Aller au contenu principal
Accès ouvert déclaré 2024 article

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

2Citations signalées, ce qui n’est pas une note de qualité
3Institutions déclarées
1Pays d’affiliation déclarés

Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

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. 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

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Predicting Health-Related Quality of Life Among Chinese Residents: Latent Class Analysis Based on Panel Survey Data
Date Crossref
01/10/2024
Éditeur
Informa UK Limited
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

  • Huazhong University of Science and Technology The Key Research Institute of Humanities and Social Science of Hubei Province pays non établi dans la notice
    Université ou école supérieure
  • Harbin Medical University pays non établi dans la notice
    Université ou école supérieure
  • Wuhan University pays non établi dans la notice
    Université ou école supérieure
  • School of Medicine and Health Management Department of Health Administration pays non établi dans la notice
    Université ou école supérieure
  • School of Health Management Department of Health Management pays non établi dans la notice
    Université ou école supérieure
  • School of Political Science and Public Administration pays non établi dans la notice
    Université ou école supérieure

The Key Research Institute of Humanities and Social Science of Hubei Province — Huazhong University of Science and Technology, Harbin Medical University et Wuhan University, avec 3 autres affiliations.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Health disparities and outcomesHealthcare Systems and ReformsHealth Systems, Economic Evaluations, Quality of Life

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.