World Health Organization. Depressive disorder (depression) [Internet]. 2023 [cited 2024 Aug 16]. Available from: https://www.who.int/en/news-room/fact-sheets/detail/depression
Rahman MS, Rahman MA, Ali M, Rahman MS, Md M. Determinants of depressive symptoms among older people in Bangladesh. J Affect Disord. 2020;264:157–62.
Google Scholar
Lu Y. Intervention effect and mechanism of digital acceptance and commitment therapy on anxiety and depression symptoms in nurses. [shandong,China]: shandong university; 2023.
Loss K, Fandino W, Almarie B, Bazan-Perkins B, Minetto J, Aranis N, et al. The impact of education level and socioeconomic status on the association between depressive symptoms and memory in an older population in Latin America: an exploratory analysis from the Brazilian longitudinal study of aging (ELSI-BRAZIL). Dialogues in Health. 2024;5:100183.
Google Scholar
Xu X, Mishra GD, Jones M. Depressive symptoms and the development and progression of physical multimorbidity in a national cohort of Australian women. Health Psychol. 2019;38:812–21.
Google Scholar
Cui L. Factors affecting the evolution of Chinese elderly depression: a cross-sectional study. BMC Geriatr. 2022;22:109.
Google Scholar
Zhang Y, Xiong Y, Yu Q, Shen S, Chen L, Lei X. The activity of daily living (ADL) subgroups and health impairment among Chinese elderly: a latent profile analysis. BMC Geriatr. 2021;21:30.
Google Scholar
Heckerman D. Bayesian networks for data mining. Data Min Knowl Discov. 1997;1:79–119.
Topuz K, Davazdahemami B, Delen D. A Bayesian belief network-based analytics methodology for early-stage risk detection of novel diseases. Ann Oper Res [Internet]. 2023 [cited 2024 Apr 3]; Available from: IF: 4.5 Q1 B4
Arora P, Boyne D, Slater JJ, Gupta A, Brenner DR, Druzdzel MJ. Bayesian networks for risk prediction using real-world data: a tool for precision medicine. Value Health. 2019;22:439–45.
Google Scholar
Da Cunha Leme DE. The use of Bayesian network models to identify factors related to frailty phenotype and health outcomes in middle-aged and older persons. Arch Gerontol Geriatr. 2021;92:104212.
Google Scholar
Chen B, Jin F. Spatial distribution, regional differences, and dynamic evolution of the medical and health services supply in China. Front Public Health. 2022;10:1020402.
Google Scholar
Liu Q, Li B, Mohiuddin M. Prediction and decomposition of efficiency differences in Chinese provincial community health services. IJERPH. 2018;15:2265.
Google Scholar
Wang X. Regional catastrophic health expenditure and health inequality in China. Front Public Health. 2023;11:1193945.
Google Scholar
Zhao Y, Hu Y, Smith JP, Strauss J, Yang G. Cohort profile: the China health and retirement longitudinal study (CHARLS). Int J Epidemiol. 2014;43:61–8.
Google Scholar
Gong W, Lin H, Ma X, Ma H, Lan Y, Sun P, et al. The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China health and retirement longitudinal study. BMC Public Health. 2024;24:1123.
Google Scholar
National Health Commission of China. 2022 China Health Statistics Yearbook. Beijing: Peking Union Medical College Publication; 2022.
Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D. Am J Prev Med. 1994;10:77–84.
Google Scholar
Huang Q, Wang X, Chen G. Reliability and validity of 10 item CESD among middle aged and older adults in China. China J Health Psychol. 2015;23:1036–41.
Cheng S, Chan ACM. The center for epidemiologic studies depression scale in older Chinese: thresholds for long and short forms. Int J Geriatr Psychiatry. 2005;20:465–70.
Google Scholar
Wang Z, Bai Z, Otsen B, Zhang P, Yu M, Chen R, et al. Urban-rural disparities in depressive symptoms and related factors among offspring of advanced maternal mothers: a national cross-sectional study in China. J Affect Disord. 2024;351:103–10.
Google Scholar
Wang J, Luo N, Sun Y, Bai R, Li X, Liu L, et al. Exploring the reciprocal relationship between activities of daily living disability and depressive symptoms among middle-aged and older Chinese people: a four-wave, cross-lagged model. BMC Public Health. 2023;23:1180.
Google Scholar
Li J, Ma W. Prevalence and influencing factors of depression symptom among middle-aged and elderly people in China. Chin J Public Health. 2017;33:177–81.
Tao H, Zhang X, Wang Z. The eastern-middle-western depression and the determinants among Chinese rural elderly. Chin J Dis Control Prev. 2018;22:696–9.
Liu Y, Jiang J, Jing H. Regional differences in disability and its influencing factors among Middle-aged and elderly people in East, central and West major regions in China. Chin Gen Pract. 2024;27:877–92.
Cheng Y, Chen Z, Wei Y, Gu N, Tang S. Examining dynamic developmental trends: the interrelationship between age-friendly environments and healthy aging in the Chinese population—evidence from China health and retirement longitudinal study, 2011–2018. BMC Geriatr. 2024;24:429.
Google Scholar
National Bureau of Statistics. Gross Regional Product (in RMB 100 million) [Internet]. 2023 [cited 2024 Jun 20]. Available from: https://data.stats.gov.cn/adv.htm?m=advquery&cn=E0103
Qiu L, Song G, Liu M, Jiang C, Sun X. The characteristics of the distribution of healthcare resources in primary healthcare institutions between provinces in China. Chin Gen Pract. 2024;27:3911–1918.
Zhang X, Han H, Chen Y, Li X, Luo G. A study on the characteristics and influencing factors of hospital Spatial distribution in China. J Zhejiang Univ (Science Edition). 2021;48:84–9299.
Ai Z, Tang C, Peng P, Wen X, Tang S. Prevalence and influencing factors of chronic pain in middle-aged and older adults in China: results of a nationally representative survey. Front Public Health. 2023;11:1110216.
Google Scholar
Honda H, Ashizawa R, Kiriyama K, Take K, Hirase T, Arizono S, et al. Chronic pain in the frail elderly mediates sleep disorders and influences falls. Arch Gerontol Geriatr. 2022;99:104582.
Google Scholar
Jiang R, Geha P, Rosenblatt M, Wang Y, Fu Z, Foster M, et al. The inflammatory and genetic mechanisms underlying the cumulative effect of co-occurring pain conditions on depression. Sci Adv. 2025. https://doi.org/10.1126/sciadv.adt1083.
Google Scholar
Hu X, Liu H, Liu Q, Yuan T, Duan M, Luo Y et al. Depressive symptoms and their influencing factors among older adults in China: a cross-sectional study. Front Public Health [Internet]. 2024 [cited 2025 Jul 14];12. Available from: https://www.frontiersin.org/articles/https://doi.org/10.3389/fpubh.2024.1423391/full
Sahril N, Chan YM, Chan YY, Ahmad NA, Kassim MSA, Shahein NA, et al. Poor self-rated health and associated factors among older persons in malaysia: a population-based study. IJERPH. 2023;20:4342.
Google Scholar
Zhang H, Yan Z. Study on the validity of the self-rated health indicators of the elderly population in China. Chin J Health Policy. 2022;15:58–65.
Jang J, Jung H-S, Chae K, Lee K-U. Trajectories of self-rated health among community-dwelling individuals with depressive symptoms: a latent class growth analysis. J Affect Disord. 2023;332:83–91.
Google Scholar
Pan Y, Pikhartova J, Bobak M, Pikhart H. Reliability and predictive validity of two scales of self-rated health in China: results from China health and retirement longitudinal study (CHARLS). BMC Public Health. 2022;22:1863.
Google Scholar
Rong J, Zhang N, Wang Y, Cheng P, Zhao D. Development and validation of a nomogram to predict the depressive symptoms among older adults: a national survey in China. J Affect Disord. 2024;361:367–75.
Google Scholar
Xu H, Yang Q, Chen T. Provincial distribution differences and influencing factors of self-assessed health among elderly population in China. J Environ Occup Med. 2024;41:193–9.
Ahmad NA, Abd Razak MA, Kassim MS, Sahril N, Ahmad FH, Harith AA, et al. Association between functional limitations and depression among community-dwelling older adults in Malaysia. Geriatr Gerontol Int. 2020;20(S2):21–5.
Google Scholar
Sim H-S, Lee S-G, Kim T-H. Physical functioning, depressive symptoms, and suicidal ideation among older Korean adults. IJERPH. 2021;18(16):8781.
Google Scholar
Takele MD, Eriku GA, Merawie DM, Zinabu FS, Fentanew M, Belay GJ, et al. Functional disability and its associated factors among community- dweller older adults living in Gondar Town, ethiopia: a community-based cross-sectional study. BMC Public Health. 2024;24:647.
Google Scholar
Wang W, Liu Y, Ji D, Xie K, Yang Y, Zhu X, et al. The association between functional disability and depressive symptoms among older adults: findings from the China health and retirement longitudinal study (CHARLS). J Affect Disord. 2024;351:518–26.
Google Scholar
Zhao L, Wang J, Deng H, Chen J, Ding D. Depressive symptoms and ADL/IADL disabilities among older adults from low-income families in Dalian, Liaoning. CIA. 2022;17:733–43.
Jafari-Koulaee A, Mohammadi E, Fox MT, Rasekhi A, Akha O. Predictors of basic and instrumental activities of daily living among older adults with multiple chronic conditions. BMC Geriatr. 2024;24:383.
Google Scholar
Song S, Seo Y, Hwang S, Kim H-Y, Kim J. Digital phenotyping of geriatric depression using a community-based digital mental health monitoring platform for socially vulnerable older adults and their community caregivers: 6-week living lab single-arm pilot study. JMIR Mhealth Uhealth. 2024;12:e55842.
Google Scholar
Lin Z, Zheng J, Wang Y, Su Z, Zhu R, Liu R, et al. Prediction of the efficacy of group cognitive behavioral therapy using heart rate variability based smart wearable devices: a randomized controlled study. BMC Psychiatry. 2024. https://doi.org/10.1186/s12888-024-05638-x.
Google Scholar
Fotteler ML, Kocar TD, Dallmeier D, Kohn B, Mayer S, Waibel A-K, et al. Use and benefit of information, communication, and assistive technology among community-dwelling older adults – a cross-sectional study. BMC Public Health. 2023;23:2004.
Google Scholar
Oudin A, Maatoug R, Bourla A, Ferreri F, Millet B, Schoeller F, et al. Digital phenotyping: data-driven psychiatry to redefine mental health. J Med Internet Res. 2023;25:e44502.
Google Scholar
link