Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jun 25;21(1):1225.
doi: 10.1186/s12889-021-11341-3.

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

Yuan-Yuan Wang #  1 , Ting Tian  2 , Da Pan  1 , Jing-Xian Zhang  2 , Wei Xie  2 , Shao-Kang Wang  1 , Hui Xia  1 , Yue Dai #  3   4 , Guiju Sun  5
Affiliations

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

Yuan-Yuan Wang et al. BMC Public Health. .

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.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
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
Fig. 2
A conceptual SEM model for the association of socio-demographic, dietary pattern, and life style with overweight and obesity
Fig. 3
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
See this image and copyright information in PMC

References

    1. World Health Organization. Obesity and overweight 2014. WHO; 2019. [2021-02-08]. http://www.who.int/topics/obesity/en.
    1. China . Report on the status of nutrition and chronic diseases among Chinese residents 2015. Beijing: People’s Publishing House; 2015.
    1. Damsgaard CT, Michaelsen KF, Molbo D, et al. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants[J]. Lancet. 2016;387(10026):1377-96. - PMC - PubMed
    1. Ortega FB, Lavie CJ, Blair SN. Obesity and cardiovascular disease. Circ Res. 2016;118(11):1752–1770. doi: 10.1161/CIRCRESAHA.115.306883. - DOI - PubMed
    1. Seravalle G, Grassi G. Obesity and hypertension. Pharmacol Res. 2017;122:1–7. doi: 10.1016/j.phrs.2017.05.013. - DOI - PubMed

Publication types