April 2-4, 2020 • Hyatt Regency • Lexington, KY
Intersectionality and Interdisciplinarity in Health Communication Research
Intersectionality and Interdisciplinarity in Health Communication Research
Abstract: Classification and Risk Factors of Depression Among Aging Americans: A Growth Mixture Analysis
Background: The quality of life, especially the mental health of the fast-growing aging population, has been a social and academic concern — research documents how depressive symptoms increase the risk of mortality of the elders. However, how depressive conditions take shape and develop along a substantial aging process needs exploration.
Objective: This study is to investigate (1) the different types of longitudinal changes in older adults’ mental status and (2) the risk factors of depression among the elderly population.
Method: Twelve waves’ (1994–2016) longitudinal panel data from the Health and Retirement Study (HRS) were used for the analysis. The number of panel participants totals 42053. Measurements included were (1) self-reported mental health status, which was measured at each time point by the subtraction of two positive dummy indicators (happiness, enjoyment) from five negative dummy indicators (e.g., loneliness, sadness); (2) self-reported physical health condition, comorbidity, job stress, drinking, smoking, and exercising behaviors measured at baseline; (3) time-invariant demographic variables, such as gender, race, birth year, and educational background. Growth mixture modeling was performed to explore the types of change in the elderly’s mental health. Logistic regression analysis was employed to examine if any demographic or behavioral factors at baseline predict the different types of longitudinal growth of mental health among the elderly.
Results: Two types of mental health growth were found. Type I represents the 60.1% participants that had more depressive symptoms at baseline (i = 2.252, p < .001) and higher longitudinal increase (s = .038, p < .001) in depression; Type II exemplifies the 39.9% elderly who lived with fewer depressive symptoms at baseline (i = .301, p < .001) and had much lower longitudinal increase (s = .004, p < .001) in depression than Type I. Logistic regression shows that being female (ß = .541, p < .001, odds ratio = 1.718) and African Americans (compared to Caucasians) (ß = .386, p < .001, odds ratio = 1.471) are positive predictors of the Type I membership. Compared to people with education level less than high school, people who received general education (ß = -.479, p < .001, odds ratio = .619), high school degree (ß = -.81, p < .001, odds ratio = .445), some college (ß = -.962, p < .001, odds ratio = .382), and college and above (ß = -1.276, p < .001, odds ratio = .279) are less likely to fall into the first type of depressive development.
Conclusion: The result suggests that a sizable number of elders in the United States may have aged with severing mental problems. Structural/demographic factors, rather than behavioral issues (e.g., drinking, smoking, and physical activities), are significantly correlated with poor mental development. Men, Caucasians, and people with higher educational levels tend to experience a better aging process than those who are women, African Americans, and people with lower education regarding mental status. Future interventions can pay special attention to the elderly who are susceptible to poor mental development over time.
Objective: This study is to investigate (1) the different types of longitudinal changes in older adults’ mental status and (2) the risk factors of depression among the elderly population.
Method: Twelve waves’ (1994–2016) longitudinal panel data from the Health and Retirement Study (HRS) were used for the analysis. The number of panel participants totals 42053. Measurements included were (1) self-reported mental health status, which was measured at each time point by the subtraction of two positive dummy indicators (happiness, enjoyment) from five negative dummy indicators (e.g., loneliness, sadness); (2) self-reported physical health condition, comorbidity, job stress, drinking, smoking, and exercising behaviors measured at baseline; (3) time-invariant demographic variables, such as gender, race, birth year, and educational background. Growth mixture modeling was performed to explore the types of change in the elderly’s mental health. Logistic regression analysis was employed to examine if any demographic or behavioral factors at baseline predict the different types of longitudinal growth of mental health among the elderly.
Results: Two types of mental health growth were found. Type I represents the 60.1% participants that had more depressive symptoms at baseline (i = 2.252, p < .001) and higher longitudinal increase (s = .038, p < .001) in depression; Type II exemplifies the 39.9% elderly who lived with fewer depressive symptoms at baseline (i = .301, p < .001) and had much lower longitudinal increase (s = .004, p < .001) in depression than Type I. Logistic regression shows that being female (ß = .541, p < .001, odds ratio = 1.718) and African Americans (compared to Caucasians) (ß = .386, p < .001, odds ratio = 1.471) are positive predictors of the Type I membership. Compared to people with education level less than high school, people who received general education (ß = -.479, p < .001, odds ratio = .619), high school degree (ß = -.81, p < .001, odds ratio = .445), some college (ß = -.962, p < .001, odds ratio = .382), and college and above (ß = -1.276, p < .001, odds ratio = .279) are less likely to fall into the first type of depressive development.
Conclusion: The result suggests that a sizable number of elders in the United States may have aged with severing mental problems. Structural/demographic factors, rather than behavioral issues (e.g., drinking, smoking, and physical activities), are significantly correlated with poor mental development. Men, Caucasians, and people with higher educational levels tend to experience a better aging process than those who are women, African Americans, and people with lower education regarding mental status. Future interventions can pay special attention to the elderly who are susceptible to poor mental development over time.