[Association between dietary patterns and abdominal obesity among the adult women in Zhejiang Province]

Wei Sheng Yan Jiu. 2022 Sep;51(5):733-739. doi: 10.19813/j.cnki.weishengyanjiu.2022.05.010.
[Article in Chinese]

Abstract

Objective: To explore the dietary patterns and its relationship with abdominal obesity among the adult women in Zhejiang Province.

Methods: We recruited 2915 female residents aged 18 and older by using multi-stage stratified cluster sampling method; We conducted questionnaires survey and physical examinations to understand the basic information and nutritional status of the residents. Dietary patterns were extracted with factor analysis, and the multivariate Logistic regression model was used to analyze the association between dietary patterns and abdominal obesity among the participants.

Results: The prevalence rate of abdominal obesity and general obesity among the subjects were 33.07% and 9.23%, respectively. The highest rate of abdominal obesity was among the female who were above 65 years old, living in rural areas with low education. On the other hand, the lowest rate of abdominal obesity was among females with higher education(P<0.0001). Four dietary patterns identified with factor analysis were grain pattern, nut-legume pattern, milk-eggs pattern and modern pattern, accounting for 38.5% of total variance. After adjusting confounding factors as age, education level, occupation, marital status, urban/rural and exercise status, the participants with the fourth quartile(Q4) score of nut-legume dietary pattern had a low risk of abdominal obesity(OR=0.720, 95% CI 0.571-0.908, P=0.0012) compared to those with the quartile(Q1) first score.

Conclusion: The nut-legume dietary pattern is negatively associated with abdominal obesity in female adults.

Keywords: dietary pattern; factor analysis; obesity; women.

MeSH terms

  • Adult
  • Aged
  • China / epidemiology
  • Cross-Sectional Studies
  • Diet
  • Female
  • Humans
  • Obesity* / epidemiology
  • Obesity, Abdominal* / epidemiology
  • Risk Factors
  • Vegetables