Time-Course of Cause-Specific Hospital Admissions During Snowstorms: An Analysis of Electronic Medical Records From Major Hospitals in Boston, Massachusetts

<span class="paragraphSection"><div class="boxTitle">Abstract</div>With global climate change, more frequent severe snowstorms are expected; however, evidence regarding their health effects is very limited. We gathered detailed medical records on hospital admissions (<span style="font-style:italic;">n</span> = 433,037 admissions) from the 4 largest hospitals in Boston, Massachusetts, during the winters of 2010–2015. We estimated the percentage increase in hospitalizations for cardiovascular and cold-related diseases, falls, and injuries on the day of and for 6 days after a day with low (0.05–5.0 inches), moderate (5.1–10.0 inches), or high (>10.0 inches) snowfall using distributed lag regression models. We found that cardiovascular disease admissions decreased by 32% on high snowfall days (relative risk (RR) = 0.68, 95% confidence interval (CI): 0.54, 0.85) but increased by 23% 2 days after (RR = 1.23, 95% CI: 1.01, 1.49); cold-related admissions increased by 3.7% on high snowfall days (RR = 3.7, 95% CI: 1.6, 8.6) and remained high for 5 days after; and admissions for falls increased by 18% on average in the 6 days after a moderate snowfall day (RR = 1.18, 95% CI: 1.09, 1.27). We did not find a higher risk of hospitalizations for injuries. To our knowledge, this is the first study in which the time course of hospitalizations during and immediately after snowfall days has been examined. These findings can be translated into interventions that prevent hospitalizations and protect public health during harsh winter conditions.</span>

http://ift.tt/2kXbN4L