Determinants of self-rated health among an older Tibetan population in a Chinese plateau area: analysis based on the conceptual framework for determinants of health

• Main Authors: Yajie Li (Author), Qucuo Nima (Author), Bin Yu (Author), Xiong Xiao (Author), Peibin Zeng (Author), Deji Suolang (Author), Ruifeng He (Author), Zhuoga Ciren (Author), Pingcuo Wangqing (Author), Ciren Laba (Author), Yangzong Silang (Author), Ling Song (Author), Yixi Kangzhu (Author), Jingzhong Li (Author)
• Format: Book
• Published: BMC, 2021-03-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12889-021-10359-x; 1471-2458
• Keywords: Self-rated health; Social determinants of health; Plateau area; Older people; Public aspects of medicine; RA1-1270
• Source: BMC Public Health, Vol 21, Iss 1, Pp 1-11 (2021)

Abstract Background Self-rated health (SRH) has been frequently used in population health surveys. However, most of these studies only focus on specific factors that might directly affect SRH, so only partial or confounding information about the determinants of SRH is potentially obtained. Conducted in an older Tibetan population in a Chinese plateau area, the aim of our study is to assess interrelationships between various factors affecting SRH based on the conceptual framework for determinants of health. Methods Between May 2018 and September 2019, 2707 Tibetans aged 50 years or older were recruited as part of the China Multi-Ethnic Cohort Study (CMEC) from the Chengguan District of Lhasa city in Tibet. The information included SRH and variables based on the conceptual framework for determinants of health (i.e., socioeconomic status, health behaviors, physical health, mental health, and chronic diseases). Structural equation modeling (SEM) was used to estimate the direct and indirect effects of multiple factors in the conceptual framework. Results Among all participants, 5.54% rated their health excellent, 51.16% very good, 33.58% good, 9.12% fairly poor and 0.59% poor. Physical health (β = − 0.23, P < 0.001), health behaviors (β = − 0.44, P < 0.001), socioeconomic status (β = − 0.29, P < 0.001), chronic diseases (β = − 0.32, P < 0.001) and gender (β = 0.19, P < 0.001) were directly associated with SRH. Socioeconomic status, physical health and gender affected SRH both directly and indirectly. In addition, there are potential complete mediator effects in which age and mental health affect SRH through mediators, such as physical health, health behaviors and chronic diseases. Conclusions The findings suggested that interventions targeting behavioral changes, health and chronic disease management should be attached to improve SRH among older populations in plateau areas without ignoring gender and socioeconomic disparities.