Lydia Kaduka (PhD)Centre for Public Health ResearchKenya Medical Research Institute

In Kenya, NCD accounts for >50% of total hospital admissions and over 55% of hospital deaths (MOH SP, 2014)

Overall, CVDs, diabetes, cancer and chronic lung disease contribute to over two thirds of morbidity & mortality from NCDs in Kenya (WHO 2010).

Leading CVDs RFs◦ Conventional - high blood pressure, dyslipideamia, tobacco and alcohol use,

physical inactivity, obesity, unhealthy diets and raised blood glucose◦ Novel – homocysteine, CRP

Obesity - associated with CVDs, diabetes and cancers → ↑risk of premature death and disabilities → reduced quality of life.

(Narkiewicz, 2006)

To assess the relationship between obesity and conventional and novel metabolic risk markers in an urban population in Kenya

Study site – Kibra and Karen Constituency of Nairobi County – hosts all the five SEC (Upper, Lower Upper, Middle, Lower Middle and Lower class).

Study design: Cross sectional design based on a three-stage cluster sampling methodology – selection of clusters, households and respondents.

Sample size – 536 (Fisher et al., 1983)

Sampling – 30 clusters sampled using the systematic Probability Proportional to Size (PPS) sampling method

Inclusion – adults aged >18yrs, absence of debilitating disease, residence>2years

Kibra and Karen Constituencies

Upper Upper Middle Middle Upper Lower Lower

Quick Count of EA

Select one Segment

Identify Eligible Respondents

Select one Respondent from the Eligibles per Household

Interview and testing

Sampling Procedure

Socio-economic and demographic assessments

Anthropometric assessments – weight, height (BMI), WC

Clinical examination- blood pressure

Biochemical assessments – fasting blood glucose, lipid profile, homocysteine and CRP

Permission – Ethical (KEMRI SERU) and informed consent

Total n = 539 (m: 50.5%; w: 49.5%); mean age 38.09 + 13.4 years.

Prevalence of overweight (BMI 25.0-29.99) ◦ m: 29.6%; w: 5.9%

Prevalence of obesity (BMI>30) ◦ m: 30.3%; w: 27.3%

Men Women

Increased blood pressure

P=0.003 P=0.010

Fasting blood glucose P<0.001 P=0.010

C-reactive protein P>0.05 P=0.002

Homocysteine P>0.05 P=0.003

Total cholesterol P=0.002 P>0.05

LDLC P<0.001 P=0.003

HDLC P<0.001 P<0.001

TAG P<0.001 P<0.001

SES P<0.001 P>0.05

Increasing age P<0.001 P<0.001

Men(WC>95cm)

WomenWC (80cm)

Increased blood pressure

P<0.001 P=0.010

Fasting blood glucose P<0.001 P=0.036

C-reactive protein P>0.05 P=0.032

Homocysteine P=0.021 P=0.025

Total cholesterol P<0.001 p= 0.004

LDLC P<0.001 P<0.001

HDLC P<0.001 P=0.002

TAG P<0.001 P<0.001

SES P<0.001 P>0.05

Increasing age P<0.001 P<0.001

Prevalence of CVD risk factors is high - consequence of components associated with urbanization

Components • More than an economic issue• Changes in lifestyle related factors, living conditions,

social structures etc, associated with and induced by urbanization as probable contributing factors

• Accelerated effects of cultural and behavioral shifts in transitional societies

Lifestyle management focusing on diet and physical activity.

Gender disparities → Patient-physician discussions of individual risks are paramount

Simple measures should be adapted as clinical components in the routine assessment and management of metabolic and cardiovascular risks

Risk factors operate in continuum - follow up longitudinal studies and prospective validation of the risk factors.

KEMRI

Kenya National Bureau of Statistics

Administration-Karen and Kibra Constituencies

University of Southampton

Coca-Cola Company