BackgroundThe evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves.ObjectivesWe situated vulnerability to heat in geographic space and identified potential areas for intervention and further research.MethodsWe mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value.ResultsFour factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat.ConclusionsThese methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.

Objectives: The authors examined the increase in mortality associated with hot and cold temperature in different locations, the determinants of the variability in effect estimates, and its implications for adaptation. Methods: The authors conducted a case-crossover study in 50 US cities. They used daily mortality and weather data for 6 513 330 deaths occurring during 1989-2000. Exposure was assessed using two approaches. First, the authors determined exposure to extreme temperatures using city-specific indicator variables based on the local temperature distribution. Secondly, they used piecewise linear variables to assess exposure to temperature on a continuous scale above/below a threshold. Effects of hot and cold temperature were examined in season-specific models. In a meta-analysis of the city-specific results, the authors examined several city characteristics as effect modifiers. Results: Mortality increases associated with both extreme cold (2-day cumulative increase 1.59% (95% CI 0.56 to 2.63)) and extreme heat (5.74% (95% CI 3.38 to 8.15)) were found, the former being especially marked for myocardial infarction and cardiac arrest deaths. The increase in mortality was less marked at less extreme temperatures. The effect of extreme cold (defined as a percentile) was homogeneous across cities with different climates, suggesting that only the unusualness of the cold temperature (and not its absolute value) had a substantial impact on mortality (that is, acclimatisation to cold). Conversely, heat effects were quite heterogeneous, with the largest effects observed in cities with milder summers, less air conditioning and higher population density. Adjustment for ozone led to similar results, but some residual confounding could be present due to other uncontrolled pollutants. Conclusions: The authors confirmed in a large sample of cities that both cold and hot temperatures increase mortality risk. These findings suggest that increases in heat-related mortality due to global warming are unlikely to be compensated for by decreases in cold-related mortality and that population acclimatisation to heat is still incomplete.

BACKGROUNDThe presence of a cardiovascular implantable electronic device has long been a contraindication for the performance of magnetic resonance imaging (MRI). We established a prospective registry to determine the risks associated with MRI at a magnetic field strength of 1.5 tesla for patients who had a pacemaker or implantable cardioverterdefibrillator (ICD) that was "non-MRI-conditional" (i.e., not approved by the Food and Drug Administration for MRI scanning). METHODSPatients in the registry were referred for clinically indicated nonthoracic MRI at a field strength of 1.5 tesla. Devices were interrogated before and after MRI with the use of a standardized protocol and were appropriately reprogrammed before the scanning. The primary end points were death, generator or lead failure, induced arrhythmia, loss of capture, or electrical reset during the scanning. The secondary end points were changes in device settings. RESULTSMRI was performed in 1000 cases in which patients had a pacemaker and in 500 cases in which patients had an ICD. No deaths, lead failures, losses of capture, or ventricular arrhythmias occurred during MRI. One ICD generator could not be interrogated after MRI and required immediate replacement; the device had not been appropriately programmed per protocol before the MRI. We observed six cases of self-terminating atrial fibrillation or flutter and six cases of partial electrical reset. Changes in lead impedance, pacing threshold, battery voltage, and P-wave and R-wave amplitude exceeded prespecified thresholds in a small number of cases. Repeat MRI was not associated with an increase in adverse events. CONCLUSIONSIn this study, device or lead failure did not occur in any patient with a non-MRIconditional pacemaker or ICD who underwent clinically indicated nonthoracic MRI at 1.5 tesla, was appropriately screened, and had the device reprogrammed in accordance with the prespecified protocol. (Funded by St. Jude Medical and others; MagnaSafe ClinicalTrials.gov number, NCT00907361.)

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