{"doi":"10.1093/sleep/zsac015","title":"Actigraphy-derived sleep health profiles and mortality in older men and women","abstract":"STUDY OBJECTIVES: To identify actigraphy sleep health profiles in older men (Osteoporotic Fractures in Men Study; N = 2640) and women (Study of Osteoporotic Fractures; N = 2430), and to determine whether profile predicts mortality. METHODS: We applied a novel and flexible clustering approach (Multiple Coalesced Generalized Hyperbolic mixture modeling) to identify sleep health profiles based on actigraphy midpoint timing, midpoint variability, sleep interval length, maintenance, and napping/inactivity. Adjusted Cox models were used to determine whether profile predicts time to all-cause mortality. RESULTS: We identified similar profiles in men and women: High Sleep Propensity [HSP] (20% of women; 39% of men; high napping and high maintenance); Adequate Sleep [AS] (74% of women; 31% of men; typical actigraphy levels); and Inadequate Sleep [IS] (6% of women; 30% of men; low maintenance and late/variable midpoint). In women, IS was associated with increased mortality risk (Hazard Ratio [HR] = 1.59 for IS vs. AS; 1.75 for IS vs. HSP). In men, AS and IS were associated with increased mortality risk (1.19 for IS vs. HSP; 1.22 for AS vs. HSP). CONCLUSIONS: These findings suggest several considerations for sleep-related interventions in older adults. Low maintenance with late/variable midpoint is associated with increased mortality risk and may constitute a specific target for sleep health interventions. High napping/inactivity co-occurs with high sleep maintenance in some older adults. Although high napping/inactivity is typically considered a risk factor for deleterious health outcomes, our findings suggest that it may not increase risk when it occurs in combination with high sleep maintenance.","journal":"SLEEP","year":2022,"id":240364,"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":45,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8194,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":426036,"name":"Soomi Lee","orcid":"0000-0002-7623-3770","position":1,"is_corresponding":false},{"id":245151,"name":"Katie L. Stone","orcid":"0000-0003-2797-3171","position":2,"is_corresponding":false},{"id":312684,"name":"Martica H. Hall","orcid":"0000-0003-0642-2098","position":3,"is_corresponding":false},{"id":868312,"name":"Stephen F Smagula","orcid":null,"position":4,"is_corresponding":false},{"id":17008,"name":"Susan Redline","orcid":"0000-0002-6585-1610","position":5,"is_corresponding":false},{"id":242503,"name":"Kristine E. Ensrud","orcid":"0000-0002-9069-3036","position":6,"is_corresponding":false},{"id":868313,"name":"Sonia Ancoli-Israel","orcid":null,"position":7,"is_corresponding":false},{"id":265804,"name":"Daniel J. Buysse","orcid":"0000-0002-3288-1864","position":8,"is_corresponding":false},{"id":312681,"name":"Meredith L. Wallace","orcid":"0000-0003-3951-890X","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":null,"created_at":"2026-07-19T00:22:46.554789Z","pmid":"35037946","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":[]}