Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Jun 15;18(1):744.
doi: 10.1186/s12889-018-5632-1.

Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study

Xingyue Song  1 , Jing Wu  1 , Canqing Yu  2 , Wenhong Dong  1 , Jun Lv  2 , Yu Guo  3 , Zheng Bian  3 , Ling Yang  4 , Yiping Chen  4 , Zhengming Chen  4 , An Pan  5 , Liming Li  6   7 ; China Kadoorie Biobank Collaborative Group
Collaborators, Affiliations

Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study

Xingyue Song et al. BMC Public Health. .

Abstract

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.

Keywords: Chinese population; Comorbidity; Cross-sectional study; Self-rated health status.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

The study got approval from the ethical review committees of the Chinese Center for Disease Control and Prevention (Beijing, China) and the Oxford Tropical Research Ethics Committee, University of Oxford (UK). Written informed consent forms were obtained from all participants.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Verropoulou G. Specific versus general self-reported health indicators predicting mortality among older adults in Europe: disparities by gender employing SHARE longitudinal data. Int J Public Health. 2014;59(4):665–678. doi: 10.1007/s00038-014-0563-9. - DOI - PubMed
    1. DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P. Mortality prediction with a single general self-rated health question. A meta-analysis. J Gen Intern Med. 2006;21(3):267–275. doi: 10.1111/j.1525-1497.2005.00291.x. - DOI - PMC - PubMed
    1. Vuorisalmi M, Lintonen T, Jylha M. Comparative vs global self-rated health: associations with age and functional ability. Aging Clin Exp Res. 2006;18(3):211–217. doi: 10.1007/BF03324651. - DOI - PubMed
    1. Eriksson I, Unden AL, Elofsson S. Self-rated health. Comparisons between three different measures. Results from a population study. Int J Epidemiol. 2001;30(2):326–333. doi: 10.1093/ije/30.2.326. - DOI - PubMed
    1. de Bruin A, Picavet HS, Nossikov A. Health interview surveys. Towards international harmonization of methods and instruments. WHO Reg Publ Eur Ser. 1996;58(i-xiii):1–161. - PubMed

LinkOut - more resources