Search Advanced

AIMS Public Health

2025, Volume 12, Issue 4: 1005-1025. doi: 10.3934/publichealth.2025050
Previous Article Next Article
Research article Special Issues

Associations between modifiable risk factors and limitation in activities of daily living among individuals aged ≥ 45 years: Evidence from the China health and retirement longitudinal study (CHARLS)

  • 1.
    School of Traditional Chinese Medicine, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, 330004, China
  • 2.
    Department of Clinical Laboratory, Heping Branch, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, China
  • 3.
    Department of Anesthesiology, Xi'an Eighth Hospital, Xi'an, Shaanxi, 710061, China
  • 4.
    School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, 030001, China
  • 5.
    Department of Geriatrics, Zhongshan Hospital of Traditional Chinese Medicine, Zhongshan, Guangdong, 528401, China
  • 6.
    School of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing 100084, China
  • 7.
    Department of Public Health, Zigong Fourth People's Hospital, Zigong, Sichuan, 643000, China
  • These authors contributed equally to this work.
  • Published: 13 October 2025
  • Background 

    With aging populations, a growing number of older people are subjected to limitations in activities of daily living (ADL), causing a tremendous burden and challenges to patients' quality of life and policymakers. Investigating modifiable risk factors for ADL remains an important project to help lower its risk. This study aimed to explore associations between the modifiable risk factors and ADL using national-scale data from the China Health and Retirement Longitudinal Study (CHARLS).

    Methods 

    Data were downloaded from CHARLS 2020, a population-based longitudinal survey. We included modifiable risk variables and ADL index, i.e., basic ADL (BALD) and instrumental ADL (IADL). Afterward, variables were included in the logistic regression model construction. Also, propensity score matching (PSM) was employed to validate the findings. Finally, we tried to discuss the associations between different age groups.

    Results 

    A total of 12,248 participants were included in this study, comprising 5799 women (47.35%) and 6449 men (52.65%). The median age was 62 (55–69) years. Among the participants, 2055 (16.78%) had limitations in BADL, and 1838 (15.01%) had limitations in IADL. Logistic regression demonstrated that exercise significantly reduced the risk of BADL and IADL impairment (BADL: OR = 0.70, 95% CI: 0.59–0.83; IADL: OR = 0.65, 95% CI: 0.55–0.78; P < 0.001). Similarly, better cognitive ability was associated with a lower risk of impairment (BADL: OR = 0.68, 95% CI: 0.61–0.75; IADL: OR = 0.60, 95% CI: 0.54–0.67; P < 0.001). Adequate sleep duration (6–8 hours) also significantly reduced the likelihood of functional decline (BADL: OR = 0.49, 95% CI: 0.45–0.55; IADL: OR = 0.48, 95% CI: 0.43–0.53; P < 0.001). In contrast, depression symptoms and chronic diseases significantly increased the risk of both BADL and IADL impairment. Besides, PSM showed similar findings, and the risk of ADL increased with age.

    Conclusions 

    Modifiable risk factors, such as exercise, cognitive ability, depression symptoms, chronic diseases, social activities, and sleeping duration, were significantly associated with ADL. Besides, as age increases, the impact of various modifiable risk factors on ADL becomes more evident, emphasizing special care for older populations and offering scientific ideas for policymakers.

    Citation: Yaheng Li, Jian Gao, Wenzhu Song, Xiaolin Liang, Xinhao He, Fuliang Yi, Wenhao Song, Dongliang Yin. Associations between modifiable risk factors and limitation in activities of daily living among individuals aged ≥ 45 years: Evidence from the China health and retirement longitudinal study (CHARLS)[J]. AIMS Public Health, 2025, 12(4): 1005-1025. doi: 10.3934/publichealth.2025050

    Related Papers:

  • Background 

    With aging populations, a growing number of older people are subjected to limitations in activities of daily living (ADL), causing a tremendous burden and challenges to patients' quality of life and policymakers. Investigating modifiable risk factors for ADL remains an important project to help lower its risk. This study aimed to explore associations between the modifiable risk factors and ADL using national-scale data from the China Health and Retirement Longitudinal Study (CHARLS).

    Methods 

    Data were downloaded from CHARLS 2020, a population-based longitudinal survey. We included modifiable risk variables and ADL index, i.e., basic ADL (BALD) and instrumental ADL (IADL). Afterward, variables were included in the logistic regression model construction. Also, propensity score matching (PSM) was employed to validate the findings. Finally, we tried to discuss the associations between different age groups.

    Results 

    A total of 12,248 participants were included in this study, comprising 5799 women (47.35%) and 6449 men (52.65%). The median age was 62 (55–69) years. Among the participants, 2055 (16.78%) had limitations in BADL, and 1838 (15.01%) had limitations in IADL. Logistic regression demonstrated that exercise significantly reduced the risk of BADL and IADL impairment (BADL: OR = 0.70, 95% CI: 0.59–0.83; IADL: OR = 0.65, 95% CI: 0.55–0.78; P < 0.001). Similarly, better cognitive ability was associated with a lower risk of impairment (BADL: OR = 0.68, 95% CI: 0.61–0.75; IADL: OR = 0.60, 95% CI: 0.54–0.67; P < 0.001). Adequate sleep duration (6–8 hours) also significantly reduced the likelihood of functional decline (BADL: OR = 0.49, 95% CI: 0.45–0.55; IADL: OR = 0.48, 95% CI: 0.43–0.53; P < 0.001). In contrast, depression symptoms and chronic diseases significantly increased the risk of both BADL and IADL impairment. Besides, PSM showed similar findings, and the risk of ADL increased with age.

    Conclusions 

    Modifiable risk factors, such as exercise, cognitive ability, depression symptoms, chronic diseases, social activities, and sleeping duration, were significantly associated with ADL. Besides, as age increases, the impact of various modifiable risk factors on ADL becomes more evident, emphasizing special care for older populations and offering scientific ideas for policymakers.



    加载中

    Acknowledgments


    We are grateful to all the authors for their preparation for this manuscript. This study was supported by Shanxi Province Youth Science Research Project (No. 202203021212078) and The National Natural Science Foundation of China (No. 82360973).

    Authors' contributions


    Yaheng Li and Jian Gao drafted the manuscript. Wenzhu Song and Xiaolin Liang performed data analysis and polished the manuscript. Xinhao He, Fuliang Yi and Wenhao Song provided valuable advice on statistical methods. Dongliang Yin was responsible for the conception and design of the research. All authors contributed to the article and approved the final version of the manuscript.

    Conflict of interest


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

    [1] Fang EF, Scheibye-Knudsen M, Jahn HJ, et al. (2015) A research agenda for aging in China in the 21st century. Ageing Res Rev 24: 197-205. https://doi.org/10.1016/j.arr.2015.08.003
    [2] Brivio P, Paladini MS, Racagni G, et al. (2019) From healthy aging to frailty: In search of the underlying mechanisms. Curr Med Chem 26: 3685-701. https://doi.org/10.2174/0929867326666190717152739
    [3] Treacy D, Hassett L, Schurr K, et al. (2022) Mobility training for increasing mobility and functioning in older people with frailty. Cochrane Db Syst Rev 6: Cd010494. https://doi.org/10.1002/14651858.CD010494.pub2
    [4] Liu C, Liao Y, Zhu Z, et al. (2021) The association between serum copper concentrations and elevated blood pressure in US children and adolescents: National health and nutrition examination survey 2011–2016. BMC Cardiovasc Disor 21: 57. https://doi.org/10.1186/s12872-021-01880-3
    [5] Guo Q, Sun Y, Fan M, et al. (2023) What is the degree of social disability risk in China under the background of the aging population? Social disability risk measurement index system design and evaluation research based on China. Frontiers Public Health 11: 1087276. https://doi.org/10.3389/fpubh.2023.1087276
    [6] Zheng PP, Guo ZL, Du XJ, et al. (2022) Prevalence of disability among the Chinese older population: A systematic review and meta-analysis. J Environ Res Public Health 19: 1656. https://doi.org/10.3390/ijerph19031656
    [7] Luo Y, Su B, Zheng X (2021) Trends and challenges for population and health during population aging - China, 2015–2050. China CDC Weekly 3: 593-598. https://doi.org/10.46234/ccdcw2021.158
    [8] Baumgart M, Snyder HM, Carrillo MC, et al. (2015) Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective. Alzheimers Dement 11: 718-726. https://doi.org/10.1016/j.jalz.2015.05.016
    [9] Johnston JN, Henter ID, Zarate CA (2023) The antidepressant actions of ketamine and its enantiomers. Pharmacol Ther 246: 108431. https://doi.org/10.1016/j.pharmthera.2023.108431
    [10] Wang Z, Ni X, Gao D, et al. (2023) The relationship between sleep duration and activities of daily living (ADL) disability in the Chinese oldest-old: A cross-sectional study. PeerJ 11: e14856. https://doi.org/10.7717/peerj.14856
    [11] Alexandre TDS, Scholes S, Santos JLF, et al. (2019) Dynapenic abdominal obesity as a risk factor for worse trajectories of ADL disability among older adults: The ELSA cohort study. J Gerontol A Biol Sci Med Sci 74: 1112-1118. https://doi.org/10.1093/gerona/gly182
    [12] Covinsky KE, Cenzer IS, Yaffe K, et al. (2014) Dysphoria and anhedonia as risk factors for disability or death in older persons: Implications for the assessment of geriatric depression. Am J Geriatr Psychiatry 22: 606-613. https://doi.org/10.1016/j.jagp.2012.12.001
    [13] Gong J, Wang G, Wang Y, et al. (2022) Nowcasting and forecasting the care needs of the older population in China: Analysis of data from the China Health and Retirement Longitudinal Study (CHARLS). Lancet Public Health 7: e1005-e1013. https://doi.org/10.1016/S2468-2667(22)00203-1
    [14] Deng Y, Zhang K, Zhu J, et al. (2023) Healthy aging, early screening, and interventions for frailty in the elderly. Biosci Trends 17: 252-261. https://doi.org/10.5582/bst.2023.01204
    [15] Zhao Y, Hu Y, Smith JP, et al. (2014) Cohort profile: The China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol 43: 61-68. https://doi.org/10.1093/ije/dys203
    [16] Song J, Wu X, Zhang Y, et al. (2023) Association between changes in depressive symptoms and falls: The China health and retirement longitudinal study (CHARLS). J Affect Disord 341: 393-400. https://doi.org/10.1016/j.jad.2023.09.004
    [17] Lei X, Liu H (2018) Gender difference in the impact of retirement on cognitive abilities: Evidence from urban China. Eur J Comp Econ 46: 1425-1446. https://doi.org/10.1016/j.jce.2018.01.005
    [18] Zhang Y, Xiong Y, Yu Q, et al. (2021) The activity of daily living (ADL) subgroups and health impairment among Chinese elderly: A latent profile analysis. BMC Geriatr 21: 30. https://doi.org/10.1186/s12877-020-01986-x
    [19] Zhang Z, Kim HJ, Lonjon G, et al. (2019) Balance diagnostics after propensity score matching. Ann Transl Med 7: 16. https://doi.org/10.21037/atm.2018.12.10
    [20] Ervasti J, Airaksinen J, Pentti J, et al. (2019) Does increasing physical activity reduce the excess risk of work disability among overweight individuals?. Scand J Work Environ Health 45: 376-385. https://doi.org/10.5271/sjweh.3799
    [21] Heiland EG, Welmer AK, Wang R, et al. (2019) Cardiovascular risk factors and the risk of disability in older adults: Variation by age and functional status. J Am Med Dir Assoc 20: 208-212.e3. https://doi.org/10.1016/j.jamda.2018.05.013
    [22] Farsijani S, Payette H, Morais JA, et al. (2017) Even mealtime distribution of protein intake is associated with greater muscle strength, but not with 3-y physical function decline, in free-living older adults: The Quebec longitudinal study on Nutrition as a Determinant of Successful Aging (NuAge study). Am J Clin Nutr 106: 113-124. https://doi.org/10.3945/ajcn.116.146555
    [23] Rosoff DB, Davey Smith G, Mehta N, et al. (2020) Evaluating the relationship between alcohol consumption, tobacco use, and cardiovascular disease: A multivariable Mendelian randomization study. PLoS Med 17: e1003410. https://doi.org/10.1371/journal.pmed.1003410
    [24] Jeon KH, Han K, Jeong SM, et al. (2023) Changes in alcohol consumption and risk of dementia in a nationwide cohort in South Korea. JAMA Netw Open 6: e2254771. https://doi.org/10.1001/jamanetworkopen.2022.54771
    [25] Lee YH, Lu P, Chang YC, et al. (2021) Associations of alcohol consumption status with activities of daily living among older adults in China. J Ethn Subst Abuse 20: 428-443. https://doi.org/10.1080/15332640.2019.1664961
    [26] Chang FK, Lin HT, Chang JH, et al. (2024) Changes in combined lifestyle risks and the transition of activities of daily living in the elderly population of Taiwan: Evidence from the Taiwan longitudinal study on aging. Nutrients 16: 1499. https://doi.org/10.3390/nu16101499
    [27] Takashima N, Miura K, Hozawa A, et al. (2010) Cigarette smoking in middle age and a long-term risk of impaired activities of daily living: NIPPON DATA80. Nicotine Tob Res 12: 944-949. https://doi.org/10.1093/ntr/ntq121
    [28] Makino K, Lee S, Bae S, et al. (2020) Relationship between instrumental activities of daily living performance and incidence of mild cognitive impairment among older adults: A 48-month follow-up study. Arch Gerontol Geriatr 88: 104034. https://doi.org/10.1016/j.archger.2020.104034
    [29] Voinescu A, Papaioannou T, Petrini K, et al. (2024) Exergaming for dementia and mild cognitive impairment. Cochrane Database Syst Rev 9: Cd013853. https://doi.org/10.1002/14651858.CD013853.pub2
    [30] Kashif M, Ahmad A, Bandpei MAM, et al. (2022) Combined effects of virtual reality techniques and motor imagery on balance, motor function and activities of daily living in patients with Parkinson's disease: A randomized controlled trial. BMC Geriatr 22: 381. https://doi.org/10.1186/s12877-022-03035-1
    [31] Chen X, Giles J, Yao Y, et al. (2022) The path to healthy ageing in China: A Peking University-Lancet Commission. Lancet 400: 1967-2006. https://doi.org/10.1016/S0140-6736(22)01546-X
    [32] Wei ZS, Chen YS, Wu Y, et al. (2022) Limitations in activities of daily living increase the risk of stroke in older Chinese adults: A population-based longitudinal study. Neural Regen Res 17: 643-648. https://doi.org/10.4103/1673-5374.320994
    [33] He M, Ma J, Ren Z, et al. (2019) Association between activities of daily living disability and depression symptoms of middle-aged and older Chinese adults and their spouses: A community based study. J Affect Disord 242: 135-142. https://doi.org/10.1016/j.jad.2018.08.060
    [34] Yan Y, Du Y, Li X, et al. (2023) Physical function, ADL, and depressive symptoms in Chinese elderly: Evidence from the CHARLS. Front Public Health 11: 1017689. https://doi.org/10.3389/fpubh.2023.1017689
    [35] Sieber S, Roquet A, Lampraki C, et al. (2023) Multimorbidity and quality of life: The mediating role of ADL, IADL, loneliness, and depressive symptoms. Innov Aging 7: igad047. https://doi.org/10.1093/geroni/igad047
    [36] Huang QM, Xie JH, Chen H, et al. (2024) Association of insomnia symptoms and trajectories with the risk of functional disability: A prospective cohort study. BMC Geriatr 24: 492. https://doi.org/10.1186/s12877-024-05108-9
    [37] Luo M, Dong Y, Fan B, et al. (2024) Sleep duration and functional disability among Chinese older adults: Cross-sectional study. JMIR Aging 7: e53548. https://doi.org/10.2196/53548
    [38] den Ouden ME, Schuurmans MJ, Mueller-Schotte S, et al. (2013) Identification of high-risk individuals for the development of disability in activities of daily living. A ten-year follow-up study. Exp Gerontol 48: 437-443. https://doi.org/10.1016/j.exger.2013.02.002
  • Reader Comments
  • © 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
AIMS Public Health
2.7 5.3

Metrics

Article views(848) PDF downloads(62) Cited by(0)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Tables(7)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog