Social factors and overweight: evidence from nine Asian INDEPTH Network sites.
BACKGROUND
Overweight/obesity increases the risk of morbidity and mortality from a number of chronic conditions, including heart disease, stroke, diabetes and some cancers. This study examined the distribution of body mass index (BMI) in nine Health and Demographic Surveillance System (HDSS) sites in five Asian countries and investigated the association between social factors and overweight.


METHODS
This cross-sectional study was conducted in nine HDSS sites in Bangladesh, India, Indonesia, Thailand and Vietnam. The methodology of the WHO STEPwise approach to Surveillance with core risk factors (Step 1) and physical measurements for weight, height and waist circumference (Step 2) were included. In each site, about 2,000 men and women aged 25-64 years were selected randomly using the HDSS database. Weight was measured using electronic scales, height was measured by portable stadiometers and waist circumference was measured by measuring tape. Overweight/obesity was assessed by BMI defined as the weight in kilograms divided by the square of the height in metres (kg/m(2)).


RESULTS
At least 10% people were overweight (BMI >/= 25) in each site except for the two sites in Vietnam and WATCH HDSS in Bangladesh where few men and women were overweight. After controlling for all the variables in the model, overweight increases with age initially and then declines, with increasing education, and with gender with women being heavier than men. People who eat vegetables and fruits below the recommended level and those who do high level of physical activity are, on the whole, less heavy than those who eat more and do less physical activity.


CONCLUSIONS
As the proportion of the population classified as being overweight is likely to increase in most sites and overweight varies by age, sex, and social and behavioural factors, behavioural interventions (physical exercise, healthy diet) should be developed for the whole population together with attention to policy around nutrition and the environment, in order to reduce the adverse effects of overweight on health.
Razzaque
Abdur
A
Matlab Health and Demographic Survillance System, Bangladesh.
Nahar
Lutfun
L
Van Minh
Hoang
H
Ng
Nawi
N
Juvekar
Sanjay
S
Ashraf
Ali
A
Ahmed
Syed Masud
SM
Soonthornthada
Kusol
K
Kanungsukkasem
Uraiwan
U
Huu Bich
Tran
T