{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T16:59:50Z","timestamp":1793465990719,"version":"4.5.0"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T00:00:00Z","timestamp":1753833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Multimorbidity is increasingly prevalent among older adults and poses significant challenges to public health systems. While previous studies have highlighted the role of individual behaviors, the complex interaction between lifestyle factors and socioeconomic status (SES) in multimorbidity remains unclear.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Using nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we developed predictive models to identify key determinants of multimorbidity among individuals aged \u226560\u202fyears. A total of 34,755 participants were included, and 17 features related to demographics, SES, and lifestyle were selected via LASSO regression. Eight machine learning algorithms including logistic regression, decision tree, naive Bayes, neural network, support vector machine, random forest, XGBoost and Bayesian Ridge Regression were applied to build predictive models. Model performance was evaluated using AUC, accuracy, precision, recall, F1-score, RMSE, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) were used to interpret model outputs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>XGBoost achieved the best predictive performance (AUC\u202f=\u202f0.788 on the test set), outperforming both linear and non-linear models across most evaluation metrics. SHAP analysis revealed that education level, activities of daily living (ADL), work status, self-assessed health status, and per capita income were the top factors associated with of multimorbidity. Subgroup analyses showed variated associations by age and sex, with psychological and geographic factors playing a larger role among those aged \u226580.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study demonstrated the feasibility and interpretability of using machine learning to model complex risk patterns of multimorbidity. Socioeconomic and functional variables were dominant factors associated with multimorbidity, suggesting structural roots of health inequality. These findings offered empirical and theoretical support for early risk stratification and targeted public health interventions aimed at mitigating multimorbidity in aging populations.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1586091","type":"journal-article","created":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T05:28:11Z","timestamp":1753853291000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey"],"prefix":"10.3389","volume":"13","author":[{"given":"Wei","family":"Gong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huimin","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxin","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianjun","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,30]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"100903","DOI":"10.1016\/j.arr.2019.04.005","article-title":"Multimorbidity and quality of life: systematic literature review and meta-analysis","volume":"53","author":"Makovski","year":"2019","journal-title":"Ageing Res Rev"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.hjc.2017.01.022","article-title":"Socioeconomic status and risk factors for cardiovascular disease: impact of dietary mediators","volume":"58","author":"Psaltopoulou","year":"2017","journal-title":"Hell J Cardiol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"2235042x19870934","DOI":"10.1177\/2235042X19870934","article-title":"Prevalence of multimorbidity in community settings: a systematic review and meta-analysis of observational studies","volume":"9","author":"Nguyen","year":"2019","journal-title":"J Comorb"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1186\/s12920-019-0629-x","article-title":"Analysis of disease comorbidity patterns in a large-scale China population","volume":"12","author":"Guo","year":"2019","journal-title":"BMC Med Genet"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1038\/s41572-022-00376-4","article-title":"Multimorbidity","volume":"8","author":"Skou","year":"2022","journal-title":"Nat Rev Dis Primers"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1038\/s41591-023-02420-6","article-title":"Biological and functional multimorbidity\u2014from mechanisms to management","volume":"29","author":"Langenberg","year":"2023","journal-title":"Nat Med"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/S0140-6736(11)61878-3","article-title":"Urbanisation and health in China","volume":"379","author":"Gong","year":"2012","journal-title":"Lancet"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"eadw3443","DOI":"10.1126\/science.adw3443","article-title":"China\u2019s urbanization at a turning point\u2014challenges and opportunities","volume":"388","author":"Bai","year":"2025","journal-title":"Science"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1659","DOI":"10.1016\/j.mayocp.2015.08.002","article-title":"Chronic disease prevalence and healthy lifestyle behaviors among US health care professionals","volume":"90","author":"Dayoub","year":"2015","journal-title":"Mayo Clin Proc"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"113263","DOI":"10.1016\/j.socscimed.2020.113263","article-title":"Lifestyle behaviors, psychological distress, and well-being: a daily diary study","volume":"263","author":"Anderson","year":"2020","journal-title":"Soc Sci Med"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"e0236242","DOI":"10.1371\/journal.pone.0236242","article-title":"Lifestyle patterns and their nutritional, socio-demographic and psychological determinants in a community-based study: a mixed approach of latent class and factor analyses","volume":"15","author":"Vajdi","year":"2020","journal-title":"PLoS One"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.3389\/fpsyg.2020.01303","article-title":"Socioeconomic status and psychological well-being: revisiting the role of subjective socioeconomic status","volume":"11","author":"Navarro-Carrillo","year":"2020","journal-title":"Front Psychol"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"116618","DOI":"10.1016\/j.socscimed.2024.116618","article-title":"The impact of socioeconomic status on health practices via health lifestyles: results of qualitative interviews with Americans from diverse socioeconomic backgrounds","volume":"344","author":"McCoy","year":"2024","journal-title":"Soc Sci Med"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.1038\/s41371-023-00842-w","article-title":"Urban-rural differences in hypertension prevalence, blood pressure control, and systolic blood pressure levels","volume":"37","author":"Heindl","year":"2023","journal-title":"J Hum Hypertens"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1161\/HYPERTENSIONAHA.123.21354","article-title":"Social determinants of health and disparities in hypertension and cardiovascular diseases","volume":"81","author":"Chaturvedi","year":"2024","journal-title":"Hypertension"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.sleep.2023.01.002","article-title":"Predicting depressive symptoms in middle-aged and elderly adults using sleep data and clinical health markers: a machine learning approach","volume":"102","author":"Gomes","year":"2023","journal-title":"Sleep Med"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"497","DOI":"10.2147\/IMCRJ.S322827","article-title":"Machine learning in an elderly man with heart failure","volume":"14","author":"Koops","year":"2021","journal-title":"Int Med Case Rep J"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3390\/jpm10020021","article-title":"Applications of machine learning predictive models in the chronic disease diagnosis","volume":"10","author":"Battineni","year":"2020","journal-title":"J Pers Med"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"1772","DOI":"10.1016\/j.cell.2023.01.035","article-title":"From patterns to patients: advances in clinical machine learning for cancer diagnosis, prognosis, and treatment","volume":"186","author":"Swanson","year":"2023","journal-title":"Cell"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nat Mach Intell"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1007\/s42835-022-01161-9","article-title":"Shap value-based feature importance analysis for short-term load forecasting","volume":"18","author":"Lee","year":"2023","journal-title":"J Electr Eng Technol"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"104813","DOI":"10.1016\/j.compbiomed.2021.104813","article-title":"Interpretable prediction of 3-year all-cause mortality in patients with heart failure caused by coronary heart disease based on machine learning and SHAP","volume":"137","author":"Wang","year":"2021","journal-title":"Comput Biol Med"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1186\/s12911-023-02238-9","article-title":"XGBoost-SHAP-based interpretable diagnostic framework for Alzheimer's disease","volume":"23","author":"Yi","year":"2023","journal-title":"BMC Med Inform Decis Mak"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1093\/ije\/dys203","article-title":"Cohort profile: the China health and retirement longitudinal study (CHARLS)","volume":"43","author":"Zhao","year":"2014","journal-title":"Int J Epidemiol"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"102268","DOI":"10.1016\/j.is.2023.102268","article-title":"A review on missing values for main challenges and methods","volume":"119","author":"Ren","year":"2023","journal-title":"Inf Syst"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"e210184","DOI":"10.1001\/jamanetworkopen.2021.0184","article-title":"Assessing missing data assumptions in EHR-based studies: a complex and underappreciated task","volume":"4","author":"Haneuse","year":"2021","journal-title":"JAMA Netw Open"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"113624","DOI":"10.1016\/j.dss.2021.113624","article-title":"Regression imputation optimizing sample size and emulation: demonstrations and comparisons to prominent methods","volume":"151","author":"Templeton","year":"2021","journal-title":"Decis Support Syst"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"9","DOI":"10.3978\/j.issn.2305-5839.2015.12.38","article-title":"Missing data imputation: focusing on single imputation","volume":"4","author":"Zhang","year":"2016","journal-title":"Ann Transl Med"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1002\/mpr.329","article-title":"Multiple imputation by chained equations: what is it and how does it work?","volume":"20","author":"Azur","year":"2011","journal-title":"Int J Methods Psychiatr Res"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1016\/j.wneu.2021.10.090","article-title":"Proper use of multiple imputation and dealing with missing covariate data","volume":"161","author":"Saffari","year":"2022","journal-title":"World Neurosurg"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1186\/s12874-022-01560-6","article-title":"Applications of Bayesian shrinkage prior models in clinical research with categorical responses","volume":"22","author":"Bhattacharyya","year":"2022","journal-title":"BMC Med Res Methodol"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"103502","DOI":"10.1016\/j.artint.2021.103502","article-title":"Explaining individual predictions when features are dependent: more accurate approximations to Shapley values","volume":"298","author":"Aas","year":"2021","journal-title":"Artif Intell"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"2166","DOI":"10.1161\/CIRCULATIONAHA.117.029652","article-title":"Socioeconomic status and cardiovascular outcomes: challenges and interventions","volume":"137","author":"Schultz","year":"2018","journal-title":"Circulation"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"e128","DOI":"10.1016\/S2468-2667(20)30001-3","article-title":"Emerging trends and future research on the role of socioeconomic status in chronic illness and multimorbidity","volume":"5","author":"Mair","year":"2020","journal-title":"Lancet Public Health"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1161\/CIRCRESAHA.121.319811","article-title":"Social determinants of cardiovascular disease","volume":"130","author":"Powell-Wiley","year":"2022","journal-title":"Circ Res"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1016\/j.geosus.2023.08.001","article-title":"Spatial pattern of urban-rural integration in China and the impact of geography","volume":"4","author":"Pan","year":"2023","journal-title":"Geogr Sustain"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"100809","DOI":"10.1016\/j.lanwpc.2023.100809","article-title":"Trends in major non-communicable diseases and related risk factors in China 2002\u20132019: an analysis of nationally representative survey data","author":"Peng","year":"2023","journal-title":"Lancet Regional Health Western Pacific"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.jamda.2022.10.002","article-title":"Chronic disease in China: geographic and socioeconomic determinants among persons aged 60 and older","volume":"24","author":"Su","year":"2023","journal-title":"J Am Med Dir Assoc"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1001\/jamacardio.2023.3990","article-title":"Educational attainment and lifetime risk of cardiovascular disease","volume":"9","author":"Magnani","year":"2024","journal-title":"JAMA Cardiol"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"571","DOI":"10.2174\/1567205013666161201200209","article-title":"Is educational attainment associated with increased risk of mortality in people with dementia? A population-based study","volume":"14","author":"Contador","year":"2017","journal-title":"Curr Alzheimer Res"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"e0321267","DOI":"10.1371\/journal.pone.0321267","article-title":"Comorbidities and health-related quality of life among rural older community-dwellers in Vietnam","volume":"20","author":"Vu","year":"2025","journal-title":"PLoS One"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1186\/s12877-025-05777-0","article-title":"Associated factors of frailty among community-dwelling older adults with multimorbidity from a health ecological perspective: a cross-sectional study","volume":"25","author":"Che","year":"2025","journal-title":"BMC Geriatr"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1177\/17423953211023964","article-title":"Multimorbidity groups based on numbers of chronic conditions are associated with daily activity","volume":"18","author":"Klinedinst","year":"2022","journal-title":"Chronic Illn"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"5257","DOI":"10.1007\/s11135-023-01724-6","article-title":"Self-assessment of health: how socioeconomic, functional, and emotional dimensions influence self-rated health among Italian nonagenarians","volume":"58","author":"Strozza","year":"2024","journal-title":"Qual Quant"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"281","DOI":"10.3390\/ijerph16020281","article-title":"Effects of socioeconomic status on physical and psychological health: lifestyle as a mediator","volume":"16","author":"Wang","year":"2019","journal-title":"Int J Environ Res Public Health"},{"key":"ref46","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1016\/j.pec.2019.11.028","article-title":"Tools to measure health literacy among Chinese speakers: a systematic review","volume":"103","author":"Zhang","year":"2020","journal-title":"Patient Educ Couns"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"e989","DOI":"10.1016\/S2468-2667(22)00207-9","article-title":"Challenges in screening and general health checks in China","volume":"7","author":"Gong","year":"2022","journal-title":"Lancet Public Health"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"318","DOI":"10.3389\/fpubh.2019.00318","article-title":"Socioeconomic inequalities in older adults' health: the roles of neighborhood and individual-level psychosocial and behavioral resources","volume":"7","author":"Zhang","year":"2019","journal-title":"Front Public Health"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s12939-016-0496-4","article-title":"Determinants of and socio-economic disparities in self-rated health in China","volume":"16","author":"Cai","year":"2017","journal-title":"Int J Equity Health"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"6249","DOI":"10.3390\/ijerph20136249","article-title":"A review of the relationship between socioeconomic status change and health","volume":"20","author":"Barakat","year":"2023","journal-title":"Int J Environ Res Public Health"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1186\/1475-9276-11-78","article-title":"Longitudinal changes in functional capacity: effects of socio-economic position among ageing adults","volume":"11","author":"Sulander","year":"2012","journal-title":"Int J Equity Health"},{"key":"ref52","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1007\/s10597-023-01088-z","article-title":"Associations between primary residence and mental health in global marginalized populations","volume":"59","author":"Knutson","year":"2023","journal-title":"Community Ment Health J"},{"key":"ref53","doi-asserted-by":"publisher","first-page":"102401","DOI":"10.1016\/j.healthplace.2020.102401","article-title":"When does geography matter most? Age-specific geographical effects in the patterning of, and relationship between, mental wellbeing and mental illness","volume":"64","author":"Griffith","year":"2020","journal-title":"Health Place"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"1329885","DOI":"10.3389\/fpubh.2023.1329885","article-title":"Impact of lifestyle and psychological resilience on survival among the oldest-old in China: a cohort study","volume":"11","author":"Cai","year":"2023","journal-title":"Front Public Health"},{"key":"ref55","doi-asserted-by":"publisher","first-page":"e6031","DOI":"10.1002\/gps.6031","article-title":"Determinants of psychosocial factors among the oldest old \u2013 evidence from the representative \"survey on quality of life and subjective well-being of the very old in North Rhine-Westphalia (NRW80+)\"","volume":"38","author":"Hajek","year":"2023","journal-title":"Int J Geriatr Psychiatry"},{"key":"ref56","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1186\/s12889-015-1900-5","article-title":"The correlates of chronic disease-related health literacy and its components among men: a systematic review","volume":"15","author":"Davey","year":"2015","journal-title":"BMC Public Health"},{"key":"ref57","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1186\/s12905-023-02319-x","article-title":"Chronic conditions in women: the development of a National Institutes of health framework","volume":"23","author":"Temkin","year":"2023","journal-title":"BMC Womens Health"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1093\/annweh\/wxad063","article-title":"Gender aspects in occupational exposure and health studies","volume":"67","author":"Schl\u00fcnssen","year":"2023","journal-title":"Ann Work Expo Health"},{"key":"ref59","doi-asserted-by":"publisher","first-page":"e282","DOI":"10.1016\/S2468-2667(24)00053-7","article-title":"Differences across the lifespan between females and males in the top 20 causes of disease burden globally: a systematic analysis of the global burden of disease study 2021","volume":"9","author":"Patwardhan","year":"2024","journal-title":"Lancet Public Health"},{"key":"ref60","doi-asserted-by":"publisher","first-page":"110072","DOI":"10.1016\/j.ejrad.2021.110072","article-title":"MRI-based radiomics model for distinguishing endometrial carcinoma from benign mimics: a multicenter study","volume":"146","author":"Chen","year":"2022","journal-title":"Eur J Radiol"},{"key":"ref61","doi-asserted-by":"publisher","first-page":"368504211031749","DOI":"10.1177\/00368504211031749","article-title":"HMGCS2 in metabolic pathways was associated with overall survival in hepatocellular carcinoma: a LASSO-derived study","volume":"104","author":"Ding","year":"2021","journal-title":"Sci Prog"},{"key":"ref62","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1007\/s00357-019-09345-1","article-title":"ROC and AUC with a binary predictor: a potentially misleading metric","volume":"37","author":"Muschelli","year":"2020","journal-title":"J Classif"},{"key":"ref63","doi-asserted-by":"publisher","first-page":"6263","DOI":"10.1038\/s41598-023-33525-0","article-title":"Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP","volume":"13","author":"Raihan","year":"2023","journal-title":"Sci Rep"},{"key":"ref64","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.shpsa.2023.12.007","article-title":"ML interpretability: Simple isn\u2019t easy","volume":"103","author":"R\u00e4z","year":"2024","journal-title":"Stud Hist Philos Sci"}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2025.1586091\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T05:28:13Z","timestamp":1753853293000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2025.1586091\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,30]]},"references-count":64,"alternative-id":["10.3389\/fpubh.2025.1586091"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2025.1586091","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,30]]},"article-number":"1586091"}}