Predicting Health-Related Quality of Life Among Chinese Residents: Latent Class Analysis Based on Panel Survey Data

Qing-Lin Li,1,2,* Xue-Jiao Liu,1,2,* Shu-E Zhang,3 Chao-Yi Chen,1,2 Liang Zhang,4 Xiang Zhang1,2 1Department of Health Administration, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2The Key Research Institute of Humanities and Social Science of Hubei Province, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 3Department of Health Management, School of Health Management, Harbin Medical University, Harbin, 150081, People’s Republic of China; 4School of Political Science and Public Administration, Wuhan University, Wuhan, 430030, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiang Zhang, Department of Health Administration, School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China, Tel +86 18907145152, Email [email protected]: This study aimed to identify distinct trends among Chinese residents based on their health-related quality of life (HR-QoL) outcomes and to analyze the demographic characteristics that contribute to these trends.Materials and Methods: The study conducted latent class analysis using baseline data obtained from a survey of health service utilization behaviors (from July to December 2016) among residents of Hubei Province, China (N = 1517). Latent classes were used to implement the HR-QoL grouping of different trends among the respondents. Multinomial logistic regression analysis was used to identify demographic characteristic factors affecting HR-QoL in the trend groups.Results: A three-class model emerged as the most suitable grouping classification for HR-QoL among Chinese residents: the low HR-QoL class, exhibiting a downward trend (5.5%); the medium HR-QoL class, exhibiting an upward trend (12.1%); and the stable HR-QoL class, exhibiting high HR-QoL (82.4%). Participants in the medium class were more likely to be without chronic diseases, aged 45– 64 years, and employed than those in the low class. Conversely, urban participants had a higher likelihood of belonging to the low class. Participants in the stable class were more likely to be without chronic diseases, aged 15– 44 years or 45– 64 years, and employed than those in the low class. Conversely, urban participants had a higher likelihood of belonging to the low class.Conclusion: Three latent trend classes of HR-QoL were observed, which exhibited distinct characteristics. Residents without chronic diseases, residents under 65 years of age, and employed residents had better HR-QoL than individuals in other classes, while urban residents had poorer HR-QoL than individuals in other classes.Plain Language Summary: Health-related quality of life (HR-QoL) is an essential predictor of healthcare utilization, mortality, morbidity, and poor health. The rapid pace of modernization has corresponded with changes in the HR-QoL of the population. However, more empirical research is needed on the changes in HR-QoL among the Chinese population. In this study, we identified different trends in HR-QoL among Chinese residents and the demographic factors influencing HR-QoL among these trends. This study highlighted variations in longitudinal HR-QoL trends among Chinese residents. HR-QoL for Chinese residents is divided into three classes: low, exhibiting a downward trend; medium, exhibiting an upward trend; and stable, exhibiting high HR-QoL. Residents without chronic diseases, residents under the age of 65, and employed residents had better HR-QoL than other classes of individuals, while urban residents had worse HR-QoL than other classes of individuals. Understanding these HR-QoL trends could aid the development of targeted interventions for Chinese residents and improve their health and quality of life.Keywords: Chinese resident, health-related quality of life, latent class analysis