Frontiers in Psychiatry (Jun 2023)

Life satisfaction, positive affect, depression and anxiety symptoms, and their relationship with sociodemographic, psychosocial, and clinical variables in a general elderly population sample from Chile

  • Sandra Saldivia,
  • Joseph Aslan,
  • Félix Cova,
  • Claudio Bustos,
  • Carolina Inostroza,
  • Anabel Castillo-Carreño

DOI
https://doi.org/10.3389/fpsyt.2023.1203590
Journal volume & issue
Vol. 14

Abstract

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BackgroundThis study aims to describe the relationship between life satisfaction, positive affect, depression and anxiety symptoms with sociodemographic, psychosocial and clinical variables, and to identify the relative importance of these predictor groups.MethodsWe evaluated life satisfaction (SWLS), positive affect (PANAS), depressive (PHQ-9), and anxiety (GAI) symptoms and their association with sociodemographic, psychosocial and clinical variables in a multistage, random general population sample of fully functioning individuals aged 60–80 years from the Concepción province and Gran Santiago, Chile (n = 396). We performed weighted multiple regression analysis, considering the complex sample structure with age group, sex, and geographical area, complemented with general and conditional dominance analyses to estimate the relevance of the predictor groups.ResultsWe found significant associations with the geographical area, sex, age, education level, household members, having a partner, employment status, caregiver status, economic satisfaction, presence of chronic diseases, medication use, and alcohol use. Satisfaction with health was the most important predictor for positive affect (p < 0.001), depressive (p < 0.001), and anxiety (p < 0.001) symptoms, while alcohol use was the most significant predictor for life satisfaction (p < 0.001).ConclusionSimultaneously studying the positive and negative dimensions of wellbeing and mental health in older adults allows for a more comprehensive perspective on the challenges faced during this stage of life. This study accounts for previously unknown associations and contributes to the identification of common and specific predictors in both dimensions.

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