Date of Award

Fall 12-2018

Degree Name

Doctor of Philosophy (PhD)

Advisor(s)

KAI ZHANG, PHD

Second Advisor

WENYAW CHAN, PHD

Third Advisor

XIANGLIN L. DU, MD, PHD

Abstract

Recent events with recorded low temperature and unusual snow accumulation in the United States and Europe have raised the public awareness of the potential health impacts of extreme winter weather. Excessive cold was the leading cause of weather-related death during 2006-2010 in the U.S., accounting for 63% of weather related deaths. Several studies worldwide have demonstrated that, in general, mortality rates are higher in winter compared to summer. Studies have also shown that the association between cold temperature and death vary across cities, regions and countries and is especially relevant with decreasing latitude or in regions with mild winter climate. In addition to cold temperatures, higher mortality rates may be attributable to cold wave, an extended period of extreme cold temperature. However, due to global climate change, attention has focused on current and future heat waves on human health rather than cold waves. Despite the fact that climate change is expected to increase the intensity of winter storms, only a few studies have investigated cold wave-mortality association. Further, the results of these studies are inconsistent. In addition, most studies have focused on all-cause and cause-specific mortality, cold-related morbidity was less studied. The long-term goal of this study is to improve the understanding of how cold temperature and cold wave affect human health and to reduce adverse health effects of future cold events.

The dissertation used time-series data with Poisson regression model to quantify both cold temperature effect and cold wave effect in Texas, one of the most populous and largest states that covers a variety of demographical and geographical feature with a general mild winter climate as located in the southern USA. Daily counts of deaths/emergency hospital admissions were modeled with both temperature and different cold-wave definitions for 12 major Metropolitan Areas (MSAs). Moreover, considering winter weather patterns are anticipated to become more variable with increasing average global temperatures, we used downscaled global climate models with population projection to estimate future public health burden attributable to cold temperature.

The study showed that cold weather generally increases health risk significantly in Texas ranging from 0.1% to 5.0% for mortality and 0.1% to 3.8% for emergency hospital admissions with a 1⁰C decrease in temperature below the cold thresholds. The cold effects vary with age groups with highest risk in people over 75-year old. The strongest cold effects were associated with mortality in heart diseases and with emergency hospital admission in respiratory diseases. We found although the annual cold- mortality rates reduced with projected temperature under climate change, the number of deaths attributable to cold temperature increased largely with projected population through the end of the century.

The findings can improve the understanding of cold-related health impacts in southern U.S. regions, and help local governments allocate resources to the areas in greatest need. This study can provide evidence for local policy makers to design strategies in reducing future public health burden of temperature-related deaths.

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