The Role of Individual-Level Socioeconomic Status on Nursing Home Placement Accounting for Neighborhood Characteristics |
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| Affiliation: | 1. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA;2. Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA;3. Division of Primary Care and Internal Medicine, Mayo Clinic, Rochester, MN, USA;1. Azienda Sanitaria Locale (ASL) Alzheimer''s Disease Day Clinic, Frosinone, Italy;2. Italian Society of Gerontology and Geriatrics (SIGG), Florence, Italy;3. Unit of Geriatrics, Department of Medicine, Campus Bio-Medico University and Teaching Hospital, Rome, Italy;4. School of Medicine and Surgery, University of Milano-Bicocca and Acute Geriatric Unit, San Gerardo Hospital, Monza, Italy;5. Department of Long-term care Geriatrics, “Villa Immacolata, Salus Infirmorum” Provincia Romana Camilliani, Roma & Viterbo, Italy;6. Geriatrics Division, Department of Medicine (DIMED), University of Padua, Italy;7. Bluecompanion Ltd, Londra, UK;8. Geriatric Intensive Care Unit, Department of Experimental and Clinical Medicine, University of Florence, Italy;9. Center for Cognitive Disorders and Dementia - Catanzaro Lido, ASP Catanzaro, Italy;10. ANASTE-Humanitas Foundation, Rome, Italy;11. Geriatrics Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy;12. Aging Branch, Neuroscience Institute, National Research Council, Padua, Italy;13. Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore di Sanità, Roma, Italy;14. Department of Medical Science, University of Ferrara, Italy;1. Geriatrics and Extended Care Data and Analysis Center (GECDAC), Finger Lakes Healthcare System, Canandaigua, NY;2. Center for Gerontology and Healthcare Research and the Department of Health Services, Policy, and Practice, School of Public Health, Brown University;3. Public Health Sciences, University of Rochester, Rochester, NY;4. Department of Medicine, University of Rochester, Rochester, NY;5. VA Connecticut Healthcare System, West Haven, CT;6. Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA;1. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada;2. Department of Family Medicine, McMaster University, Hamilton, Ontario, Canada;3. ICES, Toronto, Ontario, Canada;4. Department of Geriatrics, Florida State University College of Medicine, Tallahassee, FL, USA;5. Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada;6. City of Toronto Senior Services and Long-Term Care Division, Toronto, Ontario, Canada;7. Trillium Health Partners, Mississauga, Ontario, Canada;8. Schlegel Villages, Kitchener, Ontario, Canada;9. DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada |
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| Abstract: | ObjectiveIndependent living is desirable for many older adults. Although several factors such as physical and cognitive functions are important predictors for nursing home placement (NHP), it is also reported that socioeconomic status (SES) affects the risk of NHP. In this study, we aimed to examine whether an individual-level measure of SES is associated with the risk of NHP after accounting for neighborhood characteristics.DesignA population-based study (Olmsted County, Minnesota, USA).Setting and ParticipantsOlder adults (age 65+ years) with no prior history of NHP.MethodsElectronic health records (EHR) were used to identify individuals with any NHP between April 1, 2012 (baseline date) and April 30, 2019. Association between the (HOUsing-based index of SocioEconomic Status (HOUSES) index, an individual-level SES measure based on housing characteristics of current residence, and risk of NHP was tested using random effects Cox proportional hazard model adjusting for area deprivation index (ADI), an aggregated SES measure that captures neighborhood characteristics, and other pertinent confounders such as age and chronic disease burden.ResultsAmong 15,031 older adults, 3341 (22.2%) experienced NHP during follow-up period (median: 7.1 years). At baseline date, median age was 73 years old with 55% female persons, 91% non-Hispanic Whites, and median number of chronic conditions of 4. Accounting for pertinent confounders, the HOUSES index was strongly associated with risk of NHP (hazard ratio 1.89; 95% confidence interval 1.66‒2.15 for comparing the lowest vs highest quartiles), which was not influenced by further accounting for ADI.Conclusions and ImplicationsThis study demonstrates that an individual-level SES measure capturing current individual-specific socioeconomic circumstances plays a significant role for predicting NHP independent of neighborhood characteristics where they reside. This study suggests that older adults who are at higher risk of NHP can be identified by utilizing the HOUSES index and potential individual-level intervention strategies can be applied to reduce the risk for those with higher risk. |
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| Keywords: | Socioeconomic status the HOUSES index nursing home placement area deprivation index |
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