Background: Examining the interrelationships between symptoms of depression and sociodemographic and behavioral correlates is challengeful using traditional regression analysis.
Objective: to identify the sociodemographic, movement behaviors, and sleep correlates that contribute the most to symptoms of depression in Brazilian older females, using a network analysis approach.
Methods: This cross-sectional study analyzed 1019 older females from Brazil. Data (sociodemographic, height (meters), weight (kilograms), symptoms of depression, physical activity, sleep) were self-reported via phone calls. The relationships between symptoms of depression and their correlates were assessed using the Network Analysis (qgraph package of the Rstudio) for entire sample and age groups (60-69; 70-79 and 80+ years old).
Results: 60-69 and 70-79 groups have more weekly home exits, with aging "single, widowed or divorced" was progressively higher, and "married or stable union" and Overweight/obesity were progressively fewer (p < 0.05). 60-69 have more education years and fewest medicaments use. Sleep compliance (for the entire sample), body mass index (for the 60-69), compliance with moderate to vigorous physical activity (for the 70-79), and educational level (for 80+) were the variables with the highest expected influence values (p < 0.05) on symptoms of depression (1.370; 1.388; 1.129; and 1.354, respectively).
Conclusion: Symptoms of depression vary throughout the aging process and thus determine that intervention strategies encompass these specific factors according to each age group. Poor sleep behavior has a strong positive association with symptoms of depression. This result highlights that health professionals must be aware of the importance of sleep to mitigate the worsening of depression among older Brazilian females.
Keywords: Depression; aging; elderly; network analysis; physical activity; sleep quality.
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