{"doi":"10.1093/sleep/zsad048","title":"Multi-dimensional sleep and mortality: The Multi-Ethnic Study of Atherosclerosis","abstract":"STUDY OBJECTIVES: Multiple sleep characteristics are informative of health, sleep characteristics cluster, and sleep health can be described as a composite of positive sleep attributes. We assessed the association between a sleep score reflecting multiple sleep dimensions, and mortality. We tested the hypothesis that more favorable sleep (higher sleep scores) is associated with lower mortality. METHODS: The Multi-Ethnic Study of Atherosclerosis (MESA) is a racially and ethnically-diverse multi-site, prospective cohort study of US adults. Sleep was measured using unattended polysomnography, 7-day wrist actigraphy, and validated questionnaires (2010-2013). 1726 participants were followed for a median of 6.9 years (Q1-Q3, 6.4-7.4 years) until death (171 deaths) or last contact. Survival models were used to estimate the association between the exposure of sleep scores and the outcome of all-cause mortality, adjusting for socio-demographics, lifestyle, and medical comorbidities; follow-up analyses examined associations between individual metrics and mortality. The exposure, a sleep score, was constructed by an empirically-based Principal Components Analysis on 13 sleep metrics, selected a priori. RESULTS: After adjusting for multiple confounders, a 1 standard deviation (sd) higher sleep score was associated with 25% lower hazard of mortality (Hazard Ratio [HR]: 0.75; 95% Confidence interval: [0.65, 0.87]). The largest drivers of this association were: night-to-night sleep regularity, total sleep time, and the Apnea-Hypopnea Index. CONCLUSION: More favorable sleep across multiple characteristics, operationalized by a sleep score, is associated with lower risk of death in a diverse US cohort of adults. Results suggest that interventions that address multiple dimensions may provide novel approaches for improving health.","journal":"SLEEP","year":2023,"id":326966,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":27,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7615,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":651499,"name":"Matthew Goodman","orcid":"0000-0002-3982-7940","position":1,"is_corresponding":false},{"id":17009,"name":"Tianyi Huang","orcid":"0000-0001-8420-9167","position":2,"is_corresponding":false},{"id":312681,"name":"Meredith L. Wallace","orcid":"0000-0003-3951-890X","position":3,"is_corresponding":false},{"id":98923,"name":"Pamela L. Lutsey","orcid":"0000-0002-1572-1340","position":4,"is_corresponding":false},{"id":304720,"name":"Jarvis T. Chen","orcid":"0000-0002-7412-1783","position":5,"is_corresponding":false},{"id":454381,"name":"Cecilia Castro‐Diehl","orcid":"0000-0003-3650-4684","position":6,"is_corresponding":false},{"id":328274,"name":"Suzanne M. Bertisch","orcid":"0000-0002-4627-8871","position":7,"is_corresponding":false},{"id":17008,"name":"Susan Redline","orcid":"0000-0002-6585-1610","position":8,"is_corresponding":false},{"id":651498,"name":"Joon Chung","orcid":"0000-0002-8082-9833","position":0,"is_corresponding":true}],"reference_count":86,"raw_metadata":null,"created_at":"2026-07-19T01:08:37.840107Z","pmid":"37523657","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}