Theses and Dissertations

Prior research has established a relation between parenting behaviors and symptoms of child psychopathology, and this association may be influenced by both genetic and environmental factors. Gene-environment correlation, or the influence of a child’s genes on the environment they receive, represents one possible mechanism through which genes and environment combine to influence child outcomes. This study examined evocative gene-environment correlation in the relation between parenting and symptoms of child psychopathology in a sample of 676 twins (51.5% female, 58.5% Caucasian, 23.7% Hispanic/Latinx, primarily middle class, MAge=8.43, SD=.62) recruited from Arizona birth records. Using univariate ACE twin biometric models, genetic influences were found to moderately contribute to internalizing symptoms (A=.47, C=.25, E=.28), while externalizing (A=.86, E=.14) and ADHD (A=.84, E=.16) symptoms were found to be highly heritable. The genetic influences for positive (C=.54, E=.46) and negative (C=.44, E=.56) parenting were smaller and found to be nonsignificant. The correlations between parenting and types of psychopathology were examined and bivariate Cholesky decompositions were conducted for statistically significant correlations. Negative parenting was moderately positively correlated with externalizing and ADHD symptoms; the relation between externalizing symptoms and negative parenting was found to be due to shared genetics, whereas the relation between negative parenting and ADHD symptoms was due to the shared environment. The mixed results regarding the role of gene environment correlation in relations between parenting and child psychopathology indicate that further research on the mechanisms of this relation is needed.

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.