Short-Term Effects of Air Pollution on Total and Cardiovascular Mortality

Umeå University, Umeå, Västerbotten, Sweden
Epidemiology (Impact Factor: 6.2). 02/2005; 16(1):49-57. DOI: 10.1097/01.ede.0000142152.62400.13
Source: PubMed

ABSTRACT Air pollution is associated with total mortality. This association may be confounded by uncontrolled time-varying risk factors such as influenza epidemics.
We analyzed independent data on influenza epidemics from 7 European cities that also had data on mortality associated with particulates (PM10). We used 10 methods to control for epidemics (5 derived from influenza data and 5 from respiratory mortality series) and compared those results with analyses that did not control for these epidemics.
Adjustment for influenza epidemics increased the PM10 effect estimate in most cases (% change in the pooled regression coefficient: -1.9 to 38.9 for total mortality and 1.3 to 25.5 for cardiovascular mortality). A 10-microg/m increase in PM10 concentrations (lag 0-1) was associated with a 0.48% (95% confidence interval=0.27-0.70%) increase in daily mortality unadjusted for influenza epidemics, whereas under the various methods to control for epidemics the increase ranged from 0.45% (0.26-0.69%) to 0.67% (0.46-0.89%). The corresponding figures for cardiovascular mortality were 0.85% (0.53-1.18%) with no adjustment and from 0.86% (0.53-1.19%) to 1.06% (0.74-1.39%) with the methods of control.
The association between air pollution and mortality is not weakened by control for influenza epidemic irrespective of the method used. To adjust for influenza epidemics, one can use methods based on respiratory mortality counts instead of counts of influenza cases if the latter are not available. However, adjustment for influenza by any method tested did not markedly alter the air pollution effect estimate.

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    • "That study did not compare their results with and without influenza as a covariate. A study on the association of air pollution and mortality included similar measures to estimate influenza as confounder [18,21]. "
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    ABSTRACT: Background More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature. Methods The authors obtained counts of daily cardiac deaths and of emergency hospital admissions of the elderly for influenza during 1992–2000. Quasi-Poisson regression models were conducted estimating the association between daily cardiac mortality, and temperature. Results Controlling for influenza admissions provided a more parsimonious model with better Generalized Cross-Validation, lower residual serial correlation, and better captured Winter peaks. The temperature-response function was not greatly affected by adjusting for influenza. The pooled estimated increase in risk for a temperature decrease from 0 to −5°C was 1.6% (95% confidence interval (CI) 1.1-2.1%). Influenza accounted for 2.3% of cardiac deaths over this period. Conclusions The results suggest that including epidemic data explained most of the irregular seasonal pattern (about 18% of the total seasonal variation), allowing more parsimonious models than when adjusting for seasonality only with smooth functions of time. The effect of cold temperature is not confounded by epidemics.
    Environmental Health 10/2012; 11(1):74. DOI:10.1186/1476-069X-11-74 · 3.37 Impact Factor
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    • "by the Bureau of Meteorology and merged with the health data using a technique that weights observations from different weather stations according to population density ( Hanigan et al . , 2006 ) . Epidemics of influenza were defined as days with hospital admission rates for influenza greater than the 90th percentile of the regional distribution ( Touloumi et al . , 2005 ) ."
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    ABSTRACT: Extreme air pollution events due to bushfire smoke and dust storms are expected to increase as a consequence of climate change, yet little has been published about their population health impacts. We examined the association between air pollution events and mortality in Sydney from 1997 to 2004. Events were defined as days for which the 24h city-wide concentration of PM(10) exceeded the 99th percentile. All events were researched and categorised as being caused by either smoke or dust. We used a time-stratified case-crossover design with conditional logistic regression modelling adjusted for influenza epidemics, same day and lagged temperature and humidity. Reported odds ratios (OR) and 95% confidence intervals are for mortality on event days compared with non-event days. The contribution of elevated average temperatures to mortality during smoke events was explored. There were 52 event days, 48 attributable to bushfire smoke, six to dust and two affected by both. Smoke events were associated with a 5% increase in non-accidental mortality at a lag of 1 day OR (95% confidence interval (CI)) 1.05 (95%CI: 1.00-1.10). When same day temperature was removed from the model, additional same day associations were observed with non-accidental mortality OR 1.05 (95%CI: 1.00-1.09), and with cardiovascular mortality OR (95%CI) 1.10 (95%CI: 1.00-1.20). Dust events were associated with a 15% increase in non-accidental mortality at a lag of 3 days, OR (95%CI) 1.16 (95%CI: 1.03-1.30). The magnitude and temporal patterns of association with mortality were different for smoke and dust events. Public health advisories during bushfire smoke pollution episodes should include advice about hot weather in addition to air pollution.
    Environmental Research 05/2011; 111(6):811-6. DOI:10.1016/j.envres.2011.05.007 · 4.37 Impact Factor
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    • "Many epidemiological studies have shown that short-term increases in ambient air 49 pollutants are associated with an acute rise in mortality (Touloumi et al., 2005), hospital 50 admissions (Dominici et al., 2006), and emergency hospital visits (Guo et al., 2009). 51 However, most studies were conducted in western countries (where people have different 52 demographic characteristics compared with Asian countries) and used time series and case– 53 crossover analysis separately. "
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    ABSTRACT: Many studies have illustrated that ambient air pollution negatively impacts on health. However, little evidence is available for the effects of air pollution on cardiovascular mortality (CVM) in Tianjin, China. Also, no study has examined which strata length for the time-stratified case-crossover analysis gives estimates that most closely match the estimates from time series analysis. The purpose of this study was to estimate the effects of air pollutants on CVM in Tianjin, China, and compare time-stratified case-crossover and time series analyses. A time-stratified case-crossover and generalized additive model (time series) were applied to examine the impact of air pollution on CVM from 2005 to 2007. Four time-stratified case-crossover analyses were used by varying the stratum length (Calendar month, 28, 21 or 14 days). Jackknifing was used to compare the methods. Residual analysis was used to check whether the models fitted well. Both case-crossover and time series analyses show that air pollutants (PM(10), SO(2) and NO(2)) were positively associated with CVM. The estimates from the time-stratified case-crossover varied greatly with changing strata length. The estimates from the time series analyses varied slightly with changing degrees of freedom per year for time. The residuals from the time series analyses had less autocorrelation than those from the case-crossover analyses indicating a better fit. Air pollution was associated with an increased risk of CVM in Tianjin, China. Time series analyses performed better than the time-stratified case-crossover analyses in terms of residual checking.
    Science of The Total Environment 11/2010; 409(2):300-6. DOI:10.1016/j.scitotenv.2010.10.013 · 4.10 Impact Factor
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