Socioeconomic inequality in depression and anxiety and its determinants in Iranian older adults

Abstract

Background Older adults with lower socioeconomic status are more vulnerable to stressful life events and at increased risk of common mental health disorders like anxiety and depression. This study investigates the socioeconomic inequality in depressive symptoms and anxiety. Methods The data were from 7462 participants of the Neyshabur longitudinal study of ageing registered during 2016-2018. The outcome variables were anxiety and depressive symptoms. Anxiety was defined by the “Hospital Anxiety and Depression scale Questionnaire”, and depressive symptoms was defined and measured by the “short-term form of the Epidemiological Center Questionnaire.” The socioeconomic status was defined using principal component analysis of home assets. The Concentration Index (C) was used to measure socioeconomic inequality in anxiety and depressive symptoms. Concentration index was decomposed to its determinants to determine the role of the independent variables on inequality. Results The prevalence of depressive symptoms and anxiety was 12.2% (95% CI: 11.4, 12.9) and 7.0% (95% CI: 6.4, 7.5), respectively. Moreover, the C for anxiety was -0.195 (95% CI: -0.254, -0.136) and for depressive symptoms was -0.206 (95% CI: -0.252, -0.159), which indicate a considerable inequality in favor of high socioeconomic group for anxiety and depressive symptoms. Decomposition of the concentration Index showed that education, unemployment and male sex were the most important positive contributors to the observed inequality in anxiety and depressive symptoms, while age and number of grandchildren were main negative contributors of this inequality. Conclusion Low socioeconomic groups were more affected by anxiety and depressive symptoms. Any intervention for alleviation of inequality in anxiety and depression should be focus on education and employment of people, especially in younger elderly.

Prevalence of COVID‐19 anxiety, geriatric anxiety, and related factors among the elderly in Quchan, Iran during the COVID‐19 pandemic: a cross‐sectional study

“…These findings are consistent with the study by Raeisvandi et al ., which reported a similar prevalence of anxiety in the elderly at 35.5% 10 . However, Fakhri's study (2023) and Azizabadi's study (2022) found lower prevalence rates of anxiety in the elderly at 16.7% and 7%, respectively 17,18 . This difference could be attributed to variations in the anxiety measurement tools used and the age criteria, as Azizabadi's study included individuals aged 54–94 from four provinces, while the present study focused on those over 60 years old.…”

“…Corona Disease Anxiety Scale (CDAS): This tool, designed to assess anxiety related to COVID-19, includes 18 items grouped into two subscales: psychological symptoms (items 1-9) and physical symptoms (items [10][11][12][13][14][15][16][17][18]. It employs a four-point Likert scale (never = 0, sometimes = 1, often = 2, always = 3) for scoring, with potential scores ranging from 0 to 54.…”

“…16 Anxiety prevalence in the elderly has varied from 7% to 35.5% in different studies. 10,[17][18][19][20] Factors such as age, comorbidity, living conditions, and occupation have been found to be associated with anxiety. 10 In light of the growing elderly population and the pressing issue of anxiety among them, there is a need for comprehensive planning in this domain.…”

“…Another study identified a relationship between experienced and perceived inequality in women with anxiety 16 . Anxiety prevalence in the elderly has varied from 7% to 35.5% in different studies 10,17–20 . Factors such as age, comorbidity, living conditions, and occupation have been found to be associated with anxiety 10 …”

Experiences of poverty amongst low‐income older adults living in a high‐income country: A qualitative study

“…Indeed, many of the participants in our study reported symptoms consistent with depression. The financial, health and social situation in which the older adults are immersed could be the trigger for numerous problems related to their mental health (Azizabadi et al, 2022). To improve this situation, nurses could start by developing protocols to systematically identify and contribute to reducing the invisibility of community-dwelling older adults living under the shadow of poverty.…”