[Study on the determinants of prevalence in persons with overweight and obesity in rural areas of Kunming]

Zhonghua Liu Xing Bing Xue Za Zhi. 2008 Jul;29(7):676-8.
[Article in Chinese]

Abstract

Objective: This study was to explore the prevalence of overweight and obesity,and the effects of contextual and individual level determinants on them in the rural areas of Kunming city, China.

Methods: Shilin County was selected as the study site. Probability Proportional to Size (PPS) sampling method was used to select representative sample of 6006 residents aged 45 years and over from Shilin. Information was obtained from a cross-sectional survey on health. Data was analyzed using a multilevel logistic modeling.

Results: The prevalence rates of overweight and obesity were 12.10% and 2.15% in the study area. Males had a higher prevalence of overweight than females (13.60% vs. 10.71%). Similar situation was seen in the prevalence of obesity (2.82% vs. 1.52%). Both village level and individual level variables were associated with obesity, whereas only individual level variables were related to overweight. Elderly had lower probability of being overweight and obese than younger people with odds ratio (OR) as 0.95 (95% CI:0.83-0.97) and 0.93 (95% CI: 0.82-0.96), respectively. Males had higher probability of being overweight and obese than females: OR of 0.89 (95% CI:0.78-0.98) and OR of 0.87 (95% CI: 0.78-0.97),respectively. Individuals with lower family income had increased probability of having obesity (OR = 0.81, 95% CI: 0.73-0.95). Factor as living in a higher income village was associated with lower prevalence of obesity (OR = 0.92, 95% CI: 0.85-0.98).

Conclusion: Interventions at village level on obesity in parallel with those at individual level were needed. Prevention and intervention on obesity should be emphasized in villages with higher income.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • China / epidemiology
  • Cross-Sectional Studies
  • Data Collection
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Obesity / epidemiology*
  • Overweight / epidemiology*
  • Prevalence
  • Rural Population
  • Surveys and Questionnaires