Using Supervised Principal Components Analysis to Assess Multiple Pollutant Effects

BACKGROUND: Many investigations of the adverse health effects of multiple air pollutants analyze the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. This method can yield unstable parameter estimates when the pollutants involved suffer high intercorrelation; therefore, traditional approaches to dealing with multicollinearity, such as principal component analysis (PCA), have been promoted in this context. OBJECTIVES: A characteristic of PCA is that its construction does not consider the relationship between the covariates and the adverse health outcomes. A refined version of PCA, supervised principal components analysis (SPCA), is proposed that specifically addresses this issue. METHODS: Models controlling for long-term trends and weather effects were used in conjunction with each SPCA and PCA to estimate the association between multiple air pollutants and mortality for U.S. cities. The methods were compared further via a simulation study. RESULTS: Simulation studies demonstrated that SPCA, unlike PCA, was successful in identifying the correct subset of multiple pollutants associated with mortality. Because of this property, SPCA and PCA returned different estimates for the relationship between air pollution and mortality. CONCLUSIONS: Although a number of methods for assessing the effects of multiple pollutants have been proposed, such methods can falter in the presence of high correlation among pollutants. Both PCA and SPCA address this issue. By allowing the exclusion of pollutants that are not associated with the adverse health outcomes from the mixture of pollutants selected, SPCA offers a critical improvement over PCA

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

Effects of fossil fuel and total anthropogenic emission removal on public health and climate.

Anthropogenic greenhouse gases and aerosols are associated with climate change and human health risks. We used a global model to estimate the climate and public health outcomes attributable to fossil fuel use, indicating the potential benefits of a phaseout. We show that it can avoid an excess mortality rate of 3.61 (2.96-4.21) million per year from outdoor air pollution worldwide. This could be up to 5.55 (4.52-6.52) million per year by additionally controlling nonfossil anthropogenic sources. Globally, fossil-fuel-related emissions account for about 65% of the excess mortality, and 70% of the climate cooling by anthropogenic aerosols. The chemical influence of air pollution on aeolian dust contributes to the aerosol cooling. Because aerosols affect the hydrologic cycle, removing the anthropogenic emissions in the model increases rainfall by 10-70% over densely populated regions in India and 10-30% over northern China, and by 10-40% over Central America, West Africa, and the drought-prone Sahel, thus contributing to water and food security. Since aerosols mask the anthropogenic rise in global temperature, removing fossil-fuel-generated particles liberates 0.51(±0.03) °C and all pollution particles 0.73(±0.03) °C warming, reaching around 2 °C over North America and Northeast Asia. The steep temperature increase from removing aerosols can be moderated to about 0.36(±0.06) °C globally by the simultaneous reduction of tropospheric ozone and methane. We conclude that a rapid phaseout of fossil-fuel-related emissions and major reductions of other anthropogenic sources are needed to save millions of lives, restore aerosol-perturbed rainfall patterns, and limit global warming to 2 °C

Association of Ambient Air Pollution with Respiratory Hospitalization in a Government-Designated “Area of Concern”: The Case of Windsor, Ontario

This study is part of a larger research program to examine the relationship between ambient air quality and health in Windsor, Ontario, Canada. We assessed the association between air pollution and daily respiratory hospitalization for different age and sex groups from 1995 to 2000. The pollutants included were nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone, particulate matter ≤10 μm in diameter (PM(10)), coefficient of haze (COH), and total reduced sulfur (TRS). We calculated relative risk (RR) estimates using both time-series and case-crossover methods after controlling for appropriate confounders (temperature, humidity, and change in barometric pressure). The results of both analyses were consistent. We found associations between NO(2), SO(2), CO, COH, or PM(10) and daily hospital admission of respiratory diseases especially among females. For females 0–14 years of age, there was 1-day delayed effect of NO(2) (RR = 1.19, case-crossover method), a current-day SO(2) (RR = 1.11, time series), and current-day and 1- and 2-day delayed effects for CO by case crossover (RR = 1.15, 1.19, 1.22, respectively). Time-series analysis showed that 1-day delayed effect of PM(10) on respiratory admissions of adult males (15–64 years of age), with an RR of 1.18. COH had significant effects on female respiratory hospitalization, especially for 2-day delayed effects on adult females, with RRs of 1.15 and 1.29 using time-series and case-crossover analysis, respectively. There were no significant associations between O(3) and TRS with respiratory admissions. These findings provide policy makers with current risks estimates of respiratory hospitalization as a result of poor ambient air quality in a government designated “area of concern.

Carboxyhaemoglobin levels and their determinants in older British men

Background: Although there has been concern about the levels of carbon monoxide exposure, particularly among older people, little is known about COHb levels and their determinants in the general population. We examined these issues in a study of older British men.Methods: Cross-sectional study of 4252 men aged 60-79 years selected from one socially representative general practice in each of 24 British towns and who attended for examination between 1998 and 2000. Blood samples were measured for COHb and information on social, household and individual factors assessed by questionnaire. Analyses were based on 3603 men measured in or close to (< 10 miles) their place of residence.Results: The COHb distribution was positively skewed. Geometric mean COHb level was 0.46% and the median 0.50%; 9.2% of men had a COHb level of 2.5% or more and 0.1% of subjects had a level of 7.5% or more. Factors which were independently related to mean COHb level included season (highest in autumn and winter), region (highest in Northern England), gas cooking (slight increase) and central heating (slight decrease) and active smoking, the strongest determinant. Mean COHb levels were more than ten times greater in men smoking more than 20 cigarettes a day (3.29%) compared with non-smokers (0.32%); almost all subjects with COHb levels of 2.5% and above were smokers (93%). Pipe and cigar smoking was associated with more modest increases in COHb level. Passive cigarette smoking exposure had no independent association with COHb after adjustment for other factors. Active smoking accounted for 41% of variance in COHb level and all factors together for 47%.Conclusion: An appreciable proportion of men have COHb levels of 2.5% or more at which symptomatic effects may occur, though very high levels are uncommon. The results confirm that smoking (particularly cigarette smoking) is the dominant influence on COHb levels

Developing consistent data and methods to measure the public health impacts of ambient air quality for Environmental Public Health Tracking: progress to date and future directions

Environmental Public Health Tracking (EPHT) staff at the state and national levels are developing nationally consistent data and methods to estimate the impact of ozone and fine particulate matter on hospitalizations for asthma and myocardial infarction. Pilot projects have demonstrated the feasibility of pooling state hospitalization data and linking these data to The United States Environmental Protection Agency (EPA) statistically based ambient air estimates for ozone and fine particulates. Tools were developed to perform case-crossover analyses to estimate concentration–response (C-R) functions. A weakness of analyzing one state at a time is that the effects are relatively small compared to their confidence intervals. The EPHT program will explore ways to statistically combine the results of peer-reviewed analyses from across the country to provide more robust C-R functions and health impact estimates at the local level. One challenge will be to routinely share data for these types of analyses at fine geographic and temporal scales without disclosing confidential information. Another challenge will be to develop C-R estimates which take into account time, space, or other relevant effect modifiers

Short-Term Effects of Carbon Monoxide on Mortality: An Analysis within the APHEA Project

Objectives: We investigated the short-term effects of carbon monoxide on total and cardiovascular mortality in 19 European cities participating in the APHEA-2 (Air Pollution and Health: A European Approach) project. Methods: We examined the association using hierarchical models implemented in two stages. In the first stage, data from each city were analyzed separately, whereas in the second stage the city-specific air pollution estimates were regressed on city-specific covariates to obtain overall estimates and to explore sources of possible heterogeneity. We evaluated the sensitivity of our results by applying different degrees of smoothing for seasonality control in the city-specific analysis. Results: We found significant associations of CO with total and cardiovascular mortality. A 1-mg/m$^3$ increase in the 2-day mean of CO levels was associated with a 1.20% [95% confidence interval (CI), 0.63–1.77%] increase in total deaths and a 1.25% (95% CI, 0.30–2.21%) increase in cardiovascular deaths. There was indication of confounding with black smoke and nitrogen dioxide, but the pollutant-adjusted effect of CO on mortality remained at least marginally statistically significant. The effect of CO on total and cardiovascular mortality was observed mainly in western and southern European cities and was larger when the standardized mortality rate was lower. Conclusions: The results of this large study are consistent with an independent effect of CO on mortality. The heterogeneity found in the effect estimates among cities may be explained partly by specific city characteristics