Life Satisfaction Factors, Stress, and Depressive Symptoms among Young Women Living in Urban Kampala: Findings from the TOPOWA Project Pilot Studies.

Young women living in Kampala, Uganda, often face adversities related to Social Determinants of Mental Health (SDoMH) including poverty, food scarcity, environmental stressors such as high levels of community violence, and lack of adequate healthcare access. Two consecutive pilot studies were conducted to assess the feasibility and acceptability of survey questions, wearable fitness trackers, and daily diaries before launching a larger prospective cohort study. Preliminary associations between SDoMH factors with depressive symptoms, stress levels, and life satisfaction were examined among the total sample of 60 women across two pilot studies. A total of 32.2% of respondents (out of n = 59) reported being depressed most or all of the time in the past 30 days. Frequent depressive symptoms correlated with food insecurity (χ2 = 5.38, df = 1, p = 0.02). Higher stress levels were significantly associated with lower overall life satisfaction scores (t = 2.74, df = 6.20, p = 0.03). Additionally, frequent depressive symptoms were associated with lower satisfaction scores in the living conditions and lifestyle domain (t = 2.22, df = 36.18, p = 0.03). However, overall life satisfaction scores and other domains (social relationships and personal independence) were not statistically associated with frequent depressive symptoms. Identifying the most impactful SDoMH factors among young women in Kampala can inform targeted approaches to improve mental health outcomes.

Predicting Suicide in Counties: Creating a Quantitative Measure of Suicide Risk.

Rising rates of suicide over the past two decades have increased the need for wide-ranging suicide prevention efforts. One approach is to target high-risk groups, which requires the identification of the characteristics of these population sub-groups. This suicidology study was conducted using large-scale, secondary data to answer the question: using the research on suicide, are there variables studied at the community level that are linked to suicide and are measurable using quantitative, demographic data that are already collected and updated? Data on deaths from suicide in U.S. counties for the years 2000, 2005, 2010 and 2015 were analyzed using multiple regression, longitudinal regression, and cluster analysis. Results indicated that the suicide rate in a county can be predicted by measuring the financial stability of the residents, the quality of mental health in the county, and the economic opportunity in the county. The results are further analyzed using two sociological theories, Social Strain Theory and the Theory of Anomie, and two psychological theories, the Shame Model and the Interpersonal Theory of Suicide.