The relationship between dietary patterns and overweight and obesity among adult in Jiangsu Province of China: a structural equation model

Abstract

Aims: This study aimed to analyze the relationship between diet and overweight and obesity in Jiangsu Province by using structural equation modeling (SEM), and to determine dietary differences between genders in the model.

Methods: Data from 1739 individuals (53.8% female, n = 935) were analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to classify dietary patterns. SEM and multivariate logistic regression were used to explore the relationship between dietary patterns and overweight and obesity.

Results: Overweight and obesity was found in 49.1%, and no difference was found in gender (51.2% of men and 47.2% of women, respectively; P = 0.090). Three dietary patterns: the traditional dietary pattern (i.e., poultry, light-colored vegetables, red meat and its products, cereals and tubers products, condiment, oils and dark-colored vegetables), the fruit-egg dietary pattern (i.e., fruit, whole grains, pickled vegetables and eggs and eggs products) and nut-wine dietary pattern (i.e., nut, wine and pastry snacks) were established by using EFA and CFA. It was found that the traditional dietary pattern for adult male was positively associated with the overweight and obesity in Jiangsu Province of China through multivariate logistic regression and SEM (OR = 1.954; 95%CI: 1.258 ~ 3.036; β =0.121, P < 0.05, respectively).

Conclusion: The traditional dietary pattern only have positive association with overweight and obesity in men in Jiangsu Province, China.

Keywords: China; Dietary pattern; Overweight and obesity; Structural equation modelling.

Fig. 1

Measurement models of the latent construct of three dietary patterns among adults from Jiangsu Province, China in 2007–2014 (a men and b women). In model of men: RMSEA = 0.063, GFI = 0.946, CFI = 0.763, ACFI = 0.923 and PGFI = 0.667. In model of women: RMSEA = 0.047, GFI = 0.960, CFI = 0.862, ACFI = 0.946 and PGFI = 0.706. Rectangles indicate observed variables, and oval is latent variable in the model. All factor loadings and regression coefficients in the figure are significant (P < 0.05)

Fig. 2

A conceptual SEM model for the association of socio-demographic, dietary pattern, and life style with overweight and obesity

Fig. 3

Final structural models in men. The path standardized coefficients of variables are presented on pathways. RMSEA = 0.052, GFI =0.937, CFI = 0.745, ACFI = 0.919, PGFI = 0.730 and. a error