Theses and Dissertations

There is a lot of variation in health outcomes when it comes to individual states in America. Some states, such as Hawaii, have the life expectancy equivalent to that of developed countries, whereas states like Mississippi have the life expectancy equivalent to that of third world countries. This raised the questions of which states are doing well in health and why, and if their health has to do with their performance in the primary, secondary, tertiary, and/or quaternary prevention levels. The purpose of this research was to investigate if there is a correlation between performance in any of the prevention levels and the overall health status of a state, and if there is, which prevention level would be most beneficial for states to prioritize. The hypothesis of this research was: states that prioritized primary and secondary levels of prevention would have better health than states that prioritized tertiary and quaternary levels of prevention, since basic health measures contribute more to health outcomes than advanced medicine. To investigate this question, indicators were chosen to derive the ranking of each state in health and each of the four prevention levels. Six states were then chosen to represent the high, average, and low health statuses respectively. The six states were ranked for all indicators, and the data was analyzed and compared to determine a potential relationship between the prevention level rankings and the overarching health ranking. It was found that there is a correlation between performance in the primary and secondary prevention levels and a state’s overall health status, whereas there was no such correlation for the tertiary and quaternary levels. A model for health was proposed for states looking to improve their health status, which was to invest in primary prevention, followed by secondary, tertiary, then quaternary prevention and only moving to the next prevention level once the previous level reached a satisfactory threshold.

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.