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. 2024 Oct 25:17:2503-2514.
doi: 10.2147/RMHP.S475022. eCollection 2024.

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

Affiliations

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

Qing-Lin Li et al. Risk Manag Healthc Policy. .

Abstract

Purpose: 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.

Keywords: Chinese resident; health-related quality of life; latent class analysis.

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1
Latent classes of HR-QoL of participants in all data group (N = 1597).
Figure 2
Figure 2
Latent classes of HR-QoL of participants in complete data group (N = 1517).

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References

    1. Seppälä T, Mäntyselkä P, Saxen U, Kautiainen H, Järvenpää S, Korhonen PE. Weight change and health related quality of life: population-based longitudinal study of the effects of health related quality of life on the success of weight management. J Community Health. 2014;39(2):349–354. doi:10.1007/s10900-013-9768-8 - DOI - PubMed
    1. Yu C, Ren X, Cui Z, et al. A diagnostic prediction model for hypertension in Han and Yugur population from the China National Health Survey (CNHS). Chin Med J. 2023;136(9):1057–1066. doi:10.1097/CM9.0000000000001989 - DOI - PMC - PubMed
    1. Plans E, Gullón P, Cebrecos A, et al. Density of Green Spaces and Cardiovascular Risk Factors in the City of Madrid: the Heart Healthy Hoods Study. Int J Environ Res Public Health. 2019;16(24):4918. doi:10.3390/ijerph16244918 - DOI - PMC - PubMed
    1. Hurt CN, Mukherjee S, Bridgewater J, et al. Health-Related Quality of Life in SCALOP, a Randomized Phase 2 Trial Comparing Chemoradiation Therapy Regimens in Locally Advanced Pancreatic Cancer. Int J Radiat Oncol Biol Phys. 2015;93(4):810–818. doi:10.1016/j.ijrobp.2015.08.026 - DOI - PMC - PubMed
    1. Clancy B, Bonevski B, English C, et al. Health risk factors in Australian Stroke Survivors: a latent class analysis. Health Promot J Austr. 2024;35(1):37–44. doi:10.1002/hpja.706 - DOI - PMC - PubMed

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