Background: Adolescent pregnancies within urban resource-deprived settlements predispose young girls to adverse mental health and psychosocial adversities, notably depression. Depression in sub-Saharan Africa is a leading contributor to years lived with disability (YLD). The study’s objective was to determine the prevalence of depression and related psychosocial risks among pregnant adolescents reporting at a maternal and child health clinic in Nairobi, Kenya. Methods: A convenient sample of 176 pregnant adolescents attending antenatal clinic in Kangemi primary healthcare health facility participated in the study. We used PHQ-9 to assess prevalence of depression. Hierarchical multivariate linear regression was performed to determine the independent predictors of depression from the psychosocial factors that were significantly associated with depression at the univariate analyses. Results: Of the 176 pregnant adolescents between ages 15-18 years sampled in the study, 32.9% (n=58) tested positive for a depression diagnosis using PHQ-9 using a cut-off score of 15+. However on multivariate linear regression, after various iterations, when individual predictors using standardized beta scores were examined, having experienced a stressful life event (B=3.27, P=0.001, β =0.25) explained the most variance in the care giver burden, followed by absence of social support for pregnant adolescents (B=-2.76, P=0.008, β=-0.19), being diagnosed with HIV/AIDS (B=3.81, P=0.004, β =0.17) and being young (B=2.46, P=0.038, β =0.14). Conclusion: Depression is common among pregnant adolescents in urban resource-deprived areas of Kenya and is correlated with well-documented risk factors such as being of a younger age and being HIV positive. Interventions aimed at reducing or preventing depression in this population should target these groups and provide support to those experiencing greatest stress.
We carried out a cross-sectional study assessing depression and associated psychosocial risk factors in pregnant adolescents attending a Maternal Child Health clinic at a Nairobi community health care center located within the informal settlement. The facility is operated through the County Council of Nairobi giving free maternity services and caters for low-and-middle income wage earners from nearby informal settlements. It receives between 12 and 15 pregnant women every day and operates every weekday. We recruited 176 participants between ages 15-18 years using a prevalence rate of 13% from a study [36]; using Cochran sample size estimation (1977) for a cross-sectional study keeping alpha at p 15+) and also to identify severity [41], the higher scores are an indication of greater severity depression. Due to the peripartum nature of depression in adolescents, we used EPDS as a screener to identify likelihood of depression. We reported scores on PHQ- 9 for those who tested positive in EPDS primarily for test-retest reliability [42] and to categorize depression severity. The collection of data from these tools ensured internal validity through triangulation in evaluation of data and findings while external validity was obtained to the extent that these study findings can be generalized to other populations. During assessments, we targeted participants whose gestation period was 4 months and above and sought clarification on the duration of somatic symptoms of depression from normal pregnancy related symptoms. Participants who scored above > = 15+ on PHQ-9 (i.e. from moderately severe category onwards) were considered to have symptoms of depression and were therefore referred for specialized care. SPSS version 22 [43] was used in data analysis. The association between depression and its psychosocial correlates was determined in two ways. Firstly, we divided our sample into two groups (depressed and non-depressed according to PHQ-9 cut-off score 15+ or more) and compared these groups using chi-square test. Secondly, we assessed each potential correlates with the PHQ-9 score using independent samples t-test and ANOVA. Hierarchical multivariate linear regression analyses were performed to determine the independent predictors of depression from the psychosocial factors that were significantly associated with depression at the univariate analyses. We ran regression analysis by entering the participants’ socio-demographical variables into Block 1, followed by other characteristics/ conditions in Block 2. There were no missing data for all the independent and dependent variables. Prior to running the analysis, all assumptions were checked including univariate/multivariate normality, linearity, homoscedasticity and diagnostic testing for multi-collinearity and independence of errors. After checking for univariate normality, the PHQ depression scores was transformed by a two-step approach using inverse distribution function (IDF) using maximum likelihood estimator (MLE) in which we retained the original series mean and standard deviation to improve the interpretation of results. The level of statistical significance was kept at P < 0.05, all tests were two sided.
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