Does respiratory health contribute to the effects of long-term air pollution exposure on cardiovascular mortality?

BACKGROUND: There is growing epidemiological evidence that short-term and long-term exposure to high levels of air pollution may increase cardiovascular morbidity and mortality. In addition, epidemiological studies have shown an association between air pollution exposure and respiratory health. To what extent the association between cardiovascular mortality and air pollution is driven by the impact of air pollution on respiratory health is unknown. The aim of this study was to investigate whether respiratory health at baseline contributes to the effects of long-term exposure to high levels of air pollution on cardiovascular mortality in a cohort of elderly women. METHOD: We analyzed data from 4750 women, aged 55 at the baseline investigation in the years 1985–1994. 2593 of these women had their lung function tested by spirometry. Respiratory diseases and symptoms were asked by questionnaire. Ambient air pollution exposure was assessed by the concentrations of NO(2 )and total suspended particles at fixed monitoring sites and by the distance of residency to a major road. A mortality follow-up of these women was conducted between 2001 and 2003. For the statistical analysis, Cox' regression was used. RESULTS: Women with impaired lung function or pre-existing respiratory diseases had a higher risk of dying from cardiovascular causes. The impact of impaired lung function declined over time. The risk ratio (RR) of women with forced expiratory volume in one second (FEV(1)) of less than 80% predicted to die from cardiovascular causes was RR = 3.79 (95%CI: 1.64–8.74) at 5 years survival time and RR = 1.35 (95%CI: 0.66–2.77) at 12 years. The association between air pollution levels and cardiovascular death rate was strong and statistically significant. However, this association did only change marginally when including indicators of respiratory health into the regression analysis. Furthermore, no interaction between air pollution and respiratory health on cardiovascular mortality indicating a higher risk of those with impaired respiratory health could be detected. CONCLUSION: Respiratory health is a predictor for cardiovascular mortality. In women followed about 15 years after the baseline investigation at age 55 years long-term air pollution exposure and impaired respiratory health were independently associated with increased cardiovascular mortality

Particulate matter air pollution and national and county life expectancy loss in the USA: a spatiotemporal analysis

Background Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations, and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States. Methods and findings We used vital registration and population data with information on sex, age, cause of death and county of residence. We used four Bayesian spatio-temporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution, and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high-school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 µg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and in 14,757 deaths (12,617-16,919) for males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states, such as Arkansas, Oklahoma or Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county random intercepts. Conclusions According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate

Health impact assessment of particulate pollution in Tallinn using fine spatial resolution and modeling techniques

<p>Abstract</p> <p>Background</p> <p>Health impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.</p> <p>Methods</p> <p>Tallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390 000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM_2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM₁₀or PM_2.5levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6–11%) per 10 μg/m³increase of annual mean PM_2.5concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62–1.67%) and 0.73% (95% CI 0.47–0.93%) per 10 μg/m³increase of PM₁₀. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY).</p> <p>Results</p> <p>The annual population-weighted-modeled exposure to locally emitted PM_2.5in Tallinn was 11.6 μg/m³. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17–1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43–104) respiratory and 204 (95% CI 131–260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average €150 (95% CI 40–260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small €0.3 (95% CI 0.2–0.4) million.</p> <p>Conclusion</p> <p>Sectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.</p

Suspected association of ventricular arrhythmia with air pollution in a motorbike rider: a case report

<p>Abstract</p> <p>Introduction</p> <p>Premature ventricular complexes are to some extent a normal finding in healthy individuals and the prevalence increases with age and is more common in men. Premature ventricular complexes can occur in association with a variety of stimuli, and a lesser known cause is the association between air pollution and ventricular arrhythmias.</p> <p>Case presentation</p> <p>A previously healthy man started to ride a lightweight motorbike in heavy traffic. A few weeks later he was admitted to hospital with premature ventricular complexes in bigeminy, which decreased after a few days when he was not exposed to exhaust fumes. A few weeks later he started using the motorbike again and the same symptoms developed once more, only to subside when he stopped riding in heavy traffic.</p> <p>Conclusion</p> <p>Studies have shown an association between air pollution and premature ventricular complexes and other kinds of arrhythmias. The mechanism may be changes in cardiac autonomic function, including heart rate and heart rate variability. Air pollution should be considered when patients present with arrhythmias and no other causes are found.</p

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study

<p>Abstract</p> <p>Background</p> <p>The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM_2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles.</p> <p>Methods</p> <p>Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties.</p> <p>Results</p> <p>The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties.</p> <p>Conclusion</p> <p>When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.</p

Traffic Air Pollution and Oxidized LDL

BACKGROUND: Epidemiologic studies indirectly suggest that air pollution accelerates atherosclerosis. We hypothesized that individual exposure to particulate matter (PM) derived from fossil fuel would correlate with plasma concentrations of oxidized low-density lipoprotein (LDL), taken as a marker of atherosclerosis. We tested this hypothesis in patients with diabetes, who are at high risk for atherosclerosis. METHODOLOGY/PRINCIPAL FINDINGS: In a cross-sectional study of non-smoking adult outpatients with diabetes we assessed individual chronic exposure to PM by measuring the area occupied by carbon in airway macrophages, collected by sputum induction and by determining the distance from the patient's residence to a major road, through geocoding. These exposure indices were regressed against plasma concentrations of oxidized LDL, von Willebrand factor and plasminogen activator inhibitor 1 (PAI-1). We could assess the carbon load of airway macrophages in 79 subjects (58 percent). Each doubling in the distance of residence from major roads was associated with a 0.027 µm(2) decrease (95% confidence interval (CI): -0.048 to -0.0051) in the carbon load of airway macrophages. Independently from other covariates, we found that each increase of 0.25 µm(2) [interquartile range (IQR)] in carbon load was associated with an increase of 7.3 U/L (95% CI: 1.3 to 13.3) in plasma oxidized LDL. Each doubling in distance of residence from major roads was associated with a decrease of -2.9 U/L (95% CI: -5.2 to -0.72) in oxidized LDL. Neither the carbon load of macrophages nor the distance from residence to major roads, were associated with plasma von Willebrand factor or PAI-1. CONCLUSIONS: The observed positive association, in a susceptible group of the general population, between plasma oxidized LDL levels and either the carbon load of airway macrophages or the proximity of the subject's residence to busy roads suggests a proatherogenic effect of traffic air pollution