Depression symptoms and cognitive impairment in older nursing home residents in the USA: A latent class analysis.

Abstract

To identify subgroups of nursing home (NH) residents in the USA experiencing homogenous depression symptoms and evaluate if subgroups vary by cognitive impairment. We identified 104 465 newly admitted, long-stay residents with depression diagnosis at NH admission in 2014 using the Minimum Data Set 3.0. The Patient Health Questionnaire-9 was used to measure depression symptoms and the Brief Interview of Mental Status for cognitive impairment (intact; moderately impaired; severely impaired). Latent class analysis (LCA) with logistic regression was used to: (a) construct the depression subgroups and (b) estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) of the associations between the subgroups and cognitive impairment level, adjusting for demographic and clinical characteristics. The best-fitted LCA model suggested four subgroups of depression: minimal symptoms (latent class prevalence: 42.4%), fatigue (32.0%), depressed mood (14.5%), and multiple symptoms (11.2%). Odds of subgroup membership varied by cognitive impairment. Compared to residents with intact cognition, those with moderate or severe cognitive impairment were less likely to belong to the fatigue subgroup [aOR(95% CI): moderate: 0.75 (0.71-0.80); severe: 0.26 (0.23-0.29)] and more likely to belong to the depressed mood subgroup [aOR (95% CI): moderate: 4.54 (3.55-5.81); severe: 6.41 (4.86-8.44)]. Residents with moderate cognitive impairment had increased odds [aOR (95% CI): 1.19 (1.12-1.27)] while those with severe impairment had reduced odds of being in the multiple symptoms subgroup [aOR (95% CI): 0.63 (0.58-0.68)]. Findings provide a basis for improving depression management with consideration of both subgroups of depression symptoms and levels of cognitive function.