{"doi":"10.1002/alz.70940","title":"Neighborhood support as a protective factor for cognition: Associations with sleep, depression, and stress","abstract":"INTRODUCTION: Sleep, depression, stress, and neighborhood support are independently linked to cognition, but how these factors interact when sleep quality is poor remains understudied. METHODS: We analyzed cross-sectional baseline data from 233 adults aged ≥ 65 years in the Aging Adult Brain Connectome study. Sleep quality, depressive symptoms, stress, and neighborhood support were assessed with validated scales, and cognition was measured using the Preclinical Alzheimer's Cognitive Composite (PACC). Models tested two- and three-way interactions, adjusting for sociodemographics. RESULTS: Poor sleep quality was associated with lower PACC scores (β = -0.57, p = 0.002). This association was even more pronounced in older adults who also had depressive symptoms (β = -0.09, p < 0.001) or increased stress (β = -0.31, p < 0.001). This effect was attenuated by greater neighborhood support (interaction estimates 0.007-0.021, all p ≤ 0.014). DISCUSSION: Poor sleep quality was associated with lower cognition, compounded by psychosocial burden and buffered by neighborhood support. HIGHLIGHTS: Poor sleep quality worsened late-life cognitive performance in older adults. Depressive symptoms and stress further worsened the effect of poor sleep on cognitive performance. Neighborhood support buffered negative sleep-psychosocial impacts on cognitive performance.","journal":"Alzheimer s & Dementia","year":2025,"id":524911,"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":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8828,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1376981,"name":"Semere Bekena","orcid":"0009-0008-6514-0502","position":1,"is_corresponding":false},{"id":341625,"name":"Yiqi Zhu","orcid":"0000-0003-3400-589X","position":2,"is_corresponding":false},{"id":868701,"name":"Jean‐Francois Trani","orcid":"0000-0002-9187-0946","position":3,"is_corresponding":false},{"id":737315,"name":"Anthony Briggs","orcid":"0000-0002-9459-5214","position":4,"is_corresponding":false},{"id":278407,"name":"Omonigho M. Bubu","orcid":"0000-0001-7438-2628","position":5,"is_corresponding":false},{"id":253620,"name":"Brendan P. Lucey","orcid":"0000-0001-5400-825X","position":6,"is_corresponding":false},{"id":226074,"name":"Beau M. Ances","orcid":"0000-0003-3862-7397","position":7,"is_corresponding":false},{"id":310969,"name":"Ganesh M. Babulal","orcid":"0000-0001-7966-3509","position":8,"is_corresponding":false},{"id":1399649,"name":"for the Aging Adult Brain Connectome (AABC) study team","orcid":null,"position":9,"is_corresponding":false},{"id":1343815,"name":"Ramkrishna K. Singh","orcid":"0000-0001-9022-2317","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T02:50:16.562292Z","pmid":"41287976","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":[]}