An exceptionally severe heat wave struck France between August 1 and 15, 2003, resulting in the deaths of nearly 15,000 people. The deceased were primarily people aged 65 and older (91%), living in urban areas; 35% of the deaths occurred in the individuals’ homes. A study aimed at better understanding the risk factors for mortality among older adults living at home was conducted to guide prevention programs. A matched case-control study was conducted. Cases were individuals living in Paris, Orléans, Tours, or one of the municipalities in Val-de-Marne, who had been residing at home since at least August 4 and died between August 8 and 13 from causes other than accidents, suicides, and surgical complications. Controls were individuals who survived the heat wave, matched to cases by sex, age group, and residential area. Controls were recruited from a telephone directory including numbers on the red list. The variables collected pertained to sociodemographic characteristics, behaviors during the heat wave, social and family environment, independence, health status, housing characteristics, and environmental characteristics within a 200-meter radius. The data were analyzed using a conditional logistic regression model. A total of 259 case-control pairs were identified. The variables significantly associated with death at the 5% significance level in multivariate analysis were socioeconomic status (OR=3.6 for manual laborers), level of independence (OR=9.6 for individuals confined to bed or a chair, 4.0 for those not confined to bed or a chair but unable to dress or wash themselves), cardiovascular diseases (OR=3.7), psychiatric disorders (OR=5.0), neurological diseases (OR=3.5), the quality of home insulation (OR=4.8 for older, uninsulated buildings compared to newer buildings or older, insulated buildings), having a bedroom under the roof (OR=4.1), and the average surface temperature measured by satellite within a 200-meter radius of the home (OR=1.8 for a 1°C increase). Certain heatwave coping behaviors had a protective effect, such as wearing lighter clothing (OR=0.22) and using cooling methods (OR=0.32). The results are generally consistent with those of other studies. They help define a profile of at-risk individuals and demonstrate the importance of individual behaviors in coping with heat. Improving housing conditions also appears to be a preventive measure. The finding that temperature differences within cities themselves have an effect on mortality also allows for prevention efforts to be focused on urban planning characteristics at the neighborhood level.