The Effects of Temperature and Use of Air Conditioning on Hospitalizations
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The Effects of Temperature and Use of Air Conditioning on Hospitalizations

Abstract

Several investigators have documented the effect of temperature on mortality, although fewer have studied its impact on morbidity. In addition, little is known about the effectiveness of mitigation strategies such as use of air conditioners (AC). We investigated the association between temperatures and hospital admissions in California from 1999 to 2005. We also determined whether AC ownership and usage, assessed at the zip code level, mitigates this association. Because of the unique spatial pattern of income and climate in the state, confounding of AC effects by other local factors is less likely. We only included individuals who had a temperature monitor within 25 kilometers of their residential zip codes. Using a time-stratified case-crossover approach, we observed a significantly increased risk for hospitalization for multiple diseases including cardiovascular, ischemic heart disease, ischemic stroke, respiratory disease, pneumonia, dehydration, heat stroke, diabetes and acute renal failure with same-day apparent temperature. We also found that ownership and usage of air conditioning significantly reduced the effects of temperature on these health outcomes, after controlling for the potential confounding effects of family income and other socioeconomic factors. Our results demonstrate important effects of temperature on public health and the potential for mitigation. Several investigators have documented the acute effect of temperature on mortality in the U.S. and Europe, and in developing nations(1-3). There are far fewer studies, however, on the effects of temperature on morbidity outcomes, such as hospitalizations (4-6). According to the recent IPCC report (7), temperatures are expected to increase in the future with more frequent and severe heat waves. Therefore, it is important to obtain a better understanding of these heat-associated health risks and susceptible populations for future surveillance and targeted interventions. In addition, relatively little is known about the effectiveness of proposed mitigation strategies, such as cooling shelters, and personal use of air conditioners (AC). Studies on the effects of actual AC use on temperature-related health outcomes, however, are limited, since data are typically available for AC prevalence, rather than AC use, and only for broad geographic regions. Thus, effects of AC may be confounded by other regional characteristics (8) such as demographic and economic factors. As a result, there is need for more localized estimates of the effects of temperature on morbidity and on the effectiveness of AC use in mitigating these effects. For several reasons, California serves as an ideal study area for examining the effects of AC use on temperature-related adverse health. First, it includes a large and diverse population, residing within a wide array of climatic regions. Second, individual-level data at small levels of spatial scale over a majority of the state are available from surveys conducted by the California Public Utilities Commission (9). Finally, income is less likely to confound the estimates of the effects of AC. In general, incomes are higher in the coastal regions, but lower in the inland areas, such as the Central Valley. However, AC use is greater in the Central Valley where the summers are much hotter, and many homes in the coastal areas of California lack AC (9). In this study, we used temperature data during the warm season in California to estimate the impact on several disease-specific categories of hospitalizations. To limit exposure misclassification, we limited our study to buffer areas with individuals living in zip codes within 25 kilometers (km) of a temperature monitor. Next, we quantified the likely reduction in health impacts based on both ownership and use of ACs using individual-level data for each buffer. Finally, we examined the potential confounding effect that local measures of family income may have on our effect estimates.

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