The immediate effects of winter storms and power outages on multiple health outcomes and the time windows of vulnerability.

BACKGROUND: While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost. METHODS: We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM2.5. The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods. RESULTS: We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO. CONCLUSION: Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.

Estimating policy-relevant health effects of ambient heat exposures using spatially contiguous reanalysis data.

BACKGROUND: Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes. METHODS: We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (Tmax) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression. RESULTS: We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in Tmax on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria. CONCLUSION: Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Are the current thresholds, indicators, and time window for cold warning effective enough to protect cardiovascular health?

More extreme cold weather and larger weather variations have raised concerns regarding their effects on public health. Although prior studies assessed the effects of cold air temperature on health, especially mortality, limited studies evaluated wind chill temperatures on morbidity, and health effects under the current cold warning threshold. This study identified the thresholds, lag periods, and best indicators of extreme cold on cardiovascular disease (CVD) by comparing effects of wind chill temperatures and cold air temperatures on CVD emergency department (ED) visits in winter and winter transition months. Information was collected on 662,625 CVD ED visits from statewide hospital discharge dataset in New York State. Meteorological factors, including air temperature, wind speed, and barometric pressure were collected from National Oceanic and Atmospheric Administration. A case-crossover approach was used to assess the extreme cold-CVD relationship in winter (December-February) and transition months (November and March) after controlling for PM2.5. Conditional logistic regression models were employed to analyze the association between cold weather factors and CVD ED visits. We observed CVD effects occurred when wind chill temperatures were as high as -3.8 °C (25 °F), warmer than current wind chill warning standard (≤-28.8 °C or ≤-20 °F). Wind chill temperature was a more sensitive indicator of CVD ED visits during winter with temperatures ≤ -3.8 °C (25 °F) with delay effect (lag 6); however, air temperature was better during transition months for temperatures ≤ 7.2 °C (45 °F) at earlier lag days (1-3). Among all CVD subtypes, hypertension ED visit had the strongest negative association with both wind chill temperature and air temperature. This study recommends modifying the current cold warning temperature threshold given larger proportions of CVD cases are occurring at considerably higher temperatures than the current criteria. We also recommend issuing cold warnings in winter transitional months.