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Country Agency for Rural Development (CAD)

Report of Nutritional Assessment

In Central Chin State, 2012

29 January 2013,

Yangon

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Table of Contents

Page

1. Background of Assessment 3

2. Conceptual Analysis 4

3. Description of Assessment 7

3.1. Objective of Assessment 7

3.2. Assessment Procedures 7

3.3. Cut-offs and Standards Used in Assessment 7

3.4. Scope and Limitations 9

4. Assessment Findings 10

4.1. Characteristics of Respondents 10

4.2. Malnutrition Status by MUAC 11

4.3. Malnutrition by Study Areas (Townships) 12

4.4. Malnutrition Status by Child Sex 13

4.5. Malnutrition by Family Size 14

4.6. Malnutrition by Number of Under-Five Children in Family 15

4.7. Malnutrition by Use of Birth Spacing Method 16

4.8. Use Birth Spacing Method and Years of Child Interval 17

4.9. Malnutrition Status by ‘Avoid Meals during Pregnancy’ 18

4.10. Malnutrition Status by Educational Level of Respondents 19

4.11. Malnutrition Status by History of Diarrhea 20

4.12. Malnutrition by Status of Immunization 22

4.13. Malnutrition by Types of Respondent’s Occupation 24

5. Conclusion and Recommendations 25

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CAD nutrition survey area in central Chin State

Targeted Map of CAD Nutrition Survey in Chin State (2012)

Map of Myanmar Map of Myanmar

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Key Findings

About 14.3 percent of under-five children are severely malnourished according to

MUAC measurement. Almost half of under-five children in the study area are severely

or moderately malnourished. Thantlang hosts the highest population of severely

malnourished children followed by Matupi.

Overall, 52.3% of children in the study areas are stunting, 10.3% are wasting, and

37.1% are underweighted. The highest proportions of stunting (66.7%) and wasting

(14.6%), and underweight (50.0% in Hakha) have been found in Hakha Township.

As malnutrition status by child sex was measured, female are more severely

malnourished than male. The rates of stunting and underweight increase as the size

of family increases. But the increase is not significant for stunting.

The proportional prevalence of malnutrition among under-five children is much

higher in households who do not use birth spacing methods than those who used.

MUAC measurements show that use of birth spacing method has remarkable impacts

on severe malnutrition.

Those households with shorter intervals of child birth are not necessarily those who

do not use birth spacing method. And the highest proportion of severely

malnourished children is found in those children with an interval of two years.

The proportion of malnutrition decreases generally as the number of years with

breast-feeding increases. The proportions of malnutrition are lowest when children

are breast-fed for three years.

Overall, the proportions of under-five children suffering from stunting, wasting, and

underweight are lower among children whose mothers avoid meals during their

pregnancy periods. A much lower proportion of wasting (0.0%) is found in children

of mothers who avoid meals during pregnancy.

In practice, the educational levels of respondents have no significant impacts on the

nutritional status of their children. But it has been learned that a little knowledge

parents/respondents in nutrition can be beneficial to the nutritional status of

children.

Malnutrition for children without history of diarrhea (39.6%) is much higher than

that for those with diarrhea (60.4%). And the prevalence levels of stunting, wasting,

and underweight are highest for farmers and casual workers.

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Among under-five children who suffer from wasting and underweight, much

significant prevalence is observed in children with history of diarrhea (2.6% for

wasting and 11.6% for underweight) compared with those without diarrhea.

1. Background of Assessment

Chin State forms the northwestern part of Myanmar bordering with India. It is known as

one of the most remote and least developed regions of the country. According to UNDP1,

Chin State has the highest poverty proportion in Myanmar since 73% of its population

lives below the global poverty line. Transport is also limited in Chin State due to the bad

topography with remote location and lack of employment opportunities worsens the

problem as indicated by the assessment of WFP2. Though these, the number of

development agencies present is most limited compared with other regions in

Myanmar. Again, a collaborative assessment conducted by WFP and other agencies

showed that market access is difficult in Chin State that only 75% households have

access to market3. Moreover, the Inter-Agency Working Group on Chin also reported

migration as a significant coping mechanism for Chin people due to the declining job

opportunities and food insecurity in recent years (IAWG Chin, 2012)4.

Despite the known unfavorable topographical and agro-climatic conditions of the

region, communities in Chin State are primarily agrarian with at least 95% reliant on

agriculture as the main livelihoods according to WFP et al. (2012). The report said that

cultivation systems are largely based on plot rotation (with a cycle of about seven

years) as well as slash and burn techniques. Overall, 92% of surveyed communities

produced either upland or lowland paddies, while 48% produced maize. WFP (2012)

found out that the main cause of household food insecurity in Chin is the decline in

agricultural yields leading to a decline in available food and income at household level.

Due to yield losses in major cereals, only 16% of households depended on their own

production, 46% on purchase and 17% on borrowing. More than 40% of households

then borrowed either food or money with interests. For the majority (80%),

expenditure on food is the highest followed by on health (72%).

1 UNDP (2011), Integrated household living conditions assessment in Myanmar 2009-2010. Hereafter, IHLCA (2011).

2 WFP (2009) An Overview of food security in Chin State May 2009 (Hereafter, WFP, 2009).

3 WFP et al (2012) Emergency food security assessment in Southern Chin State (Hereafter, WFP et al., 2012).

4 IAWG Chin, 2012.

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The major income sources for the target communities in Chin State are agriculture and

casual labor. According to WFP (2009), 37% of households in Chin State rely on

agriculture as their major income source. Decline in agricultural yields thus leads to

decline in available income at household level. The lack of employment opportunities

and weak road/transport infrastructure also limits income earning opportunities and

access to market as indicated by IAWG (2012). WFP et al. (2012) reported that 75%

households have access to market, but the access is confined to local market which

might be definitely counted with limited demand. The report also said that more than

40% of households borrowed either food or cash with interests due to the lack of

reliable income sources. Moreover, WFP (2009) stressed that 80% of households

allocated the highest proportion of their expenditure on food and also that debt

repayment remains a major burden for most households as caused by the lack of

income sources and employment opportunities.

In fact, the problem of food insecurity is not a new issue for Chin State and people of the

region usually deal with it through different coping strategies. However, situations

became immediately reversed due to the rodent outbreak in 2008 and the untimely

heavy rains in 2010. Substantial reduction in crop yield necessitated humanitarian

interventions executed mainly by WFP and its partners. According to the food security

assessment reports of WFP5, low farm yield, limited income sources, and repayment of

debt remain primary problems from which other poverty problems derive for people of

the surveyed areas in Chin State. And malnutrition is found to be potentially a major

sequential problem of food insecurity especially among children under five of the

affected areas.

It was believed by many that famines in Chin State might have imposed negative

impacts on the nutritional status of under-five children in the region. However, previous

assessments mainly focused on food security situations and not on the nutritional status

of under-five children in the affected areas. Therefore, this survey is intended to

investigate the nutritional status of under-five children within CAD project areas in

Central Chin State affected by the famine. Thus, the survey was conducted with the

limited capacity of CAD and is expected to yield critical recommendations to various

stakeholders for timely intervention of the potential nutritional problems of the region. 5 WFP (May 2009), An Overview of the Food Security Situation in Chin, p.8

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2. Conceptual Analysis

Malnutrition is a particular cause of death among pre-school children. One of three

under-five children in developing countries suffers from stunting as a result of chronic

under-nutrition. Eighty percent of those children live in just 20 countries in Africa and

Asia-Pacific regions including Myanmar (Black et al., 2008). According to the conceptual

framework of UNICEF (UNICEF, 1990), inadequate access to food, inadequate care for

mother and children, and insufficient health services and unhealthy environment are

major determinants of malnutrition among children under five. The conceptual

framework outlines the causes of malnutrition in different levels as basic causes,

underlying causes, immediate causes, and outcomes that are malnutrition and death of

children (see Figure 1 below).

Briefly interpreting the conceptual framework, it indicates that access to potential

resources is limited by the economic status and educational level of the households

concerned which further results in inadequate access to food, inadequate care for

mother and children, and insufficient health services and unhealthy environment which

are categorized as underlying causes of malnutrition. These underlying causes together

result in inadequate dietary intake and disease which finally cause malnutrition and

death of children. Another important and critical feature of the framework is that the

two immediate causes of malnutrition, inadequate dietary intake and disease are

interdependent, meaning that a child with inadequate dietary intake is more susceptible

to disease and a child with disease fail to absorb adequate dietary intake.

Along the conceptual framework, the three underlying causes (inadequate access to

food, inadequate care for mother and children, and insufficient health services and

unhealthy environment) are found most convenient to measure. Whereas access to food

is translated as food security, it would be of significance to also know how people

ensure access to food. As World Bank (1986) indicated, the resources necessary for

gaining food are food production, income for food purchases, or in-kind transfers of

food, connoting that available food are not always accessible. A broader and contextual

definition is used by FAO (1996) stating that food security exists when all people, at all

times, have physical and economic access to food, stability of supply and access, and

safe and healthy food utilization.

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Regarding inadequate care for mother and children, the key determinant would be

much characterized by the education and knowledge of the persons taking care of

children. The practices of caring and feeding children are much influenced by the

education and knowledge of the persons, especially women, who usually take care of

children. Again, the good practices of caring and feeding children need a healthy

environment like sanitation and safe drinking water. In addition, inadequate care for

mother and child can also exist where cultural traditions limit the role of women in

decision-making process of the household even though they have the required

education and knowledge in a healthy environment.

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Figure 1 Conceptual Framework

Source: UNICEF, 1990.

Outcomes

Immediate

causes

Underlying

causes

Basic

causes

Malnutrition and death

Inadequate

dietary

intake

Disease

Potential

resources

Formal & non-formal

institutions

Political& ideological superstructure

Economic structure

Inadequate education

Inadequate care

for mothers &

children

Insufficient

health services

& unhealthy

environment

Inadequate access to food

The conceptual framework shows that the effects of access to food and health issues are

dependent upon care for mothers and children. Whatever good food and health services

may not work if care for mothers and children is inadequate. The overlapping circles

among food, health and care in Figure 1 above are meant to imply that these three are

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related to each other in complex ways, which must be analyzed and properly

understood in a given context in order to design appropriate actions. For instance, food

secure households may still contain malnourished children because the burden of

women’s agricultural and other work (as well as other factors such as inadequate

knowledge of caretaker) may compromise the quality of child care. Moreover, efforts to

increase household food security may increase or decrease child (and maternal)

malnutrition, depending upon how this is achieved. Similar contingencies exist between

care and health (World Bank & UNICEF, 2002).

3. Description of Assessment

3.1. Objective of Assessment

The primary objective of this survey is to identify the prevalence level of malnutrition

among under five children in villages covered by CAD intervention. The study was

conducted based on the assumption that famines caused by rodent outbreak in 2008

and untimely heavy rains in 2010 might affect the nutritional status of especially

children under five. By knowing the nutritional status of children under five, any

appropriate intervention can be taken by any development agency or government line

department and so on.

3.2. Assessment Procedures

The study was conducted in a total 13 villages in three Townships (3 villages in Matupi,

9 villages in Thantlang, and 1 village in Hakha) of central Chin State during early 2012

and a total of 835 under-five children including male 434 (52%), female 401 (48%)

were surveyed using a structured questionnaire. The survey team includes eight field

staff of CAD led by a public health practitioner. The seven field staffs designated for the

survey were trained in Hakha for six days prior to the data collection. The survey

sample consists of 600 under-five children from Thantlang Township, 131 from Matupi

Township, and 44 from Hakha Township. Using the structured questionnaire,

interviews were conducted with a person in the household who usually takes care of the

child under study whereas body measurements of MUAC (Mid Upper Arm

Circumference), weight, and height were made directly on the child. The respondents

include 711 men and 124 women.

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3.3. Cut-offs and Standards Used in this Assessment

Mid-upper arm circumference (MUAC):

Mid-Upper Arm Circumference (MUAC) is a good indicator of muscle mass and can be

used as a proxy of wasting and also a very good predictor of the risk of death among

children aged 6 to 59 months without adjustment for age. It has also been

recommended for targeting intervention to pregnant women at risk of poor pregnancy

outcome.2 Cut-off values may be population specific. It is mainly used for detecting

individuals in need of therapeutic treatment. In children 6-59 month old, MUAC < 110

mm is recommended as a criterion of admission to therapeutic feeding programmes. It

is particularly recommended for the detection of severe malnourished 6-59 month-old

children at community-level. MUAC is also sometimes used to detect moderately

malnourished children and as a criterion of admission to supplementary feeding

centres. Cut-offs used for these purposes are generally 120 mm or 125 mm. Again,

however, there is no international agreement on the use of MUAC and on cut-offs for

detection of moderately malnourished children and admission to supplementary

feeding centres.

MUAC is therefore a very successful screening tool that rapidly identifies children likely

to die unless provided with nutritional and medical treatment. Children with low MUAC

tend to be found among the poorest segments of the population. MUAC is measured to

the nearest mm and can be reported either in mm or cm. It is measured on one arm and

quoted directly, without the use of any reference. Although MUAC values vary slightly

between 6 and 59 months, it has been proven that MUAC is a good predictor of death in

these children, without adjustment for age. The cut-off of 110 mm for admission to

therapeutic feeding centres has been determined according to the relationship between

MUAC values and risk of deaths reported by several studies. Underlying factors of

malnutrition, such as health status and food security, should be assessed as explanatory

elements. Since its objective was for intervention, the MUAC cut off point for this study

is set at 12.5cm which varies a little from which used by United Nations System,

Standing Committee on Nutrition Task Force on Assessment, Monitoring, and

Evaluation6.

Measurement of dispersion (Z-Scores):

6 www.unsystem.org/.../task_force/Factsheet%20MUAC%20Hanoi.doc.

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For child malnutrition we utilize a measure of the prevalence of underweight children

under five (CHMAL). The criteria we use for identifying an underweight child is that the

child's weight-for-age (identifying protein-energy malnutrition or underweight) be

more than 2 standard deviations below the median based on National Center for Health

Statistics/World Health Organization standards. This measure represents a synthesis of

height-for-age (identifying long-term growth faltering or stunting) and weight-for-

height (identifying acute growth disturbances or wasting).The large majority of the

data, 75 percent, are from the World Health Organization's Global Database on Child

Growth and Malnutrition (WHO 1997). These data have been subjected to strict quality

control standards for inclusion in the database (Smith & Haddad, 1999).

Anthropometric indices:

Anthropometry is the most common technique used to assess the presence and degree

of protein-energy malnutrition. It is the measurement of body parameters to indicate

nutritional status. Anthropometry can be used to measure an individual to determine if

he or she needs nutrition intervention or it can be used to measure many individuals to

determine if malnutrition is a problem in a population. Height (or length) and weight

are the most common anthropometric measures used to indicate protein-energy

nutritional status in emergencies. Anthropometric measurements are combined with

each other or with other data to calculate anthropometric indices. The most common

indices used in emergencies include those listed in the table below:

Index Nutritional problem measured

Weight-for-height Acute malnutrition (wasting)

Height-for-age Chronic malnutrition (stunting)

Weight-for-age Any protein-energy malnutrition

(underweight) If we want to measure the prevalence of acute protein-energy malnutrition, you should

use weight-for-height. However, in practice, all three indices are usually available. Most

emergency nutrition surveys measure sex, height, weight, and age. Absence of acute

protein-energy malnutrition, or normal nutritional status, is defined as having a weight-

for-height z-score of -2.0 or greater. Moderate acute protein-energy malnutrition is

defined as having a weight-for-height z-score of -3.0 to less than -2.0. Severe acute

protein-energy malnutrition is defined as having a weight-for-height z-score less than -

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3.0 (London School of Hygiene and Tropical Medicine, 2009). In this study, the cut-off

used for this study is a z-score of -2.0.

3.4. Scope and Limitations

The study was conducted to find out if the nutritional status of especially children under

five were affected by the previous famines. The survey covered thirteen villages of CAD

project areas in Hakha, Thantlang, and Matupi Townships and investigated the

nutritional status of children under five in those villages. Therefore, findings of this

study cannot be representative to the nutritional status of all children under five in the

entire Chin State. Moreover, the survey was designed for investigating the nutritional

status of children under five and not necessary the causes of child malnutrition. In fact,

the findings of this survey are expected to bring critical recommendations for improving

the nutritional status of children under five in the region.

4. Assessment Findings

4.1. Characteristics of Respondents

The study sample is composed of households with various livelihoods groups and

different levels of education. Composition of the sample according to livelihoods groups

thus is: 743 (89%) engage in farm works, 31 (3.7%) in casual works, 32 (3.8%) in

government services, 20 (2.4%) in religion, 2 (0.2%) retired, another 2 (0.2%) engage in

traditional healing and only 5 (0.6%) engages in other miscellaneous activities. Of the

entire sample, 131 (15.7%) are illiterate, 401 (48%) have primary education, 191

(22.9%) have middle school level, 90 (10.8%) have high school level, and only 22

(2.6%) studied up to graduate level.

The average household size of the study sample is

5.39 (Min: 1, Max: 19, SD: 2.815). Of the 835 study

households, 258 (30.9%) have less than five family

members and 367 households (44%) have 4-7

members whereas households with more than 8

members are 210 (25.1%). The average number of

under-five children in within households is 1.89 (Min:

1, Max: 4, SD: 0.674). Of the study households, 55.1%

have each two under-five children and 15.8% of households have each 3 under-five

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children. According to grouping of households by number of under-five children, 137

households (16.4% of total) have more than three children. Households with only one

under-five children constitute almost one-third (28.5%) of the sample.

The averaged actual age of under-five children under study is 26.41 months (min: 1;

max: 60; SD: 16.014). Average weight of the children studies is 10.68kg (min: 3; max:

30; SD: 4.102) and their average height reads 30.92 inches or 78.54cm (min: 14 inches

or 35.6cm, max: 47 inches or 119.4cm; SD: 4.935 inches or 12.533 cm). Again, average

MUAC measure is 1.935cm with min: 6.5, max: 127cm, and SD: 4.0787cm. The

household size of the study area is 5.39 (min:1: max: 19; SD: 2.815) and the average

number of under-five children for each household is 1.89 ranging from min:1 to max:4

and SD: 0.674.

A very few proportion of households (0.6%) have even 4 under-five children whose

respondents have high-school or graduate level education. Majority of households with

2-3 under-five children are concentrated among households with primary-school and

middle-school categories of respondents’ education. There is no significant relationship

between low educational level and high number of under-five children. Among under-

five children under study, 645 (77.2%) received one or more forms of immunization.

Regarding the types of immunization, 601 children (72%) received DPT immunization7,

504 children (60.5%) received poliomyelitis of Immunization, and 183 children (21.9%)

received measles Immunization. Again, 265 (31.7%) of the under-five children under

study have history of diarrhea.

Almost all respondents (98.1%) reported that they practiced breastfeeding. For almost

all households (92.5%) again, however, feeding of the child with weaning or normal

food is started before six months and those who start feeding at the age of four months

account for more than half (52.7%) of the total sample. Only 7.5% of the sample starts

feeding after six months. The proportion of respondents who avoid meal during

pregnancy period is 3.5 percent whereas 96.5 percent do no avoid meal during

pregnancy period. Among the children under study, 41.7 percent reported history of

ARI (Acute Respiratory Infection).

7 DPT (also DTP and DTwP) refers to a class of combination vaccines against three infectious diseases in humans:

diphtheria, pertussis (whooping cough) and tetanus.

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4.2. Malnutrition Status by MUAC

MUAC measurements were conducted with a total of 835 under-five children within the

three survey Townships. The cut-off point for MUAC measurement was set at 12.5 cm.

Based on this cut-off point, MUAC measures less than 12.5cm are categorized as “red”

meaning severely malnourished, 12.5cm to 13.5cm

as “yellow” meaning moderately malnourished, and

above 13.5cm as green or normal. The survey found

that almost half of under-five children in the study

area are severely or moderately malnourished. In

the study area, about 14.3 percent of under-five

children fall under ‘red’ category and 31 percent

moderately malnourished. The mean of MUAC

measurements for all study children is 13.9cm

(median: 13.8cm, SD: 4.08 cm).

Figure 2 Malnutrition by MUAC measurements

4.3. Malnutrition by Study Areas (Townships)

Overall, 52.3% of children in the study areas are stunting, 10.3% are wasting, and

37.1% are underweighted. Of all the under-five children available for measurement,

52.3% were found having suffered from stunting, 10.3% from wasting, and 37.1% from

underweight. Studied by Township, 50.7% of under-five children in Thantlang, 56% in

Matupi, and 66.7% in Hakha suffer from stunting. Wasting by Township among under-

five children is a bit lower; 11.1% in Thantlang, 4.7% in Matupi, and 14.6% in Hakha.

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Then, the proportions of underweight children in the three study Townships are 36.8%

in Thantlang, 34.4% in Matupi, and 50.0% in Hakha, respectively. This information

indicates that the proportions of malnutrition are higher in Thantlang and Hakha

Townships compared with Matupi.

MUAC measurements also indicate that the total proportion of severely malnourished

children among the total population of under-five children in the study area is 15.2

percent. This percentage is shared across the three Townships as 11.5% for Thantlang,

2.9% for Matupi and 0.8% for Hakha. Of the three Townships studied, Thantlang hosts

the highest population of severely malnourished children followed by Matupi whereas

the proportion for Thantlang ranks the highest. In analyzing these proportions, it is

worth noting that the cut-off point for severe malnutrition is set at 12.5cm in this study.

The proportions can be much lower if 11.0cm is used as cut-off point for this

assessment.

Figure 3 Malnutrition by study areas (Townships)

Figure 4 Types of malnutrition by study areas (Townships)

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Figure 5

Study areas by types of malnutrition

4.4. Malnutrition Status by Child Sex

Of the sample, stunting children account 52.3% and are distributed as 28.7% male and

23.6% female. Within the stunting population (52.3% of total sample), 55.5% are male

and 49.1% are female. Stunting rate is higher in male than female. Wasting within the

sample (10.3%) are distributed as 4.6% male and 5.7% female. The distribution within

wasting children is 8.9% male and 11.7% female (total 10.3% of sample). More cases of

wasting are observed in female children. Underweight within the total sample (37.1%)

is distributed as 19.7% male and 17.5% female whereas distribution within

underweight children is 37.9% male and 36.3% female of the underweight proportion

(37.1%). Underweight proportion is higher among male than female.

The proportions of different types of malnutrition differ according to the sex type of the

children. As aggregate data show, female children are less malnourished than are their

male counterparts. Stunting is the most prevalent form of malnutrition across all types

of malnutrition, but there is no significant difference based on the different types of

malnutrition regarding the proportion of prevalence. Male children are less

malnourished only in terms of wasting and further interesting is the cause that makes it

happen since Chin society is male-dominated and it is supposed that more resources

including food will be allocated to male children than to female ones.

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Figure 6 Malnutrition by child sex

As malnutrition status is also cross-tabulated with the sex type of children under study,

it is found that a remarkably higher proportion of children (9.3%) out of the total 15.2

percent of severely malnourished children (red) are female compared with the

proportion of male (5.9%). Within the severely malnourished population, 38.7 percent

are male and 61.3 percent are female, imposing again a significant difference. However,

the distribution of the proportions between male and female is proportionate for the

malnourished children and the total population. Results are obtained for moderately

malnourished (yellow) and normal children (green), but the two categories count much

higher proportions, that is, 29.8 percent of children under study are moderately

malnourished and 55.0 percent are normal.

Figure 7 Malnutrition Status by Child Sex measured by MUAC

4.5. Malnutrition by Family Size

The proportion of stunting children is 52.3%. As malnutrition and different groups of

family size are cross-tabulated, it has been found that stunting rates increase as family

sizes increase such as 44.4% for families with <3 persons, 53.2% for families with 4-7

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persons and 60.2% for those with >8 persons. Proportions within stunting population

differ from those within the total sample (13.4% for families with <3 persons, 23.6% for

families with 4-7 persons, and 15.3% for families with >8 persons) making the

proportion for families with 4-7 persons the highest. Why? Increase in family size does

not have direct relationship with the proportions of wasting in children.

Distribution by family size within the wasting population (10.3% of total sample) are

10.5% for families with <3 persons, 10.3% for families with 4-7 persons, and 9.9% for

families with >8 persons). This differs from the distribution within the total sample

(2.9% for families with <3 persons, 4.7% for families with 4-7 persons, and 2.6% for

families with >8 persons) where wasting proportion is highest among families 4-7

persons. Underweight total (37.1%) distributed by family sizes as 26.5% for families

with <3 persons, 39.5% for families with 4-7 persons, 45.5% for families with >8

persons. It is found that the percentage of underweight children increase as the size of

families increase. However, the group of families with >8 persons ranks the highest

underweight proportions within the total sample (7.9% for families with <3 persons,

17.6% for families with 4-7 persons, and 11.6% for families with >8 persons, making

families with 4-7 persons rank the highest.

Figure 8 Malnutrition by family size

4.6. Malnutrition by Number of Under-Five Children in Family

As cross tabulation is made between malnutrition and the number of under-five

children in each family. Within the total sample, stunting is significantly higher for

families with <2 children (44.8%) than for families with >3 children (7.5%) whereas the

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proportion of stunting population is 52.3% of the total population. But in the stunting

population, the difference is not that significant (53% for <2 children and 46.8% for >3

children). The proportions of stunted children are not much influenced by the number

of under-five children in each family, meaning that the number of stunted children does

not significantly increase following the number of children per family.

The results of cross-tabulations also indicate that the proportions of children suffering

from wasting are 10.1% for families with <2 children and 11.3% for those with

>3children while the total of children suffering from wasting accounts 10.3% of the total

children under study. This shows that high number of under-five children within family

is not major cause of malnutrition in the form of wasting. Similar regards apply to the

results of underweight cross-tabulated with groups of number of under-five children

within family since there is no significant difference between the proportions of under-

five children who suffer from stunting (37.7% for families with <2 children and 34.1%

for >3children and both are not much difference from the total proportion of children

suffering from wasting (37.1%).

Figure 9 Malnutrition by number of under-five children

4.7. Malnutrition by Use of Birth Spacing Method

In order to study the impacts of birth spacing on malnutrition, a cross tabulation is

made between the use of birth spacing methods and the prevalence levels of

malnutrition across the three types of malnutrition. According to the cross tabulation,

the proportions of malnutrition prevalence among under-five children are much higher

in households who do not use birth spacing methods than in households who used. The

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difference of proportions between households who use and who do no use birth spacing

methods is by around 7.5% percent in stunting, more than 5.6 percent in wasting, and

almost 10.4 percent in underweight. The differences between the proportions of

stunting children within families who used birth spacing methods and who did not use

are much significant at the level of total proportion for all types of malnutrition.

The cross-tabulation made between MUAC measurement and the use of birth spacing

method also indicate that severely malnourished population are much higher for those

who do not use birth spacing method than those who use birth spacing method. The

proportions result in 0.4 percent for those who use birth spacing method and 14.8

percent for those who do not use while the total population of severely malnourished

population accounts for 15.2 percent of the total population. It is observed that the

difference is quite significant between the two groups.

Figure 10 Malnutrition by Use of Birth Spacing Method

4.8. Use Birth Spacing Method and Years of Child Interval

As high as 93.4 percent of the sample reported that they do not use birth spacing

method and only 22(2.6%) of the respondents said they use of birth spacing methods.

Most of the respondents (59.9%) reported a child interval of two years and 14.5%

reported one-year intervals. Households with three-year interval accounts for 20.2

percent and 5.4 percent have an interval of more than three years. It is observed that

those households with shorter intervals of child birth are not necessarily those who do

not use birth spacing methods because the proportions of households with shorter child

intervals (one and two years) are proportionately high among those who use birth

spacing. It might be important to know whether birth spacing methods are used

correctly and on a regular basis.

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The relationship between ‘years of child interval’ and MUAC measurement is also

investigated. It is found that the proportion of severely malnourished children is the

lowest among children with more than three years of interval. The highest proportion of

severely malnourished children is found in those children with an interval of two years

followed by those of one year and three years, together these constitute the total

proportion of 15.2 percent. From this information, it can be observed that higher child

interval does not always result in better nutritional status of children under five.

Figure 10 Malnutrition by breast feeding

As similar cross-tabulations are made, it has been found in overall that the number of

years children are breast-fed is significantly correlated with the prevalence level of

malnutrition. The results show that the proportion of malnutrition decreases generally

as the number of years with breast-feeding increases. For all the three forms of

malnutrition, however, it is observed that the proportions of decrease in malnutrition

are not constant across the number of years within which breastfeeding is practiced.

According to the cross-tabulation results, the proportions of malnutrition are lowest

when children are breast-fed for three years followed by the proportions for a breast-

feeding period of one year. The prevalence is highest for children breast-fed for two

years.

While a positive impact of breastfeeding on the nutritional status of under-five children

is observed, it is still unclear about why the prevalence of malnutrition is higher for

children breast-fed for two years than for those breast-fed for one year. This indicates

that the number of breast-feeding contributes to the nutritional status of under-five

children whereas there can also be other factors confounding the results of breast-

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feeding irrespective of the length of breast-feeding period. Moreover, this inconsistency

across different number of years with breast-feeding may also be characterized by what

happened in the study area and to the study population before and during the survey

which disturb lactating mothers from regular breast-feeding.

Figure 11 Malnutrition by years of breast-feeding

4.9. Malnutrition Status by ‘Avoid Meals during Pregnancy’

As malnutrition status among children is cross-tabulated with ‘avoid meals during

pregnancy period’, higher proportions of prevalence of the three forms of malnutrition

are observed being significant among the target under-five children whose mothers

avoided meals during pregnancy. For those who avoided meals during pregnancy, the

proportions are 1.8% for stunting, 0.0% for wasting, and 1.1% for underweight. For

those who did not avoid meals during pregnancy, however, such higher proportions as

50.5% for stunting, 10.3% for wasting, and 36.0% for underweight have been observed.

Overall, the proportions of under-five children suffering from stunting, wasting, and

underweight are lower among children whose mothers avoid meals during their

pregnancy periods. On the contrary, a much lower proportion of wasting (0.0%) is

found in children of mothers who avoid meals during pregnancy compared with the

proportion for children of mothers who did not avoid meals, that is 10.6 percent.

Looking at the data, however, it can be concluded that the prevalence of malnutrition is

higher among children with mothers who did not avoid meals during pregnancy period

than those children with mothers who avoided meals during their pregnancy periods.

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Figure 12 Malnutrition by avoid meals during pregnancy

4.10. Malnutrition Status by Educational Level of Respondents

It is found that the prevalence of malnutrition decreases as educational levels of

respondents increases though the increase in proportion is not that significant.

However, it is also found the relationship between the educational levels of respondents

and the proportions of malnourished children is generally not consistent especially

among children suffering from wasting and underweight. It is observed that educational

levels of respondents, which are thought higher in range by category but not applicable

for practical purpose, have no significant impacts on the nutritional status of their

children. However, it is also found, as evidenced by the malnourished proportion of

respondents who are traditional healers, a little knowledge of respondents in health

education is beneficial to the nutritional status of children of those families concerned.

The prevalence of wasting among the target under-five children is distributed

depending on the different educational levels of respondents as 15.4% for illiterate,

53.8% for primary education, 26.9% for middle school, 3.8% for high school, and none

for graduate education. Similarly, the proportions of underweight among under-five

children are 16.1% for illiterate, 45.4% for primary education, 27.3% for middle school,

8.6% for high school, and only 2.6% for graduate education. Overall, prevalence of

wasting and underweight are most severe among respondents with primary and middle

levels of education and lowest in illiterate and graduate respondents, meaning that

education levels below high school are not much different from illiterate.

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Figure 13 Malnutrition by education level of respondent

4.11. Malnutrition Status by History of Diarrhea

While studying the prevalence of malnutrition among under-five children with history

of diarrhea, it has been explored that stunting accounts much higher proportions

(52.3%) than wasting (10.3%) and underweight (37.1%). Among under-five children

who suffer from wasting and underweight, much significant prevalence is observed in

children with history of diarrhea (2.6% for wasting and 11.6% for underweight)

compared with those without diarrhea, that is 7.6% for wasting and 25.5% for

underweight. This is in correlation with the fact that diarrhea in practical term can

cause wasting of energy conserved by children that might lead to underweight.

According to the aggregate data resulted for wasting and underweight cross-tabulated

with history of diarrhea, malnutrition in the forms of stunting, wasting, and

underweight happened remarkably more among children with history of diarrhea. In

fact, the proportions of malnourished children across the three types of malnutrition

are not much different between children with history of diarrhea and without diarrhea.

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Moreover, the impacts of the history of diarrhea in child life for stunting are not as

significant as those for wasting and underweight. At the same time, this information

connotes that history of diarrhea in child life is not necessarily the case for stunting

among children under five while wasting and underweight are much characterized by

history of diarrhea in child life.

Figure 13 Malnutrition by history of diarrhea in child life

Malnutrition according to MUAC measurements is cross-tabulated also with the history

of diarrhea in child life and cut off points are set as “red or severe” if less than 12.5cm,

“yellow or moderate” if 12.5cm to 13.5cm, and “green or normal” if more than 13.5cm,

respectively. Based on the criteria, under-five children who suffer from severe

malnutrition are 15.2% which is allocated as 6.0% in children with history of diarrhea

and 9.2% in those without diarrhea. History of diarrhea does impose a certain level of

significant difference between children with and without diarrhea within the category

of moderately malnourished and similar regards apply to children with normal

measurements.

However, the level of difference between children with history of diarrhea and those

with diarrhea is remarkable at aggregate levels of proportion. The results of cross-

tabulation between MUAC measurement and the history of diarrhea in child life show

that the prevalence level of malnutrition for children without history of diarrhea

(39.6%) is much higher than that for those with diarrhea (60.4%) at aggregate level. But

the results are reversed at the levels categorized according to with/without diarrhea

(9.2% for children with history of diarrhea and 6.0% for those without history of

diarrhea). As MUAC measures the level of muscle mass, it can be concluded based on

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this information that history of diarrhea in child life seems to be related to the loss of

muscle mass that can be related in many ways to stunting, wasting, and underweight

among children under five.

4.12. Malnutrition by Status of Immunization

Within the stunted population, the proportion of malnutrition among under-five

children who are immunized (80.1%) is significantly higher at aggregate level than that

of those who are not immunized (19.9%). But such results are mainly confined to

stunting and wasting. The results at group level categorized by with/without

immunization are much positive except in the case of wasting where children without

immunization has lower level of malnutrition prevalence (76.9% for with and 23.1% for

without immunization). The difference is not significant in underweight. However,

immunization does not make much difference between immunized children and those

not immunized. Similar regards apply to the proportions of wasted and underweighted

children according. Of the total population, the prevalence of children suffering from

underweight is much higher among immunized children than that of those not

immunized.

The state of being not immunized may not be the direct cause of malnutrition, but it

would be rather related to diseases that will further cause malnutrition. However,

further investigation might be needed to clarify if immunization has not imposed

positive impacts on the nutritional status of children under five. On the other hand,

could it be due to the quality of foods consumed if immunization would not be the case

for malnutrition. The causes of malnutrition can be carious in kind, but the quality and

perhaps volume of food consumed by children and their mother can also be decisive in

terms of the nutritional level of children.

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Figure 14 Malnutrition by immunization status of child

A rather different proportion has been resulted for the cross-tabulation of MUAC and

immunization status of children under study. The result shows that the prevalence

proportion of severely malnourished for immunized children is 10.5 percent and for

those not immunized is 4.7 percent within the total population of severely

malnourished children. On the other hand, the proportion of severely malnourished

population is shared as 69.4 percent for those children immunized and 30.6 percent for

those not immunized. The difference is almost by half and this information somewhat

means that immunization status has not much relationship with the nutritional status of

children. Separate cross-tabulations are made between malnutrition status and three

types of immunization (DPT, Poliomyelitis, and Measles), but the results are more or

less the same, showing that children who were not immunized are among the less

severely malnourished population.

Figure 15 Malnutrition status by DPT immunization

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Figure 16 Malnutrition status by poliomyelitis immunization

Figure 17 Malnutrition Status by measles immunization

4.13. Malnutrition by Types of Respondent’s Occupation

The prevalence levels of malnutrition according to the types of occupation reported by

the respondents are also cross-tabulated. The aggregate data show that prevalence

levels of stunting, wasting, and underweight are highest for farmers and casual workers.

Children with respondents’ occupation as government employees and pastors are

subject to high proportions of malnutrition in the form of stunting and underweight.

Within the same forms of malnutrition, stunting and underweight account highest for

farmers, casual labors, and government employees. Here again, the prevalence level of

malnutrition is very low for traditional healers who are supposed to have more

knowledge on health education.

In fact, the relationship between malnutrition and respondents’ occupation may or may

not be relevant for assessing the impacts of nutritional status among children under

30 | P a g e

five. However, the respondents were selected to be the ones who take care of the

children under study or who got involved in child care directly or indirectly. This

connotes that the children under study may be directly or indirectly related to the

occupation of the respondent interviewed. For example, nutritional status of the

children under study can be very positive if the respondent is a health staff of either

government or NGO compared with that of children for whom the respondents are

farmers or casual workers.

Figure 18 Malnutrition by types of respondent’s occupation

5. Conclusion and Recommendations

Malnutrition among children under five is a multi-faceted problem. About 14.3 percent

of under-five children are severely malnourished according to MUAC measurement.

Results of measurements by z-scores again show that 52.3% of children in the study

areas are stunting, 10.3% are wasting, and 37.1% are underweighted. According to

malnutrition by sex type, female are more severely malnourished than male. However,

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it is necessary to know why these high proportions of malnutrition are prevalent among

children under five in the study areas. And this might be more rational if we assess the

results against the conceptual framework that is globally referred.

According to the conceptual framework, access to potential resources is limited by the

economic status and educational level of the households concerned which further

results in inadequate access to food, inadequate care for mother and children, and

insufficient health services and unhealthy environment. These underlying causes

(inadequate access to food, inadequate care for mother and children, and insufficient

health services and unhealthy environment) together result in inadequate dietary

intake and disease which finally cause malnutrition and death of children. Whereas

access to food is translated as food security, it would be of significance to also know

how people ensure access to food. As defined by FAO (1996), food security exists when

all people, at all times, have physical and economic access to food, stability of supply and

access, and safe and healthy food utilization.

Contrary to what was assumed before this assessment, it is found that not all failures of

households contribute to under-five malnutrition. Listed here are some important

findings that are worth recommending for the purpose of practical replication. The use

of birth spacing methods and the number of breast-feeding years have remarkable

positive impacts on severe malnutrition. Similarly, higher family size also contribute to

lower stunting and underweight though the use of birth spacing methods does not

always results in shorter intervals of child birth. The assessment also found that history

of diarrhea is responsible mainly for wasting and underweight and avoiding meals by

mother during pregnancy periods imposes lower malnutrition especially wasting. A

little knowledge in health education is more effective for improved malnutrition than

higher level of formal education.

Having reviewed these findings, it can be drawn that most of nutritional problems

among children under five mainly derive from the knowledge and behavior of the

parents or those people who take care of children. On the other hand, the nutritional

problems will not be solved unless the households concerned have adequate access to

food and health services and there is supportive environment. In order to combat

under-five malnutrition, therefore, one can intervene by providing various forms of

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support for increased access to food. At the same time, the target communities should

be provided with awareness-raising on basic health education especially how to process

and consume the available food for improved nutrition. Most of these suggested

interventions will be more effective if a further study can be conducted to investigate

why and how the nutritional problems identified occur and are linked to the

interventions suggested.

References

UNICEF (1990) Strategy for improved nutrition of children and women in developing

countries, New York: UNICEF.

World Bank and UNICEF (2002) World Bank/UNICEF Nutrition Assessment

Background Papers, Washington D.C. & New York: Nutrition Section, Programme

Division UNICEF & Health, Nutrition and Population Unit, The World Bank, New

York: World Bank and UNICEF.

United Nations System, Standing Committee on Nutrition Task Force on Assessment,

Monitoring, and Evaluation, Fact sheets on Food and Nutrition Security

Indicators/Measures: Mid-Upper Arm Circumference (MUAC).

www.unsystem.org/.../task_force/Factsheet%20MUAC%20Hanoi.doc

Lisa C. Smith and Lawrence Haddad (1999) Explaining Child Malnutrition in Developing

Countries: A Cross-Country Analysis, FCND Discussion Paper No. 60, Washington,

D.C.: Food Consumption and Nutrition Division, International Food Policy Research

Institute.

London School of Hygiene and Tropical Medicine (2009) The use of epidemiological

tools in conflict-affected populations: open-access educational resources for policy-

makers, London: London School of Hygiene and Tropical Medicine.

http://conflict.lshtm.ac.uk/page_125.htm