This study aimed to assess the prevalence of depressive symptoms and associated factors among a group of indigenous older adults.
A cross-sectional study was conducted with participants aged 54 years and older. The instruments used included the Yesavage Geriatric Depression Scale, the mini-mental state examination (MMSE), the Medical Outcomes Study Social Support Survey and the Family APGAR Scale. Latent class analysis was employed to identify subgroups according to depressive symptom patterns.
The mean scores were as follows: MMSE (24), Yesavage Scale (4.7), APGAR (22.4) and Lawton and Brody’s Instrumental Activities of Daily Living Scale (6.5). The analysis identified a two-class model as the best fit (Bayesian information criterion (BIC) = 4771.22; entropy = 0.83). Class 1, representing 72% of the sample, corresponded to a low-risk profile. Class 2, representing 29% of the sample, reflected a high-risk profile for depressive symptoms. Among the covariates, family functioning (APGAR) was a protective factor against belonging to the high-risk group (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.80–0.96; p = 0.007).
The research presents a series of limitations such as: the cross-sectional study design does not allow the evaluation of any cause-effect mechanisms; the sample of the population may not be representative; the assessment of some scales was carried out through self-report. The above could result in biases due to the low or no level of schooling in the majority of older indigenous adults.
It is worth highlighting as a strength of this study the exploration and association of depressive symptom profiles with multidimensional variables.
