General and Central Obesity in Two Iranian Ethnic Groups Living in Urmia, West Azerbaijan, Iran: Effect of the Neighborhood Environment

Emerging evidence suggests that neighborhood characteristics can have direct and indirect effects on the weight status of the residents.
To assess the relationship between general and central obesity and the neighborhood environment in two ethnic groups (Azeri Turks and Kurds) living in Urmia city, Northwestern Iran.
Patients and In this cross-sectional study, 723 participants (427 women and 296 men) aged 20 - 64 years from two ethnic groups (Azeri Turks, n = 445; Kurds, n = 278) were selected from 38 neighborhoods using a combination of cluster, random, and systematic sampling methods. Neighborhood characteristics were obtained by a validated 22-item neighborhood and a health observational checklist. General and central obesity were measured and evaluated using standard methods. Principal component analysis (PCA) was used to define the dominant neighborhood environment. The association of neighborhood characteristics with general and central obesity was analyzed by a logistic regression model.
Three common neighborhood environments were identified: 1) modern-affluent, 2) central-high access and 3) marginal. These three factors explained 73.2% of the total variance. Overall, the participants living in a higher tertile of the central-high access neighborhoods had an increased chance of central obesity (OR = 1.63, 95% CI: 1.13 - 2.34). Azeri Turks living in the highest tertile of the modern-affluent neighborhoods had a significantly higher likelihood of having general obesity (OR = 2.49, 95% CI: 1.37 - 4.01). Adjustment for age, gender, marital status, socioeconomic status (SES), energy intake, and physical activity did not change the results. However, after adjustment for educational level, the association was not significant.
The findings point to a relationship between neighborhood characteristics and obesity only in the Azeri Turks. However, educational level was more important than neighborhood quality in predicting the risk of obesity.