Abstract

Drought conditions are considered to be one of the most far reaching natural disasters and a leading cause for climate related mortality. Yet, there is limited research examining the drought and health relationship. This absence is partly attributed to the complexity of quantifying drought, which is slow to develop with a potential long latency and heterogeneity across space and time. As a natural event, drought cannot be explored through the perspective of a randomized trial; however, it can be evaluated through the lens of observational health data. One alternative approach is to use quasi-experimental designs to evaluate how an exogenous event, specifically a drought, impacts populations over time. Among the most vulnerable subgroups to drought exposures are agricultural populations. Close economic ties to the land, reliance on surface water, and reduced access to care can make agricultural populations increasingly vulnerable. Previous research has linked drought conditions to increased psychosocial stress and suicide. However, the quantitative evidence for droughts effect on mental health is still limited and shows uncertainty. In addition, almost no research on drought and mental health exists for U.S. populations. In this talk, we will explore the association between drought and health outcomes through the quasi-experimental approach of interrupted time-series. We will discuss how to estimate the association between drought and mortality using a temporally robust daily data set across a 14-year period. In a second example, we will discuss the challenges of evaluating drought and health using more temporally limited data. In this example, we explore psychosocial stress and drought conditions among a cohort of 518 Midwestern farmers using 3.5 years of repeated surveys for occupational stress. Our goal is to present the importance of drought and health research, and explore methodology to evaluate this complex environmental exposure.

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