Abstract

OBJECTIVE: To compare the prevalence of obesity, household food consumption patterns, physical activity patterns and smoking between a rural and an urban community in the Palestinian West Bank and to describe the associations of the latter factors with body mass index (BMI). DESIGN: A population-based cross-sectional survey in a rural and an urban Palestinian West Bank community. SUBJECTS: A total of 549 women and 387 men aged 30-65 y, excluding pregnant women. MEASUREMENTS: Obesity was defined as BMI >/=30 kg/m(2). RESULTS: The prevalence of obesity was 36.8 and 18.1% in rural women and men, respectively, compared with 49.1 and 30.6% in urban women and men, respectively. The mean difference (s.e) in BMI levels was 1.6 (0.52) kg/m(2) between urban and rural women and 0.9 (0.46) kg/m(2) in men. At the household level, the mean energy consumption from 25 selected food items was 13.8 MJ (3310 kcal)/consumption unit/day in the rural community compared to 14.5 MJ (3474 kcal)/consumption unit/day in the urban community (P=0.021). BMI was positively associated with age in both men and women and with urban residence in women. BMI was negatively associated with smoking and physical activity in men and with educational level in women. CONCLUSION: BMI was associated with urban residence in women after adjusting for age, smoking, education, physical activity and nutrition-related variables, suggesting that the differences in the conventional determinants of obesity could not fully explain the difference in the prevalence of obesity between the two communities. Among men, the measured determinants explained the rural-urban differences in BMI.

Year
2003
Language
English
Date Published
Jan
Volume
27
Pages
140-6
Accession Number
12532166
ISBN Number
0307-0565 (Print)0307-0565 (Linking)
Journal Name
Int J Obes Relat Metab Disord
Keywords
Adipose Tissue
Adult
Arabs
statistics & numerical data
Body Mass Index
Cross-Sectional Studies
Energy Metabolism
Exercise
Female
Humans
Male
Middle Aged
Middle East
epidemiology
Obesity
Metabolism
Prevalence
Regression Analysis
Rural Health
Urban Health