title: Who is sensitive to extremes of temperature?: A case-only analysis.
abstract: BACKGROUND
  Extremes of temperature are well known to be associated with excess mortality. Less is known about the characteristics of persons that put them at higher risk, particularly the role of medical conditions.
  
  
  METHODS
  To investigate these effects, I used a case-only approach to analyze 160,062 deaths in Wayne County, Michigan, among persons who were 65 years of age or older, who were covered by Medicare, and who had a previous hospital admission for heart and lung disease. Using their unique Medicare identification number, I traced deaths through Medicare hospital admission records to identify primary and secondary diagnoses for all admissions before death. I investigated the role of diabetes, myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, and pneumonia as modifiers of the risk of dying on an extreme temperature day. Hot days were defined as those greater than the 99th percentile of all days and cold days as those less than the 1st percentile. I also examined the role of sex, age (85 years of age and older), and nonwhite race as modifiers.
  
  
  RESULTS
  I found that patients with diabetes had a higher risk of dying on hot days than other subjects (odds ratio=1.17; 95% confidence interval=1.04-1.32). Persons with chronic obstructive pulmonary disease had elevated risks of dying on cold days (1.19; 1.07-1.33). Nonwhites had greater risks on both hot (1.22; 1.09-1.37) and cold (1.25; 1.12-1.40) days, and women had elevated risks on cold days (1.14; 1.02-1.26). The other conditions conveyed no higher risks than average.
  
  
  CONCLUSIONS
  Sociodemographic characteristics and medical conditions can increase the likelihood of death associated with temperature extremes.
authors.affiliation: Exposure, Epidemiology, and Risk Program Harvard School of Public Health, Boston, Massachusetts 02215, USA. jschwrtz@hsph.harvard.edu
authors.forename: Joel
authors.initials: J
authors.lastname: Schwartz
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002908:Chronic Disease; D003710:Demography; D004781:Environmental Exposure / Q000009:adverse effects*; D005260:Female; D006304:Health Status; D006331:Heart Diseases / Q000209:etiology* / Q000401:mortality; D006801:Humans; D016015:Logistic Models; D008171:Lung Diseases / Q000209:etiology* / Q000401:mortality; D008297:Male; D008824:Michigan / Q000453:epidemiology; D012307:Risk Factors; D012621:Seasons; D012959:Socioeconomic Factors; D013696:Temperature