{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T23:40:47Z","timestamp":1793144447294,"version":"4.5.0"},"reference-count":73,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T00:00:00Z","timestamp":1754870400000},"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>Objective<\/jats:title><jats:p>To develop and validate an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A total of 471 older adults with multimorbidity were recruited between October and November 2024. We employed six machine learning (ML) methods, namely logistic regression (LR), neural network (NN), support vector machine (SVM), gradient boosting machine (GBM), K-Nearest Neighbors (KNN), and light gradient boosting machine (LightGBM), to predict the risk of sleep disorders based on their sociodemographic data, health behavior factors, mental health, and disease-related data. The optimal model was identified through the evaluation of the area under the curve (AUC). This study also employed explainable machine learning techniques to provide insights into the model\u2019s predictions and outcomes using the SHAP (Shapley Additive Explanations) approach.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The prevalence of sleep disorders was 28.7%. Among the six models developed, the GBM model achieved the best performance with an AUC of 0.881. The analysis of feature importance revealed that the top seven predictors of sleep disorders were frailty, cognitive status, nutritional status, living alone, depression, smoking status, and anxiety.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study is the first to predict sleep disorders in Chinese older adults with multimorbidity using explainable machine learning methods and to identify seven significant risk factors. The SHAP method enhances the interpretability of machine learning models and helps medical staff better understand the rationale behind the predicted outcomes more effectively.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1619406","type":"journal-article","created":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T04:10:39Z","timestamp":1754885439000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Development and validation of an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity: a cross-sectional study"],"prefix":"10.3389","volume":"13","author":[{"given":"Xia","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liu","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujie","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ru","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e1003138","DOI":"10.1371\/journal.pmed.1003138","article-title":"Population ageing and mortality during 1990-2017: A global decomposition analysis","volume":"17","author":"Cheng","year":"2020","journal-title":"PLoS Med"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"526","DOI":"10.3390\/ijerph16040526","article-title":"The relationship between socioeconomic status, mental health, and need for long-term services and supports among the Chinese elderly in Shandong province-a cross-sectional study","volume":"16","author":"Kong","year":"2019","journal-title":"Int J Environ Res Public Health"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1038\/s43587-024-00772-3","article-title":"A global analysis of adaptation to societal aging across low-, middle- and high-income countries using the Global Aging Society Index","volume":"5","author":"Chen","year":"2025","journal-title":"Nat Aging"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.arr.2017.05.003","article-title":"Evidence on multimorbidity from definition to intervention: An overview of systematic reviews","volume":"37","author":"Xu","year":"2017","journal-title":"Ageing Res Rev"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"e13562","DOI":"10.1111\/acel.13562","article-title":"Different responses to DNA damage determine ageing differences between organs","volume":"21","author":"Vougioukalaki","year":"2022","journal-title":"Aging Cell"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1093\/ageing\/afy169","article-title":"Sarcopenia: revised European consensus on definition and diagnosis","volume":"48","author":"Cruz-Jentoft","year":"2019","journal-title":"Age Ageing"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"101860","DOI":"10.1016\/j.eclinm.2023.101860","article-title":"Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis","volume":"57","author":"Chowdhury","year":"2023","journal-title":"EClinicalMedicine"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1081518","DOI":"10.3389\/fpubh.2023.1081518","article-title":"Social determinants of multimorbidity patterns: A systematic review","volume":"11","author":"\u00c1lvarez-G\u00e1lvez","year":"2023","journal-title":"Front Public Health"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"479","DOI":"10.5664\/jcsm.6506","article-title":"Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American academy of sleep medicine clinical practice guideline","volume":"13","author":"Kapur","year":"2017","journal-title":"J Clin Sleep Med"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1097\/cm9.0000000000001769","article-title":"CX3C-chemokine receptor 1 modulates cognitive dysfunction induced by sleep deprivation","volume":"135","author":"Xin","year":"2021","journal-title":"Chin Med J"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"728278","DOI":"10.3389\/fpsyt.2021.728278","article-title":"What factors are most closely associated with mood disorders in adolescents during the COVID-19 pandemic? A cross-sectional study based on 1,771 adolescents in Shandong Province, China","volume":"12","author":"Ren","year":"2021","journal-title":"Front Psych"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1514524","DOI":"10.3389\/fpubh.2025.1514524","article-title":"Correlation between sleep and multimorbidity in community-dwelling older adults in Hunan Province: a cross-sectional study","volume":"13","author":"Su","year":"2025","journal-title":"Front Public Health"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.maturitas.2022.01.007","article-title":"Association between physical multimorbidity and sleep problems in 46 low- and middle-income countries","volume":"160","author":"Smith","year":"2022","journal-title":"Maturitas"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.smrv.2015.01.003","article-title":"Risk factors for sleep disturbances in older adults: Evidence from prospective studies","volume":"25","author":"Smagula","year":"2016","journal-title":"Sleep Med Rev"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1007\/s11325-025-03267-6","article-title":"The prevalence and risk factors of sleep disturbances in community-dwelling older adults: a systematic review and meta-analysis","volume":"29","author":"Fu","year":"2025","journal-title":"Sleep Breath"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.sleep.2017.01.016","article-title":"Relationship between sleep disturbances and multimorbidity among community-dwelling men and women aged 65-93 years: results from the KORA Age Study","volume":"33","author":"Helbig","year":"2017","journal-title":"Sleep Med"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"e1004109","DOI":"10.1371\/journal.pmed.1004109","article-title":"Association of sleep duration at age 50, 60, and 70 years with risk of multimorbidity in the UK: 25-year follow-up of the Whitehall II cohort study","volume":"19","author":"Sabia","year":"2022","journal-title":"PLoS Med"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.sleep.2020.05.004","article-title":"Prediction of sleep-disordered breathing after stroke","volume":"75","author":"Brown","year":"2020","journal-title":"Sleep Med"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.sleep.2020.11.022","article-title":"Sleep apnea prediction in acute ischemic stroke (SLAPS score): a derivation study","volume":"77","author":"\u0160iarnik","year":"2021","journal-title":"Sleep Med"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"732","DOI":"10.5498\/wjp.v13.i10.732","article-title":"Sleep disturbances are associated with anxiety, depression, and decreased quality of life in patients with coronary heart disease","volume":"13","author":"Zheng","year":"2023","journal-title":"World J Psychiatry"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"e37712","DOI":"10.1097\/md.0000000000037712","article-title":"Evaluation of risk factors related to sleep disorders in patients undergoing hemodialysis using a nomogram model","volume":"103","author":"Liu","year":"2024","journal-title":"Medicine (Baltimore)"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"100041","DOI":"10.1016\/j.sleepe.2022.100041","article-title":"Modeling and feature assessment of the sleep quality among chronic kidney disease patients","volume":"2","author":"Matharaarachchi","year":"2022","journal-title":"Sleep Epidemiol"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1186\/s12877-024-05456-6","article-title":"Construction and verification of the prediction model for risk of sleep disturbance in elderly patients with hypertension: a cross-sectional survey based on NHANES database from 2005 to 2018","volume":"24","author":"Zhang","year":"2024","journal-title":"BMC Geriatr"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"I615","DOI":"10.1093\/eurjpc\/zwae175.413","article-title":"Association between frailty and heart failure incident after acute coronary syndrome","volume":"31","author":"Ueno","year":"2024","journal-title":"Eur J Prev Cardiol"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1186\/s12905-024-03222-9","article-title":"Development and validation of a nomogram model of depression and sleep disorders and the risk of disease progression in patients with breast cancer","volume":"24","author":"Shen","year":"2024","journal-title":"BMC Womens Health"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1080\/02770903.2020.1742352","article-title":"Deep learning approaches for sleep disorder prediction in an asthma cohort","volume":"58","author":"Phan","year":"2021","journal-title":"J Asthma"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"1511874","DOI":"10.3389\/fmed.2025.1511874","article-title":"Development and validation of a predictive model for acute exacerbation in chronic obstructive pulmonary disease patients with comorbid insomnia","volume":"12","author":"Gao","year":"2025","journal-title":"Front Med"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"S574","DOI":"10.21037\/jtd.2019.01.25","article-title":"Developing prediction models for clinical use using logistic regression: an overview","volume":"11","author":"Shipe","year":"2019","journal-title":"J Thorac Dis"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/j.ijrobp.2021.08.007","article-title":"Logistic Regression in Clinical Studies","volume":"112","author":"Zabor","year":"2022","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1186\/s12884-025-07197-9","article-title":"Construction and validation of a predictive model for sleep disorders among pregnant women","volume":"25","author":"Yang","year":"2025","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.jpsychores.2008.01.012","article-title":"On the nature of burnout-insomnia relationships: a prospective study of employed adults","volume":"65","author":"Armon","year":"2008","journal-title":"J Psychosom Res"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1093\/jjco\/hyab169","article-title":"Comorbid insomnia among breast cancer survivors and its prediction using machine learning: a nationwide study in Japan","volume":"52","author":"Ueno","year":"2022","journal-title":"Jpn J Clin Oncol"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"e00656-19","DOI":"10.1128\/mSystems.00656-19","article-title":"Predicting phenotypic polymyxin resistance in Klebsiella pneumoniae through machine learning analysis of genomic data","volume":"5","author":"Macesic","year":"2020","journal-title":"mSystems"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"e13389","DOI":"10.1111\/ijcp.13389","article-title":"Machine learning to predict cardiovascular risk","volume":"73","author":"Quesada","year":"2019","journal-title":"Int J Clin Pract"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1186\/s12931-021-01690-3","article-title":"Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation","volume":"22","author":"Chen","year":"2021","journal-title":"Respir Res"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"319","DOI":"10.3389\/fmed.2019.00319","article-title":"Machine learning increases diagnosticity in psychometric evaluation of alexithymia in fibromyalgia","volume":"6","author":"Orr\u00f9","year":"2019","journal-title":"Front Med (Lausanne)"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"e125","DOI":"10.2196\/mhealth.6562","article-title":"Sleep Quality Prediction From Wearable Data Using Deep Learning","volume":"4","author":"Sathyanarayana","year":"2016","journal-title":"JMIR Mhealth Uhealth"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"107555","DOI":"10.1016\/j.compbiomed.2023.107555","article-title":"The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review","volume":"166","author":"Ali","year":"2023","journal-title":"Comput Biol Med"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"q902","DOI":"10.1136\/bmj.q902","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","year":"2024","journal-title":"BMJ"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/0165-1781(89)90047-4","article-title":"The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research","volume":"28","author":"Buysse","year":"1989","journal-title":"Psychiatry Res"},{"key":"ref41","first-page":"67","article-title":"Structural and construct validity of the Czech version of the Pittsburgh Sleep Quality Index in chronic insomnia","volume":"38","author":"Dudysov\u00e1","year":"2017","journal-title":"Neuro Endocrinol Lett"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1016\/s0022-3999(02)00330-6","article-title":"Test-retest reliability and validity of the Pittsburgh Sleep Quality Index in primary insomnia","volume":"53","author":"Backhaus","year":"2002","journal-title":"J Psychosom Res"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/bf02982161","article-title":"The I.A.N.A Task Force on frailty assessment of older people in clinical practice","volume":"12","author":"Abellan Van Kan","year":"2008","journal-title":"J Nutr Health Aging"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1007\/s12603-012-0084-2","article-title":"A simple frailty questionnaire (FRAIL) predicts outcomes in middle aged African Americans","volume":"16","author":"Morley","year":"2012","journal-title":"J Nutr Health Aging"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","article-title":"\"Mini-mental state\". A practical method for grading the cognitive state of patients for the clinician","volume":"12","author":"Folstein","year":"1975","journal-title":"J Psychiatr Res"},{"key":"ref46","first-page":"709","article-title":"Geriatric Depression Scale","volume":"24","author":"Yesavage","year":"1988","journal-title":"Psychopharmacol Bull"},{"key":"ref47","first-page":"98","article-title":"Theoretical basis and research application of social support rating scale","volume":"4","author":"Xiao","year":"1994","journal-title":"J Clin Psychiatry"},{"key":"ref48","article-title":"Mini Nutritional Assessment: a practical assessment tool for grading the nutritional state of elderly patients","author":"Guigoz","year":"1997"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1093\/geront\/9.3_Part_1.179","article-title":"Assessment of older people: self-maintaining and instrumental activities of daily living","volume":"9","author":"Lawton","year":"1969","journal-title":"Gerontologist"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"d40","DOI":"10.1136\/bmj.d40","article-title":"Strategy for intention to treat analysis in randomised trials with missing outcome data","volume":"342","author":"White","year":"2011","journal-title":"BMJ"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1002\/(sici)1097-0258(19970228)16:4<385::aid-sim380>3.0.co;2-3","article-title":"The lasso method for variable selection in the Cox model","volume":"16","author":"Tibshirani","year":"1997","journal-title":"Stat Med"},{"key":"ref52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v036.i11","article-title":"Feature selection with the Boruta package","volume":"36","author":"Kursa","year":"2010","journal-title":"J Stat Softw"},{"key":"ref53","doi-asserted-by":"publisher","first-page":"e0183518","DOI":"10.1371\/journal.pone.0183518","article-title":"Robust Adaptive Lasso method for parameter's estimation and variable selection in high-dimensional sparse models","volume":"12","author":"Wahid","year":"2017","journal-title":"PLoS One"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.eswa.2019.05.028","article-title":"A Comparison of Random Forest Variable Selection Methods for Classification Prediction Modeling","volume":"134","author":"Speiser","year":"2019","journal-title":"Expert Syst Appl"},{"key":"ref55","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J Artif Intell Res"},{"key":"ref56","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"Delong","year":"1988","journal-title":"Biometrics"},{"key":"ref57","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.sleep.2023.07.002","article-title":"The relationship between sleep health and multimorbidity in community dwelling populations: Systematic review and global perspectives","volume":"109","author":"Nistor","year":"2023","journal-title":"Sleep Med"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"591","DOI":"10.5664\/jcsm.6550","article-title":"Insomnia and Multimorbidity in the Community Elderly in China","volume":"13","author":"Wang","year":"2017","journal-title":"J Clin Sleep Med"},{"key":"ref59","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.mayocp.2020.06.012","article-title":"Polypharmacy Management in Older Patients","volume":"96","author":"Hoel","year":"2021","journal-title":"Mayo Clin Proc"},{"key":"ref60","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1093\/ageing\/afw200","article-title":"Health professional perspectives on the management of multimorbidity and polypharmacy for older patients in Australia","volume":"46","author":"Mc Namara","year":"2017","journal-title":"Age Ageing"},{"key":"ref61","doi-asserted-by":"publisher","first-page":"e0245475","DOI":"10.1371\/journal.pone.0245475","article-title":"Identifying causative mechanisms linking early-life stress to psycho-cardio-metabolic multi-morbidity: the EarlyCause project","volume":"16","author":"Mariani","year":"2021","journal-title":"PLoS One"},{"key":"ref62","doi-asserted-by":"publisher","first-page":"e0191651","DOI":"10.1371\/journal.pone.0191651","article-title":"Physical multimorbidity and loneliness: A population-based study","volume":"13","author":"Stickley","year":"2018","journal-title":"PLoS One"},{"key":"ref63","doi-asserted-by":"publisher","first-page":"5364","DOI":"10.1109\/jbhi.2022.3197910","article-title":"Gradient boosting machine and efficient combination of features for speech-based detection of COVID-19","volume":"26","author":"Dash","year":"2022","journal-title":"IEEE J Biomed Health Inform"},{"key":"ref64","doi-asserted-by":"publisher","first-page":"e46520","DOI":"10.2196\/46520","article-title":"Predicting the risk of sleep disorders using a machine learning-based simple questionnaire: development and validation study","volume":"25","author":"Ha","year":"2023","journal-title":"J Med Internet Res"},{"key":"ref65","doi-asserted-by":"publisher","first-page":"2930","DOI":"10.1016\/j.procs.2022.09.351","article-title":"Explainable machine learning for sleep apnea prediction","volume":"207","author":"Troncoso-Garc\u00eda","year":"2022","journal-title":"Proc Comput Sci"},{"key":"ref66","doi-asserted-by":"publisher","first-page":"1187","DOI":"10.1007\/s11325-020-02061-w","article-title":"Sleep and frailty risk: a systematic review and meta-analysis","volume":"24","author":"Pourmotabbed","year":"2020","journal-title":"Sleep Breath"},{"key":"ref67","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.jsmc.2022.02.003","article-title":"Circadian rhythm sleep-wake disorders in older adults","volume":"17","author":"Kim","year":"2022","journal-title":"Sleep Med Clin"},{"key":"ref68","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/3142874","article-title":"The effects of dietary nutrition on sleep and sleep disorders","volume":"2020","author":"Zhao","year":"2020","journal-title":"Mediat Inflamm"},{"key":"ref69","doi-asserted-by":"publisher","first-page":"811082","DOI":"10.3389\/fpsyg.2022.811082","article-title":"Depression, anxiety, insomnia, and quality of life in a representative community sample of older adults living at home","volume":"13","author":"Kennair","year":"2022","journal-title":"Front Psychol"},{"key":"ref70","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.mce.2011.06.042","article-title":"Circadian rhythms in the hypothalamo-pituitary-adrenal (HPA) axis","volume":"349","author":"Kalsbeek","year":"2012","journal-title":"Mol Cell Endocrinol"},{"key":"ref71","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1186\/s12877-020-01935-8","article-title":"The impact of interventions on management of frailty in hospitalized frail older adults: a systematic review and meta-analysis","volume":"20","author":"Rezaei-Shahsavarloo","year":"2020","journal-title":"BMC Geriatr"},{"key":"ref72","doi-asserted-by":"publisher","first-page":"S13","DOI":"10.1007\/s40279-014-0147-0","article-title":"Sleep in elite athletes and nutritional interventions to enhance sleep","author":"Halson","year":"2014","journal-title":"Sports Med"},{"key":"ref73","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.maturitas.2019.06.007","article-title":"Non-pharmacological treatments for sleep disturbance in mild cognitive impairment and dementia: a systematic review and meta-analysis","volume":"127","author":"O'caoimh","year":"2019","journal-title":"Maturitas"}],"updated-by":[{"DOI":"10.3389\/fpubh.2025.1684776","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T00:00:00Z","timestamp":1756425600000}}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2025.1619406\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T15:39:48Z","timestamp":1756481988000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2025.1619406\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,11]]},"references-count":73,"alternative-id":["10.3389\/fpubh.2025.1619406"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2025.1619406","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,11]]},"article-number":"1619406"}}