Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study.
AuthorSong, X; Wu, J; Yu, C; Dong, W; Lv, J; Guo, Y; Bian, Z; Yang, L; Chen, Y; Chen, Z; ...
Source TitleBMC Public Health
PublisherSpringer Science and Business Media LLC
University of Melbourne Author/sSchmidt, Daniel
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsSong, X., Wu, J., Yu, C., Dong, W., Lv, J., Guo, Y., Bian, Z., Yang, L., Chen, Y., Chen, Z., Pan, A., Li, L. & China Kadoorie Biobank Collaborative Group, (2018). Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study.. BMC Public Health, 18 (1), pp.744-. https://doi.org/10.1186/s12889-018-5632-1.
Access StatusOpen Access
Open Access at PMChttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC6003165
BACKGROUND: Understanding the correlates of self-rated health (SRH) can help public health professionals prioritize health-promotion and disease-prevention interventions. This study aimed to investigate the association between multiple comorbidities and global SRH and age-comparative SRH. METHODS: A total of 512,891 participants aged 30-79 years old were recruited into the China Kadoorie Biobank study from ten regions between 2004 and 2008. Multivariate logistic regression models were used to estimate the odds ratios (ORs) for the associations between comorbidities (including diabetes, hypertension, coronary heart disease, rheumatic heart disease, stroke, tuberculosis, emphysema/bronchitis, asthma, cirrhosis/chronic hepatitis, peptic ulcer, gallbladder disease, kidney disease, fracture, rheumatic arthritis, psychiatric disorders, depressive symptoms, neurasthenia, head injury and cancer) and SRH. Population attributable risks (PARs) were used to estimate the contribution of multiple comorbidities to poor global SRH and worse age-comparative SRH. RESULTS: After adjusting for covariates, suffering from various diseases increased the chance of reporting a poor global SRH [OR (95% CI) ranged from 1.10 (1.07, 1.13) for fracture to 3.21 (2.68, 3.83) for rheumatic heart disease] and a worse age-comparative SRH [OR (95% CI) ranged from 1.18 (1.13, 1.23) for fracture to 7.56 (6.93, 8.25) for stroke]. From the population perspective, 20.23% of poor global SRH and 45.12% of worse age-comparative SRH could attributed to the cardiometabolic diseases, with hypertension (7.84% for poor global SRH and 13.79% for worse age-comparative SRH), diabetes (4.35% for poor global SRH and 10.71% for worse age-comparative SRH), coronary heart disease (4.44% for poor global SRH and 9.51% for worse age-comparative SRH) and stroke (3.20% for poor global SRH and 10.19% for worse age-comparative SRH) making the largest contribution. CONCLUSIONS: Various diseases were major determinants of global and age-comparative SRH, and cardiometabolic diseases had the strongest impact on both global SRH and age-comparative SRH at the population level. Prevention measures concentrated on these conditions would greatly reduce the total burden of poor SRH and its consequences such as poor quality of life and use of health care services.
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