Impact of Sociodemographic Characteristics, Lifestyle, and Obesity on Coexistence of Diabetes and Hypertension: A Structural Equation Model Analysis amongst Chinese Adults

Wenwen Wu; Jie Diao; Jinru Yang; Donghan Sun; Ying Wang; Ziling Ni; Fen Yang; Xiaodong Tan; Ling Li; Li Li

doi:10.1155/2021/4514871

Impact of Sociodemographic Characteristics, Lifestyle, and Obesity on Coexistence of Diabetes and Hypertension: A Structural Equation Model Analysis amongst Chinese Adults

Int J Hypertens. 2021 Oct 25:2021:4514871. doi: 10.1155/2021/4514871. eCollection 2021.

Authors

Wenwen Wu^{1

2

3}, Jie Diao⁴, Jinru Yang⁵, Donghan Sun¹, Ying Wang⁶, Ziling Ni⁷, Fen Yang⁸, Xiaodong Tan⁹, Ling Li¹⁰, Li Li¹

Affiliations

¹ Institute for Evidence-Based Nursing, Renmin Hospital, Hubei University of Medicine, Shiyan 442000, China.
² School of Public Health, Hubei University of Medicine, Shiyan 442000, China.
³ Center for Environment and Health in Water Source Area of South-to-North Water Diversion, Hubei University of Medicine, Shiyan 442000, China.
⁴ School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
⁵ Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
⁶ Department of Nosocomial Infection Management, Wuhan University Zhongnan Hospital, Wuhan 430071, Hubei, China.
⁷ School of Medicine, Hangzhou Normal University, Hangzhou 311121, China.
⁸ College of Nursing, Hubei University of Chinese Medicine, Wuhan 430065, China.
⁹ School of Health Sciences, Wuhan University, Wuhan 430071, China.
¹⁰ Nursing Department, Dongfeng Hospital, Hubei University of Medicine, Shiyan 442000, China.

Abstract

Background: In general, given the insufficient sample size, considerable literature has been found on single studies of diabetes and hypertension and few studies have been found on the coexistence of diabetes and hypertension (CDH) and its influencing factors with a large range of samples. This study aimed to establish a structural equation model for exploring the direct and indirect relationships amongst sociodemographic characteristics, lifestyle, obesity, and CDH amongst Chinese adults.

Methods: A cross-sectional study was conducted in a representative sample of 25356 adults between June 1, 2015, and September 30, 2018, in Hubei province, China. Confirmatory factor analysis was initially conducted to test the latent variables. A structural equation model was then performed to analyse the association between latent variables and CDH.

Results: The total prevalence of CDH was 2.8%. The model paths indicated that sociodemographic characteristics, lifestyle, and obesity were directly associated with CDH, and the effects were 0.187, 0.739, and 0.353, respectively. Sociodemographic characteristics and lifestyle were also indirectly associated with CDH, and the effects were 0.128 and 0.045, respectively. Lifestyle had the strongest effect on CDH (β = 0.784, P < 0.001), followed by obesity (β = 0.353, P < 0.001) and sociodemographic characteristics (β = 0.315, P < 0.001). All paths of the model were significant (P < 0.001).

Conclusion: CDH was significantly associated with sociodemographic characteristics, lifestyle, and obesity amongst Chinese adults. The dominant predictor of CDH was lifestyle. Targeting these results might develop lifestyle and weight loss intervention to prevent CDH according to the characteristics of the population.