The association between short-term temperature variability and mortality in Virginia

The objective of this study is to determine the relationship between short-term temperature variability on neighboring days and mortality. The change in maximum temperature in Northern Virginia, Richmond, Roanoke, and Norfolk, Virginia, on neighboring days was calculated from airport observations and associated with total mortality over a multi-county area surrounding each weather station. The association between day-to-day temperature change and mortality, lagged over a 28-day period, was analyzed using distributed lag non-linear models that controlled for air quality, temporal trends, and other factors. Days following large temperature declines were associated with an increased risk of mortality in three of the four locations, and temperature increases were linked to higher mortality risk in two cities. For example, the relative risk of mortality for a 12°C daily temperature decline (1st percentile) was 1.74 [0.92, 3.27] in Roanoke and 1.16 [0.70, 1.92] in Richmond. The net effect of short-term temperature increases was smaller, with the largest relative risk of 1.03 [0.58, 1.83] for a 12°C increase (99th percentile) in maximum temperature in Norfolk. In Richmond and Roanoke, there was an observed lagged effect of increased mortality (maximum relative risks varying from 1.08 to 1.10) that extended from 5 to 25 days associated with large temperature declines of 15°C or more. In contrast, there was a strong and immediate (lag 0-3 day) increase in the risk of mortality (1.10 to 1.15) in northern Virginia and Norfolk when the temperature increase exceeded 10°C (short-term warming). In general, consecutive day warming had a more immediate mortality impact than short-term cooling, when the peak mortality is lagged by one week or more. However, cooling of at least 10°C after a hot (summer) day reduced mortality relative to comparable cooling following a cold (winter) day, which is associated with high mortality. This differential mortality response as a function of temperature suggests that there is some relationship between average temperature, temperature variability, and season. The findings of this study may be useful to public health officials in developing mitigation strategies to reduce the adverse health risks associated with short-term temperature variability.