Loneliness and social isolation risk factors in community-dwelling older adults receiving home health services.

backgroundSocial isolation and loneliness are highly prevalent in older adults. Older adults who are receiving home health services (HHS) post hospital discharge are at high risk for social isolation and loneliness related to multimorbidity and functional decline. Yet, the prevalence of social isolation and loneliness in this population is not commonly described.

methodsWe analyzed electronic health record (EHR) data from 2,026 community-dwelling older adults (mean age 77.5 ± 8.2, 61.7% female, 35% Black/African American, 42.2% Hispanic) who were discharged with HHS from three acute care facilities in Bronx County, NY. Marital and living alone status were assessed as proxy measures for social isolation. Loneliness was assessed with a one-item loneliness question. The prevalence and overlap between loneliness and social isolation risk factors were examined with descriptive and inferential statistics. Logistic regression models were used to examine correlates of loneliness, living alone, and marital status.

resultsOf 2,026 individuals, 29.5% lived alone, 33.5% were married, and 11.6% reported feeling lonely at least some of the time. Those who lived alone had better cognitive and physical function, were more likely to be female, White/Caucasian, and lonely- and less likely to need assistance with activities of daily living (ADLs). Individuals who were unmarried or living alone were more likely to be lonely. After adjusting for covariates, Black/African Americans and those who had better cognitive function had lower odds of loneliness. Living alone, depressive symptoms, multimorbidity, functional impairment were associated with increased odds of being lonely, after adjusting for covariates.

conclusionsRisk for social isolation is highly prevalent among diverse, homebound older adults. Home health care is ideally situated for loneliness assessment and intervention for an otherwise hard to reach, vulnerable population. EHR data can be leveraged to identify individuals at risk and additional brief indicators integrated into the EHR (e.g., validated loneliness assessment, social isolation metrics) may be valuable to facilitate identification and stratification of individuals at risk.