr (

LMIC

)Ar

gent

ina

3 27

41

179

10 8

4239

628

25 3

2780

252

(235

07, 1

0973

0)37

329

0

Eur (

LMIC

)Ar

men

ia28

530

51

573

10 7

595

650

18 5

71(7

69, 2

8210

)1

239

814

Wpr

(HIC

)Au

stra

lia3

512

232

615

461

0(9

, 189

58)

53

Eur (

HIC

)Au

stria

5941

05

910

9 85

84

003

20 2

41(1

3832

, 253

22)

468

216

Eur (

LMIC

)Az

erba

ijan

5 42

435

21

479

22 4

7913

611

43 3

45(9

822,

633

92)

920

1 00

2

Amr (

HIC

)Ba

ham

as11

71

3820

916

152

5(2

, 804

)27

627

0

Emr (

HIC

)Ba

hrai

n67

4916

358

038

91

249

(111

3, 1

388)

249

531

Sear

Bang

lade

sh15

6 97

576

788

30 5

7278

697

118

505

461

536

(376

188,

563

712)

601

814

Amr (

HIC

)Ba

rbad

os24

130

164

154

373

(0, 5

49)

255

173

Eur (

LMIC

)Be

laru

s10

920

11

637

55 3

5220

372

77 6

71(1

303,

111

090)

1 52

976

5

Eur (

HIC

)Be

lgiu

m52

642

7 55

27

434

5 53

821

218

(136

38, 2

7183

)37

619

3

Amr (

LMIC

)Be

lize

501

2214

612

834

8(5

4, 5

16)

206

369

Afr

Beni

n29

279

348

199

10 6

2715

582

56 0

34(1

7331

, 879

11)

1 11

11

398

Sear

Bhut

an80

125

423

289

178

22

959

(239

4, 3

597)

860

1 18

8

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

10 9

2868

41

162

13 2

6113

218

39 2

54(3

0416

, 477

82)

768

875

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na89

769

2 92

310

886

14 7

7029

437

(230

46, 3

6220

)1

531

817

Afr

Bots

wan

a1

571

2646

1 13

32

200

4 97

5(2

8, 7

816)

466

679

Amr (

LMIC

)Br

azil

8 13

44

195

30 1

3812

7 19

711

2 01

328

1 67

7(1

2202

8, 4

2817

8)27

427

1

Wpr

HIC

Brun

ei D

arus

sala

m0

01

42

7(0

, 429

)4

5

Eur (

LMIC

)Bu

lgar

ia76

51

326

4 49

230

608

30 5

2267

713

(555

52, 7

9643

)1

805

822

97

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Burk

ina

Faso

69 2

3580

967

916

091

24 8

2011

1 63

3(5

3548

, 172

413)

1 33

41

539

Afr

Buru

ndi

56 7

3657

934

66

009

12 5

3476

204

(309

87, 1

2358

8)1

486

1 40

2

Afr

Cab

o Ve

rde

12 0

5652

32

475

15 3

9514

319

44 7

69(3

168,

694

17)

589

772

Wpr

(LM

IC)

Cam

bodi

a10

5 72

11

423

853

21 7

6533

935

163

697

(132

518,

201

931)

1 51

11

617

Afr

Cam

eroo

n46

163

5 07

36

348

2 48

314

113

(240

, 518

28)

8045

Amr (

HIC

)C

anad

a22

129

1826

270

51

236

(764

, 173

4)48

760

4

Afr

Cen

tral A

frica

n Re

publ

ic16

868

627

127

3 52

15

138

26 2

82(1

2380

, 416

30)

1 12

21

159

Afr

Cha

d93

313

684

289

9 38

414

996

118

666

(627

93, 1

8087

3)1

868

1 65

5

Amr (

HIC

)C

hile

596

548

5 30

17

426

9 59

123

461

(170

99, 2

8858

)26

620

6

Wpr

(LM

IC)

Chi

na25

7 59

567

4 32

31

453

252

2 62

0 15

24

804

159

9 80

9 48

0(8

3499

19, 1

1390

232)

1 48

31

265

Amr (

LMIC

)C

olom

bia

5 99

41

904

7 17

933

582

21 9

7570

635

(491

12, 8

7387

)29

732

0

Afr

Com

oros

1 30

320

037

571

82

417

(388

, 345

0)66

484

1

Afr

Con

go11

128

338

574

314

6 73

022

568

(102

07, 3

5361

)1

053

1 26

4

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a70

171

494

2 99

11

757

5 48

2(4

012,

666

1)23

622

4

Eur (

HIC

)C

roat

ia14

271

3 53

610

087

6 98

820

896

(150

57, 2

5987

)94

141

1

Amr (

LMIC

)C

uba

272

572

8 45

715

560

10 1

3634

997

(308

0, 5

2022

)62

040

5

Eur (

HIC

)C

ypru

s12

928

067

935

01

330

(905

, 166

4)24

116

2

Eur (

HIC

)C

zech

Rep

ublic

114

567

8 56

323

933

9 92

543

102

(337

32, 5

1588

)80

337

4

Afr

Côt

e d’

Ivoi

re59

202

513

441

18 1

1228

254

106

521

(110

78, 1

7183

9)1

030

1 27

5

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

10 3

259

559

36 3

6838

170

69 8

2016

4 24

2(2

2547

, 273

082)

1 29

71

089

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

423

559

4 61

983

759

455

107

418

595

889

(277

324,

933

537)

1 69

01

626

Eur (

HIC

)D

enm

ark

333

14

361

2 46

72

195

9 35

7(4

13, 1

5866

)33

217

2

Emr (

LMIC

)D

jibou

ti2

060

6068

633

1 02

03

840

(128

1, 6

329)

905

1 08

6

Amr (

LMIC

)D

omin

ica

31

757

6513

2(7

, 192

)36

633

2

Amr (

LMIC

)D

omin

ican

Rep

ublic

3 16

317

91

546

12 0

267

639

24 5

53(2

382,

350

51)

482

558

Amr (

LMIC

)Ec

uado

r3

408

268

1 45

57

167

6 41

418

711

(918

5, 2

4474

)24

326

6

Emr (

LMIC

)Eg

ypt

44 5

0516

469

17 0

4022

7 78

517

3 09

247

8 89

0(3

9744

6, 5

6877

7)1

129

1 45

2

98

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)El

Sal

vado

r1

823

709

1 05

410

301

4 18

118

067

(143

64, 2

1967

)56

359

5

Afr

Equa

toria

l Gui

nea

2 05

262

4569

298

73

837

(202

, 667

7)1

018

1 20

8

Afr

Eritr

ea13

773

293

287

3 71

26

807

24 8

72(9

802,

394

51)

1 01

71

349

Eur (

HIC

)Es

toni

a0

419

01

535

419

2 14

8(2

6, 4

170)

304

119

Afr

Ethi

opia

185

983

1 14

76

718

22 0

5848

508

264

415

(867

34, 4

2027

7)57

359

0

Wpr

(LM

IC)

Fiji

10

012

317

(0, 2

690)

45

Eur (

HIC

)Fi

nlan

d6

722

11

224

470

1 92

8(9

, 973

9)70

28

Eur (

HIC

)Fr

ance

118

587

27 8

9119

899

21 1

2769

620

(246

25, 9

7125

)21

311

1

Afr

Gab

on1

870

136

179

1 30

51

821

5 31

0(9

60, 8

644)

665

769

Afr

Gam

bia

4 51

357

401

380

2 27

88

267

(350

, 149

48)

906

1 24

1

Eur (

LMIC

)G

eorg

ia39

834

683

716

390

12 8

6530

836

(194

51, 3

8983

)1

421

759

Eur (

HIC

)G

erm

any

188

3 82

852

206

77 7

8542

801

176

808

(844

31, 2

3366

6)43

118

4

Afr

Gha

na40

887

747

499

22 5

1545

407

110

054

(704

01, 1

4458

7)85

41

131

Eur (

HIC

)G

reec

e38

464

3 23

514

852

13 5

8732

175

(116

23, 4

2388

)56

724

4

Amr (

LMIC

)G

rena

da1

17

8986

184

(0, 2

67)

349

364

Amr (

LMIC

)G

uate

mal

a16

147

511

1 90

68

842

5 71

333

119

(262

08, 4

0349

)42

247

9

Afr

Gui

nea

28 4

7530

818

410

740

15 1

6954

875

(478

2, 8

7626

)94

61

148

Afr

Gui

nea-

Biss

au6

300

5851

1 63

32

357

10 3

99(5

57, 1

7488

)1

204

1 34

6

Amr (

LMIC

)G

uyan

a14

17

571

497

1 34

73

049

(1, 4

706)

806

1 00

3

Amr (

LMIC

)H

aiti

23 9

3111

91

425

10 3

7121

027

56 8

73(5

454,

874

58)

1 09

31

308

Amr (

LMIC

)H

ondu

ras

4 08

853

298

57

345

5 48

618

435

(144

79, 2

2554

)47

664

7

Eur (

LMIC

)H

unga

ry14

21

265

18 7

0133

186

14 2

7667

570

(516

99, 8

2224

)1

293

639

Eur (

HIC

)Ic

elan

d0

250

5532

139

(0, 4

72)

8750

Sear

Indi

a1

857

079

1 02

3 75

919

8 70

62

306

544

2 41

4 82

27

800

910

(651

7074

, 929

3312

)1

282

1 52

0

Sear

Indo

nesi

a98

053

5 40

538

394

130

612

416

064

688

528

(362

860,

912

704)

560

706

Emr (

LMIC

)Ira

n (Is

lam

ic

Repu

blic

of)

26 2

083

380

13 1

5915

7 16

779

310

279

224

(240

070,

319

522)

740

1 03

3

Emr (

LMIC

)Ira

q42

264

1 28

75

539

42 6

8031

022

122

792

(790

44, 1

7159

0)75

41

156

Eur (

HIC

)Ire

land

2180

1 26

92

504

1 04

44

917

(339

, 791

5)21

014

0

99

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)Is

rael

2219

12

982

2 64

41

999

7 83

7(5

787,

970

7)20

214

1

Eur (

HIC

)Ita

ly14

22

489

34 3

7146

326

41 1

2712

4 45

5(8

5411

, 155

902)

405

157

Amr (

LMIC

)Ja

mai

ca28

531

416

1 89

33

232

5 85

8(4

160,

727

0)42

238

7

Wpr

(HIC

)Ja

pan

792

675

44 8

3157

353

69 7

1017

3 36

1(6

8199

, 233

248)

266

106

Emr (

LMIC

)Jo

rdan

2 50

019

165

07

237

6 18

916

767

(144

05, 1

9191

)49

380

1

Eur (

LMIC

)Ka

zakh

stan

3 47

288

43

294

59 7

8638

564

106

000

(138

55, 1

6255

5)1

218

1 15

6

Afr

Keny

a80

928

345

917

12 5

2120

579

115

291

(372

21, 1

6193

6)54

256

9

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 2

66)

00

Emr (

HIC

)Ku

wai

t42

424

220

2 04

01

106

3 81

5(3

377,

428

3)25

467

7

Eur (

LMIC

)Ky

rgyz

stan

1 86

226

048

811

953

7 25

721

820

(882

9, 2

8663

)76

31

000

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

15 1

5246

11

109

7 54

37

234

31 4

99(1

1532

, 473

52)

967

1 21

7

Eur (

HIC

)La

tvia

1533

731

8 80

74

591

14 1

76(1

0520

, 171

64)

1 28

251

0

Emr (

LMIC

)Le

bano

n23

014

91

627

4 73

72

721

9 46

3(7

740,

111

46)

389

399

Afr

Leso

tho

3 41

512

838

1 13

33

037

7 75

1(5

, 144

03)

743

887

Afr

Libe

ria2

797

4418

1 00

91

274

5 14

1(1

, 140

82)

247

308

Emr (

LMIC

)Li

bya

1 16

542

393

09

671

7 26

319

452

(135

55, 2

5798

)62

993

6

Eur (

HIC

)Li

thua

nia

4162

844

11 0

355

576

17 5

58(1

3377

, 210

57)

1 07

946

6

Eur (

HIC

)Lu

xem

bour

g2

2427

019

824

173

5(4

75, 9

46)

276

157

Afr

Mad

agas

car

37 1

7357

969

513

221

26 5

4678

214

(336

71, 1

0799

6)69

997

9

Afr

Mal

awi

34 7

4238

315

38

793

15 3

4559

415

(123

7, 9

7031

)75

592

5

Wpr

(LM

IC)

Mal

aysi

a1

175

810

6 37

030

873

19 1

1358

341

(332

13, 7

4942

)39

855

3

Sear

Mal

dive

s27

1416

193

111

362

(89,

483

)21

034

6

Afr

Mal

i94

987

1 11

071

017

242

25 2

2313

9 27

3(7

1065

, 214

508)

1 74

41

844

Eur (

HIC

)M

alta

05

165

526

187

883

(462

, 111

0)42

222

1

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia11

696

212

107

3 02

24

847

19 8

83(1

1770

, 303

74)

1 05

91

224

Afr

Mau

ritiu

s63

615

71

168

766

2 16

0(9

44, 2

783)

340

289

Amr (

LMIC

)M

exic

o18

624

5 32

312

182

85 5

9350

304

172

027

(127

788,

209

804)

280

324

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

00

1(0

, 229

)2

3

100

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)M

onac

o0

08

2413

45(0

, 85)

235

101

Wpr

(LM

IC)

Mon

golia

1 39

316

429

85

370

5 18

312

408

(860

6, 1

5357

)87

61

226

Eur (

LMIC

)M

onte

negr

o12

356

776

31

039

2 38

4(1

744,

296

8)75

545

6

Emr (

LMIC

)M

oroc

co14

418

539

2 61

136

185

46 7

7510

0 52

8(7

5973

, 121

784)

601

675

Afr

Moz

ambi

que

51 4

6377

360

27

904

15 5

3776

279

(179

6, 1

2523

8)57

857

9

Sear

Mya

nmar

58 4

0917

927

33 7

6281

429

140

657

332

184

(276

447,

393

004)

1 23

51

461

Afr

Nam

ibia

1 41

797

881

225

2 71

65

543

(657

, 869

9)47

069

9

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al32

168

19 5

0914

486

36 2

7237

045

139

481

(104

679,

181

830)

985

1 31

5

Eur (

HIC

)N

ethe

rland

s52

1 02

416

884

7 48

37

307

32 7

50(1

7038

, 444

84)

388

212

Wpr

(HIC

)N

ew Z

eala

nd2

237

7139

151

(1, 3

452)

74

Amr (

LMIC

)N

icar

agua

2 71

932

366

46

966

4 91

715

591

(248

5, 2

3519

)52

367

1

Afr

Nig

er11

9 15

81

041

4614

942

25 6

8316

0 87

0(9

5851

, 244

409)

1 83

81

774

Afr

Nig

eria

864

235

7 18

44

557

128

099

211

378

1 21

5 45

3(9

7139

3, 1

4878

89)

1 47

11

441

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay5

921

254

1 88

71

135

4 37

3(1

64, 8

766)

175

90

Emr (

HIC

)O

man

469

3915

21

986

1 45

14

096

(278

1, 5

459)

314

620

Emr (

LMIC

)Pa

kist

an53

4 05

927

645

11 6

6623

5 71

720

3 29

31

012

379

(836

044,

122

0982

)1

174

1 36

3

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a73

039

270

1 60

71

352

3 99

8(5

25, 5

875)

214

222

Wpr

(LM

IC)

Papu

a N

ew G

uine

a6

763

7626

52

433

1 24

810

785

(0, 2

5810

)30

833

5

Amr (

LMIC

)Pa

ragu

ay1

679

9652

64

731

4 92

911

961

(556

1, 1

5661

)38

147

8

Amr (

LMIC

)Pe

ru6

541

1 11

67

660

18 6

8116

256

50 2

54(3

8661

, 610

80)

333

366

Wpr

(LM

IC)

Philip

pine

s68

621

3 45

718

623

143

385

120

160

354

247

(269

559,

429

507)

746

940

Eur (

HIC

)Po

land

413

2 61

243

455

81 4

0871

253

199

140

(159

581,

236

994)

999

525

Eur (

HIC

)Po

rtuga

l26

791

588

4 01

85

752

11 4

63(4

95, 1

8432

)20

891

Emr (

HIC

)Q

atar

5218

188

525

183

966

(851

, 108

8)18

956

6

Wpr

(HIC

)Re

publ

ic o

f Kor

ea25

41

067

25 8

8017

101

33 2

8477

586

(617

70, 9

3155

)31

119

2

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

661

141

988

17 4

868

838

28 1

14(0

, 442

76)

1 32

992

1

101

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Ro

man

ia3

602

861

10 9

9951

272

47 6

3811

4 37

2(8

7652

, 137

810)

1 11

459

9

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

5 61

23

421

40 1

7169

9 14

946

9 39

21

217

745

(520

667,

165

2256

)1

585

864

Afr

Rwan

da29

859

378

227

5 77

711

399

47 6

40(2

4511

, 736

23)

844

963

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

332

2112

117

535

3(5

7, 5

08)

383

362

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s4

06

118

9021

8(0

, 316

)40

341

5

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe20

34

692

173

479

(0, 7

65)

534

733

Emr (

HIC

)Sa

udi A

rabi

a2

612

1 55

22

877

30 8

5132

992

70 8

84(6

1575

, 807

67)

552

1 06

9

Afr

Sene

gal

24 0

9253

643

46

568

10 1

1941

749

(325

42, 5

1479

)59

472

1

Eur (

LMIC

)Se

rbia

130

584

10 1

1315

556

19 3

5045

734

(322

84, 5

7582

)99

554

1

Afr

Seyc

helle

s2

29

7842

134

(10,

193

)28

926

8

Afr

Sier

ra L

eone

32 0

4916

410

16

434

10 4

5549

203

(0, 9

1290

)1

610

1 74

5

Wpr

(HIC

)Si

ngap

ore

4962

2 14

93

911

2 52

58

695

(438

6, 1

1710

)32

423

8

Eur (

HIC

)Sl

ovak

ia21

513

92

838

16 1

857

209

26 5

86(2

0620

, 318

09)

953

532

Eur (

HIC

)Sl

oven

ia11

531

467

1 56

51

852

4 94

8(3

517,

618

9)47

621

7

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 1

028)

00

Emr (

LMIC

)So

mal

ia56

878

238

347

3 00

25

622

66 0

86(3

022,

118

382)

1 31

094

9

Afr

Sout

h Af

rica

46 2

323

244

14 6

2746

663

92 6

0420

3 36

9(1

6088

2, 2

4338

8)75

686

3

Emr (

LMIC

)So

uth

Suda

n47

572

403

426

5 79

810

960

65 1

59(2

8646

, 990

84)

1 18

71

112

Eur (

HIC

)Sp

ain

7831

48

154

16 6

5512

742

37 9

43(6

952,

599

88)

160

75

Sear

Sri L

anka

1 20

81

644

2 74

135

253

19 8

4660

692

(442

72, 7

6426

)57

653

4

Emr (

LMIC

)Su

dan

111

077

1 86

71

174

20 7

1940

639

175

475

(961

65, 2

6640

3)93

41

024

Amr (

LMIC

)Su

rinam

e11

646

367

380

810

(0, 1

312)

307

318

Afr

Swaz

iland

2 07

183

3673

31

558

4 48

1(0

, 759

2)71

792

3

Eur (

HIC

)Sw

eden

12

4015

065

258

(0, 1

2682

)5

2

Eur (

HIC

)Sw

itzer

land

1517

13

442

3 95

02

243

9 82

1(2

578,

137

45)

242

115

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

4 39

442

52

703

33 7

2412

004

53 2

50(3

1883

, 726

63)

539

906

102

Num

ber o

f YLL

s YL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Ta

jikis

tan

19 4

171

024

1 17

520

221

17 2

9759

134

(319

10, 8

8088

)1

505

2 30

6

Sear

Thai

land

3 85

33

690

37 8

2285

872

69 1

9120

0 42

8(1

6061

1, 2

3859

9)58

946

7

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

4814

01

481

3 10

66

440

11 2

16(9

174,

133

31)

1 08

072

6

Sear

Tim

or-L

este

2 12

120

259

916

699

4 01

5(0

, 791

8)74

083

4

Afr

Togo

21 0

2117

711

35

493

8 82

635

630

(563

8, 5

8792

)1

042

1 23

2

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o12

95

187

1 71

493

62

971

(0, 4

369)

438

375

Emr (

LMIC

)Tu

nisi

a1

750

754

853

21 4

8215

248

40 0

87(3

2733

, 475

28)

730

722

Eur (

LMIC

)Tu

rkey

9 14

26

887

24 9

3213

0 95

810

3 45

727

5 37

5(2

3271

9, 3

1889

4)72

371

8

Eur (

LMIC

)Tu

rkm

enis

tan

4 80

164

287

726

246

13 1

8045

746

(139

26, 6

5576

)1

741

2 30

2

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

121

133

2 38

82

071

17 6

7336

036

179

301

(137

192,

230

643)

1 01

21

153

Eur (

LMIC

)U

krai

ne2

342

1 26

711

243

349

292

126

850

490

993

(628

6, 7

0517

1)2

015

968

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

311

9647

71

867

1 20

73

959

(336

8, 4

580)

173

535

Eur (

HIC

)U

nite

d Ki

ngdo

m53

73

256

43 5

7942

355

29 2

9911

9 02

7(3

8097

, 167

686)

369

192

Afr

Uni

ted

Repu

blic

of

Tanz

ania

76 3

071

083

420

17 3

0523

795

118

910

(670

53, 1

6146

2)48

654

7

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1 32

36

262

85 5

3915

8 08

255

912

307

117

(134

18, 6

6858

0)19

311

8

Amr (

HIC

)U

rugu

ay16

669

893

1 89

71

934

4 95

9(1

432,

685

3)28

217

8

Eur (

LMIC

)U

zbek

ista

n27

448

1 89

73

746

100

577

60 6

0819

4 27

6(9

2850

, 278

471)

1 33

71

712

Wpr

(LM

IC)

Vanu

atu

30

19

821

(0, 3

94)

1728

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

4 94

31

126

9 25

630

067

17 6

8363

075

(451

19, 7

9002

)42

148

6

Wpr

(LM

IC)

Viet

Nam

20 9

147

587

35 9

3034

617

118

649

217

697

(157

770,

276

307)

476

465

Emr (

LMIC

)Ye

men

57 2

481

578

893

31 4

9629

396

120

610

(491

71, 1

9164

4)98

01

380

Afr

Zam

bia

42 9

6228

528

55

156

9 02

357

711

(120

02, 8

9782

)77

975

4

Afr

Zim

babw

e31

355

405

940

4 11

28

510

45 3

23(1

868,

730

01)

614

659

YLL :

yea

r of l

ife lo

st ; A

AP : A

mbi

ent a

ir po

llutio

n ; A

LRI :

Acut

e lo

wer

resp

irato

ry d

isea

se ; C

OPD

: Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; IH

D : I

scha

emic

hea

rt di

seas

e. A

fr : A

frica

; Am

r : A

mer

ica ;

Em

r : E

aste

rn

Med

iterra

nean

; Eur

: Eur

ope ;

Sea

r : S

outh

-Eas

t Asi

a ; W

pr : W

este

rn P

acifi

c ; L

MIC

: Low

- and

mid

dle-

inco

me

coun

tries

; HIC

: Hig

h-in

com

e co

untri

es ; N

A : N

ot a

vaila

ble.

a Age

gro

up in

clud

es le

ss th

an 5

yea

rs o

ld.

b Age

gro

up in

clud

es 2

5 ye

ars

and

abov

e.

103

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n17

9 17

92

429

7 11

564

378

37 9

9729

1 09

7(2

2882

9, 3

6267

8)1

904

2 49

8

Eur (

LMIC

)Al

bani

a42

519

43

047

9 87

26

824

20 3

62(8

611,

271

65)

1 41

01

142

Afr

Alge

ria17

446

1 84

315

626

87 7

1773

469

196

101

(791

30, 2

7700

4)1

040

1 31

1

Eur (

HIC

)An

dorra

03

4415

543

245

(8, 3

69)

627

388

Afr

Ango

la20

2 91

81

917

735

28 2

2425

812

259

607

(391

70, 4

3307

0)2

308

2 06

7

Amr (

HIC

)An

tigua

and

Bar

buda

41

1515

083

254

(0, 3

67)

597

640

Amr (

LMIC

)Ar

gent

ina

4 43

62

061

26 3

8069

550

32 2

3013

4 65

7(3

9258

, 185

786)

654

644

Eur (

LMIC

)Ar

men

ia46

562

18

093

20 2

067

124

36 5

08(1

714,

570

14)

2 46

72

255

Wpr

(HIC

)Au

stra

lia3

617

970

013

51

022

(16,

296

38)

96

Eur (

HIC

)Au

stria

2061

310

516

16 7

593

771

31 6

79(2

1683

, 395

95)

767

466

Eur (

LMIC

)Az

erba

ijan

6 82

958

35

914

38 3

3714

498

66 1

61(1

5454

, 966

50)

1 42

31

751

Amr (

HIC

)Ba

ham

as15

42

8741

920

686

8(3

, 132

2)47

653

9

Emr (

HIC

)Ba

hrai

n79

9645

11

641

692

2 95

8(2

655,

326

3)35

675

2

Sear

Bang

lade

sh19

2 68

891

010

90 0

8818

6 03

912

0 66

268

0 48

8(5

6266

8, 8

1862

1)86

81

192

Amr (

HIC

)Ba

rbad

os34

362

294

206

598

(0, 8

79)

443

349

Eur (

LMIC

)Be

laru

s23

299

413

507

89 6

3322

486

126

852

(291

4, 1

8545

3)2

876

2 27

0

Eur (

HIC

)Be

lgiu

m71

1 19

820

203

16 5

205

817

43 8

08(2

7226

, 567

71)

806

491

Amr (

LMIC

)Be

lize

3418

5621

114

045

8(7

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273

474

Afr

Beni

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556

697

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12 2

2516

147

64 9

90(1

9753

, 102

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1 29

81

706

Sear

Bhut

an1

053

391

231

1 41

663

13

723

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8, 4

544)

932

1 20

6

Amr (

LMIC

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rinat

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l St

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of

13 1

6367

21

061

18 6

0015

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49 1

85(3

8356

, 595

65)

959

1 15

0

Eur (

LMIC

)Bo

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and

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na12

31

106

11 9

2618

218

13 4

9344

866

(346

54, 5

5437

)2

354

1 58

6

Afr

Bots

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651

3822

51

112

1 35

24

378

(23,

697

8)41

162

0

Amr (

LMIC

)Br

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9 81

95

920

44 2

2222

7 51

912

7 35

341

4 83

4(1

7974

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2515

1)41

647

1

Wpr

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103

13(0

, 734

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9

Eur (

LMIC

)Bu

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ia1

045

2 13

621

942

48 8

4532

999

106

967

(866

78, 1

2665

5)3

011

1 84

8

104

Num

ber o

f YLL

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ion

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ALR

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ty in

terv

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Age-

stan

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ized

rate

Afr

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80 5

751

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734

17 9

1027

972

128

251

(613

63, 1

9842

7)1

560

2 04

2

Afr

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ndi

68 3

4268

534

611

504

18 4

1499

290

(414

94, 1

5906

7)1

987

1 97

1

Afr

Cab

o Ve

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16 5

4864

94

375

19 8

7615

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56 8

27(3

900,

884

70)

786

1 14

4

Wpr

(LM

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2 12

12

639

1 51

628

446

35 5

8020

0 30

2(1

6193

5, 2

4771

2)1

850

1 98

1

Afr

Cam

eroo

n45

178

5 76

414

337

2 34

522

669

(449

, 767

99)

131

86

Amr (

HIC

)C

anad

a23

991

2353

191

71

800

(111

8, 2

532)

729

1 22

3

Afr

Cen

tral A

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publ

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156

759

238

4 80

45

096

35 0

52(1

6358

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11)

1 54

01

563

Afr

Cha

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6 87

186

139

812

481

17 8

3315

8 44

5(8

3654

, 241

698)

2 49

02

163

Amr (

HIC

)C

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955

793

8 11

518

937

12 6

5341

452

(308

41, 5

0306

)48

344

8

Wpr

(LM

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na35

3 52

781

3 07

53

739

353

2 96

5 89

25

370

805

13 2

42 6

51(1

1194

228,

15

4250

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1 88

81

755

Amr (

LMIC

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8 38

72

536

11 1

9755

842

20 0

0897

970

(683

69, 1

2045

1)42

451

1

Afr

Com

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1 56

720

2957

897

33

166

(545

, 449

5)85

61

183

Afr

Con

go18

264

586

148

6 49

16

722

32 2

11(1

4300

, 510

58)

1 50

31

722

Wpr

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land

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AN

AN

AN

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AN

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LMIC

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191

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6 17

11

953

9 40

8(6

962,

113

15)

404

418

Eur (

HIC

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550

11 0

7816

158

7 55

135

357

(245

23, 4

4731

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711

1 05

2

Amr (

LMIC

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320

716

14 8

2426

794

12 2

7354

927

(501

2, 8

1450

)96

371

0

Eur (

HIC

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301

047

2 10

537

93

562

(238

3, 4

474)

618

504

Eur (

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143

1 02

220

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41 3

5910

216

73 2

71(5

6758

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1 41

490

1

Afr

Côt

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780

1 24

485

127

131

37 7

6913

7 77

4(1

5084

, 221

544)

1 28

11

503

Sear

Dem

ocra

tic P

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e’s

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blic

of K

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10 5

8214

116

51 8

2258

629

99 5

7723

4 72

6(3

1916

, 389

541)

1 94

02

148

Afr

Dem

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tic R

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of th

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6 74

51

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3210

5 10

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7(3

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1464

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2 08

61

993

Eur (

HIC

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34

408

5 30

42

268

12 2

93(7

43, 1

9728

)44

226

6

Emr (

LMIC

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836

5667

943

1 37

85

280

(178

3, 8

628)

1 23

21

514

Amr (

LMIC

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52

2089

6618

2(1

0, 2

68)

512

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Amr (

LMIC

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4 52

117

02

412

13 1

257

155

27 3

83(2

582,

393

79)

541

648

Amr (

LMIC

)Ec

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r4

405

366

1 98

311

724

7 56

726

045

(130

93, 3

3841

)33

840

4

Emr (

LMIC

)Eg

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41 9

2724

566

44 1

3635

1 67

523

2 86

469

5 16

9(5

7914

2, 8

2094

9)1

607

2 33

5

105

Num

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f YLL

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Age-

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ized

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Amr (

LMIC

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vado

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332

513

1 22

612

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3 55

819

720

(157

96, 2

3782

)68

981

9

Afr

Equa

toria

l Gui

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3 58

412

113

81

587

1 29

46

724

(353

, 116

63)

1 69

41

852

Afr

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103

326

301

5 93

18

991

34 6

53(1

3804

, 546

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1 41

62

082

Eur (

HIC

)Es

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a15

1264

22

655

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3 83

1(6

7, 7

669)

620

432

Afr

Ethi

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319

258

8 37

16

104

41 9

8768

949

444

669

(144

873,

714

179)

966

982

Wpr

(LM

IC)

Fiji

10

040

647

(0, 6

924)

1013

Eur (

HIC

)Fi

nlan

d5

1346

42

679

513

3 67

3(2

2, 1

8053

)13

879

Eur (

HIC

)Fr

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237

1 25

676

241

47 5

1122

042

147

287

(515

58, 2

0982

1)47

630

5

Afr

Gab

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410

204

318

1 84

11

631

7 40

4(1

235,

122

41)

908

1 07

6

Afr

Gam

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5 83

312

412

11

800

2 79

210

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(442

, 194

18)

1 19

31

557

Eur (

LMIC

)G

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94

265

23 8

3013

060

42 4

44(2

6861

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2 15

51

667

Eur (

HIC

)G

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274

5 65

310

4 21

314

9 09

242

019

301

252

(146

398,

398

718)

763

411

Afr

Gha

na46

994

972

1 80

530

095

34 7

2711

4 59

3(7

3314

, 150

588)

905

1 24

2

Eur (

HIC

)G

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e54

567

15 7

0928

232

13 2

9657

858

(212

06, 7

8220

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064

627

Amr (

LMIC

)G

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221

170

118

312

(0, 4

54)

592

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Amr (

LMIC

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mal

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811

620

2 41

212

350

5 83

541

028

(325

68, 4

9874

)54

667

4

Afr

Gui

nea

34 1

5552

141

711

509

15 8

1062

411

(522

4, 1

0036

0)1

071

1 27

2

Afr

Gui

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Biss

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144

109

641

839

2 68

412

840

(636

, 217

66)

1 50

91

641

Amr (

LMIC

)G

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813

632

347

1 71

04

292

(1, 6

562)

1 13

01

375

Amr (

LMIC

)H

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28 0

9217

41

147

10 9

2919

645

59 9

87(5

457,

926

22)

1 17

91

469

Amr (

LMIC

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4 89

279

41

452

12 6

716

801

26 6

10(2

1079

, 323

52)

688

1 02

8

Eur (

LMIC

)H

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11

959

34 4

9049

458

17 5

3010

3 61

8(7

8527

, 126

682)

2 18

91

479

Eur (

HIC

)Ic

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d0

345

127

3220

7(1

, 623

)12

793

Sear

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a1

767

111

1 49

2 94

060

6 82

55

106

390

2 81

5 82

911

789

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(994

6795

, 138

9327

0)1

799

2 27

2

Sear

Indo

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1 81

713

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98 6

5930

8 72

148

9 62

71

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818

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138

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41

116

Emr (

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of)

28 2

175

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24 7

3526

4 93

910

0 96

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3 98

4(3

6633

7, 4

8256

5)1

104

1 37

2

Emr (

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417

2 31

314

251

89 1

8749

637

204

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138,

280

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1 22

92

289

Eur (

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01

842

5 09

097

28

024

(625

, 125

50)

345

273

Eur (

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)Is

rael

7133

76

368

5 82

92

409

15 0

14(1

1058

, 186

04)

395

363

Eur (

HIC

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ly67

4 30

796

071

85 1

8738

245

223

878

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539,

284

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106

Num

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f YLL

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Age-

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394

1 71

42

924

3 57

68

742

(601

5, 1

1014

)63

666

4

Wpr

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pan

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2 84

113

3 41

513

6 21

710

8 40

438

1 73

4(1

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2111

1)61

731

8

Emr (

LMIC

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3 22

656

63

677

13 5

736

838

27 8

79(2

3823

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44)

776

1 37

0

Eur (

LMIC

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4 57

51

829

15 7

5599

132

39 3

5316

0 64

4(2

1034

, 248

898)

1 97

92

410

Afr

Keny

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2 50

943

91

375

23 5

3428

494

156

350

(525

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1819

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583

0

Wpr

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Kirib

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00

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54)

01

Emr (

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750

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8 12

52

050

11 5

48(1

0319

, 128

34)

602

1 17

2

Eur (

LMIC

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2 53

741

21

659

19 3

729

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33 7

48(1

3887

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1 21

01

881

Wpr

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Lao

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D

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21 0

0946

92

484

9 45

58

287

41 7

04(1

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1 29

71

727

Eur (

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74

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13 1

574

545

21 9

24(1

5868

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2 35

31

591

Emr (

LMIC

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93

647

14 0

282

300

20 5

34(1

6998

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14)

823

845

Afr

Leso

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4 04

319

212

51

115

2 12

87

603

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4504

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01

032

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958

6335

1 17

11

340

5 56

7(1

, 152

58)

264

344

Emr (

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1 59

672

95

956

15 3

688

209

31 8

58(2

1655

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41)

998

1 65

2

Eur (

HIC

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2624

14

919

16 4

785

145

26 8

09(1

9974

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1 93

01

367

Eur (

HIC

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3158

451

424

41

373

(884

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0)51

736

7

Afr

Mad

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4160

13

280

20 6

3628

204

98 4

63(4

2789

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764)

886

1 25

9

Afr

Mal

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33 0

7656

626

09

221

14 1

9357

317

(126

8, 9

3704

)73

299

9

Wpr

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Mal

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a1

495

2 08

712

441

61 7

8224

547

102

352

(581

83, 1

3127

2)71

291

4

Sear

Mal

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s36

1279

322

326

776

(200

, 103

8)44

968

0

Afr

Mal

i11

3 02

82

541

990

14 1

5119

811

150

522

(749

60, 2

3606

2)1

852

1 85

9

Eur (

HIC

)M

alta

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470

984

255

1 72

2(8

79, 2

202)

833

514

Wpr

(LM

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Mar

shal

l Isl

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NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

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130

314

225

3 33

25

046

28 0

47(1

6326

, 434

64)

1 47

71

604

Afr

Mau

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s11

826

420

2 67

91

305

4 54

7(1

984,

586

3)73

068

7

Amr (

LMIC

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exic

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819

6 52

619

435

148

593

51 7

8525

0 15

9(1

8808

8, 3

0242

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252

1

Wpr

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11

2(0

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6

Eur (

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122

4813

84(0

, 163

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329

2

Wpr

(LM

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Mon

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2 17

430

01

392

11 1

677

346

22 3

79(1

5576

, 276

40)

1 60

82

382

107

Num

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f YLL

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Age-

stan

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ized

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Eur (

LMIC

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onte

negr

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111

826

2 57

91

719

6 15

3(4

488,

763

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997

1 48

4

Emr (

LMIC

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1 24

221

211

54 6

8442

883

139

069

(102

817,

170

336)

856

991

Afr

Moz

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71 1

3662

81

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8 81

417

996

99 5

82(2

079,

163

848)

795

804

Sear

Mya

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80 4

7613

594

42 7

2663

058

158

676

358

529

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718,

424

251)

1 39

81

820

Afr

Nam

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1 66

212

215

91

147

1 64

24

733

(510

, 755

4)42

569

9

Wpr

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Nau

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AN

AN

AN

AN

AN

AN

AN

AN

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Nep

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992

18 4

4013

357

51 2

9138

569

156

649

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368,

201

233)

1 17

41

566

Eur (

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1 12

824

895

15 9

386

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48 5

50(2

5883

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585

355

Wpr

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234

161

3022

8(2

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8

Amr (

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3 85

039

41

014

11 2

205

918

22 3

96(3

551,

334

21)

773

1 10

5

Afr

Nig

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8 24

61

416

254

15 7

6227

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212

731

(125

664,

325

508)

2 39

51

969

Afr

Nig

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1 15

4 31

610

471

4 29

517

5 45

122

8 04

11

572

574

(125

5275

, 19

2813

4)1

837

1 72

4

Wpr

(LM

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Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

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orw

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931

694

3 76

71

127

6 69

1(2

98, 1

2905

)26

617

6

Emr (

HIC

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man

420

8957

04

982

3 43

79

498

(650

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2470

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485

1

Emr (

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)Pa

kist

an70

8 38

187

437

58 8

4129

8 86

617

9 45

51

332

980

(108

7099

, 16

2762

4)1

462

1 66

5

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a63

548

554

3 59

21

615

6 44

4(8

93, 9

278)

343

388

Wpr

(LM

IC)

Papu

a N

ew G

uine

a8

227

169

518

3 62

33

107

15 6

43(0

, 374

28)

429

525

Amr (

LMIC

)Pa

ragu

ay2

140

206

2 23

39

532

6 97

321

084

(981

2, 2

7736

)65

186

6

Amr (

LMIC

)Pe

ru8

255

1 05

67

810

29 1

0718

591

64 8

19(5

0539

, 780

13)

430

521

Wpr

(LM

IC)

Philip

pine

s82

543

10 5

2446

822

302

322

191

986

634

196

(485

332,

766

829)

1 30

61

806

Eur (

HIC

)Po

land

677

6 22

910

1 28

716

6 14

386

516

360

851

(287

762,

429

651)

1 93

21

376

Eur (

HIC

)Po

rtuga

l29

201

6 40

27

993

6 73

421

359

(973

, 362

42)

427

253

Emr (

HIC

)Q

atar

7345

1 02

43

350

1 18

35

676

(505

0, 6

317)

377

736

Wpr

(HIC

)Re

publ

ic o

f Kor

ea42

22

984

73 3

3840

024

46 7

3616

3 50

4(1

2816

1, 1

9768

4)66

353

5

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

764

357

4 40

022

849

9 67

638

046

(0, 6

1639

)1

941

1 77

3

Eur (

LMIC

)Ro

man

ia4

360

2 40

646

943

90 8

1656

042

200

568

(149

781,

244

879)

2 07

31

437

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

6 50

511

682

224

659

1 24

0 51

649

2 82

41

976

187

(855

234,

269

9613

)2

973

2 40

3

108

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Rwan

da37

090

465

395

8 84

414

188

60 9

82(3

1633

, 936

98)

1 17

91

503

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

516

5721

322

555

2(9

0, 8

00)

621

639

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s5

115

156

8726

4(0

, 383

)47

854

0

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe24

89

1877

144

496

(0, 8

12)

558

802

Emr (

HIC

)Sa

udi A

rabi

a2

711

3 02

57

813

75 0

6747

197

135

813

(119

012,

153

380)

815

1 64

9

Afr

Sene

gal

31 6

191

030

711

7 85

710

644

51 8

61(4

0207

, 642

67)

768

960

Eur (

LMIC

)Se

rbia

235

1 12

627

692

32 3

4419

506

80 9

03(5

5695

, 102

887)

1 84

41

235

Afr

Seyc

helle

s5

443

188

8432

4(2

4, 4

75)

672

742

Afr

Sier

ra L

eone

35 6

1326

118

36

829

10 0

4652

933

(0, 9

8733

)1

772

1 81

9

Wpr

(HIC

)Si

ngap

ore

8221

84

371

9 43

33

132

17 2

36(8

807,

231

10)

659

521

Eur (

HIC

)Sl

ovak

ia19

729

27

941

26 6

139

297

44 3

39(3

4039

, 533

29)

1 68

91

302

Eur (

HIC

)Sl

oven

ia0

109

3 68

13

568

2 03

49

391

(657

3, 1

1794

)91

856

9

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 1

994)

00

Emr (

LMIC

)So

mal

ia66

774

163

382

5 35

17

621

80 2

89(3

850,

142

755)

1 60

91

235

Afr

Sout

h Af

rica

59 1

106

942

30 3

1074

187

80 8

5325

1 40

1(1

9807

5, 3

0217

0)96

91

520

Emr (

LMIC

)So

uth

Suda

n61

323

710

557

8 95

312

982

84 5

25(3

7287

, 128

451)

1 53

91

467

Eur (

HIC

)Sp

ain

159

1 37

734

615

40 0

7013

879

90 1

00(1

6480

, 150

243)

392

245

Sear

Sri L

anka

1 77

33

328

7 29

381

936

33 1

1612

7 44

6(9

3595

, 159

445)

1 28

81

312

Emr (

LMIC

)Su

dan

150

132

3 25

62

395

31 5

5647

697

235

036

(128

740,

357

480)

1 24

21

359

Amr (

LMIC

)Su

rinam

e14

83

164

582

471

1 36

7(0

, 226

4)51

658

5

Afr

Swaz

iland

2 64

774

6854

470

54

039

(0, 7

019)

665

799

Eur (

HIC

)Sw

eden

01

4126

860

371

(0, 1

6816

)8

4

Eur (

HIC

)Sw

itzer

land

1824

25

834

8 09

02

023

16 2

07(4

634,

224

82)

409

246

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

6 13

990

311

866

62 0

9224

701

105

700

(617

40, 1

4568

1)1

046

1 89

5

Eur (

LMIC

)Ta

jikis

tan

26 0

7793

11

828

22 8

8813

012

64 7

37(3

4560

, 970

55)

1 61

82

378

Sear

Thai

land

5 58

913

514

76 7

8013

1 06

191

144

318

088

(250

916,

383

741)

960

841

109

Num

ber o

f YLL

sYL

Ls 1

00 0

00 p

er c

apita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

5329

46

622

6 85

47

268

21 0

90(1

7019

, 251

88)

2 04

61

611

Sear

Tim

or-L

este

2 45

227

537

995

788

4 79

9(0

, 963

0)85

71

016

Afr

Togo

22 9

0332

528

76

025

8 69

738

237

(597

2, 6

3385

)1

149

1 39

4

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o12

934

546

3 83

41

348

5 89

1(0

, 867

8)88

883

6

Emr (

LMIC

)Tu

nisi

a2

307

1 23

313

282

39 8

4520

789

77 4

55(6

2330

, 924

90)

1 43

81

517

Eur (

LMIC

)Tu

rkey

12 6

6413

120

171

170

237

820

135

919

570

692

(471

676,

669

656)

1 55

21

780

Eur (

LMIC

)Tu

rkm

enis

tan

6 96

489

03

168

47 9

8315

442

74 4

47(2

2665

, 105

624)

2 92

54

029

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

163

918

2 49

02

123

31 3

1344

348

244

191

(187

570,

313

203)

1 38

11

677

Eur (

LMIC

)U

krai

ne3

392

4 14

461

870

447

498

120

322

637

226

(111

22, 9

3365

9)3

041

2 25

5

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

518

296

1 60

815

118

6 22

523

765

(205

91, 2

6974

)35

662

0

Eur (

HIC

)U

nite

d Ki

ngdo

m59

93

504

54 2

1796

879

26 7

6018

1 95

9(6

4682

, 247

933)

582

371

Afr

Uni

ted

Repu

blic

of

Tanz

ania

97 3

081

584

588

28 2

1131

919

159

610

(910

61, 2

1577

5)66

176

1

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1 63

66

016

107

023

307

662

54 5

6047

6 89

8(2

1813

, 992

433)

306

222

Amr (

HIC

)U

rugu

ay15

819

33

303

4 57

71

910

10 1

40(2

771,

144

46)

619

509

Eur (

LMIC

)U

zbek

ista

n38

033

2 59

410

850

149

210

65 0

3826

5 72

5(1

2791

2, 3

7950

4)1

889

2 76

4

Wpr

(LM

IC)

Vanu

atu

40

221

1845

(0, 8

31)

3659

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

6 46

51

269

12 3

8964

706

22 4

7010

7 29

8(7

8529

, 132

226)

721

914

Wpr

(LM

IC)

Viet

Nam

32 8

489

988

111

953

77 1

5821

0 25

744

2 20

4(3

1831

5, 5

5936

3)99

11

239

Emr (

LMIC

)Ye

men

71 2

371

800

2 49

658

212

37 3

2117

1 06

8(7

2537

, 266

686)

1 36

12

079

Afr

Zam

bia

47 5

1413

339

89

726

13 4

6771

237

(163

39, 1

0915

3)96

51

141

Afr

Zim

babw

e32

269

581

1 60

94

709

7 28

346

452

(191

0, 7

5197

)64

672

5

YLL :

yea

r of l

ife lo

st ;

AAP

: Am

bien

t air

pollu

tion ;

ALR

I : Ac

ute

low

er re

spira

tory

dis

ease

; C

OPD

: C

hron

ic o

bstru

ctiv

e pu

lmon

ary

dise

ase ;

IHD

: Is

chae

mic

hea

rt di

seas

e. A

fr : A

frica

; Am

r : A

mer

ica ;

Em

r : E

aste

rn M

edite

rrane

an ; E

ur : E

urop

e ; S

ear :

Sou

th-E

ast A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

; NA

: Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

111

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n34

3 35

89

245

9 91

512

1 75

788

934

573

208

(450

258,

714

931)

1 92

82

501

Eur (

LMIC

)Al

bani

a74

560

44

593

16 7

2314

504

37 1

69(1

5554

, 497

30)

1 29

099

6

Afr

Alge

ria31

601

7 53

719

433

138

062

135

436

332

068

(133

038,

474

968)

887

1 09

7

Eur (

HIC

)An

dorra

07

5823

491

390

(11,

588

)49

227

1

Afr

Ango

la33

5 54

36

552

1 18

647

195

53 9

0044

4 37

5(6

8199

, 744

254)

1 95

91

833

Amr (

HIC

)An

tigua

and

Bar

buda

84

2225

416

345

1(0

, 657

)50

652

1

Amr (

LMIC

)Ar

gent

ina

7 91

05

339

37 5

4611

0 61

759

090

220

501

(646

76, 3

0496

1)52

446

3

Eur (

LMIC

)Ar

men

ia76

21

391

9 71

331

157

12 9

7856

001

(263

4, 8

7447

)1

880

1 49

3

Wpr

(HIC

)Au

stra

lia8

2230

41

050

318

1 70

2(2

7, 5

0732

)7

5

Eur (

HIC

)Au

stria

992

110

16 5

8127

161

8 73

054

681

(371

86, 6

8807

)64

735

4

Eur (

LMIC

)Az

erba

ijan

12 2

832

214

7 45

061

409

28 5

7911

1 93

5(2

5959

, 165

568)

1 19

61

375

Amr (

HIC

)Ba

ham

as27

415

126

636

393

1 44

4(5

, 222

3)38

840

4

Emr (

HIC

)Ba

hrai

n16

151

162

02

277

1 16

14

731

(415

2, 5

354)

355

708

Sear

Bang

lade

sh35

3 83

527

1 66

212

1 86

527

0 58

324

9 31

01

267

255

(101

9971

, 156

5478

)81

61

114

Amr (

HIC

)Ba

rbad

os60

1992

467

381

1 01

9(0

, 151

8)36

226

7

Eur (

LMIC

)Be

laru

s37

22

086

15 3

0014

5 78

143

834

207

374

(458

6, 3

0211

8)2

185

1 42

0

Eur (

HIC

)Be

lgiu

m15

52

955

28 0

4524

910

12 5

3968

602

(431

93, 8

8932

)61

935

3

Amr (

LMIC

)Be

lize

9339

7936

428

185

6(1

39, 1

322)

254

445

Afr

Beni

n65

079

2 76

557

423

087

31 8

4212

3 34

8(3

7519

, 196

565)

1 22

71

587

Sear

Bhut

an1

876

1 00

546

52

333

1 45

27

132

(567

9, 8

840)

959

1 27

4

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

24 3

332

468

2 25

332

124

29 1

0090

278

(699

20, 1

1014

1)88

21

033

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na22

73

084

14 9

9529

394

28 5

9376

293

(590

30, 9

4725

)1

993

1 21

9

Afr

Bots

wan

a3

245

296

277

2 28

23

578

9 67

8(5

2, 1

5664

)45

468

0

Amr (

LMIC

)Br

azil

18 9

8216

749

74 9

2136

0 29

824

4 53

271

5 48

2(3

0880

4, 1

0873

05)

353

372

Wpr

HIC

Brun

ei D

arus

sala

m0

01

155

21(0

, 118

4)5

7

Eur (

LMIC

)Bu

lgar

ia1

844

5 24

526

629

80 1

3864

096

177

952

(144

728,

210

701)

2 43

61

329

Afr

Burk

ina

Faso

150

221

4 87

21

426

34 4

3352

956

243

908

(116

116,

380

407)

1 47

01

810

112

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Buru

ndi

125

544

3 40

470

417

749

31 0

1417

8 41

5(7

3231

, 290

149)

1 76

21

734

Afr

Cab

o Ve

rde

28 9

003

427

6 92

935

678

30 3

2710

5 26

1(7

373,

166

998)

710

976

Wpr

(LM

IC)

Cam

bodi

a23

8 43

411

197

2 40

250

839

69 8

3737

2 70

9(3

0010

0, 4

6259

0)1

721

1 86

9

Afr

Cam

eroo

n92

600

10 9

6821

070

6 17

838

908

(742

, 136

028)

112

68

Amr (

HIC

)C

anad

a47

026

943

808

1 63

13

220

(194

7, 4

671)

643

919

Afr

Cen

tral A

frica

n Re

publ

ic41

185

2 67

637

98

431

10 3

0762

979

(292

01, 1

0138

1)1

363

1 41

2

Afr

Cha

d22

0 46

63

830

698

22 1

1132

959

280

064

(147

516,

429

122)

2 20

31

953

Amr (

HIC

)C

hile

1 64

72

848

13 5

3026

963

23 2

2768

215

(500

86, 8

3865

)39

233

4

Wpr

(LM

IC)

Chi

na62

7 49

31

814

679

5 24

3 32

75

662

869

10 3

27 2

3523

675

602

(200

0745

2, 2

7642

228)

1 73

71

546

Amr (

LMIC

)C

olom

bia

15 1

966

759

18 5

6190

746

43 3

1817

4 58

0(1

2124

9, 2

1661

8)37

242

2

Afr

Com

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2 88

910

629

965

1 69

55

684

(944

, 814

6)77

51

029

Afr

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go29

494

2 15

421

810

900

13 5

2156

287

(248

57, 9

0402

)1

313

1 54

7

Wpr

(LM

IC)

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k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

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564

11

502

9 30

63

908

15 5

82(1

1394

, 189

78)

335

334

Eur (

HIC

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ia43

1 45

714

733

26 5

1614

899

57 6

47(4

0452

, 727

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1 34

572

6

Amr (

LMIC

)C

uba

699

2 32

323

481

42 8

4623

308

92 6

58(8

281,

138

762)

817

573

Eur (

HIC

)C

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336

2 81

979

25

059

(339

1, 6

374)

448

341

Eur (

HIC

)C

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Rep

ublic

291

3 12

829

383

65 9

0821

071

119

780

(928

27, 1

4428

2)1

136

639

Afr

Côt

e d’

Ivoi

re13

0 37

84

355

1 31

445

623

66 2

0424

7 87

4(2

6334

, 402

957)

1 17

51

424

Sear

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ocra

tic P

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e’s

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blic

of K

orea

21 1

2328

316

88 7

8498

002

171

148

407

373

(555

92, 6

8401

5)1

645

1 55

9

Afr

Dem

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tic R

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lic

of th

e C

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957

459

26 2

092

700

146

091

213

509

1 34

5 96

7(6

2222

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1272

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1 91

51

859

Eur (

HIC

)D

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ark

2697

08

864

8 00

04

818

22 6

79(1

269,

375

51)

405

228

Emr (

LMIC

)D

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922

357

136

1 60

42

408

9 42

7(3

114,

158

28)

1 10

51

348

Amr (

LMIC

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2814

813

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5(1

8, 4

79)

453

437

Amr (

LMIC

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ican

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7 81

189

73

995

25 4

1715

179

53 3

00(5

078,

771

06)

525

619

Amr (

LMIC

)Ec

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979

1 36

63

463

19 1

6114

295

46 2

64(2

2877

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300

344

Emr (

LMIC

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88 0

5775

577

61 5

8458

6 04

840

9 09

01

220

357

(100

5641

, 146

0546

)1

425

1 94

7

Amr (

LMIC

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Sal

vado

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305

1 85

42

299

22 6

038

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39 0

87(3

0999

, 477

07)

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113

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

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ng c

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r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Equa

toria

l Gui

nea

5 65

335

918

42

297

2 29

610

788

(563

, 190

51)

1 39

41

589

Afr

Eritr

ea33

084

1 85

859

59

785

15 8

4061

162

(239

67, 9

8360

)1

250

1 74

5

Eur (

HIC

)Es

toni

a16

2983

94

235

1 00

36

122

(99,

121

39)

462

258

Afr

Ethi

opia

507

048

26 5

6412

909

65 8

9511

8 25

373

0 67

0(2

3606

9, 1

1892

41)

793

823

Wpr

(LM

IC)

Fiji

20

052

964

(0, 9

832)

79

Eur (

HIC

)Fi

nlan

d14

3569

23

969

1 06

45

774

(33,

287

07)

106

54

Eur (

HIC

)Fr

ance

507

4 71

610

4 98

169

974

49 5

7822

9 75

6(8

2127

, 325

137)

361

215

Afr

Gab

on5

313

735

503

3 18

73

484

13 2

22(2

248,

223

04)

819

966

Afr

Gam

bia

10 4

2452

216

33

219

5 08

819

416

(803

, 360

06)

1 07

41

449

Eur (

LMIC

)G

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ia1

119

1 61

15

139

40 6

1826

204

74 6

92(4

7163

, 951

43)

1 80

51

184

Eur (

HIC

)G

erm

any

723

14 9

0415

8 01

323

2 05

593

848

499

543

(240

916,

663

000)

621

307

Afr

Gha

na88

159

5 67

42

324

53 3

3980

391

229

888

(146

097,

304

536)

900

1 22

1

Eur (

HIC

)G

reec

e11

61

725

19 1

6043

631

27 6

2992

262

(340

43, 1

2390

6)83

043

8

Amr (

LMIC

)G

rena

da4

629

261

208

508

(0, 7

44)

482

567

Amr (

LMIC

)G

uate

mal

a36

351

2 11

84

350

21 4

9311

989

76 3

02(6

0240

, 931

77)

496

590

Afr

Gui

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62 8

802

172

610

22 4

9031

085

119

237

(101

57, 1

9309

9)1

025

1 23

9

Afr

Gui

nea-

Biss

au14

488

426

117

3 51

15

057

23 5

99(1

221,

402

73)

1 37

61

526

Amr (

LMIC

)G

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850

120

3 86

43

072

7 42

3(2

, 114

55)

979

1 19

7

Amr (

LMIC

)H

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52 2

9886

22

590

21 5

3940

891

118

179

(111

82, 1

8281

9)1

149

1 40

3

Amr (

LMIC

)H

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ras

9 11

02

082

2 45

520

255

12 4

6246

363

(363

78, 5

6936

)59

985

8

Eur (

LMIC

)H

unga

ry35

45

035

53 5

6883

414

32 6

6517

5 03

5(1

3290

4, 2

1425

3)1

758

1 03

3

Eur (

HIC

)Ic

elan

d0

796

187

7336

3(2

, 115

3)11

276

Sear

Indi

a3

663

274

3 28

2 84

181

3 67

47

455

375

5 29

0 85

120

506

014

(170

4620

4, 2

4531

628)

1 62

31

986

Sear

Indo

nesi

a23

1 72

741

378

138

292

444

628

913

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1 76

9 10

0(9

3395

9, 2

3580

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713

923

Emr (

LMIC

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n (Is

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of)

55 6

6023

441

38 2

5842

5 11

418

3 55

472

6 02

7(6

2254

8, 8

3416

1)95

31

239

Emr (

LMIC

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673

8 82

819

894

133

068

81 4

3733

5 90

0(2

1681

0, 4

6825

8)1

019

1 73

2

Eur (

HIC

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land

5030

63

145

7 74

52

229

13 4

75(1

051,

214

35)

289

213

Eur (

HIC

)Is

rael

126

1 17

89

436

8 87

65

075

24 6

90(1

8152

, 308

09)

321

266

Eur (

HIC

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ly31

412

191

131

947

136

139

86 6

6336

7 25

3(2

4672

5, 4

6537

7)61

528

8

114

Num

ber o

f DAL

YsD

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100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

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r bIH

D b

Stro

ke b

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l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)Ja

mai

ca76

628

32

143

4 88

86

927

15 0

07(1

0442

, 188

56)

543

539

Wpr

(HIC

)Ja

pan

1 86

87

141

180

791

199

245

197

984

587

030

(233

989,

798

287)

462

219

Emr (

LMIC

)Jo

rdan

5 78

11

722

4 35

321

028

13 2

1846

102

(392

83, 5

3271

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91

117

Eur (

LMIC

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stan

8 09

94

387

19 2

0515

9 61

878

448

269

757

(354

69, 4

1925

4)1

604

1 71

8

Afr

Keny

a18

4 20

03

767

2 30

836

802

49 3

5227

6 42

8(9

1167

, 388

740)

650

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Wpr

(LM

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Kirib

ati

00

00

00

(0, 8

39)

00

Emr (

HIC

)Ku

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138

903

870

10 3

253

307

16 5

43(1

4565

, 187

08)

484

1 02

0

Eur (

LMIC

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stan

4 42

31

095

2 16

331

545

17 1

5356

379

(231

19, 7

4453

)99

81

417

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Lao

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36 2

071

925

3 62

217

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15 7

5274

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1355

4)1

153

1 49

4

Eur (

HIC

)La

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54

852

22 1

559

388

36 7

95(2

6937

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74)

1 80

697

7

Emr (

LMIC

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31

197

5 32

219

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5 29

531

392

(257

07, 3

7039

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766

0

Afr

Leso

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7 48

859

817

02

287

5 18

915

731

(10,

302

74)

765

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Afr

Libe

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781

172

532

210

2 62

610

842

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9905

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933

1

Emr (

LMIC

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2 87

32

782

6 91

625

355

15 7

1153

638

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73, 7

3079

)85

41

333

Eur (

HIC

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55

811

27 7

6311

126

45 4

04(3

4144

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1 50

587

9

Eur (

HIC

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102

865

740

533

2 24

2(1

445,

289

4)42

127

6

Afr

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83 2

403

440

3 98

734

331

54 8

5517

9 85

3(7

7621

, 249

698)

807

1 14

1

Afr

Mal

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68 2

972

764

426

18 3

3129

624

119

442

(260

4, 1

9787

9)76

199

3

Wpr

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Mal

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810

5 68

818

970

93 3

1445

039

165

821

(937

72, 2

1482

1)57

175

1

Sear

Mal

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5496

521

457

1 19

4(3

00, 1

623)

346

537

Afr

Mal

i20

8 35

46

954

1 71

631

584

45 1

9229

3 80

0(1

4730

4, 4

6029

9)1

823

1 90

4

Eur (

HIC

)M

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149

641

1 53

247

72

700

(138

8, 3

448)

650

375

Wpr

(LM

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Mar

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l Isl

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NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

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906

1 87

633

96

466

9 95

349

540

(286

63, 7

7709

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312

1 48

4

Afr

Mau

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s18

815

958

33

892

2 15

26

974

(304

2, 9

097)

554

496

Amr (

LMIC

)M

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o44

235

16 4

3832

017

237

465

106

252

436

407

(325

031,

532

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358

432

Wpr

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5

Eur (

HIC

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7328

135

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59)

360

200

Wpr

(LM

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Mon

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3 60

579

71

714

16 6

7012

598

35 3

84(2

4539

, 439

02)

1 26

01

791

115

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

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Stro

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terv

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rate

Age-

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ized

rate

Eur (

LMIC

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onte

negr

o34

842

409

3 40

22

797

8 72

6(6

362,

108

66)

1 39

995

9

Emr (

LMIC

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oroc

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877

4 68

923

994

92 0

6990

543

245

171

(182

357,

300

280)

743

849

Afr

Moz

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123

049

3 42

91

645

17 0

7833

718

178

918

(397

3, 2

9674

4)69

570

4

Sear

Mya

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139

242

54 0

7176

965

145

603

302

550

718

432

(592

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858

889)

1 36

71

689

Afr

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3 11

055

125

52

414

4 38

710

716

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2, 1

7457

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873

1

Wpr

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Nau

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AN

AN

AN

AN

AN

AN

AN

AN

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53 7

3927

934

88 4

7977

065

315

230

(234

391,

415

553)

1 14

61

533

Eur (

HIC

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ethe

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s13

63

703

42 1

6824

287

15 5

3585

829

(453

88, 1

1645

0)51

229

5

Wpr

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ew Z

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771

238

7439

4(2

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7)9

6

Amr (

LMIC

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6 67

31

080

1 69

018

339

10 9

6638

748

(612

4, 5

8700

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988

9

Afr

Nig

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8 09

17

262

317

31 1

2052

962

379

751

(223

946,

583

674)

2 15

31

945

Afr

Nig

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2 02

2 04

542

132

8 98

830

7 25

944

1 65

02

822

073

(225

0524

, 346

6303

)1

677

1 62

0

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay24

278

2 98

05

787

2 48

911

558

(497

, 227

33)

230

138

Emr (

HIC

)O

man

929

631

727

7 07

14

967

14 3

25(9

601,

194

12)

404

780

Emr (

LMIC

)Pa

kist

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246

970

203

138

71 7

0354

0 88

639

0 11

22

452

808

(199

2965

, 300

3450

)1

383

1 60

5

Wpr

(LM

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Pala

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AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

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406

188

833

5 28

13

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10 7

59(1

478,

157

38)

287

312

Wpr

(LM

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Papu

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a15

096

477

791

6 17

24

455

26 9

92(0

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34)

377

439

Amr (

LMIC

)Pa

ragu

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939

601

2 78

214

433

12 0

7033

825

(157

64, 4

4631

)53

068

8

Amr (

LMIC

)Pe

ru15

256

5 58

615

578

48 5

9535

789

120

804

(928

34, 1

4777

8)40

146

1

Wpr

(LM

IC)

Philip

pine

s15

2 42

931

229

66 0

5344

9 53

531

5 92

81

015

174

(771

359,

123

7902

)1

057

1 39

4

Eur (

HIC

)Po

land

1 26

414

825

145

980

249

921

160

893

572

883

(456

917,

683

994)

1 48

493

4

Eur (

HIC

)Po

rtuga

l65

480

8 05

212

354

12 9

7833

929

(160

9, 5

6590

)32

317

2

Emr (

HIC

)Q

atar

131

749

1 21

73

975

1 55

67

627

(660

5, 8

757)

378

759

Wpr

(HIC

)Re

publ

ic o

f Kor

ea84

77

319

100

350

59 4

8885

509

253

512

(199

622,

306

641)

511

364

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

1 43

580

25

422

40 5

6918

817

67 0

46(0

, 108

018)

1 64

51

316

Eur (

LMIC

)Ro

man

ia8

053

6 09

358

336

143

543

104

935

320

959

(241

726,

390

976)

1 60

91

009

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

12 5

7626

139

266

721

1 95

0 24

397

3 21

73

228

897

(140

0443

, 440

8243

)2

253

1 52

9

116

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Rwan

da67

395

3 58

263

314

892

25 6

8311

2 18

6(5

7267

, 175

976)

1 03

71

251

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

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int L

ucia

8618

7933

940

993

1(1

50, 1

358)

515

510

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s11

521

276

181

495

(0, 7

23)

452

489

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe45

325

2417

131

999

3(0

, 162

3)55

678

1

Emr (

HIC

)Sa

udi A

rabi

a5

842

15 1

5210

749

107

302

81 5

3722

0 58

3(1

9029

0, 2

5357

1)74

81

438

Afr

Sene

gal

56 0

724

088

1 16

314

689

20 9

5396

965

(748

92, 1

2081

6)70

487

4

Eur (

LMIC

)Se

rbia

409

2 98

738

000

48 4

6339

455

129

313

(896

74, 1

6449

4)1

440

891

Afr

Seyc

helle

s8

1053

268

128

467

(37,

689

)49

451

1

Afr

Sier

ra L

eone

67 7

5694

828

813

372

20 5

4510

2 90

9(0

, 192

638)

1 70

31

804

Wpr

(HIC

)Si

ngap

ore

139

373

6 57

513

533

5 98

026

600

(135

53, 3

5797

)50

238

3

Eur (

HIC

)Sl

ovak

ia42

91

077

10 8

8643

118

16 9

0772

417

(556

87, 8

7238

)1

337

896

Eur (

HIC

)Sl

oven

ia17

441

5 19

65

232

4 10

514

990

(105

17, 1

8898

)72

740

2

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 3

114)

00

Emr (

LMIC

)So

mal

ia12

3 95

11

234

735

8 52

113

293

147

735

(696

1, 2

6486

7)1

472

1 11

2

Afr

Sout

h Af

rica

105

724

26 6

8945

262

122

366

174

714

474

754

(371

260,

576

900)

899

1 16

5

Emr (

LMIC

)So

uth

Suda

n10

9 25

32

819

991

14 9

7024

060

152

094

(667

40, 2

3276

6)1

385

1 32

3

Eur (

HIC

)Sp

ain

272

2 57

843

157

58 2

3729

352

133

596

(249

74, 2

1925

7)28

616

2

Sear

Sri L

anka

3 13

29

962

10 0

8311

8 06

554

977

196

219

(141

976,

249

981)

961

931

Emr (

LMIC

)Su

dan

262

610

13 8

443

600

53 1

4888

820

422

022

(228

768,

650

658)

1 11

91

240

Amr (

LMIC

)Su

rinam

e16

735

211

962

871

2 24

6(1

, 374

5)42

546

2

Afr

Swaz

iland

4 73

731

310

81

301

2 27

78

735

(0, 1

5241

)70

990

1

Eur (

HIC

)Sw

eden

16

8342

413

765

0(0

, 305

58)

73

Eur (

HIC

)Sw

itzer

land

411

295

9 38

712

379

5 05

528

158

(784

1, 3

9714

)35

119

3

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

10 9

534

291

14 5

8896

682

37 3

4016

3 85

4(9

5388

, 228

829)

820

1 42

9

Eur (

LMIC

)Ta

jikis

tan

45 5

923

397

3 02

943

484

30 5

6812

6 06

9(6

7187

, 190

103)

1 59

02

390

Sear

Thai

land

9 61

029

447

115

769

219

454

167

934

542

214

(427

557,

656

102)

807

672

117

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

115

938

8 14

910

109

13 8

4033

150

(268

10, 3

9716

)1

602

1 18

0

Sear

Tim

or-L

este

4 58

310

579

71

927

1 51

28

924

(0, 1

7939

)81

094

2

Afr

Togo

44 1

021

506

405

11 6

6417

590

75 2

67(1

1746

, 126

011)

1 11

61

345

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o26

999

739

5 59

72

346

9 04

9(0

, 134

24)

675

607

Emr (

LMIC

)Tu

nisi

a4

130

4 33

314

246

62 0

4636

526

121

282

(975

77, 1

4557

6)1

115

1 14

1

Eur (

LMIC

)Tu

rkey

23 0

3833

004

197

655

371

760

242

166

867

624

(720

077,

101

8543

)1

159

1 23

9

Eur (

LMIC

)Tu

rkm

enis

tan

11 7

992

224

4 06

874

505

28 8

0812

1 40

4(3

7051

, 173

952)

2 34

73

151

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

287

096

14 1

924

228

49 7

7280

711

435

999

(332

422,

563

596)

1 23

21

472

Eur (

LMIC

)U

krai

ne5

780

9 57

173

745

800

250

252

438

1 14

1 78

5(1

8112

, 166

5776

)2

519

1 53

2

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

866

2 53

92

102

17 2

507

722

30 4

79(2

5728

, 357

15)

340

624

Eur (

HIC

)U

nite

d Ki

ngdo

m1

247

11 6

1798

923

141

450

61 2

6031

4 49

7(1

0826

0, 4

3723

2)49

529

1

Afr

Uni

ted

Repu

blic

of

Tanz

ania

174

605

8 07

01

037

46 3

4056

141

286

193

(161

705,

391

100)

588

679

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

3 28

320

221

195

036

473

323

129

932

821

795

(372

19, 1

7525

38)

261

176

Amr (

HIC

)U

rugu

ay33

340

64

233

6 58

63

964

15 5

23(4

369,

219

75)

457

336

Eur (

LMIC

)U

zbek

ista

n65

552

9 03

914

709

251

377

126

711

467

389

(223

133,

674

971)

1 63

52

230

Wpr

(LM

IC)

Vanu

atu

81

330

2668

(0, 1

282)

2744

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

11 9

184

212

21 8

4395

764

41 1

0817

4 84

5(1

2630

2, 2

1802

3)58

670

7

Wpr

(LM

IC)

Viet

Nam

54 5

7637

308

149

065

113

987

333

882

688

818

(493

511,

882

658)

763

845

Emr (

LMIC

)Ye

men

129

343

6 71

53

472

90 4

1567

112

297

057

(123

087,

471

950)

1 19

41

759

Afr

Zam

bia

90 8

212

071

694

15 1

1322

568

131

267

(287

30, 2

0440

3)88

896

4

Afr

Zim

babw

e63

863

2 81

52

578

9 05

115

960

94 2

67(3

907,

154

648)

647

725

DAL

Y : D

isab

ility-

adju

sted

life

year

s ; A

AP : A

mbi

ent a

ir po

llutio

n ; A

LRI :

Acut

e lo

wer

resp

irato

ry d

isea

se ; C

OPD

: Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; IH

D : I

scha

emic

hea

rt di

seas

e. A

fr : A

frica

; Am

r : A

mer

ica ;

Em

r: Ea

ster

n M

edite

rrane

an ; E

ur : E

urop

e ; S

ear :

Sou

th-E

ast A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

; NA:

Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

118

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n16

3 61

14

545

2 69

656

907

50 7

0627

8 46

5(2

1897

9, 3

4686

8)1

929

2 45

6

Eur (

LMIC

)Al

bani

a31

527

91

514

6 76

87

599

16 4

77(6

807,

220

37)

1 14

783

2

Afr

Alge

ria13

818

3 17

13

666

49 5

3161

381

131

566

(525

25, 1

8862

7)70

885

8

Eur (

HIC

)An

dorra

03

1377

4513

8(3

, 207

)34

315

4

Afr

Ango

la13

2 21

42

860

420

18 7

7727

952

182

222

(285

88, 3

0445

1)1

593

1 56

6

Amr (

HIC

)An

tigua

and

Bar

buda

32

710

377

192

(0, 2

79)

412

403

Amr (

LMIC

)Ar

gent

ina

3 36

82

259

10 9

1940

289

26 1

2482

959

(241

29, 1

1429

7)38

630

0

Eur (

LMIC

)Ar

men

ia29

053

81

579

10 8

455

753

19 0

05(7

93, 2

9275

)1

268

836

Wpr

(HIC

)Au

stra

lia4

1112

333

716

764

1(9

, 199

20)

63

Eur (

HIC

)Au

stria

6998

15

960

10 1

124

482

21 6

03(1

4672

, 272

69)

500

234

Eur (

LMIC

)Az

erba

ijan

5 43

81

011

1 48

922

749

13 8

3844

525

(997

9, 6

6106

)94

51

027

Amr (

HIC

)Ba

ham

as11

86

3821

217

755

1(2

, 852

)29

028

2

Emr (

HIC

)Ba

hrai

n74

169

164

598

413

1 41

8(1

236,

161

5)28

257

5

Sear

Bang

lade

sh15

8 98

212

4 06

130

763

81 0

1012

2 60

351

7 41

8(4

1193

8, 6

4578

9)67

391

0

Amr (

HIC

)Ba

rbad

os25

830

168

164

396

(0, 5

92)

270

184

Eur (

LMIC

)Be

laru

s12

562

81

657

55 7

4320

908

79 0

62(1

328,

113

898)

1 55

678

2

Eur (

HIC

)Be

lgiu

m68

1 20

67

617

7 86

96

098

22 8

59(1

4658

, 294

78)

405

210

Amr (

LMIC

)Be

lize

5510

2314

913

437

0(5

7, 5

62)

220

388

Afr

Beni

n29

398

1 13

720

110

737

15 6

4157

113

(175

30, 9

0675

)1

132

1 43

4

Sear

Bhut

an81

239

723

290

079

53

137

(250

4, 3

873)

911

1 26

0

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

11 0

441

272

1 17

513

393

13 3

0640

189

(309

90, 4

9214

)78

789

8

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na96

1 39

32

949

11 0

2414

913

30 3

75(2

3611

, 376

99)

1 58

084

9

Afr

Bots

wan

a1

582

128

471

149

2 21

65

121

(28,

820

0)48

069

9

Amr (

LMIC

)Br

azil

8 61

27

641

30 3

1912

9 83

611

4 39

529

0 80

3(1

2563

2, 4

4460

0)28

328

0

Wpr

HIC

Brun

ei D

arus

sala

m0

01

52

8(0

, 440

)4

5

Eur (

LMIC

)Bu

lgar

ia78

12

248

4 52

730

936

30 8

0169

294

(566

79, 8

1887

)1

847

846

Afr

Burk

ina

Faso

69 4

352

293

682

16 3

0724

911

113

627

(542

19, 1

7720

4)1

357

1 58

2

119

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Buru

ndi

56 9

661

679

352

6 11

912

565

77 6

80(3

1354

, 127

378)

1 51

51

452

Afr

Cab

o Ve

rde

12 1

981

742

2 50

315

599

14 6

4446

687

(328

8, 7

4301

)61

480

7

Wpr

(LM

IC)

Cam

bodi

a10

6 01

04

751

860

22 0

5834

090

167

768

(135

168,

208

012)

1 54

91

683

Afr

Cam

eroo

n46

295

5 12

86

519

3 14

815

136

(275

, 554

44)

8648

Amr (

HIC

)C

anad

a22

699

1926

871

01

323

(794

, 192

3)52

164

9

Afr

Cen

tral A

frica

n Re

publ

ic16

947

1 24

813

13

569

5 17

627

070

(125

97, 4

3574

)1

155

1 21

0

Afr

Cha

d93

449

1 76

529

29

499

15 0

5912

0 06

4(6

3304

, 183

941)

1 89

01

698

Amr (

HIC

)C

hile

640

1 31

75

340

7 68

910

058

25 0

44(1

8119

, 311

54)

284

221

Wpr

(LM

IC)

Chi

na26

5 08

582

7 72

51

467

555

2 65

3 78

44

871

317

10 0

85 4

65(8

5506

89, 1

1763

242)

1 52

51

300

Amr (

LMIC

)C

olom

bia

6 38

33

132

7 24

734

217

22 5

6873

547

(507

91, 9

1728

)30

933

3

Afr

Com

oros

1 31

255

038

172

02

468

(394

, 355

1)67

886

3

Afr

Con

go11

178

914

614

355

6 76

423

271

(103

63, 3

7219

)1

086

1 31

6

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a97

310

498

3 05

61

841

5 80

2(4

206,

713

5)25

023

8

Eur (

HIC

)C

roat

ia18

599

3 56

110

216

7 16

321

558

(154

45, 2

6983

)97

142

8

Amr (

LMIC

)C

uba

323

1 06

18

518

15 7

8410

543

36 2

29(3

171,

544

29)

642

421

Eur (

HIC

)C

ypru

s13

3928

169

537

91

406

(949

, 177

4)25

417

2

Eur (

HIC

)C

zech

Rep

ublic

130

1 34

28

638

24 2

1610

366

44 6

92(3

4810

, 538

13)

833

392

Afr

Côt

e d’

Ivoi

re59

397

1 56

844

418

265

28 3

3910

8 01

3(1

1168

, 175

802)

1 04

41

300

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

10 4

3111

985

36 6

1338

787

70 7

2816

8 54

4(2

2900

, 284

130)

1 33

11

118

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

424

752

11 8

0087

160

000

107

876

605

299

(280

122,

956

296)

1 71

61

673

Eur (

HIC

)D

enm

ark

951

14

403

2 56

82

355

9 84

7(4

51, 1

6835

)34

918

2

Emr (

LMIC

)D

jibou

ti2

073

184

6964

61

024

3 99

5(1

306,

676

2)94

11

137

Amr (

LMIC

)D

omin

ica

32

758

6713

7(7

, 201

)37

934

4

Amr (

LMIC

)D

omin

ican

Rep

ublic

3 22

543

21

558

12 1

477

817

25 1

79(2

416,

362

84)

495

573

Amr (

LMIC

)Ec

uado

r3

487

642

1 46

47

291

6 55

919

444

(946

6, 2

5696

)25

227

7

Emr (

LMIC

)Eg

ypt

45 2

8133

741

17 1

6223

0 91

117

4 59

950

1 69

3(4

1172

8, 6

0373

6)1

183

1 51

9

Amr (

LMIC

)El

Sal

vado

r1

896

1 08

11

063

10 4

134

319

18 7

73(1

4805

, 230

50)

585

618

120

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Equa

toria

l Gui

nea

2 06

013

845

698

994

3 93

5(2

06, 6

985)

1 04

41

249

Afr

Eritr

ea13

873

956

290

3 78

26

828

25 7

29(9

977,

416

92)

1 05

21

409

Eur (

HIC

)Es

toni

a0

1019

21

557

462

2 22

1(2

8, 4

329)

314

125

Afr

Ethi

opia

186

856

8 50

46

760

22 9

0448

890

273

914

(887

17, 4

4427

5)59

362

5

Wpr

(LM

IC)

Fiji

10

013

317

(0, 2

792)

45

Eur (

HIC

)Fi

nlan

d8

1422

31

252

512

2 00

8(1

0, 1

0191

)73

30

Eur (

HIC

)Fr

ance

191

2 08

228

077

21 0

8024

400

75 8

30(2

7007

, 106

138)

233

121

Afr

Gab

on1

886

319

181

1 32

21

837

5 54

5(9

77, 9

312)

694

810

Afr

Gam

bia

4 55

121

240

1 39

82

287

8 48

8(3

55, 1

5697

)93

01

285

Eur (

LMIC

)G

eorg

ia40

373

084

316

583

13 0

2231

582

(198

37, 4

0182

)1

456

782

Eur (

HIC

)G

erm

any

314

6 63

952

661

80 0

5747

119

186

789

(891

54, 2

4808

6)45

619

6

Afr

Gha

na41

021

2 67

950

322

854

45 5

3111

2 58

9(7

1527

, 149

172)

874

1 16

1

Eur (

HIC

)G

reec

e50

836

3 27

315

109

13 9

2633

195

(119

41, 4

3983

)58

525

3

Amr (

LMIC

)G

rena

da2

28

9088

190

(0, 2

78)

360

376

Amr (

LMIC

)G

uate

mal

a16

336

1 04

81

919

8 99

05

912

34 2

05(2

6949

, 418

43)

435

498

Afr

Gui

nea

28 5

9794

718

610

860

15 2

1855

808

(483

9, 9

0054

)96

21

174

Afr

Gui

nea-

Biss

au6

321

181

521

652

2 36

510

570

(563

, 179

70)

1 22

41

377

Amr (

LMIC

)G

uyan

a15

021

571

506

1 35

53

089

(1, 4

795)

816

1 01

6

Amr (

LMIC

)H

aiti

24 0

6439

81

433

10 4

9121

126

57 5

12(5

526,

887

94)

1 10

61

324

Amr (

LMIC

)H

ondu

ras

4 15

192

499

37

456

5 55

919

083

(148

79, 2

3560

)49

367

0

Eur (

LMIC

)H

unga

ry15

62

235

18 8

1633

555

14 7

2069

483

(529

92, 8

4973

)1

330

660

Eur (

HIC

)Ic

elan

d0

351

5736

147

(1, 4

99)

9154

Sear

Indi

a1

875

402

1 38

5 38

620

0 79

12

324

770

2 44

1 64

28

227

991

(679

1629

, 991

6369

)1

352

1 60

3

Sear

Indo

nesi

a98

944

15 7

2538

802

132

955

419

319

705

745

(369

868,

942

950)

574

722

Emr (

LMIC

)Ira

n

(Isla

mic

Rep

ublic

of)

26 7

9410

461

13 2

5715

8 46

480

783

289

758

(247

234,

334

417)

768

1 06

7

Emr (

LMIC

)Ira

q42

735

3 90

75

576

43 2

7931

377

126

874

(808

50, 1

7947

1)77

91

196

Eur (

HIC

)Ire

land

2514

41

282

2 57

01

140

5 16

2(3

60, 8

373)

220

148

Eur (

HIC

)Is

rael

3852

33

008

2 82

52

320

8 71

4(6

403,

109

16)

224

160

Eur (

HIC

)Ita

ly19

45

208

34 7

3048

418

44 6

8013

3 23

1(9

1124

, 167

870)

434

171

121

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Amr (

LMIC

)Ja

mai

ca30

910

341

91

927

3 28

96

047

(427

3, 7

536)

436

401

Wpr

(HIC

)Ja

pan

900

2 52

245

592

59 9

8379

696

188

692

(741

86, 2

5446

5)28

911

7

Emr (

LMIC

)Jo

rdan

2 52

763

565

57

338

6 26

217

416

(148

69, 2

0090

)51

283

0

Eur (

LMIC

)Ka

zakh

stan

3 49

71

748

3 32

260

090

38 8

5110

7 50

8(1

3978

, 166

466)

1 23

51

172

Afr

Keny

a81

300

1 83

392

412

858

20 7

2411

7 63

9(3

7893

, 166

207)

553

588

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 2

75)

00

Emr (

HIC

)Ku

wai

t43

730

122

22

087

1 15

04

197

(365

4, 4

806)

280

718

Eur (

LMIC

)Ky

rgyz

stan

1 87

447

549

112

051

7 32

222

213

(896

1, 2

9373

)77

71

017

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

15 1

7497

81

119

7 61

17

343

32 2

26(1

1699

, 490

33)

989

1 25

1

Eur (

HIC

)La

tvia

1813

373

88

902

4 72

714

519

(107

40, 1

7627

)1

313

528

Emr (

LMIC

)Le

bano

n25

051

01

640

4 83

92

812

10 0

50(8

138,

119

94)

414

424

Afr

Leso

tho

3 43

026

640

1 15

33

051

7 94

0(5

, 150

94)

761

913

Afr

Libe

ria2

809

7518

1 02

41

279

5 20

5(1

, 143

50)

250

313

Emr (

LMIC

)Li

bya

1 21

91

221

937

9 81

67

367

20 5

60(1

4039

, 280

32)

665

982

Eur (

HIC

)Li

thua

nia

5221

485

311

156

5 79

518

070

(137

16, 2

1749

)1

110

485

Eur (

HIC

)Lu

xem

bour

g2

4827

321

126

379

7(5

13, 1

034)

299

172

Afr

Mad

agas

car

37 3

321

736

700

13 4

3726

596

79 8

00(3

4195

, 111

029)

713

1 00

3

Afr

Mal

awi

34 9

761

297

158

8 95

215

385

60 7

68(1

252,

100

625)

772

955

Wpr

(LM

IC)

Mal

aysi

a1

244

2 16

06

419

31 1

7319

671

60 6

67(3

4118

, 788

86)

414

573

Sear

Mal

dive

s28

2816

196

121

390

(94,

535

)22

736

9

Afr

Mal

i95

151

2 68

671

617

343

25 2

9414

1 18

9(7

1709

, 219

164)

1 76

81

890

Eur (

HIC

)M

alta

118

166

536

204

924

(482

, 117

1)44

323

3

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia11

735

851

108

3 07

64

875

20 6

45(1

2030

, 321

97)

1 09

91

289

Afr

Mau

ritiu

s67

6815

91

189

805

2 28

7(9

82, 3

001)

360

306

Amr (

LMIC

)M

exic

o19

473

7 80

412

314

87 1

7652

245

179

012

(132

184,

219

783)

292

337

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

00

1(0

, 239

)2

3

Eur (

HIC

)M

onac

o0

18

2414

48(0

, 90)

248

108

122

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Wpr

(LM

IC)

Mon

golia

1 41

133

230

45

429

5 21

712

692

(877

3, 1

5800

)89

61

251

Eur (

LMIC

)M

onte

negr

o14

4257

080

01

058

2 48

5(1

811,

310

7)78

747

9

Emr (

LMIC

)M

oroc

co14

612

1 96

02

641

36 7

6247

169

103

143

(775

55, 1

2555

9)61

769

2

Afr

Moz

ambi

que

51 6

821

885

613

8 08

315

641

77 9

04(1

852,

129

366)

590

599

Sear

Mya

nmar

58 5

8630

229

33 9

2882

007

142

251

347

000

(285

845,

415

517)

1 29

01

524

Afr

Nam

ibia

1 43

226

290

1 24

52

732

5 76

1(6

71, 9

291)

489

727

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al32

578

27 3

8514

513

36 7

0237

666

148

843

(109

737,

197

727)

1 05

21

403

Eur (

HIC

)N

ethe

rland

s61

1 82

317

011

7 86

28

069

34 8

26(1

8165

, 476

13)

412

226

Wpr

(HIC

)N

ew Z

eala

nd2

437

7441

157

(1, 3

598)

74

Amr (

LMIC

)N

icar

agua

2 76

950

966

87

037

4 97

715

961

(252

9, 2

4390

)53

568

7

Afr

Nig

er11

9 48

73

201

4915

138

25 7

8116

3 65

6(9

6959

, 250

625)

1 87

01

834

Afr

Nig

eria

865

909

18 7

434

587

129

845

212

374

1 23

1 45

8(9

8255

7, 1

5118

46)

1 49

01

474

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay9

141

1 26

61

944

1 24

34

603

(177

, 927

6)18

495

Emr (

HIC

)O

man

488

207

153

2 01

91

479

4 34

7(2

890,

596

4)33

365

0

Emr (

LMIC

)Pa

kist

an53

6 18

864

594

11 8

1323

8 54

020

6 18

81

057

323

(865

895,

128

6013

)1

226

1 43

8

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a74

989

272

1 64

21

391

4 14

3(5

43, 6

148)

222

231

Wpr

(LM

IC)

Papu

a N

ew G

uine

a6

811

191

268

2 48

41

293

11 0

48(0

, 269

94)

315

346

Amr (

LMIC

)Pa

ragu

ay1

734

245

530

4 80

74

999

12 3

16(5

690,

162

31)

392

492

Amr (

LMIC

)Pe

ru6

762

2 91

97

709

19 0

5816

694

53 1

42(4

0460

, 655

42)

352

387

Wpr

(LM

IC)

Philip

pine

s69

227

11 7

5718

781

145

146

121

997

366

909

(276

926,

449

216)

773

974

Eur (

HIC

)Po

land

496

5 65

143

761

82 5

0472

796

205

208

(163

918,

245

221)

1 03

054

4

Eur (

HIC

)Po

rtuga

l31

183

1 60

24

182

6 00

111

999

(520

, 193

90)

218

96

Emr (

HIC

)Q

atar

5515

218

854

221

61

152

(982

, 134

5)22

662

3

Wpr

(HIC

)Re

publ

ic o

f Kor

ea34

02

706

26 2

1618

267

35 8

5483

383

(661

74, 1

0056

4)33

420

8

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

666

291

994

17 6

028

993

28 5

46(0

, 453

40)

1 35

093

7

Eur (

LMIC

)Ro

man

ia3

646

2 27

211

074

51 9

7448

246

117

212

(894

67, 1

4178

3)1

141

617

123

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

5 83

99

006

40 5

1070

4 44

047

5 18

91

234

984

(527

150,

168

0821

)1

608

878

Afr

Rwan

da30

079

1 80

223

15

904

11 4

4949

465

(250

80, 7

8080

)87

61

014

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

347

2112

317

936

5(5

8, 5

30)

396

375

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s5

26

119

9222

4(0

, 327

)41

342

5

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe20

410

793

174

488

(0, 7

88)

544

749

Emr (

HIC

)Sa

udi A

rabi

a2

853

5 53

82

890

31 3

3233

455

76 0

67(6

5190

, 879

50)

592

1 12

9

Afr

Sene

gal

24 2

671

792

438

6 70

010

217

43 4

14(3

3590

, 539

83)

618

761

Eur (

LMIC

)Se

rbia

151

1 22

910

159

15 8

1819

624

46 9

80(3

3048

, 594

79)

1 02

355

9

Afr

Seyc

helle

s3

49

7943

138

(10,

202

)29

827

6

Afr

Sier

ra L

eone

32 0

9540

610

26

485

10 4

7749

564

(0, 9

2534

)1

622

1 76

5

Wpr

(HIC

)Si

ngap

ore

5310

52

167

3 99

72

662

8 98

4(4

528,

121

30)

335

246

Eur (

HIC

)Sl

ovak

ia22

346

12

860

16 3

357

413

27 2

93(2

1087

, 328

09)

978

549

Eur (

HIC

)Sl

oven

ia13

189

1 47

91

609

1 95

55

246

(370

7, 6

608)

505

234

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 1

070)

00

Emr (

LMIC

)So

mal

ia57

026

680

350

3 08

25

647

66 7

83(3

053,

120

293)

1 32

497

2

Afr

Sout

h Af

rica

46 4

1811

699

14 7

3747

429

93 2

8121

3 56

4(1

6718

8, 2

5912

7)79

490

8

Emr (

LMIC

)So

uth

Suda

n47

751

1 27

142

95

899

11 0

1866

368

(290

30, 1

0171

5)1

209

1 14

7

Eur (

HIC

)Sp

ain

9573

78

211

17 3

2914

080

40 4

52(7

494,

641

93)

171

80

Sear

Sri L

anka

1 28

14

155

2 75

635

646

20 8

6864

706

(462

74, 8

3474

)61

456

9

Emr (

LMIC

)Su

dan

111

778

6 27

21

187

21 1

1840

873

181

229

(980

58, 2

7984

8)96

51

073

Amr (

LMIC

)Su

rinam

e15

1847

373

390

842

(0, 1

391)

319

331

Afr

Swaz

iland

2 08

015

937

745

1 56

54

586

(0, 7

901)

734

951

Eur (

HIC

)Sw

eden

13

4115

271

267

(0, 1

3190

)6

2

Eur (

HIC

)Sw

itzer

land

1962

43

478

4 10

22

621

10 8

44(2

860,

154

47)

267

130

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

4 60

41

834

2 70

734

104

12 3

2055

568

(327

06, 7

7627

)56

394

1

Eur (

LMIC

)Ta

jikis

tan

19 4

631

764

1 18

220

390

17 4

1260

211

(322

52, 9

0532

)1

532

2 34

9

124

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

IaC

OPD

bLu

ng c

ance

rbIH

Db

Stro

keb

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Sear

Thai

land

3 93

49

545

38 2

1087

104

72 6

9421

1 48

6(1

6814

0, 2

5434

1)62

249

2

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

5539

51

489

3 17

36

495

11 6

06(9

434,

138

86)

1 11

775

4

Sear

Tim

or-L

este

2 12

649

259

924

710

4 06

8(0

, 810

3)75

084

9

Afr

Togo

21 1

0965

711

45

565

8 86

036

305

(571

1, 6

0632

)1

062

1 26

5

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o13

430

188

1 73

597

13

057

(0, 4

540)

451

386

Emr (

LMIC

)Tu

nisi

a1

785

1 89

786

121

809

15 4

8341

833

(338

29, 5

0181

)76

175

3

Eur (

LMIC

)Tu

rkey

9 73

413

423

25 1

7813

2 38

610

4 84

028

5 56

1(2

3971

2, 3

3343

0)75

074

5

Eur (

LMIC

)Tu

rkm

enis

tan

4 81

71

001

882

26 3

7013

273

46 3

43(1

4031

, 669

68)

1 76

42

330

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

122

133

7 02

42

085

18 0

1736

198

185

457

(140

980,

240

534)

1 04

71

220

Eur (

LMIC

)U

krai

ne2

365

3 32

511

354

351

024

129

729

497

797

(637

5, 7

1894

1)2

043

984

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

329

599

480

1 92

61

267

4 60

1(3

773,

555

8)20

257

0

Eur (

HIC

)U

nite

d Ki

ngdo

m59

15

841

44 0

5343

328

31 6

6612

5 48

0(4

0268

, 178

286)

389

204

Afr

Uni

ted

Repu

blic

of

Tanz

ania

76 7

903

874

433

17 6

8624

012

122

794

(687

71, 1

6858

5)50

257

4

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1 46

710

443

86 6

5516

1 52

465

810

325

901

(145

81, 7

1501

6)20

512

6

Amr (

HIC

)U

rugu

ay17

114

089

91

949

1 99

65

155

(147

8, 7

170)

293

186

Eur (

LMIC

)U

zbek

ista

n27

482

4 22

83

773

101

309

61 1

1519

7 90

6(9

3815

, 286

989)

1 36

21

742

Wpr

(LM

IC)

Vanu

atu

40

19

822

(0, 4

21)

1829

Amr (

LMIC

)Ve

nezu

ela,

Bol

ivar

ian

Repu

blic

of

5 19

02

044

9 31

930

503

18 1

2365

179

(463

43, 8

2205

)43

550

1

Wpr

(LM

IC)

Viet

Nam

21 2

9318

044

36 2

7835

674

121

354

232

643

(166

229,

300

933)

509

497

Emr (

LMIC

)Ye

men

57 6

593

237

913

31 8

3229

562

123

202

(497

69, 1

9827

0)1

001

1 41

7

Afr

Zam

bia

43 1

311

127

290

5 26

29

062

58 8

70(1

2202

, 925

38)

795

782

Afr

Zim

babw

e31

471

1 32

095

04

229

8 59

546

566

(193

5, 7

6231

)63

169

1

DAL

Y : D

isab

ility-

adju

sted

life

yea

rs ; A

AP : A

mbi

ent a

ir po

llutio

n ; A

LRI :

Acut

e lo

wer

resp

irato

ry d

isea

se ; C

OPD

: Chr

onic

obs

truct

ive

pulm

onar

y di

seas

e ; IH

D : I

scha

emic

hea

rt di

seas

e. A

fr : A

frica

; Am

r :

Amer

ica ;

Em

r: Ea

ster

n M

edite

rrane

an ; E

ur: E

urop

e ; S

ear :

Sou

th-E

ast A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC: H

igh-

inco

me

coun

tries

; NA

: Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.

125

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Af

ghan

ista

n17

9 74

74

700

7 21

964

849

38 2

2829

4 74

3(2

3128

5, 3

6806

4)1

928

2 54

3

Eur (

LMIC

)Al

bani

a43

032

53

078

9 95

56

905

20 6

92(8

739,

277

12)

1 43

31

161

Afr

Alge

ria17

783

4 36

715

767

88 5

3174

055

200

502

(802

65, 2

8638

5)1

064

1 33

9

Eur (

HIC

)An

dorra

04

4515

746

252

(8, 3

81)

644

399

Afr

Ango

la20

3 33

03

692

765

28 4

1925

948

262

154

(395

17, 4

3980

3)2

331

2 11

0

Amr (

HIC

)An

tigua

and

Bar

buda

52

1515

286

259

(0, 3

78)

610

655

Amr (

LMIC

)Ar

gent

ina

4 54

23

080

26 6

2770

328

32 9

6613

7 54

3(3

9993

, 190

704)

668

658

Eur (

LMIC

)Ar

men

ia47

285

28

134

20 3

137

225

36 9

96(1

732,

582

07)

2 50

02

286

Wpr

(HIC

)Au

stra

lia4

1218

171

315

11

060

(17,

308

51)

97

Eur (

HIC

)Au

stria

301

130

10 6

2117

049

4 24

833

078

(225

48, 4

1572

)80

048

8

Eur (

LMIC

)Az

erba

ijan

6 84

51

202

5 96

138

661

14 7

4167

410

(156

13, 9

9461

)1

450

1 78

1

Amr (

HIC

)Ba

ham

as15

69

8842

421

689

3(3

, 137

1)49

055

4

Emr (

HIC

)Ba

hrai

n87

342

456

1 67

974

93

313

(291

5, 3

739)

398

803

Sear

Bang

lade

sh19

4 85

314

7 60

191

102

189

574

126

707

749

837

(607

961,

919

646)

956

1 30

9

Amr (

HIC

)Ba

rbad

os35

1162

299

217

623

(0, 9

27)

462

364

Eur (

LMIC

)Be

laru

s24

71

458

13 6

4390

038

22 9

2612

8 31

2(2

936,

188

471)

2 90

92

297

Eur (

HIC

)Be

lgiu

m87

1 74

920

428

17 0

406

440

45 7

44(2

8453

, 594

54)

842

514

Amr (

LMIC

)Be

lize

3829

5721

514

748

5(7

6, 7

62)

289

496

Afr

Beni

n35

681

1 62

837

312

350

16 2

0266

234

(199

71, 1

0587

9)1

323

1 75

0

Sear

Bhut

an1

064

608

233

1 43

365

73

995

(317

5, 4

967)

1 00

01

292

Amr (

LMIC

)Bo

livia

, Plu

rinat

iona

l St

ates

of

13 2

891

197

1 07

818

732

15 7

9450

089

(389

42, 6

0930

)97

61

173

Eur (

LMIC

)Bo

snia

and

H

erze

govi

na13

11

691

12 0

4618

370

13 6

8045

918

(353

06, 5

7027

)2

409

1 62

6

Afr

Bots

wan

a1

663

168

230

1 13

31

363

4 55

7(2

3, 7

471)

428

645

Amr (

LMIC

)Br

azil

10 3

709

108

44 6

0223

0 46

213

0 13

742

4 67

9(1

8350

8, 6

4289

0)42

648

2

Wpr

HIC

Brun

ei D

arus

sala

m0

01

103

13(0

, 749

)6

9

Eur (

LMIC

)Bu

lgar

ia1

063

2 99

722

101

49 2

0233

295

108

658

(878

55, 1

2899

3)3

058

1 88

0

126

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Afr

Burk

ina

Faso

80 7

862

579

744

18 1

2628

045

130

281

(619

61, 2

0325

5)1

585

2 09

3

Afr

Buru

ndi

68 5

781

725

352

11 6

3118

449

100

735

(418

65, 1

6277

1)2

016

2 02

1

Afr

Cab

o Ve

rde

16 7

021

685

4 42

620

078

15 6

8258

574

(398

7, 9

2741

)81

01

184

Wpr

(LM

IC)

Cam

bodi

a13

2 42

46

446

1 54

228

781

35 7

4720

4 94

1(1

6495

9, 2

5460

0)1

893

2 05

9

Afr

Cam

eroo

n45

305

5 84

014

552

3 03

023

772

(484

, 807

16)

137

90

Amr (

HIC

)C

anad

a24

416

924

539

920

1 89

7(1

151,

274

9)76

91

282

Afr

Cen

tral A

frica

n Re

publ

ic24

238

1 42

824

84

862

5 13

235

909

(166

13, 5

7810

)1

578

1 62

4

Afr

Cha

d12

7 01

72

065

407

12 6

1217

900

160

001

(842

19, 2

4518

0)2

515

2 21

3

Amr (

HIC

)C

hile

1 00

71

531

8 19

019

274

13 1

7043

171

(319

45, 5

2726

)50

346

6

Wpr

(LM

IC)

Chi

na36

2 40

898

6 95

43

775

771

3 00

9 08

55

455

918

13 5

90 1

37(1

1453

348,

15

8950

66)

1 93

71

800

Amr (

LMIC

)C

olom

bia

8 81

33

626

11 3

1456

529

20 7

5010

1 03

3(7

0274

, 124

947)

437

526

Afr

Com

oros

1 57

751

2958

597

53

217

(553

, 459

4)86

91

205

Afr

Con

go18

315

1 24

115

76

545

6 75

733

016

(144

82, 5

3167

)1

540

1 78

4

Wpr

(LM

IC)

Coo

k Is

land

sN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)C

osta

Ric

a12

833

11

004

6 25

02

068

9 78

0(7

184,

118

48)

420

435

Eur (

HIC

)C

roat

ia25

857

11 1

7216

300

7 73

636

090

(249

65, 4

5828

)1

746

1 07

6

Amr (

LMIC

)C

uba

377

1 26

214

963

27 0

6212

765

56 4

28(5

158,

843

32)

990

731

Eur (

HIC

)C

ypru

s0

601

055

2 12

541

33

653

(243

8, 4

604)

633

517

Eur (

HIC

)C

zech

Rep

ublic

161

1 78

620

745

41 6

9110

706

75 0

89(5

7985

, 905

84)

1 45

092

6

Afr

Côt

e d’

Ivoi

re70

981

2 78

787

027

358

37 8

6413

9 86

1(1

5190

, 227

195)

1 30

01

535

Sear

Dem

ocra

tic P

eopl

e’s

Repu

blic

of K

orea

10 6

9216

331

52 1

7159

216

100

420

238

829

(323

56, 3

9993

7)1

973

2 18

2

Afr

Dem

ocra

tic R

epub

lic

of th

e C

ongo

532

707

14 4

091

828

86 0

9110

5 63

374

0 66

8(3

4250

1, 1

1711

49)

2 11

52

046

Eur (

HIC

)D

enm

ark

1745

94

460

5 43

22

463

12 8

32(7

81, 2

0723

)46

227

9

Emr (

LMIC

)D

jibou

ti2

850

173

6895

81

383

5 43

2(1

806,

906

0)1

268

1 56

5

Amr (

LMIC

)D

omin

ica

54

2190

6818

8(1

0, 2

78)

528

533

Amr (

LMIC

)D

omin

ican

Rep

ublic

4 58

746

52

437

13 2

707

362

28 1

21(2

633,

408

40)

555

666

Amr (

LMIC

)Ec

uado

r4

492

724

1 99

911

870

7 73

626

820

(133

93, 3

5088

)34

841

6

127

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Emr (

LMIC

)Eg

ypt

42 7

7641

837

44 4

2235

5 13

723

4 49

271

8 66

4(5

9380

4, 8

5661

9)1

661

2 40

9

Amr (

LMIC

)El

Sal

vado

r2

409

773

1 23

612

190

3 70

620

314

(161

84, 2

4659

)71

084

3

Afr

Equa

toria

l Gui

nea

3 59

322

113

91

599

1 30

26

854

(356

, 120

68)

1 72

71

900

Afr

Eritr

ea19

211

902

305

6 00

39

012

35 4

33(1

3988

, 566

67)

1 44

82

141

Eur (

HIC

)Es

toni

a15

1964

72

678

541

3 90

1(7

0, 7

830)

632

440

Afr

Ethi

opia

320

192

18 0

606

149

42 9

9169

363

456

756

(147

255,

745

078)

993

1 02

9

Wpr

(LM

IC)

Fiji

10

040

647

(0, 7

043)

1113

Eur (

HIC

)Fi

nlan

d6

2146

92

717

553

3 76

6(2

3, 1

8586

)14

181

Eur (

HIC

)Fr

ance

316

2 63

376

905

48 8

9425

178

153

926

(544

70, 2

1928

8)49

731

9

Afr

Gab

on3

427

417

322

1 86

51

647

7 67

8(1

255,

130

05)

942

1 12

6

Afr

Gam

bia

5 87

330

912

31

821

2 80

210

928

(448

, 203

09)

1 22

11

610

Eur (

LMIC

)G

eorg

ia71

688

14

296

24 0

3513

182

43 1

10(2

7173

, 549

89)

2 18

91

695

Eur (

HIC

)G

erm

any

409

8 26

510

5 35

315

1 99

846

729

312

754

(152

163,

415

287)

792

429

Afr

Gha

na47

138

2 99

51

821

30 4

8534

860

117

299

(744

56, 1

5543

7)92

71

277

Eur (

HIC

)G

reec

e66

889

15 8

8728

522

13 7

0359

067

(216

33, 8

0081

)1

086

641

Amr (

LMIC

)G

rena

da3

422

171

120

319

(0, 4

66)

604

793

Amr (

LMIC

)G

uate

mal

a20

016

1 07

02

431

12 5

036

077

42 0

97(3

3300

, 513

35)

560

696

Afr

Gui

nea

34 2

821

224

424

11 6

3015

867

63 4

29(5

271,

103

042)

1 08

91

301

Afr

Gui

nea-

Biss

au8

167

245

651

859

2 69

213

029

(648

, 223

02)

1 53

11

677

Amr (

LMIC

)G

uyan

a16

829

632

358

1 71

74

335

(1, 6

661)

1 14

11

389

Amr (

LMIC

)H

aiti

28 2

3446

31

157

11 0

4819

766

60 6

67(5

505,

940

26)

1 19

21

488

Amr (

LMIC

)H

ondu

ras

4 96

01

158

1 46

212

798

6 90

327

280

(214

99, 3

3372

)70

51

054

Eur (

LMIC

)H

unga

ry19

72

800

34 7

5249

859

17 9

4510

5 55

2(7

9789

, 129

379)

2 23

01

508

Eur (

HIC

)Ic

elan

d0

445

130

3721

6(2

, 655

)13

398

Sear

Indi

a1

787

871

1 89

7 45

661

2 88

35

130

605

2 84

9 20

912

278

024

(102

6216

6,

1460

6630

)1

874

2 36

3

Sear

Indo

nesi

a13

2 78

325

653

99 4

9031

1 67

349

3 75

61

063

355

(561

844,

141

5551

)85

11

136

Emr (

LMIC

)Ira

n (Is

lam

ic

Repu

blic

of)

28 8

6612

981

25 0

0126

6 65

010

2 77

143

6 26

9(3

7512

6, 4

9963

8)1

136

1 40

9

Emr (

LMIC

)Ira

q49

938

4 92

114

319

89 7

8850

060

209

026

(135

965,

288

780)

1 25

42

333

Eur (

HIC

)Ire

land

2516

11

863

5 17

61

090

8 31

4(6

48, 1

3074

)35

728

4

128

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)Is

rael

8865

56

429

6 05

02

755

15 9

76(1

1742

, 198

91)

420

387

Eur (

HIC

)Ita

ly11

96

983

97 2

1787

721

41 9

8323

4 02

3(1

5531

5, 2

9820

2)80

742

2

Amr (

LMIC

)Ja

mai

ca45

718

01

724

2 96

13

638

8 96

1(6

146,

113

37)

652

681

Wpr

(HIC

)Ja

pan

968

4 62

013

5 19

913

9 26

211

8 28

839

8 33

7(1

5771

5, 5

4435

2)64

433

2

Emr (

LMIC

)Jo

rdan

3 25

51

087

3 69

713

691

6 95

628

686

(244

04, 3

3165

)79

81

405

Eur (

LMIC

)Ka

zakh

stan

4 60

32

639

15 8

8399

528

39 5

9716

2 24

9(2

1184

, 252

935)

1 99

92

433

Afr

Keny

a10

2 90

01

934

1 38

423

944

28 6

2815

8 79

0(5

3320

, 222

532)

747

850

Wpr

(LM

IC)

Kirib

ati

00

00

00

(0, 5

65)

01

Emr (

HIC

)Ku

wai

t70

160

264

88

238

2 15

712

346

(109

09, 1

3904

)64

31

227

Eur (

LMIC

)Ky

rgyz

stan

2 55

062

01

672

19 4

949

831

34 1

66(1

4021

, 450

95)

1 22

51

902

Wpr

(LM

IC)

Lao

Peop

le’s

D

emoc

ratic

Rep

ublic

21 0

3294

72

503

9 52

38

409

42 4

15(1

5025

, 645

45)

1 31

91

764

Eur (

HIC

)La

tvia

2722

24

113

13 2

534

661

22 2

76(1

6099

, 274

05)

2 39

11

618

Emr (

LMIC

)Le

bano

n31

368

73

682

14 1

772

483

21 3

42(1

7553

, 250

44)

856

878

Afr

Leso

tho

4 05

833

213

01

134

2 13

87

791

(5, 1

5185

)76

91

065

Afr

Libe

ria2

972

9735

1 18

61

347

5 63

7(1

, 155

53)

267

349

Emr (

LMIC

)Li

bya

1 65

41

561

5 97

915

540

8 34

533

079

(222

09, 4

5072

)1

036

1 70

3

Eur (

HIC

)Li

thua

nia

3740

14

958

16 6

075

331

27 3

35(2

0321

, 333

13)

1 96

81

396

Eur (

HIC

)Lu

xem

bour

g0

5359

253

027

01

445

(929

, 185

9)54

438

6

Afr

Mad

agas

car

45 9

081

704

3 28

720

894

28 2

6010

0 05

3(4

3326

, 138

723)

901

1 28

5

Afr

Mal

awi

33 3

211

467

268

9 37

914

239

58 6

74(1

292,

972

77)

750

1 03

1

Wpr

(LM

IC)

Mal

aysi

a1

566

3 52

912

551

62 1

4125

368

105

154

(593

44, 1

3595

9)73

193

7

Sear

Mal

dive

s38

2580

325

336

804

(205

, 108

8)46

570

3

Afr

Mal

i11

3 20

34

269

1 00

014

241

19 8

9915

2 61

1(7

5546

, 241

047)

1 87

81

912

Eur (

HIC

)M

alta

131

475

997

273

1 77

6(9

03, 2

280)

859

531

Wpr

(LM

IC)

Mar

shal

l Isl

ands

NA

NA

NA

NA

NA

NA

NA

NA

NA

Afr

Mau

ritan

ia19

171

1 02

623

03

390

5 07

828

895

(166

24, 4

5511

)1

521

1 68

0

Afr

Mau

ritiu

s12

191

424

2 70

31

347

4 68

6(2

032,

609

8)75

270

8

Amr (

LMIC

)M

exic

o24

762

8 63

419

703

150

289

54 0

0725

7 39

5(1

9280

3, 3

1252

2)42

453

5

Wpr

(LM

IC)

Mic

rone

sia

(Fed

erat

ed S

tate

s of

)0

00

11

2(0

, 425

)4

6

129

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

HIC

)M

onac

o0

123

4914

87(0

, 169

)47

730

1

Wpr

(LM

IC)

Mon

golia

2 19

446

51

410

11 2

417

382

22 6

92(1

5755

, 281

08)

1 63

02

413

Eur (

LMIC

)M

onte

negr

o20

421

838

2 60

21

739

6 24

1(4

548,

776

0)2

026

1 50

6

Emr (

LMIC

)M

oroc

co19

265

2 72

921

354

55 3

0743

374

142

028

(104

639,

174

822)

874

1 01

2

Afr

Moz

ambi

que

71 3

661

545

1 03

28

995

18 0

7710

1 01

4(2

118,

167

374)

806

824

Sear

Mya

nmar

80 6

5723

843

43 0

3763

596

160

299

371

432

(306

289,

443

553)

1 44

81

882

Afr

Nam

ibia

1 67

828

916

41

168

1 65

54

955

(527

, 816

6)44

573

3

Wpr

(LM

IC)

Nau

ruN

AN

AN

AN

AN

AN

AN

AN

AN

A

Sear

Nep

al35

435

26 3

5413

421

51 7

7839

398

166

387

(124

723,

217

702)

1 24

71

666

Eur (

HIC

)N

ethe

rland

s75

1 87

925

158

16 4

257

466

51 0

03(2

7229

, 689

19)

614

375

Wpr

(HIC

)N

ew Z

eala

nd2

334

164

3323

6(2

, 491

5)11

8

Amr (

LMIC

)N

icar

agua

3 90

357

11

022

11 3

025

989

22 7

87(3

599,

343

18)

787

1 12

4

Afr

Nig

er16

8 60

44

061

267

15 9

8227

181

216

095

(126

988,

333

049)

2 43

32

040

Afr

Nig

eria

1 15

6 13

623

389

4 40

017

7 41

422

9 27

61

590

615

(126

8077

, 195

4374

)1

858

1 76

1

Wpr

(LM

IC)

Niu

eN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)N

orw

ay15

137

1 71

43

843

1 24

66

955

(310

, 134

68)

276

183

Emr (

HIC

)O

man

441

424

574

5 05

13

488

9 97

8(6

705,

134

52)

445

881

Emr (

LMIC

)Pa

kist

an71

0 78

113

8 54

359

890

302

346

183

925

1 39

5 48

6(1

1271

21,

1716

701)

1 53

11

765

Wpr

(LM

IC)

Pala

uN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Pa

nam

a65

799

562

3 63

91

659

6 61

5(9

11, 9

593)

352

398

Wpr

(LM

IC)

Papu

a N

ew G

uine

a8

285

286

524

3 68

83

162

15 9

44(0

, 387

48)

437

538

Amr (

LMIC

)Pa

ragu

ay2

205

356

2 25

29

625

7 07

121

509

(996

1, 2

8424

)66

488

3

Amr (

LMIC

)Pe

ru8

494

2 66

77

869

29 5

3719

096

67 6

63(5

2367

, 822

70)

449

543

Wpr

(LM

IC)

Philip

pine

s83

202

19 4

7147

272

304

389

193

931

648

265

(493

810,

788

684)

1 33

51

847

Eur (

HIC

)Po

land

768

9 17

410

2 21

916

7 41

788

097

367

674

(292

598,

439

065)

1 96

81

404

Eur (

HIC

)Po

rtuga

l34

297

6 45

18

171

6 97

721

930

(100

4, 3

7264

)43

826

0

Emr (

HIC

)Q

atar

7659

71

028

3 43

31

340

6 47

5(5

621,

741

2)43

079

6

Wpr

(HIC

)Re

publ

ic o

f Kor

ea50

64

613

74 1

3441

221

49 6

5517

0 12

9(1

3326

1, 2

0629

2)69

055

7

Eur (

LMIC

)Re

publ

ic o

f Mol

dova

769

511

4 42

822

968

9 82

438

500

(0, 6

2769

)1

964

1 79

4

130

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Ro

man

ia4

406

3 82

047

262

91 5

6856

690

203

747

(151

783,

249

488)

2 10

61

461

Eur (

HIC

)Ru

ssia

n Fe

dera

tion

6 73

817

133

226

211

1 24

5 80

349

8 02

81

993

913

(861

636,

272

9202

)2

999

2 42

5

Afr

Rwan

da37

317

1 78

040

28

988

14 2

3462

721

(321

79, 9

7908

)1

213

1 56

6

Amr (

HIC

)Sa

int K

itts

and

Nev

isN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

LMIC

)Sa

int L

ucia

5211

5821

622

956

6(9

2, 8

28)

637

655

Amr (

LMIC

)Sa

int V

ince

nt a

nd th

e G

rena

dine

s6

315

157

8927

1(0

, 397

)49

155

4

Wpr

(LM

IC)

Sam

oaN

AN

AN

AN

AN

AN

AN

AN

AN

A

Eur (

HIC

)Sa

n M

arin

oN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Sao

Tom

e an

d Pr

inci

pe24

915

1878

145

505

(0, 8

36)

568

821

Emr (

HIC

)Sa

udi A

rabi

a2

989

9 61

47

860

75 9

7148

082

144

516

(125

044,

165

703)

868

1 71

8

Afr

Sene

gal

31 8

062

296

726

7 98

810

735

53 5

51(4

1279

, 668

17)

793

1 00

7

Eur (

LMIC

)Se

rbia

258

1 75

827

841

32 6

4519

832

82 3

33(5

6535

, 105

013)

1 87

61

258

Afr

Seyc

helle

s5

644

189

8532

9(2

4, 4

87)

682

753

Afr

Sier

ra L

eone

35 6

6154

218

66

887

10 0

6953

345

(0, 1

0010

4)1

786

1 84

2

Wpr

(HIC

)Si

ngap

ore

8626

84

408

9 53

63

317

17 6

16(8

985,

236

66)

674

532

Eur (

HIC

)Sl

ovak

ia20

661

68

026

26 7

839

494

45 1

25(3

4565

, 544

31)

1 71

91

326

Eur (

HIC

)Sl

oven

ia3

252

3 71

73

623

2 15

09

744

(679

8, 1

2304

)95

259

2

Wpr

(LM

IC)

Solo

mon

Isla

nds

00

00

00

(0, 2

046)

00

Emr (

LMIC

)So

mal

ia66

926

555

385

5 44

07

646

80 9

52(3

884,

144

582)

1 62

21

258

Afr

Sout

h Af

rica

59 3

0614

990

30 5

2574

937

81 4

3326

1 19

0(2

0399

6, 3

1762

0)1

007

1 57

5

Emr (

LMIC

)So

uth

Suda

n61

502

1 54

956

19

072

13 0

4385

726

(377

23, 1

3105

0)1

561

1 50

3

Eur (

HIC

)Sp

ain

177

1 84

034

946

40 9

0915

272

93 1

44(1

7124

, 155

444)

405

254

Sear

Sri L

anka

1 85

15

807

7 32

682

420

34 1

0913

1 51

3(9

5676

, 166

551)

1 33

01

354

Emr (

LMIC

)Su

dan

150

832

7 57

22

413

32 0

3047

946

240

793

(130

714,

370

769)

1 27

21

410

Amr (

LMIC

)Su

rinam

e15

217

164

589

482

1 40

5(0

, 235

6)53

060

1

Afr

Swaz

iland

2 65

715

471

556

711

4 14

9(0

, 734

5)68

483

2

Eur (

HIC

)Sw

eden

13

4227

166

382

(0, 1

7361

)8

5

Eur (

HIC

)Sw

itzer

land

2267

15

909

8 27

72

435

17 3

14(4

982,

242

68)

437

264

Emr (

LMIC

)Sy

rian

Arab

Rep

ublic

6 34

92

457

11 8

8162

579

25 0

2010

8 28

6(6

2671

, 151

214)

1 07

21

935

131

Num

ber o

f DAL

YsD

ALYs

100

000

per

cap

ita

Reg

ion

Cou

ntry

ALR

I aC

OPD

bLu

ng c

ance

r bIH

D b

Stro

ke b

Tota

l U

ncer

tain

ty in

terv

alC

rude

rate

Age-

stan

dard

ized

rate

Eur (

LMIC

)Ta

jikis

tan

26 1

281

634

1 84

723

094

13 1

5565

858

(349

33, 9

9535

)1

646

2 42

4

Sear

Thai

land

5 67

619

903

77 5

5913

2 35

095

240

330

728

(259

399,

401

893)

998

874

Eur (

LMIC

)Th

e fo

rmer

Yug

osla

v Re

publ

ic o

f M

aced

onia

6054

36

661

6 93

67

345

21 5

44(1

7335

, 258

32)

2 09

11

647

Sear

Tim

or-L

este

2 45

756

538

1 00

380

24

857

(0, 9

831)

868

1 03

3

Afr

Togo

22 9

9384

929

16

099

8 73

038

962

(604

8, 6

5378

)1

171

1 43

2

Wpr

(LM

IC)

Tong

aN

AN

AN

AN

AN

AN

AN

AN

AN

A

Amr (

HIC

)Tr

inid

ad a

nd T

obag

o13

469

551

3 86

31

375

5 99

2(0

, 888

6)90

385

0

Emr (

LMIC

)Tu

nisi

a2

345

2 43

713

386

40 2

3721

044

79 4

48(6

3618

, 954

45)

1 47

51

555

Eur (

LMIC

)Tu

rkey

13 3

0419

581

172

478

239

374

137

326

582

063

(479

717,

685

447)

1 58

31

815

Eur (

LMIC

)Tu

rkm

enis

tan

6 98

21

223

3 18

648

135

15 5

3575

061

(227

82, 1

0701

2)2

949

4 06

3

Wpr

(LM

IC)

Tuva

luN

AN

AN

AN

AN

AN

AN

AN

AN

A

Afr

Uga

nda

164

963

7 16

92

143

31 7

5544

513

250

542

(191

462,

323

201)

1 41

71

751

Eur (

LMIC

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krai

ne3

416

6 24

662

391

449

226

122

709

643

988

(112

07, 9

4780

9)3

074

2 27

9

Emr (

HIC

)U

nite

d Ar

ab E

mira

tes

537

1 94

01

623

15 3

246

454

25 8

78(2

1954

, 301

59)

388

648

Eur (

HIC

)U

nite

d Ki

ngdo

m65

65

776

54 8

7098

122

29 5

9418

9 01

7(6

7307

, 259

080)

604

386

Afr

Uni

ted

Repu

blic

of

Tanz

ania

97 8

154

196

604

28 6

5432

129

163

399

(926

71, 2

2255

4)67

678

8

Amr (

HIC

)U

nite

d St

ates

of

Amer

ica

1 81

59

778

108

381

311

799

64 1

2249

5 89

4(2

2891

, 103

8384

)31

823

2

Amr (

HIC

)U

rugu

ay16

326

63

334

4 63

71

968

10 3

68(2

830,

148

24)

633

521

Eur (

LMIC

)U

zbek

ista

n38

070

4 81

210

936

150

068

65 5

9626

9 48

2(1

2902

3, 3

8799

5)1

916

2 80

1

Wpr

(LM

IC)

Vanu

atu

50

221

1846

(0, 8

62)

3760

Amr (

LMIC

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nezu

ela,

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ivar

ian

Repu

blic

of

6 72

72

168

12 5

2465

261

22 9

8510

9 66

6(7

9967

, 135

829)

737

934

Wpr

(LM

IC)

Viet

Nam

33 2

8319

264

112

787

78 3

1321

2 52

845

6 17

5(3

2644

6, 5

8234

3)1

022

1 27

5

Emr (

LMIC

)Ye

men

71 6

843

478

2 56

058

582

37 5

5017

3 85

5(7

3256

, 273

680)

1 38

32

120

Afr

Zam

bia

47 6

9194

440

49

851

13 5

0672

396

(165

19, 1

1187

1)98

11

171

Afr

Zim

babw

e32

392

1 49

61

628

4 82

27

364

47 7

01(1

966,

783

93)

664

760

DAL

Y : D

isab

ility-

adju

sted

life

yea

rs ;

AAP

: Am

bien

t air

pollu

tion ;

ALR

I : Ac

ute

low

er re

spira

tory

dis

ease

; C

OPD

: C

hron

ic o

bstru

ctiv

e pu

lmon

ary

dise

ase ;

IHD

: Is

chae

mic

hea

rt di

seas

e. A

fr : A

frica

; Am

r :

Amer

ica ;

Em

r: Ea

ster

n M

edite

rrane

an ; E

ur: E

urop

e ; S

ear :

Sou

th-E

ast A

sia ;

Wpr

: Wes

tern

Pac

ific ;

LM

IC : L

ow- a

nd m

iddl

e-in

com

e co

untri

es ; H

IC : H

igh-

inco

me

coun

tries

; NA:

Not

ava

ilabl

e.a A

ge g

roup

incl

udes

less

than

5 y

ears

old

.b A

ge g

roup

incl

udes

25

year

s an

d ab

ove.