Shi Yulin, Wang Baohua, Zhao Jian, Wang Chunping, Li Ning, Chen Min, Wan Xia
Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, 5 Dong Dan San Tiao, Dong Cheng District, Beijing, 100005, China, 8610-65233870.
National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
JMIR Public Health Surveill. 2024 Jul 31;10:e52019. doi: 10.2196/52019.
The core Healthy Days measures were used to track the population-level health status in the China Chronic Disease and Risk Factor Surveillance; however, they were not easily combined to create a summary of the overall health-related quality of life (HRQOL), limiting this indicator's use.
This study aims to develop a summary score based on the Chinese version of the core Healthy Days measures (HRQOL-5) and apply it to estimate HRQOL and its determinants in a Chinese population.
From November 2018 to May 2019, a multistage stratified cluster survey was conducted to examine population health status and behavioral risk factors among the resident population older than 15 years in Weifang City, Shandong Province, China. Both exploratory factor analyses and confirmatory factor analyses were performed to reveal the underlying latent construct of HRQOL-5 and then to quantify the overall HRQOL by calculating its summary score. Tobit regression models were finally carried out to identify the influencing factors of the summary score.
A total of 26,269 participants (male: n=13,571, 51.7%; mean age 55.9, SD 14.9 years) were included in this study. A total of 71% (n=18,663) of respondents reported that they had excellent or very good general health. One summary factor was extracted to capture overall HRQOL using exploratory factor analysis. The confirmatory factor analysis further confirmed this one-factor model (Tucker-Lewis index, comparative fit index, and goodness-of-fit index >0.90; root mean square error of approximation 0.02). Multivariate Tobit regression analysis showed that age (β=-0.06), educational attainments (primary school: β=0.72; junior middle school: β=1.46; senior middle school or more: β=2.58), average income (≥¥30,000 [US $4200]: β=0.69), physical activity (β=0.75), alcohol use (β=0.46), self-reported disease (β=-6.36), and self-reported injury (β=-5.00) were the major influencing factors on the summary score of the HRQOL-5.
This study constructs a summary score from the HRQOL-5, providing a comprehensive representation of population-level HRQOL. Differences in summary scores of different subpopulations may help set priorities for health planning in China to improve population HRQOL.
在中国慢性病与危险因素监测中,核心健康日指标用于追踪人群健康状况;然而,这些指标不易合并以生成总体健康相关生活质量(HRQOL)的汇总结果,限制了该指标的应用。
本研究旨在基于核心健康日指标的中文版(HRQOL-5)开发一个汇总分数,并将其应用于评估中国人群的HRQOL及其决定因素。
2018年11月至2019年5月,在中国山东省潍坊市对15岁以上常住人口进行了多阶段分层整群调查,以检查人群健康状况和行为危险因素。进行探索性因素分析和验证性因素分析,以揭示HRQOL-5潜在的潜在结构,然后通过计算其汇总分数来量化总体HRQOL。最后进行Tobit回归模型以确定汇总分数的影响因素。
本研究共纳入26269名参与者(男性:n = 13571,占51.7%;平均年龄55.9岁,标准差14.9岁)。共有71%(n = 18663)的受访者表示他们的总体健康状况为优秀或非常好。通过探索性因素分析提取了一个汇总因素来反映总体HRQOL。验证性因素分析进一步证实了这一单因素模型(塔克-刘易斯指数、比较拟合指数和拟合优度指数>0.90;近似均方根误差为0.02)。多变量Tobit回归分析表明,年龄(β = -0.06)、教育程度(小学:β = 0.72;初中:β = 1.46;高中及以上:β = 2.58)、平均收入(≥30000元[4200美元]:β = 0.69)、体育活动(β = 0.75)、饮酒(β = 0.46)、自我报告的疾病(β = -6.36)和自我报告的伤害(β = -5.00)是HRQOL-5汇总分数的主要影响因素。
本研究从HRQOL-5构建了一个汇总分数,全面反映了人群水平的HRQOL。不同亚人群汇总分数的差异可能有助于为中国的健康规划设定优先事项,以提高人群的HRQOL。