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The seasonal human mortality response to synoptic scale atmospheric circulation changes in the central United States
Jill S. M. Coleman, Ball State University, Muncie, IN
The relationship between weather and human mortality has been limited to studies centering on one or two meteorological variables, often in connection with a distinct weather “event”, such as a heat waves. Recently, the focus is shifting toward a more holistic approach to weather, with several meteorological elements being combined to describe an air mass or weather situation that can effect the human environment. This study continues the trend of recognizing discrete atmospheric circulation types that are most associated with negative health effects (i.e., death) and identifies those causes of death occurring most regularly with a specific weather situation. Seventeen MSAs are investigated for significant mortality rate differences among a set of synoptic types prevalent in the central United States, a region that encounters frequent changes in weather conditions.
Atmospheric circulation types are determined using statistical techniques. S-mode principal component analysis (PCA) is performed on a 7,305 x 1,225 ((the number of days between 1979-1998) x (25 atmospheric variables x 49 grid points)) matrix in the SPSS statistical package. The unrotated score solution is then entered into a two-step clustering procedure to resolve days into groups with similar atmospheric circulation conditions. The final cluster solution categorizes each day into one of nine synoptic types that characterize seasonal changes in atmospheric circulation over the central and eastern United States. Three of the synoptic types occur dominantly in summer and the winter types show some interannual variation with modes of Pacific atmospheric teleconnections.
The nine synoptic classes are compared using the ANOVA F-test statistic for significant differences in daily mortality for each MSA by mortality grouping (e.g., respiratory deaths) and season. Significant differences in mortality rates among the synoptic types are most prevalent during spring and autumn at a one-day lag period, especially between the generally lower warm-season cluster mortality rates and higher rates in cold season clusters. Mortality differences among synoptic types for larger MSAs (> one million people) are typically two-three additional deaths above daily background levels after adverse weather conditions. Mortality rates are significantly different among the synoptic types for people over age 65, for weather related causes, and for circulatory death categories. ANOVA results for the younger cohorts (i.e., below the age of 44) and neoplasm deaths are usually not significant for any of the seasons or lag periods. Significant results for winter and especially summer are more irregular and do not display the sharp contrast between the warm season and cooler-colder season cluster sets.
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Session 1, Human biometeorology: General weather response
Tuesday, 23 May 2006, 9:00 AM-10:00 AM, Boardroom
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