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Cohort profile: Beijing Healthy Aging Cohort Study (BHACS)

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Abstract

The Beijing Healthy Aging Cohort Study (BHACS) was established to supplement the limited data of a large representative cohort of older people based on the general population and was designed to evaluate the prevalence, incidence, and natural history of cognitive decline, functional disability, and conventional vascular risk factors. The aim was to determine the evolution of these conditions by estimating the rates and determinants of progression and regression to adverse outcomes, including dementia, cardiovascular events, cancer, and all-cause death. It can therefore provide evidence to help policy makers develop better policies to promote healthy aging in China. BHACS consisted of three cohorts (BLSA, CCHS-Beijing, and BECHCS) in Beijing with a total population of 11 235 (6281 in urban and 4954 in rural areas) and an age range of 55 years or older (55–101 years) with a mean age of 70.35 ± 7.71 years (70.69 ± 7.62 years in urban and 69.92 ± 7.80 years in rural areas). BHACS-BLSA conducted the baseline survey in 2009 with a multistage stratification-random clustering procedure for people aged 55 years or older; BHACS-CCHS-Beijing conducted the baseline survey in 2013–2015 with a stratified multistage cluster random sampling method for people aged 55 years or older; and BHACS-BECHCS conducted the baseline survey in 2010–2014 with two-stage cluster random sampling method for people aged 60 years or older. Data were collected through questionnaires, physical measurements, and laboratory analyses. Topics covered by BHACS include a wide range of physical and mental health indicators, lifestyles and personal, family, and socio-economic determinants of health. There are no immediate plans to make the cohort data freely available to the public, but specific proposals for further collaboration are welcome. For further information and collaboration, please contact the corresponding author Yao He (e-mail: yhe301@x263.net).

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References

  1. Department of Economic and Social Affairs. The aging of population and its economic and social implications. United Nations; 1956. https://unog.primo.exlibrisgroup.com/permalink/41UNOG_INST/146850g/alma991001553369602391. Accessed 18 Oct 2022.

  2. Department of Economic and Social Affairs. World Population prospects 2022: Summary of results. United Nations; 2022. https://doi.org/10.18356/9789210014380. Accessed 18 Oct 2022.

  3. China Statistics Press. China Statistical Yearbook 2021. National Bureau of Statistics of China. 2022. http://www.stats.gov.cn/sj/ndsj/2021/indexch.htm. Accessed 22 Oct 2022.

  4. Jiang Q, Feng Q, Editorial. Aging and health in China. Front Public Health. 2022;10:998769. https://doi.org/10.3389/fpubh.2022.998769.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Department of Ageing Health, National Aging Development Bulletin. National Health Commission of the People’s Republic of China. 2020; 2021. Accessed 22 Oct 2022. http://www.nhc.gov.cn/lljks/pqt/202110/c794a6b1a2084964a7ef45f69bef5423.shtml.

  6. Fang EF, Xie C, Schenkel JA, et al. A research agenda for ageing in China in the 21st century (2nd edition): focusing on basic and translational research, long-term care, policy and social networks. Ageing Res Rev. 2020;64:101174. https://doi.org/10.1016/j.arr.2020.101174.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Zhang G, Yu C, Zhou M, Wang L, Zhang Y, Luo L. Burden of ischaemic heart disease and attributable risk factors in China from 1990 to 2015: findings from the global burden of disease 2015 study. BMC Cardiovasc Disord. 2018;18(1):18. https://doi.org/10.1186/s12872-018-0761-0.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell. 2013;153(6):1194–217. https://doi.org/10.1016/j.cell.2013.05.039.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wang W, Liu Y, Liu J, et al. Mortality and years of life lost of cardiovascular diseases in China, 2005–2020: empirical evidence from national mortality surveillance system. Int J Cardiol. 2021;340:105–12. https://doi.org/10.1016/j.ijcard.2021.08.034.

    Article  PubMed  Google Scholar 

  10. Lautrup S, Sinclair DA, Mattson MP, Fang EF. NAD(+) in Brain Aging and Neurodegenerative Disorders. Cell Metab. 2019;30(4):630–55. https://doi.org/10.1016/j.cmet.2019.09.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Prince MJ, Wu F, Guo Y, et al. The burden of disease in older people and implications for health policy and practice. The Lancet. 2015;385(9967):549–62. https://doi.org/10.1016/s0140-6736(14)61347-7.

    Article  Google Scholar 

  12. Cheng X, Yang Y, Schwebel DC, et al. Population ageing and mortality during 1990–2017: a global decomposition analysis. PLoS Med. 2020;17(6):e1003138. https://doi.org/10.1371/journal.pmed.1003138.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pilleron S, Sarfati D, Janssen-Heijnen M, et al. Global cancer incidence in older adults, 2012 and 2035: a population-based study. Int J Cancer. 2019;144(1):49–58. https://doi.org/10.1002/ijc.31664.

    Article  CAS  PubMed  Google Scholar 

  14. Xu J, Wang J, Wimo A, Fratiglioni L, Qiu C. The economic burden of dementia in China, 1990–2030: implications for health policy. Bull World Health Organ. 2017;95(1):18–26. https://doi.org/10.2471/BLT.15.167726.

    Article  PubMed  Google Scholar 

  15. GBD 2019 Dementia Forecasting Collaborators. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the global burden of Disease Study 2019. The Lancet Public Health. 2022;7(2):e105–e25. https://doi.org/10.1016/s2468-2667(21)00249-8.

    Article  Google Scholar 

  16. Dovjak P. Polypharmacy in elderly people. Wien Med Wochenschr. 2022;172(5–6):109–13. https://doi.org/10.1007/s10354-021-00903-0.

    Article  PubMed  Google Scholar 

  17. de Lima JD, Teixeira IA, Silva FO, Deslandes AC. The comorbidity conditions and polypharmacy in elderly patients with mental illness in a middle income country: a cross-sectional study. IBRO Rep. 2020;9:96–101. https://doi.org/10.1016/j.ibror.2020.07.008.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Park M, Reynolds CF. Depression among older adults with diabetes Mellitus. Clin Geriatr Med. 2015;31(1):117–37. https://doi.org/10.1016/j.cger.2014.08.022.

    Article  PubMed  Google Scholar 

  19. Gorska-Ciebiada M, Saryusz-Wolska M, Ciebiada M, Loba J. Mild cognitive impairment and depressive symptoms in elderly patients with diabetes: prevalence, risk factors, and comorbidity. J Diabetes Res. 2014;2014:179648. https://doi.org/10.1155/2014/179648.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Fan ZY, Yang Y, Zhang CH, Yin RY, Tang L, Zhang F. Prevalence and patterns of Comorbidity among Middle-Aged and Elderly People in China: a cross-sectional study based on CHARLS Data. Int J Gen Med. 2021;14:1449–55. https://doi.org/10.2147/IJGM.S309783.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf. 2014;13(1):57–65. https://doi.org/10.1517/14740338.2013.827660.

    Article  PubMed  Google Scholar 

  22. Komiya H, Umegaki H, Asai A, et al. Factors associated with polypharmacy in elderly home-care patients. Geriatr Gerontol Int. 2018;18(1):33–41. https://doi.org/10.1111/ggi.13132.

    Article  PubMed  Google Scholar 

  23. Enlund. JJ, Korhonen H, MJ, Sulkava. R, Hartikainen S. Patterns of drug use and factors associated with polypharmacy and excessive polypharmacy in elderly persons: results of the Kuopio 75 study: a cross-sectional analysis. Drugs Aging. 2009;26(6):493–503.

    Article  PubMed  Google Scholar 

  24. Tao L, Qu X, Gao H, Zhai J, Zhang Y, Song Y. Polypharmacy and potentially inappropriate medications among elderly patients in the geriatric department at a single-center in China: a retrospective cross-sectional study. Med (Baltim). 2021;100(42):e27494. https://doi.org/10.1097/MD.0000000000027494.

    Article  Google Scholar 

  25. Roderka MN, Puri S, Batsis JA. Addressing obesity to promote healthy aging. Clin Geriatr Med. 2020;36(4):631–43. https://doi.org/10.1016/j.cger.2020.06.006.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Himes CL, Reynolds SL. Effect of obesity on falls, injury, and disability. J Am Geriatr Soc. 2012;60(1):124–9. https://doi.org/10.1111/j.1532-5415.2011.03767.x.

    Article  PubMed  Google Scholar 

  27. Kritchevsky SB, Beavers KM, Miller ME, et al. Intentional weight loss and all-cause mortality: a meta-analysis of randomized clinical trials. PLoS ONE. 2015;10(3):e0121993. https://doi.org/10.1371/journal.pone.0121993.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: a systematic review and meta-analysis. JAMA. 2013;309(1):71–82. https://doi.org/10.1001/jama.2012.113905.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Martinez-Tapia C, Diot T, Oubaya N et al. The obesity paradox for mid- and long-term mortality in older cancer patients: a prospective multicenter cohort study. Am J Clin Nutr. 2020;nqaa238.

  30. Bijani A, Cumming RG, Hosseini SR, et al. Obesity paradox on the survival of elderly patients with diabetes: an AHAP-based study. J Diabetes Metab Disord. 2018;17(1):45–51. https://doi.org/10.1007/s40200-018-0337-7.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Keating N. A research framework for the United Nations Decade of healthy ageing (2021–2030). Eur J Ageing. 2022;19(3):775–87. https://doi.org/10.1007/s10433-021-00679-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Rudnicka E, Napierala P, Podfigurna A, Meczekalski B, Smolarczyk R, Grymowicz M. The World Health Organization (WHO) approach to healthy ageing. Maturitas. 2020;139:6–11. https://doi.org/10.1016/j.maturitas.2020.05.018.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Global Report. World report on Ageing and Health. World Health Organization. 2015. https://www.who.int/publications/i/item/9789241565042. Accessed 26 Sep 2022.

  34. Hu D, Yan W, Zhu J, Zhu Y, Chen J. Age-related Disease Burden in China, 1997–2017: findings from the global burden of Disease Study. Front Public Health. 2021;9:638704. https://doi.org/10.3389/fpubh.2021.638704.

    Article  PubMed  PubMed Central  Google Scholar 

  35. World Health Assembly 50. The World health report 1997: conquering suffering, enriching humanity: summary. World Health Organization. 1997. https://apps.who.int/iris/handle/10665/179593. Accessed 26 Sep 2022.

  36. Nie P, Li Y, Zhang N, Sun X, Xin B, Wang Y. The change and correlates of healthy ageing among chinese older adults: findings from the China health and retirement longitudinal study. BMC Geriatr. 2021;21(1):78. https://doi.org/10.1186/s12877-021-02026-y.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zhang Q, Wu Y, Han T, Liu E. Changes in cognitive function and risk factors for cognitive impairment of the Elderly in China: 2005–2014. Int J Environ Res Public Health. 2019;16(16):2847. https://doi.org/10.3390/ijerph16162847.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Yang Y, Meng Y. Is China moving toward healthy aging? A Tracking Study based on 5 phases of CLHLS Data. Int J Environ Res Public Health. 2020;17(12):4343. https://doi.org/10.3390/ijerph17124343.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zhang T, Liu C, Lu B, Wang X. Changes of inequality in functional disability of older populations in China from 2008 to 2018: a decomposition analysis. BMC Geriatr. 2022;22(1):308. https://doi.org/10.1186/s12877-022-02987-8.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Zhou YF, Song XY, Wu J, et al. Association between dietary patterns in midlife and healthy ageing in chinese adults: the Singapore Chinese Health Study. J Am Med Dir Assoc. 2021;22(6):1279–86. https://doi.org/10.1016/j.jamda.2020.09.045.

    Article  PubMed  Google Scholar 

  41. Guo Y, Ge T, Mei L, Wang L, Li J. Widowhood and Health Status among Chinese older adults: the Mediation Effects of different types of support. Front Public Health. 2021;9:745073. https://doi.org/10.3389/fpubh.2021.745073.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Jiang J, Tang Z, Futatsuka M. The impact of ADL disability on depression symptoms in a community of Beijing elderly, China. Environ Health Prev Med. 2002;7(5):199–204. https://doi.org/10.1007/BF02898005.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Tang Z, Wang HX, Meng C, et al. The prevalence of functional disability in activities of daily living and instrumental activities of daily living among elderly Beijing Chinese. Arch Gerontol Geriatr. 1999;29(2):115–25. https://doi.org/10.1016/s0167-4943(99)00026-6.

    Article  CAS  PubMed  Google Scholar 

  44. Fang X, Wang Z, Wang C, et al. Cardiovascular and Cognitive Health Study in Middle-Aged and Elderly residents of Beijing(CCHS-Beijing): design and rationale. Neuroepidemiology. 2016;46(3):182–90. https://doi.org/10.1159/000443707.

    Article  PubMed  Google Scholar 

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Acknowledgements

All authors thank the Beijing Longitudinal Study of Aging team, the Cardiovascular and Cognitive Health Study in Middle-Aged and Elderly Residents of Beijing team, and the Beijing Elderly Comprehensive Health Cohort Study team for providing data and sharing the use of the data sets in the Beijing Healthy Aging Cohort Study. We thank all volunteers and staff involved in this research.

Funding

This work was supported by the National Natural Science Foundation of China (82173589, 82173590); Capital’s Funds for Health Improvement and Research (2022-2G-5031); National Key Research and Development Program of China (2022YFC2503605); the National Key Program in the Twelfth Five-year Plan (Grant No. 2011BAI 11 B01) from the Chinese Ministry of Science and Technology; Commission of Science and Technology of Beijing (Grant No. D121100004912002); and Beijing Municipal Science & Technology Commission (Z171100001017019).

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Authors and Affiliations

Authors

Contributions

All authors contributed to the study’s conception and design. Xianghua Fang, Yao He, Zhe Tang, and Miao Liu designed the Study. Yao He, Miao Liu, Chunxiu Wang, Shanshan Yang, Jianhua Wang, Chengbei Hou, Shengshu Wang, Xiaoying Li, and Hongbing Yang directed the study’s implementation. Junhan Yang, Haowei Li, Shaohua Liu, Yang Song, Shimin Chen, Shimin Hu, Xuehang Li, Zhiqiang Li, Rongrong Li, Huaihao Li, Yinghui Bao, and Yueting Shi designed the analytical strategy and helped to interpret the findings. Junhan Yang, Huaihao Li, Yinghui Bao, and Yueting Shi helped to write the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yao He.

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The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

BHACS was performed in line with the principles of the Declaration of Helsinki, approved by the Ethics Committee of Chinese PLA General Hospital (S2022-412-02), and registered by the China Clinical Trial Registry (ChiCTR2200066177).

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Liu, M., Yang, J., Wang, C. et al. Cohort profile: Beijing Healthy Aging Cohort Study (BHACS). Eur J Epidemiol 39, 101–110 (2024). https://doi.org/10.1007/s10654-023-01050-z

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