Association between dietary patterns and prediabetes risk in a middle-aged Chinese population

Nutr J. 2020 Jul 30;19(1):77. doi: 10.1186/s12937-020-00593-1.

Abstract

Background: Information regarding dietary patterns associated with prediabetes in the Chinese population is lacking. The objective of the present study was to explore the association between major dietary patterns and the risk of prediabetes in a middle-aged Chinese population.

Methods: A total of 1761 participants (aged 45 to 59 years) were recruited in Hangzhou city, the capital of Zhejiang Province, China from June 2015 to December 2016. Dietary information was obtained by interview using a 138-item, validated semi-quantitative food frequency questionnaire (SQFFQ). Multivariate logistic regression models were used to analyze the associations between dietary patterns and the risk of prediabetes with adjustment of potential confounding variables.

Results: Three dietary patterns were ascertained by factor analysis and labeled as traditional southern Chinese, Western, and grains-vegetables patterns. After controlling of the potential confounders, participants in the top quartile of the Western pattern scores had greater odds ratio (OR) for prediabetes (OR = 1.54; 95% confidence interval (CI):1.068-2.059; P = 0.025) than did those in the bottom quartile. Compared with those in the bottom quartile, participants in the top quartile of the grains-vegetables pattern scores had a lower OR for prediabetes (OR = 0.83; 95% CI:0.747-0.965; P = 0.03). Besides, no statistically significant association was observed in the association between the traditional southern Chinese pattern and prediabetes risk (P > 0.05).

Conclusions: The findings of this study showed that the Western pattern was associated with higher risk, and the grains-vegetables pattern was associated with lower risk of prediabetes. Future prospective studies are required to validate our findings.

Keywords: China; Cross-sectional study; Dietary patterns; Factor analysis; Prediabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China / epidemiology
  • Cross-Sectional Studies
  • Diet
  • Humans
  • Middle Aged
  • Prediabetic State* / epidemiology
  • Risk Factors