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Abstract
Background: Prediabetes is an important public health problem concern globally, to which dietary patterns have shown varied effects. This study aims to analyze the relationship between dietary patterns and prediabetes in Chinese adults. Methods: A total of 7555 adults from Jiangsu province, China, were recruited using a stratified multistage cluster sampling method. Information on diet intake, demographic, blood glucose and other indices were collected by structured questionnaires. Four dietary patterns of Meat diet, Healthy diet, Traditional diet and Fried food with staple diet were identified using Principle Component Analysis and followingly divided into T1 - T4 groups according to their quartiles of factor scores. Multivariate logistic regression analysis was used to investigate the association between dietary patterns and prediabetes. Results: Healthy diet was found to be associated with the lowest prevalence of prediabetes (P < 0.05). Multivariate logistic regression analysis after adjusting the confounding factors demonstrated that the lowest odds ratio with prediabetes was associated with the third quartile (T3 group) of Healthy diet (Odds Ratio = 0.745, 95% Confidence Interval: 0.645–0.860, P < 0.01), compared with the lower quartile (T1 group). The Meat diet was a potential risk factor for the isolated IFG (Odds Ratio = 1.227, 95%Confidence Interval: 1.070–1.406, P-value<0.01) while Fried food with staple diet was positively linked to the presence of IFG combined with IGT (Odds Ratio = 1.735, 95% Confidence Interval: 1.184–2.543, P-value < 0.01). Conclusions: Dietary patterns rich in meat but low in fresh fruit, fresh vegetable, milk, and fish are positively associated with higher risk of prediabetes, particularly the IFG. Higher Healthy diet consumption was associated with significantly lower risk of prediabetes.
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Details
1 Southeast University, School of Public Health, Nanjing, P.R. China (GRID:grid.263826.b) (ISNI:0000 0004 1761 0489)
2 Jiangsu Provincial Center for Disease Control and Prevention, Department of Chronic Non-communicable Disease Control, Nanjing, China (GRID:grid.198530.6) (ISNI:0000 0000 8803 2373)
3 Xuzhou Center for Disease Control and Prevention, Department of Chronic Non-communicable Disease Control, Xuzhou, P.R. China (GRID:grid.263826.b)