Correlates of Depression and Anxiety among Older Public Housing Residents
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Older adults represent the fastest growing segment of the worldwide population. Mental health disorders present a major challenge to older individuals. Depression and anxiety are two of the most common mental health problems experienced by the older population and give rise to high impact adverse consequences, such as decreased quality of life and increased mortality. Poverty level older adults suffer from higher rates of mental health disorders than do their more highly resourced counterparts. Given worldwide growth of the older population an increasing number of low-income elderly live in public housing. This study examined the prevalence of depression and anxiety in older public housing residents and explored factors related to these disorders within context of the Social Antecedents Model of Psychopathology (SAMP). The SAMP posits a multi-stage model of cumulative demographic, behavioral and social factors that represent mental health risk correlates, with more proximal factors representing greater risk (George, 1989). Study participants included 187 older adults residing in two public housing facilities located in a mid-size city in the southeast United States. Data was gathered concerning residents’ demographic characteristics, psychiatric symptomatology, substance usage, health conditions, and social support via face-to-face interviews. The majority of the residents were male and the average age was 66.2 years (SD= 7.6). Residents reported high levels of clinically significant depression (20.1%) and anxiety (10%). Generalized linear models (GZLM) were used to identify variables that significantly predicted depression and anxiety among the residents. Social support, self-rated health, pain, years smoking, and opioid misuse were significant predictors of depression scores (LR x2(11) = 90.4, p < .001) while age, employment, pain, medical conditions, IADLs, and benzodiazepine misuse significantly predicted anxiety scores (LR x2(13) = 110.857, p <.001). Study findings partially supported the SAMP model.Implications for research and practice are discussed.
Abstract
Older adults represent the fastest growing segment of the worldwide population. Mental health disorders present a major challenge to older individuals. Depression and anxiety are two of the most common mental health problems experienced by the older population and give rise to high impact adverse consequences, such as decreased quality of life and increased mortality. Poverty level older adults suffer from higher rates of mental health disorders than do their more highly resourced counterparts. Given worldwide growth of the older population an increasing number of low-income elderly live in public housing. This study examined the prevalence of depression and anxiety in older public housing residents and explored factors related to these disorders within context of the Social Antecedents Model of Psychopathology (SAMP). The SAMP posits a multi-stage model of cumulative demographic, behavioral and social factors that represent mental health risk correlates, with more proximal factors representing greater risk (George, 1989). Study participants included 187 older adults residing in two public housing facilities located in a mid-size city in the southeast United States. Data was gathered concerning residents’ demographic characteristics, psychiatric symptomatology, substance usage, health conditions, and social support via face-to-face interviews. The majority of the residents were male and the average age was 66.2 years (SD= 7.6). Residents reported high levels of clinically significant depression (20.1%) and anxiety (10%). Generalized linear models (GZLM) were used to identify variables that significantly predicted depression and anxiety among the residents. Social support, self-rated health, pain, years smoking, and opioid misuse were significant predictors of depression scores (LR x2(11) = 90.4, p < .001) while age, employment, pain, medical conditions, IADLs, and benzodiazepine misuse significantly predicted anxiety scores (LR x2(13) = 110.857, p <.001). Study findings partially supported the SAMP model.Implications for research and practice are discussed.
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