Do Biometeorological Indices Improve Modeling Outcomes of Heat-Related Mortality?

Abstract

Various biometeorological indices and temperature measures have been used to assess heat-related health risks. Composite indices are expected to assess human comfort more accurately than do temperature measures alone. The performances of several common biometeorological indices and temperature measures in evaluating the heat-related mortality in Brisbane, Australia-a city with a subtropical climate-were compared. Daily counts of deaths from organic causes [International Statistical Classification of Diseases and Related Health Problems, 9th Revision, (ICD9) codes 001-799 and ICD, 10th Revision, (ICD10) codes A00-R99] during the period from 1 January 1996 to 30 November 2004 were used. Several composite biometeorological indices were considered, such as apparent temperature, relative strain index, Thom discomfort index, the humidex, and wetbulb globe temperature. Hot days were defined as those days falling into the 95th percentile of each thermal stress indicator. Case-crossover analysis was applied to estimate the relationship between exposure to heat and mortality. The performances of various biometeorological indices and temperature measures were compared using the jackknife resampling method. The results show that more deaths were likely to occur on hot days than on other (i.e., control) days regardless of the temperature measure or biometeorological index that is considered. The magnitude of the odds ratios varied with temperature indicators, between 1.08 [95% confidence interval (CI): 1.02-1.14] and 1.41 (95% CI: 1.22-1.64) after adjusting for air pollutants (particulate matter with aerodynamic diameter less than 10 mm and ozone). Average temperature performed similarly to the composite indices, but minimum and maximum temperatures performed relatively poorer. Thus, average temperature may be suitable for the development of weather-health warning systems if the findings presented herein are confirmed in different locations.

Humidity: A review and primer on atmospheric moisture and human health

“…Similarly, increasing specific humidity was also found to be more dangerous at high temperatures (Barreca, 2009). These results contrast with those for Australia (Vaneckova et al, 2011) and the United States (Barnett et al, 2010), where humidity was found to have little to no added effect on temperature-related health outcomes. Montero et al (2012) suggested temperature and 21 humidity associations should be analyzed separately, acknowledging that humidity may display negative and positive relationships with mortality for hot-dry and warm-humid climate settings, respectively.…”

“…Humidity plays a more noticeable role in increasing mortality in "cold compared to warm counties" in the United States, suggesting that adaptation may be important in moderating the climate and health relationship (Barreca, 2012). The lack of any humidity effects in Brisbane, Australia (Vaneckova et al, 2011) may be related to acclimatization or adaptation of the population to the warm humid climate there.…”

The effects of the 1996–2012 summer heat events on human mortality in Slovakia

“…The authors of that study did not find any significant differences between the usage of simple air temperature characteristics and biometeorological indices, and state that the selection of the mortality predictor is much less important than some other tasks. Daily mean temperature is an equivalent alternative, and in the case of an evaluation of heat-related mortality it shows similar results as various biometeorological indices according to other studies as well (Kim et al, 2011;Vaneckova et al, 2011). Urban and Kyselý (2014) also confirmed this finding in Central Europe when evaluating heat effects on cardiovascular mortality in the neighbouring Czech Republic.…”

The surface temperatures of Earth: steps towards integrated understanding of variability and change

“…Agam et al, 2008;Kalma et al, 2008;Anderson et al, 2011Anderson et al, , 2012, emergency responses to heat waves (e.g. Endlicher et al, 2008;Tong et al, 2012;Vaneckova et al, 2011;Zanobetti et al, 2012), infectious disease control (e.g. Reisen et al, 2006;Midekisa et al, 2012), lake ecology (e.g.…”