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      On the estimation of heat-intensity and heat-duration effects in time series models of temperature-related mortality in Stockholm, Sweden

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      1 , , 2 , 3
      Environmental Health
      BioMed Central

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          Abstract

          Background

          We examine the effect of heat waves on mortality, over and above what would be predicted on the basis of temperature alone.

          Methods

          Present modeling approaches may not fully capture extra effects relating to heat wave duration, possibly because the mechanisms of action and the population at risk are different under more extreme conditions. Modeling such extra effects can be achieved using the commonly left-out effect-modification between the lags of temperature in distributed lag models.

          Results

          Using data from Stockholm, Sweden, and a variety of modeling approaches, we found that heat wave effects amount to a stable and statistically significant 8.1-11.6% increase in excess deaths per heat wave day. The effects explicitly relating to heat wave duration (2.0–3.9% excess deaths per day) were more sensitive to the degrees of freedom allowed for in the overall temperature-mortality relationship. However, allowing for a very large number of degrees of freedom indicated over-fitting the overall temperature-mortality relationship.

          Conclusions

          Modeling additional heat wave effects, e.g. between lag effect-modification, can give a better description of the effects from extreme temperatures, particularly in the non-elderly population. We speculate that it is biologically plausible to differentiate effects from heat and heat wave duration.

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          Most cited references14

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          Heat stress and public health: a critical review.

          Heat is an environmental and occupational hazard. The prevention of deaths in the community caused by extreme high temperatures (heat waves) is now an issue of public health concern. The risk of heat-related mortality increases with natural aging, but persons with particular social and/or physical vulnerability are also at risk. Important differences in vulnerability exist between populations, depending on climate, culture, infrastructure (housing), and other factors. Public health measures include health promotion and heat wave warning systems, but the effectiveness of acute measures in response to heat waves has not yet been formally evaluated. Climate change will increase the frequency and the intensity of heat waves, and a range of measures, including improvements to housing, management of chronic diseases, and institutional care of the elderly and the vulnerable, will need to be developed to reduce health impacts.
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            Heat Waves in the United States: Mortality Risk during Heat Waves and Effect Modification by Heat Wave Characteristics in 43 U.S. Communities

            Background Devastating health effects from recent heat waves, and projected increases in frequency, duration, and severity of heat waves from climate change, highlight the importance of understanding health consequences of heat waves. Objectives We analyzed mortality risk for heat waves in 43 U.S. cities (1987–2005) and investigated how effects relate to heat waves’ intensity, duration, or timing in season. Methods Heat waves were defined as ≥ 2 days with temperature ≥ 95th percentile for the community for 1 May through 30 September. Heat waves were characterized by their intensity, duration, and timing in season. Within each community, we estimated mortality risk during each heat wave compared with non-heat wave days, controlling for potential confounders. We combined individual heat wave effect estimates using Bayesian hierarchical modeling to generate overall effects at the community, regional, and national levels. We estimated how heat wave mortality effects were modified by heat wave characteristics (intensity, duration, timing in season). Results Nationally, mortality increased 3.74% [95% posterior interval (PI), 2.29–5.22%] during heat waves compared with non-heat wave days. Heat wave mortality risk increased 2.49% for every 1°F increase in heat wave intensity and 0.38% for every 1-day increase in heat wave duration. Mortality increased 5.04% (95% PI, 3.06–7.06%) during the first heat wave of the summer versus 2.65% (95% PI, 1.14–4.18%) during later heat waves, compared with non-heat wave days. Heat wave mortality impacts and effect modification by heat wave characteristics were more pronounced in the Northeast and Midwest compared with the South. Conclusions We found higher mortality risk from heat waves that were more intense or longer, or those occurring earlier in summer. These findings have implications for decision makers and researchers estimating health effects from climate change.
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              The distributed lag between air pollution and daily deaths.

              Many studies have reported associations between air pollution and daily deaths. Those studies have not consistently specified the lag between exposure and response, although most have found associations that persisted for more than 1 day. A systematic approach to specifying the lag association would allow better comparison across sites and give insight into the nature of the relation. To examine this question, I fit unconstrained and constrained distributed lag relations to the association between daily deaths of persons 65 years of age and older with PM10 in 10 U.S. cities (New Haven, Birmingham, Pittsburgh, Canton, Detroit, Chicago, Minneapolis, Colorado Springs, Spokane, and Seattle) that had daily monitoring for PM10. After control for temperature, humidity, barometric pressure, day of the week, and seasonal patterns, I found evidence in each city that the effect of a single day's exposure to PM10 was manifested across several days. Averaging over the 10 cities, the overall effect of an increase in exposure of 10 microg/m3 on a single day was a 1.4% increase in deaths (95% confidence intervals (CI) = 1.15-1.68) using a quadratic distributed lag model, and a 1.3% increase (95% CI = 1.04-1.56) using an unconstrained distributed lag model. In contrast, constraining the model to assume the effect all occurs in one day resulted in an estimate of only 0.65% (95% CI = 0.49-0.81), indicating that this constraint leads to a substantial underestimate of effect. Combining the estimated effect at each day's lag across the 10 cities showed that the effect was spread over several days and did not reach zero until 5 days after the exposure. Given the distribution of sensitivities likely in the general population, this result is biologically plausible. I also found a protective effect of barometric pressure in all 10 locations.
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                Author and article information

                Journal
                Environ Health
                Environ Health
                Environmental Health
                BioMed Central
                1476-069X
                2012
                10 April 2012
                : 11
                : 23
                Affiliations
                [1 ]Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden
                [2 ]Institute of Health and Biomedical Innovation & School of Public Health, Queensland University of Technology, Brisbane, Australia
                [3 ]School of Population Health, University of Auckland, Auckland, New Zealand
                Article
                1476-069X-11-23
                10.1186/1476-069X-11-23
                3431980
                22490779
                3b8ae35c-6a52-4919-9eaf-b3374f460dc3
                Copyright ©2012 Rocklov et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 November 2011
                : 10 April 2012
                Categories
                Research

                Public health
                Public health

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