Time series studies show that hot temperatures are associated with increased death rates in the short term. In light of evidence of adaptation to usual temperature but higher deaths at unusual temperatures, a long-term exposure relevant to mortality might be summertime temperature variability, which is expected to increase with climate change. We investigated whether the standard deviation (SD) of summer (June-August) temperatures was associated with survival in four cohorts of persons over age 65 y with predisposing diseases in 135 US cities. Using Medicare data , we constructed cohorts of persons hospitalized with chronic obstructive pulmonary disease, diabetes, congestive heart failure, and myocardial infarction. City-specific yearly summer temperature variance was linked to the individuals during follow-up in each city and was treated as a time-varying exposure. We applied a Cox proportional hazard model for each cohort within each city, adjusting for individual risk factors, wintertime temperature variance, yearly ozone levels, and long-term trends, to estimate the chronic effects on mortality of long-term exposure to summer temperature SD, and then pooled results across cities. Mortality hazard ratios ranged from 1.028 (95% confidence interval, 1.013-1.042) per 1°C increase in summer temperature SD for persons with congestive heart failure to 1.040 (95% confidence interval, 1.022-1.059) per 1°C increase for those with diabetes. Associations were higher in elderly persons and lower in cities with a higher percentage of land with green surface. Our data suggest that long-term increases in temperature variability may increase the risk of mortality in different subgroups of susceptible older populations.health | climate variability | temperature related mortality | ozone related mortality R ecords of daily weather conditions and air pollution concentrations measured at airports and other local stations, along with daily registries of health outcomes, such as mortality or hospitalizations, routinely compiled by health authorities, are sometimes merged to form multiyear time series datasets. These time series can be analyzed to yield information on how environmental conditions may contribute to increases in deaths and illness on a short-term time scale (days to weeks after the environmental exposure). In the last decade, numerous multicity time series analyses have demonstrated that cold and hot temperatures, as well as extremes of cold and hot temperature, are associated with increased death rates in the days after these weather conditions (1-10). These findings have important implications for understanding the health effects of climate change, given that climate change is increasing both the variability of temperatures and the frequency, duration, and intensity of heat waves (11-13).As with the short-term associations between particulate air pollution and health, these findings, by their nature, are unable to address the question of the extent to which temperature exposure may decrease life expectancy. Studies...