Air pollution and daily mortality in Philadelphia

Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.

Exploration of the heterogeneous effect of climate change on ozone concentration in an urban environment

Ozone is a significant causative agent of mortality in cities. Urban environments are expressly vulnerable to global warming because of the extensive emission of air pollutants with urban heat island effect enhancing much rapidly the ozone concentration than in the less urbanized regions. This effect previously was not studied in local scale. It was hypothesized that climate change will cause heterogenic increase of ozone concentration in the different parts of the cities. To study this effect, the near-surface ozone concentration of 10 points of a Hungarian city was measured and modeled. At first step, the local correlations between solar radiation, air temperature, relative humidity and the near surface ozone concentrations at 3 m height were determined, specifying the local ozone-producing conditions. Then, based on the scenario of the Intergovernmental Panel on Climate Change 5th assessment report, the future seasonal near-surface ozone concentrations were modeled. Based on the model, it was determined that climate change will result in a heterogenic increase of near-surface ozone concentration.

The influence of the winter North Atlantic Oscillation index on hospital admissions through diseases of the circulatory system in Lisbon, Portugal

The aim of this paper is to analyze the relationship between North Atlantic Oscillation (NAO), meteorological variables, air pollutants, and hospital admissions due to diseases of circulatory systems in Lisbon (Portugal) during winter months (2003-2012). This paper is one of the few studies analyzing the impact of NAO on health through its influence on thermal stress and air pollution and is the first to be conducted in Lisbon. This study uses meteorological data (synthetized into a thermal comfort index), air pollutant metrics, and the NAO index (all clustered in 10-day cycles to overcome daily variability of the NAO index). The relationship between morbidity, thermal comfort index, NAO index, and air pollutants was explored through several linear models adjusted to seasonality through a periodic function. The possible indirect effect between the NAO index and hospital admissions was tested, assuming that NAO (independent variable) is affecting hospital admissions (outcome variable) through thermal discomfort and/or pollution levels (tested as individual mediators). This test was conducted through causal mediation analysis and adjusted for seasonal variation. The results from this study suggest a possible indirect relationship between NAO index and hospital admissions. Although NAO is not significantly associated with hospital admissions, it is significantly associated with CO, PM_2.5, NO, and SO₂ levels, which in turn increase the probability of hospitalization. The discomfort index (built with temperature and relative humidity) is significantly associated with hospital admissions, but its variability is not explained by the NAO index. This study highlights the impacts of the atmospheric circulation patterns on health. Furthermore, understanding the influence of the atmospheric circulation patterns can support the improvement of the existing contingency plans.

Measuring the burden of disease due to climate change and developing a forecast model in South Korea

OBJECTIVES

Climate change influences human health in various ways, and quantitative assessments of the effect of climate change on health at national level are becoming essential for environmental health management.

STUDY DESIGN

This study quantified the burden of disease attributable to climate change in Korea using disability-adjusted life years (DALY), and projected how this would change over time.

METHODS

Diseases related to climate change in Korea were selected, and meteorological data for each risk factor of climate change were collected. Mortality was calculated, and a database of incidence and prevalence was established. After measuring the burden of each disease, the total burden of disease related to climate change was assessed by multiplying population-attributable fractions. Finally, an estimation model for the burden of disease was built based on Korean climate data.

RESULTS

The total burden of disease related to climate change in Korea was 6.85 DALY/1000 population in 2008. Cerebrovascular diseases induced by heat waves accounted for 72.1% of the total burden of disease (hypertensive disease 1.82 DALY/1000 population, ischaemic heart disease 1.56 DALY/1000 population, cerebrovascular disease 1.56 DALY/1000 population). According to the estimation model, the total burden of disease will be 11.48 DALY/1000 population in 2100, which is twice the total burden of disease in 2008.

CONCLUSIONS

This study quantified the burden of disease caused by climate change in Korea, and provides valuable information for determining the priorities of environmental health policy in East Asian countries with similar climates.

An evidence-based appraisal of global association between air pollution and risk of stroke

BACKGROUND

The aim of this study was to evaluate the transient effects of air pollutants on stroke morbidity and mortality using the meta-analytic approach.

METHODS

Three databases were searched for case-crossover and time series studies assessing associations between daily increases in particles with diameter<2.5 μm (PM2.5) and diameter<10 μm (PM10), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), ozone, and risks of stroke hospitalizations and mortality. Risk estimates were combined using random-effects model.

RESULTS

A total of 34 studies were included in the meta-analysis. Stroke hospitalizations or mortality increased 1.20% (95%CI: 0.22-2.18) per 10 μg/m3 increase in PM2.5, 0.58% (95%CI: 0.31-0.86) per 10 μg/m3 increase in PM10, 1.53% (95%CI: 0.66-2.41) per 10 parts per billion (ppb) increase in SO2, 2.96% (95%CI: 0.70-5.27) per 1 ppm increase in CO, and 2.24% (95%CI: 1.16-3.33) per 10ppb increase in NO2. These positive associations were the strongest on the same day of exposure, and appeared to be more apparent for ischemic stroke (for all 4 gaseous pollutants) and among Asian countries (for all 6 pollutants). In addition, an elevated risk (2.45% per 10 ppb; 95%CI: 0.35-4.60) of ischemic stroke associated with ozone was found, but not for hemorrhagic stroke.

CONCLUSION

Our study indicates that air pollution may transiently increase the risk of stroke hospitalizations and stroke mortality. Although with a weak association, these findings if validated may be of both clinical and public health importance given the great global burden of stroke and air pollution.

Assessment of trend and seasonality in road accident data: an Iranian case study

BACKGROUND

Road traffic accidents and their related deaths have become a major concern, particularly in developing countries. Iran has adopted a series of policies and interventions to control the high number of accidents occurring over the past few years. In this study we used a time series model to understand the trend of accidents, and ascertain the viability of applying ARIMA models on data from Taybad city.

METHODS

This study is a cross-sectional study. We used data from accidents occurring in Taybad between 2007 and 2011. We obtained the data from the Ministry of Health (MOH) and used the time series method with a time lag of one month. After plotting the trend, non-stationary data in mean and variance were removed using Box-Cox transformation and a differencing method respectively. The ACF and PACF plots were used to control the stationary situation.

RESULTS

The traffic accidents in our study had an increasing trend over the five years of study. Based on ACF and PACF plots gained after applying Box-Cox transformation and differencing, data did not fit to a time series model. Therefore, neither ARIMA model nor seasonality were observed.

CONCLUSION

Traffic accidents in Taybad have an upward trend. In addition, we expected either the AR model, MA model or ARIMA model to have a seasonal trend, yet this was not observed in this analysis. Several reasons may have contributed to this situation, such as uncertainty of the quality of data, weather changes, and behavioural factors that are not taken into account by time series analysis.

Critical considerations in evaluating scientific evidence of health effects of ambient ozone: a conference report

The U.S. Environmental Protection Agency (EPA), under the authority of the Clean Air Act (CAA), is required to promulgate National Ambient Air Quality Standards (NAAQSs) for criteria air pollutants, including ozone. Each NAAQS includes a primary health-based standard and a secondary or welfare-based standard. This paper considers only the science used for revision of the primary standard for ozone in 2008. This paper summarizes deliberations of a small group of scientists who met in June 2007 to review the scientific information informing the EPA Administrator's proposed revision of the 1997 standard. The Panel recognized that there is no scientific methodology that, in the absence of judgment, can define the precise numerical level, related averaging time, and statistical form of the NAAQS. The selection of these elements of the NAAQS involves policy judgments that should be informed by scientific information and analyses. Thus, the Panel members did not feel it appropriate to offer either their individual or collective judgment on the specific numerical level of the NAAQS for ozone. The Panel deliberations focused on the scientific data available on the health effects of exposure to ambient concentrations of ozone, controlled ozone exposure studies with human volunteers, long-term epidemiological studies, time- series epidemiological studies, human panel studies, and toxicological investigations. The deliberations also dealt with the issue of background levels of ozone of nonanthropogenic origin and issues involved with conducting formal risk assessments of the health impacts of current and prospective levels of ambient ozone. The scientific issues that were central to the EPA Administrator's 2008 revision of the NAAQS for ozone will undoubtedly also be critical to the next review of the ozone standard. That review should begin very soon if it is to be completed within the 5-year cycle specified in the CAA. It is hoped that this Report will stimulate discussion of these scientific issues, conduct of additional research, and conduct of new analyses that will provide an improved scientific basis for the policy judgment that will have to be made by a future EPA Administrator in considering potential revision of the ozone standard.

Health effects of particulate air pollution

In the 1980's it was generally felt that particulate air pollution concentrations in the United States were not a hazard to the public health. However, in the early 1990's the application of econometric time-series studies and prospective cohort studies suggested increased mortality associated with acute (daily) and chronic (decades) exposures to particulate air pollution commonly observed in the developed world. The epidemiologic evidence was not supported by evidence of causal associations from other disciplines. Nevertheless, the EPA moved to tighten controls on fine particulate air pollution. The debate over the science was played out in public hearings and the courts. The experience provides lessons on the use of epidemiologic data in setting public policy.

Evidence of Health Impacts of Sulfate-and Nitrate-Containing Particles in Ambient Air

Ambient particulate matter (PM) is a complex mixture of inorganic and organic compounds. The U.S. Environmental Protection Agency (EPA) regulates PM as a criteria pollutant and promulgates National Ambient Air Quality Standards for it. The PM indicator is based on mass concentration, unspecified as to chemical composition, for specific size fractions. The numerical standards are based on epidemiologic evidence of associations between the various size-related particle mass concentrations as indicators and excess mortality and cardiorespiratory health effects as endpoints. The U.S. National Research Council has stated that more research is needed to differentiate the apparent health effects associated with different particle chemical constituents. Sulfate and nitrate constitute a significant portion of the particle mass in the atmosphere, but are accompanied by similar amounts of carbonaceous material, along with low concentrations of various species, including bioactive organic compounds and redox cycling metals. Extensive animal and human toxicology data show no significant effects for particles consisting only of sulfate and nitrate compounds at levels in excess of ambient air concentrations. A few epidemiologic studies, including both short-term time-series studies and long-term cohort studies, have included the sulfate content of PM as a specific variable in health effect analyses. There are much less data for nitrate. The results from the epidemiologic studies with PM sulfate are inconsistent. A detailed analysis of the time-series epidemiological studies shows that PM sulfate has a weaker "risk factor" than PM2.5 for health effects. Since sulfate is correlated with PM2.5, this result is inconsistent with sulfate having a strong health influence. However, there are many limitations with these types of studies that warrant caution for any comparison between a chemical component and mass concentration. In total, the epidemiologic and toxicologic evidence provide little or no support for a causal association of PM sulfate and health risk at ambient concentrations. For nitrate-containing PM, virtually no epidemiological data exist. Limited toxicological evidence does not support a causal association between particulate nitrate compounds and excess health risks. There are some possible indirect processes through which sulfate and nitrate in PM may affect health-related endpoints, including interactions with certain metal species and a linkage with production of secondary organic matter. There is insufficient evidence to include or exclude these processes as being potentially important to PM-associated health risk.

Effect of short-term exposure to air pollution and pollen on medical emergency calls: a case-crossover study in Spain

BACKGROUND

A symmetric case-crossover design was used to analyse the short-term relationship between air pollution, pollen and emergency calls to medical services.

METHODS

This study covered patients who made medical emergency calls in the City of Vigo (Spain) during the period 1996-1999. Morbidity data were obtained from the records of the 061 Medical Emergency Control Center, in its capacity as the body officially coordinating all medical emergencies by telephone. Air pollution data were furnished by the Vigo Municipal Air Pollution Surveillance Grid. Pollen levels were provided by the staff of the Spanish Aerobiology Network in Vigo.

RESULTS

A rise of 10 microg/m(3) in ambient particulate levels led to the risk of medical emergency calls requesting attention increasing by: (i) 1.97% [95% confidence interval (95% CI): 1.83-2.11%] for circulatory causes on the same day; (ii) 1.95% (95% CI: 1.76-2.14%) for respiratory causes at 2 days and (iii) 1.34% (95% CI: 1.23-1.45%) for combined circulatory and respiratory causes on the same day. A number of pollens displayed a statistically significant relationship with emergency calls. No interaction was in evidence between pollens and air pollutants.

CONCLUSIONS

While elevations in particulate air pollution increase medical emergency calls because of cardiac or respiratory causes or both combined, elevations in pollen levels increase medical emergency calls because of respiratory causes.

Air pollution and postneonatal mortality in a tropical city: Kaohsiung, Taiwan

With growing evidence of the association between daily mortality and air pollution in adults, it is important to investigate whether infants are also susceptible to the adverse health effects of ambient air pollutants. The purpose of this study is to examine the relationship between air pollution and postneonatal mortality in Kaohsiung, Taiwan, a large industrial city with a tropical climate, during the period 1994-2000, using a case-crossover analysis. Case-crossover analysis provides an alternative to Poisson time-series regression for studying the short-term adverse health effects of air pollution. The air pollutants examined included particulate matter (PM(10)), sulfur dioxide (SO(2)), ozone (O(3)), nitrogen dioxide (NO(2)), and carbon monoxide (CO). The risk of postneonatal deaths was estimated to increase by 4.0% per 67 microg/m(3) (the interquartile range in daily ambient concentration of PM(10)) for PM(10), 1.8% per 17.84 ppb for NO(2), 5.1% per 0.31 ppm for CO, and 4.6% per 19.20 ppb for O(3). Although positive, none of these associations achieved statistical significance. The established link between air pollution levels and infant mortality may not be as strong in cities with tropical climates, although other factors such as differences in pollutant mix or the underlying health of the postneonates may explain the lack of a strong association in this study. Further studies of this type in cities with varying climates and cultures are needed.

Time-Varying Coefficient Models for the Analysis of Air Pollution and Health Outcome Data

In this article a time-varying coefficient model is developed to examine the relationship between adverse health and short-term (acute) exposure to air pollution. This model allows the relative risk to evolve over time, which may be due to an interaction with temperature, or from a change in the composition of pollutants, such as particulate matter, over time. The model produces a smooth estimate of these time-varying effects, which are not constrained to follow a fixed parametric form set by the investigator. Instead, the shape is estimated from the data using penalized natural cubic splines. Poisson regression models, using both quasi-likelihood and Bayesian techniques, are developed, with estimation performed using an iteratively re-weighted least squares procedure and Markov chain Monte Carlo simulation, respectively. The efficacy of the methods to estimate different types of time-varying effects are assessed via a simulation study, and the models are then applied to data from four cities that were part of the National Morbidity, Mortality, and Air Pollution Study.

Correlation between air pollution and postneonatal mortality in a subtropical city: Taipei, Taiwan

With growing evidence of the association between daily mortality and air pollution exposure in adults, it is important to investigate whether infants are also susceptible. The purpose of this study was to examine the relationship between air pollution exposure and postneonatal, defined as infant of more than 27 d and less than 1 yr old, mortality in Taipei, Taiwan's largest city, which has a subtropical climate, for the period 1994-2000, using a case-crossover analysis. This design is an alternative to Poisson time-series regression for studying the short-term adverse health effects of air pollution. The air pollutants examined included particulate matter (PM10), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). The risk of postneonatal deaths was estimated to increase by 3.1% for PM10, 4.1% for SO2, 1.7% for NO2, 3.8% for CO, and 0.1% for O3 for each interquartile range change, respectively. However, the associations were without statistical significance. The established link between air pollution levels and infant mortality may not be as strong in cities with subtropical climates, although other factors such as differences in pollutant component composition or the underlying health of the postneonates may explain the lack of a strong association in this study. Further studies of this type in cities with varying climates and cultures are needed.

A comparison of methods for the analysis of recurrent health outcome data with environmental covariates

Recurrent events such as repeated hospital admissions for the same health outcome occur frequently in environmental health studies. Dewanji and Moolgavkar proposed a flexible parametric model and a conditional likelihood analysis for recurrent events based on a Poisson process formulation. In this paper, we examine the statistical properties of the Dewanji-Moolgavkar (DM) estimator of the risk of an adverse health outcome associated with environmental exposures based on recurrent event data using computer simulation. We also compare the DM approach with both case-crossover analysis for multiple observations and time series analysis when there are no subject-specific covariates. When using a correctly specified model, the DM method produced better estimates with respect to relative mean square error when each subject had constant or curved baseline intensity functions than it did when baseline intensities were increasing or decreasing in a linear fashion. For under-specified models, the DM method outperformed case-crossover analysis for decreasing straight line intensity functions, was outperformed by case-crossover analysis for increasing straight line intensity functions, and was roughly equivalent to case-crossover analysis for constant and curved intensity functions. Case-crossover analysis produced superior risk estimates more frequently than the other two methods in the cases considered here, especially for linear representations of the baseline intensities.

Ozone exposure and mortality: an empiric bayes metaregression analysis

BACKGROUND

Results from time-series epidemiologic studies evaluating the relationship between ambient ozone concentrations and premature mortality vary in their conclusions about the magnitude of this relationship, if any, making it difficult to estimate public health benefits of air pollution control measures. We conducted an empiric Bayes metaregression to estimate the ozone effect on mortality, and to assess whether this effect varies as a function of hypothesized confounders or effect modifiers.

METHODS

We gathered 71 time-series studies relating ozone to all-cause mortality, and we selected 48 estimates from 28 studies for the metaregression. Metaregression covariates included the relationship between ozone concentrations and concentrations of other air pollutants, proxies for personal exposure-ambient concentration relationships, and the statistical methods used in the studies. For our metaregression, we applied a hierarchical linear model with known level-1 variances.

RESULTS

We estimated a grand mean of a 0.21% increase (95% confidence interval = 0.16-0.26%) in mortality per 10-microg/m increase of 1-hour maximum ozone (0.41% increase per 10 ppb) without controlling for other air pollutants. In the metaregression, air-conditioning prevalence and lag time were the strongest predictors of between-study variability. Air pollution covariates yielded inconsistent findings in regression models, although correlation analyses indicated a potential influence of summertime PM2.5.

CONCLUSIONS

These findings, coupled with a greater relative risk of ozone in the summer versus the winter, demonstrate that geographic and seasonal heterogeneity in ozone relative risk should be anticipated, but that the observed relationship between ozone and mortality should be considered for future regulatory impact analyses.

A Meta-Analysis of Time-Series Studies of Ozone and Mortality With Comparison to the National Morbidity, Mortality, and Air Pollution Study

BACKGROUND

Although many time-series studies of ozone and mortality have identified positive associations, others have yielded null or inconclusive results, making the results of these studies difficult to interpret.

METHODS

We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups, cause-specific mortality, and concentration metrics. We compared results with pooled estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. urban centers from 1987 to 2000.

RESULTS

Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current-day ozone exposure. In both analyses, results were insensitive to adjustment for particulate matter and model specifications. In the meta-analysis, a 10-ppb increase in daily ozone at single-day or 2-day average of lags 0, 1, or 2 days was associated with an 0.87% increase in total mortality (95% posterior interval = 0.55% to 1.18%), whereas the lag 0 NMMAPS estimate is 0.25% (0.12% to 0.39%). Several findings indicate possible publication bias: meta-analysis results were consistently larger than those from NMMAPS; meta-analysis pooled estimates at lags 0 or 1 were larger when only a single lag was reported than when estimates for multiple lags were reported; and heterogeneity of city-specific estimates in the meta-analysis were larger than with NMMAPS.

CONCLUSIONS

This study provides evidence of short-term associations between ozone and mortality as well as evidence of publication bias.

Associations Between Ozone and Daily Mortality

BACKGROUND

There is ample evidence that short-term ozone exposure is associated with transient decrements in lung functions and increased respiratory symptoms, but the short-term mortality effect of such exposures has not been established.

METHODS

We conducted a review and meta-analysis of short-term ozone mortality studies, identified unresolved issues, and conducted an additional time-series analysis for 7 U.S. cities (Chicago, Detroit, Houston, Minneapolis-St. Paul, New York City, Philadelphia, and St. Louis).

RESULTS

Our review found a combined estimate of 0.39% (95% confidence interval = 0.26-0.51%) per 10-ppb increase in 1-hour daily maximum ozone for the all-age nonaccidental cause/single pollutant model (43 studies). Adjusting for the funnel plot asymmetry resulted in a slightly reduced estimate (0.35%; 0.23-0.47%). In a subset for which particulate matter (PM) data were available (15 studies), the corresponding estimates were 0.40% (0.27-0.53%) for ozone alone and 0.37% (0.20-0.54%) with PM in model. The estimates for warm seasons were generally larger than those for cold seasons. Our additional time-series analysis found that including PM in the model did not substantially reduce the ozone risk estimates. However, the difference in the weather adjustment model could result in a 2-fold difference in risk estimates (eg, 0.24% to 0.49% in multicity combined estimates across alternative weather models for the ozone-only all-year case).

CONCLUSIONS

Overall, the results suggest short-term associations between ozone and daily mortality in the majority of the cities, although the estimates appear to be heterogeneous across cities.

A review and critique of the EPA’s rationale for a fine particle standard

I review the rationale for the Environmental Protection Agency's 1996 fine particle standard, which was based almost entirely on the epidemiological data with neither support from Toxicology nor understanding of mechanism. While many epidemiological papers available in 1996 reported associations between ambient particles and adverse effects on human health, many others did not and the evidence fell far short of supporting a causal association between particle mass concentration and human health. The literature appearing after 1996 further complicates the picture. The large studies that have appeared after 1996, such as National Mortality Morbidity and Air Pollution Study, and the reanalyses of the American Cancer Society II study, report risks that are substantially smaller than the risks reported in the 1996 Criteria Document and Staff Paper. Moreover, concerns about confounding by weather, temporal trends and co-pollutants remain unresolved. Other issues having to do with model choice have resurfaced as a result of reanalyses of critical data to address a glitch in a widely used software package for time-series epidemiology studies of air pollution. Finally, contemporary examples show that the results of observational epidemiology studies can be seriously biased, particularly when estimated risks are small, as is the case with studies of air pollution. The Agency has largely ignored these issues. I conclude that a particle mass standard is not defensible on the basis of a causal association between ambient particle mass and adverse effects on human health. Such a standard may be justifiable on the basis of the precautionary principle, however. The Agency could argue that the Science raises concerns about current levels of air pollution, and that reduction of ambient fine particulate matter mass, if it could be achieved without an increase in the level of the ultrafines, could have positive effects on human health. If the Agency justifies a particulate matter mass standard on these grounds then the debate over the form and level of the standard will, for all practical purposes, belong strictly in the Policy arena.

Seasonal analyses of air pollution and mortality in 100 US cities

Time series models relating short-term changes in air pollution levels to daily mortality counts typically assume that the effects of air pollution on the log relative rate of mortality do not vary with time. However, these short-term effects might plausibly vary by season. Changes in the sources of air pollution and meteorology can result in changes in characteristics of the air pollution mixture across seasons. The authors developed Bayesian semiparametric hierarchical models for estimating time-varying effects of pollution on mortality in multisite time series studies. The methods were applied to the database of the National Morbidity and Mortality Air Pollution Study, which includes data for 100 US cities, for the period 1987-2000. At the national level, a 10-microg/m(3) increase in particulate matter less than 10 microm in aerodynamic diameter at a 1-day lag was associated with 0.15% (95% posterior interval (PI): -0.08, 0.39), 0.14% (95% PI: -0.14, 0.42), 0.36% (95% PI: 0.11, 0.61), and 0.14% (95% PI: -0.06, 0.34) increases in mortality for winter, spring, summer, and fall, respectively. An analysis by geographic region found a strong seasonal pattern in the Northeast (with a peak in summer) and little seasonal variation in the southern regions of the country. These results provide useful information for understanding particle toxicity and guiding future analyses of particle constituent data.

Health-related benefits of attaining the 8-hr ozone standard

During the 2000-2002 time period, between 36 and 56% of ozone monitors each year in the United States failed to meet the current ozone standard of 80 ppb for the fourth highest maximum 8-hr ozone concentration. We estimated the health benefits of attaining the ozone standard at these monitors using the U.S. Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program. We used health impact functions based on published epidemiologic studies, and valuation functions derived from the economics literature. The estimated health benefits for 2000 and 2001 are similar in magnitude, whereas the results for 2002 are roughly twice that of each of the prior 2 years. The simple average of health impacts across the 3 years includes reductions of 800 premature deaths, 4,500 hospital and emergency department admissions, 900,000 school absences, and > 1 million minor restricted activity days. The simple average of benefits (including premature mortality) across the 3 years is 5.7 billion dollars [90% confidence interval (CI), 0.6-15.0] for the quadratic rollback simulation method and 4.9 billion dollars (90% CI, 0.5-14.0) for the proportional rollback simulation method. Results are sensitive to the form of the standard and to assumptions about background ozone levels. If the form of the standard is based on the first highest maximum 8-hr concentration, impacts are increased by a factor of 2-3. Increasing the assumed hourly background from zero to 40 ppb reduced impacts by 30 and 60% for the proportional and quadratic attainment simulation methods, respectively.

Assessing ozone-related health impacts under a changing climate

Climate change may increase the frequency and intensity of ozone episodes in future summers in the United States. However, only recently have models become available that can assess the impact of climate change on O3 concentrations and health effects at regional and local scales that are relevant to adaptive planning. We developed and applied an integrated modeling framework to assess potential O3-related health impacts in future decades under a changing climate. The National Aeronautics and Space Administration-Goddard Institute for Space Studies global climate model at 4 degrees x 5 degrees resolution was linked to the Penn State/National Center for Atmospheric Research Mesoscale Model 5 and the Community Multiscale Air Quality atmospheric chemistry model at 36 km horizontal grid resolution to simulate hourly regional meteorology and O3 in five summers of the 2050s decade across the 31-county New York metropolitan region. We assessed changes in O3-related impacts on summer mortality resulting from climate change alone and with climate change superimposed on changes in O3 precursor emissions and population growth. Considering climate change alone, there was a median 4.5% increase in O3-related acute mortality across the 31 counties. Incorporating O3 precursor emission increases along with climate change yielded similar results. When population growth was factored into the projections, absolute impacts increased substantially. Counties with the highest percent increases in projected O3 mortality spread beyond the urban core into less densely populated suburban counties. This modeling framework provides a potentially useful new tool for assessing the health risks of climate change.

Interactions between particulate air pollution and temperature in air pollution mortality time series studies

In many community time series studies on the effect of particulate air pollution on mortality, particulate air pollution is modeled additively. In this study, we investigated the interaction between daily particulate air pollution and daily mean temperature in Cook County, Illinois and Allegheny County, Pennsylvania, using data for the period 1987-1994. This was done through the use of joint particulate air pollution-temperature response surfaces and by stratifying the effect of particulate air pollution on mortality by temperature. Evidence that the effect of particulate air pollution on mortality may depend on temperature is found. However, the results were sensitive to the number of degrees of freedom used in the confounder adjustments, the particulate air pollution exposure measure, and how the effects of temperature on mortality are modeled. The results were less sensitive to the estimation method used--generalized linear models and natural cubic splines or generalized additive models and smoothing splines. The results of this study suggest that in community particulate air pollution mortality time series studies the possibility of an interaction between daily particulate air pollution and daily mean temperature should be considered.

Non-linear short-term effects of airborne pollen levels with allergenic capacity on asthma emergency room admissions in Madrid, Spain

BACKGROUND

Several time-series studies have shown positive associations between pollen levels and asthma morbidity. However, few studies have included air pollution as a potential confounder when examining this relationship, and they have only done so on a linear basis.

OBJECTIVE

To investigate the potential non-linear short-term effects of the types of pollen with allergenic capacity across the whole range of exposure on the daily number of asthma-related hospital emergencies in Madrid for the period 1995-1998.

METHODS

Data were collected on the daily number of asthma emergency room admissions and daily average levels of major types of pollen with allergenic capacity: Olea, Plantago, Poaceae and Urticaceae. We used Poisson regression with generalized additive models, controlling for trend and seasonality, meteorological variables, acute respiratory infections and air pollutants. To study the non-linear effect of pollen levels on asthma emergency room admissions, pollens were categorized into five groups defined on the basis of their respective distributions.

RESULTS

The strongest associations were registered in respect of a lag of 1 day for Urticaceae, a lag of 2 days for Plantago, and a day lag of 3 days for Poaceae. Adjustment for the different types of pollen failed to result in major changes. Non-linearities were evident for pollen levels. The greatest increase in risk vs. the reference category (minimum value - 50th percentile) was observed for the categories between the 95th and 99th percentiles, with increases of 32.0% for Plantago, 32.2% for Poaceae and 24.6% for Urticaceae, and between the 99th percentile and the maximum value, with increases of 31.3%, 78.7% and 49.8%, respectively. Olea was not related with asthma emergency room admissions.

CONCLUSIONS

Pollens with allergenic capacity in Madrid are positively associated with asthma-related hospital emergencies. These associations remain stable when simultaneous adjustment is made for the four types of pollen and for air pollutants and meteorological variables. In terms of non-linear effects, Poaceae register the strongest association with asthma emergency room admissions.

Relationship between air pollution and daily mortality in a subtropical city: Taipei, Taiwan

Air pollution has been associated with daily mortality in numerous studies over the past decade. However most of these studies were conducted in the United States and Europe with relatively few done in Asia. In the current study, the association between ambient air pollution and daily mortality in Taipei, Taiwan's largest city which has a subtropical climate was undertaken, for the period 1994-1998 using a case-crossover analysis. This design is an alternative to Poisson time series regression for studying the short-term adverse health effects of air pollution. The air pollutants examined included particulate matter (PM(10)), sulfur dioxide (SO(2)), ozone (O(3)), nitrogen dioxide (NO(2)), and carbon monoxide (CO). The largest observed effect, which was without statistical significance, was seen for NO(2) and CO levels on deaths due to respiratory diseases (ORs=1.013 and 1.014, respectively). The well established link between air pollution levels and daily mortality may not be as strong in cities in subtropical areas, although other factors such as differences in pollutant mix or the underlying health of the population may explain the lack of a strong association in this study. Further studies of this type in cities with varying climates and cultures are needed.

Comparison of time series and case-crossover analyses of air pollution and hospital admission data

BACKGROUND

Time series analysis is the most commonly used technique for assessing the association between counts of health events over time and exposure to ambient air pollution. Recently, case-crossover analysis has been proposed as an alternative analytical approach. While each technique has its own advantages and disadvantages, there remains considerable uncertainty as to which statistical methodology is preferable for evaluating data of this type.

METHODS

The objective of this paper is to evaluate the performance of different variations of these two procedures using computer simulation. Hospital admission data were generated under realistic models with known parameters permitting estimates based on time series and case-crossover analyses to be compared with these known values.

RESULTS

While accurate estimates can be achieved with both methods, both methods require some decisions to be made by the researcher during the course of the analysis. With time series analysis, it is necessary to choose the time span in the LOESS smoothing process, or degrees of freedom when using natural cubic splines. For case-crossover studies using either uni- or bi-directional control selection strategies, the choice of time intervals needs to be made.

CONCLUSIONS

We prefer the times series approach because the best estimates of risk that can be obtained with time series analysis are more precise than the best estimates based on case-crossover analysis.

Relationship between air pollution and daily mortality in a tropical city: Kaohsiung, Taiwan

Air pollution has been associated with daily mortality in numerous studies over the past decade. However, most of these studies were conducted in the United States and Europe, with relatively few done in Asia. In this study, the association between ambient air pollution and daily mortality in Kaohsiung, Taiwan, a large industrial city with a tropical climate, was investigated for the period 1994-2000 using a case-crossover analysis. This design is an alternative to Poisson time-series regression for studying the short-term adverse health effects of air pollution. The air pollutants examined included particulate matter (PM10), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). No significant effects were found between PM10 and SO2 exposure levels and respiratory-related mortality. The well-established link between air pollution levels and daily mortality may not be as strong in cities in tropical areas, although other factors such as differences in pollutant mixtures or underlying health of the population may explain the lack of a strong association in this study. Further studies of this type in cities with varying climates and cultures are needed.

Effect of short-term exposure to gaseous pollution on asthma hospitalisation in children: a bi-directional case-crossover analysis

STUDY OBJECTIVE

Assess associations between short-term exposure to gaseous pollutants and asthma hospitalisation among boys and girls 6 to12 years of age.

DESIGN

A bi-directional case-crossover analysis was used. Conditional logistic regression models were fitted to the data for boys and girls separately. Exposures averaged over periods ranging from one to seven days were used to assess the effects of gaseous pollutants on asthma hospitalisation. Estimated relative risks for asthma hospitalisation were calculated for an incremental exposure corresponding to the interquartile range in pollutant levels, adjusted for daily weather conditions and concomitant exposure to particulate matter.

SETTING

Toronto, Ontario, Canada.

PARTICIPANTS

A total of 7319 asthma hospitalisations for children 6 to 12 years of age (4629 for boys and 2690 for girls) in Toronto between 1981 and 1993.

MAIN RESULTS

A significant acute effect of carbon monoxide on asthma hospitalisation was found in boys, and sulphur dioxide showed significant effects of prolonged exposure in girls. Nitrogen dioxide was positively associated with asthma admissions in both sexes. The lag time for certain gaseous pollutant effects seemed to be shorter in boys (around two to three days for carbon monoxide and nitrogen dioxide), as compared with girls (about six to seven days for sulphur dioxide and nitrogen dioxide). The effects of gaseous pollutants on asthma hospitalisation remained after adjustment of particulate matter. The data showed no association between ozone and asthma hospitalisation in children.

CONCLUSIONS

The study showed positive relations between gaseous pollutants (carbon monoxide, sulphur dioxide, and nitrogen dioxide) at comparatively low levels and asthma hospitalisation in children, using bi-directional case-crossover analyses. Though, the effects of certain specific gaseous pollutants were found to vary in boys and girls.

A population exposure model for particulate matter: case study results for PM(2.5) in Philadelphia, PA

A population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied in a case study of daily PM(2.5) exposures for the population living in Philadelphia, PA. SHEDS-PM is a probabilistic model that estimates the population distribution of total PM exposures by randomly sampling from various input distributions. A mass balance equation is used to calculate indoor PM concentrations for the residential microenvironment from ambient outdoor PM concentrations and physical factor data (e.g., air exchange, penetration, deposition), as well as emission strengths for indoor PM sources (e.g., smoking, cooking). PM concentrations in nonresidential microenvironments are calculated using equations developed from regression analysis of available indoor and outdoor measurement data for vehicles, offices, schools, stores, and restaurants/bars. Additional model inputs include demographic data for the population being modeled and human activity pattern data from EPA's Consolidated Human Activity Database (CHAD). Model outputs include distributions of daily total PM exposures in various microenvironments (indoors, in vehicles, outdoors), and the contribution from PM of ambient origin to daily total PM exposures in these microenvironments. SHEDS-PM has been applied to the population of Philadelphia using spatially and temporally interpolated ambient PM(2.5) measurements from 1992-1993 and 1990 US Census data for each census tract in Philadelphia. The resulting distributions showed substantial variability in daily total PM(2.5) exposures for the population of Philadelphia (median=20 microg/m(3); 90th percentile=59 microg/m(3)). Variability in human activities, and the presence of indoor-residential sources in particular, contributed to the observed variability in total PM(2.5) exposures. The uncertainty in the estimated population distribution for total PM(2.5) exposures was highest at the upper end of the distribution and revealed the importance of including estimates of input uncertainty in population exposure models. The distributions of daily microenvironmental PM(2.5) exposures (exposures due to time spent in various microenvironments) indicated that indoor-residential PM(2.5) exposures (median=13 microg/m(3)) had the greatest influence on total PM(2.5) exposures compared to the other microenvironments. The distribution of daily exposures to PM(2.5) of ambient origin was less variable across the population than the distribution of daily total PM(2.5) exposures (median=7 microg/m(3); 90th percentile=18 microg/m(3)) and similar to the distribution of ambient outdoor PM(2.5) concentrations. This result suggests that human activity patterns did not have as strong an influence on ambient PM(2.5) exposures as was observed for exposure to other PM(2.5) sources. For most of the simulated population, exposure to PM(2.5) of ambient origin contributed a significant percent of the daily total PM(2.5) exposures (median=37.5%), especially for the segment of the population without exposure to environmental tobacco smoke in the residence (median=46.4%). Development of the SHEDS-PM model using the Philadelphia PM(2.5) case study also provided useful insights into the limitations of currently available data for use in population exposure models. In addition, data needs for improving inputs to the SHEDS-PM model, reducing uncertainty and further refinement of the model structure, were identified.

Epidemiological studies of acute ozone exposures and mortality

Many, but not all, observational epidemiological studies of ozone (O(3)) air pollution have yielded significant associations between variations in daily ambient concentrations of this pollutant and a wide range of adverse health outcomes. We evaluate some past epidemiological studies that have assessed the short-term association of O(3) with mortality, and investigate one possible reason for variations in their O(3) effect estimate, i.e., differences in their approaches to the modeling of weather influences on mortality. For all of the total mortality-air pollution time-series studies considered, the combined analysis yielded a relative risk, RR=1.036 per 100-ppb increase in daily 1-h maximum O(3) (95% CI: 1.023-1.050). However, the subset of studies that specified the nonlinear nature of the temperature-mortality association yielded a combined estimate of RR=1.056 per 100 ppb (95% CI: 1.032-1.081). This indicates that past time-series studies using linear temperature-mortality specifications have underpredicted the premature mortality effects of O(3) air pollution. For Detroit, MI, an illustrative analysis of daily total mortality during 1985-1990 also indicated that the model weather specification choice can influence the O(3) health effects estimate. Results were intercompared for alternative weather specifications. Nonlinear specifications of temperature and relative humidity (RH) yielded lower intercorrelations with the O(3) coefficient, and larger O(3) RR estimates, than a base model employing a simple linear spline of hot and cold temperature. We conclude that, unlike for particulate matter (PM) mass, the mortality effect estimates derived by time-series analyses for O(3) can be sensitive to the way that weather is addressed in the model. The same may well also be true for other pollutants with largely temperature-dependent formation mechanisms, such as secondary aerosols. Generally, we find that the O(3)-mortality effect estimate increases in size and statistical significance when the nonlinearity and the humidity interaction of the temperature-health effect association are incorporated into the model weather specification. We recommend that a minimization of the intercorrelations of model coefficients be considered (along with other critical factors such as goodness of fit, autocorrelation, and overdispersion) when specifying such a model, especially when individual coefficients are to be interpreted for risk estimation.

Short-term effects of air pollution on mortality in the cities of Rouen and Le Havre, France, 1990-1995

In this study, the authors examined the short-term effects of ambient air pollution on mortality across 2 French cities: Rouen and Le Havre. In Poisson regression models, which controlled for day-of-week effects, the authors used nonparametric smoothing to control for temporal trend, weather, and influenza epidemics. In Rouen, an interquartile range increase of 60.5-94.1 microg/m3 of ozone was associated with an increase of 4.1% (95% confidence interval = 0.6, 7.8) of total mortality. Daily variations in sulfur dioxide (interquartile range increase = 17.6-36.4 microg/m3) were also associated with an 8.2% increase (95% confidence interval = 0.4, 16.6) in respiratory mortality. An increase of 6.1% (95% confidence interval = 1.5, 10.9) of cardiovascular mortality was also observed with an interquartile range increase of nitrogen dioxide (i.e., 25.3-42.2 microg/m3). With respect to Le Havre, an interquartile range increase in daily levels of sulfur dioxide (11.3-35.6 microg/m3) was associated with an increase of approximately 3% (95% confidence interval = 0.8, 5) of cardiovascular mortality. For particulate matter less than or equal to 13 microm in diameter (interquartile increase = 21.5, 45.4 microg/m3), an increase of 6.2% (95% confidence interval = 0.1, 12.8) was observed. The estimates of pollutant effects and their standard deviations were slightly affected by the degree of smoothing temporal variations in this study. When low collinearity was present, the 2-pollutant models provided acceptable estimates of pollutant effects. They suggested that the ozone effect was independent of the Black Smoke effect, and that the effects of sulfur dioxide and nitrogen dioxide were unlikely to be confounded by ozone concentrations. However, high collinearity leads to large estimates of the pollutant coefficient variances and, therefore, leads to inaccurate estimates of pollutant effects. The analysis of the contributory effects of different pollutant mixtures requires further investigation in those instances in which high collinearity between pollutants is present.

What do epidemiologic findings tell us about health effects of environmental aerosols?

In the last 10 years there has been an abundance of new epidemiological studies on health effects of particulate air pollution. The overall evidence suggests that fine particulate pollution can be an important risk factor for cardiopulmonary disease. Long-term, repeated exposure to fine particulate air pollution may increase the risk of chronic respiratory disease and the risk of cardiopulmonary mortality. Short-term exposures exacerbate existing cardiovascular and pulmonary disease and increase the risk of becoming symptomatic, requiring medical attention, or even dying. This paper outlines the results of the basic epidemiologic studies and briefly reviews and discusses recent studies that have looked at specific physiologic health endpoints in addition to lung function. A few recent, mostly exploratory pilot studies, have observed particulate pollution associations with blood plasma viscosity, heart rate, heart rate variability, and indicators of bone marrow stimulation. A systemic response to particulate-related pulmonary inflammation remains somewhat speculative. The epidemiologic evidence, nevertheless, seems consistent with the hypothesis that particle-induced pulmonary inflammation, cytokine release, and altered cardiac autonomic function may be part of the pathophysiological mechanisms or pathways linking particulate pollution with cardiopulmonary disease.

The effects of changing weather on public health

Many diseases are influenced by weather conditions or display strong seasonality, suggestive of a possible climatic contribution. Projections of future climate change have, therefore, compelled health scientists to re-examine weather/disease relationships. There are three projected physical consequences of climate change: temperature rise, sea level rise, and extremes in the hydrologic cycle. This century, the Earth has warmed by about 0.5 degrees centigrade, and the mid-range estimates of future temperature change and sea level rise are 2.0 degrees centigrade and 49 centimeters, respectively, by the year 2100. Extreme weather variability associated with climate change may especially add an important new stress to developing nations that are already vulnerable as a result of environmental degradation, resource depletion, overpopulation, or location (e.g. low-lying coastal deltas). The regional impacts of climate change will vary widely depending on existing population vulnerability. Health outcomes of climate change can be grouped into those of: (a) direct physical consequences, e.g. heat mortality or drowning; (b) physical/chemical sequelae, e.g. atmospheric transport and formation of air pollutants; (c) physical/biological consequences, e.g. response of vector- and waterborne diseases, and food production; and (d) sociodemographic impacts, e.g. climate or environmentally induced migration or population dislocation. Better understanding of the linkages between climate variability as a determinant of disease will be important, among other key factors, in constructing predictive models to guide public health prevention.

Daily deaths are associated with combustion particles rather than SO(2) in Philadelphia

OBJECTIVES

To assess whether the association between SO(2) and daily deaths in Philadelphia during the years 1974-88 is due to its correlation with airborne particles, and vice versa.

METHODS

There is a significant variation in the relation between total suspended particulate (TSP) and SO(2) in Philadelphia by year and season. Firstly, 30 separate regressions were fitted for each pollutant in the warm and cold season of each year. These regressions controlled for weather, long term temporal patterns, and day of the week. Then a meta-regression was performed to find whether the effect of SO(2) was due to TSP, or vice versa.

RESULTS

Controlling for TSP, there was no significant association between SO(2) and daily deaths. By contrast, in periods when TSP was less correlated with SO(2), its association with daily deaths was higher. However, all of the association between TSP and daily deaths was explained by its correlation with extinction coefficient, a measurement of the scattering of light by fine particles, which has been shown to be highly correlated with fine combustion particles in Philadelphia.

CONCLUSIONS

The association between air pollution and daily deaths in Philadelphia is due to fine combustion particles, and not to SO(2).

Migration bias in ecologic studies

Differential migration may provoke bias in an epidemiological assessment of the public health risks from exposure to environmental agents, particularly in ecologic studies of health outcomes with a long latency or induction period. The potential impact of migration bias on epidemiological research is complex, and it depends not only on the direction of the factor-related migration, but also on its extent. This study shows that even a small amount of differential migration can bias the assessment of the exposure outcome relationship. Migration bias may result from a number of circumstances that are related to the way in which 'populations' are defined and ascertained. It is important to understand and minimise this type of bias in epidemiological research.

Daily mortality in relation to weather and air pollution in Christchurch, New Zealand

OBJECTIVE

To investigate the relationship between the daily number of deaths, weather and ambient air pollution.

METHOD

An ecological study. We assembled daily data for the city of Christchurch, New Zealand (population 300,000) from June 1988 to December 1993. We used Poisson regression models, controlling for season using a parametric method.

RESULTS

Above the third quartile (20.5 degrees C) of maximum temperature, an increase of 1 degree C was associated with a 1% (95% CI: 0.4 to 2.1%) increase in all-cause mortality and a 3% (0.1 to 6.0%) increase in respiratory mortality. An increase in PM10 of 10 micrograms/m3 was associated (after a lag of one day) with a 1% (0.5 to 2.2%) increase in all-cause mortality and a 4% (1.5 to 5.9%) increase in respiratory mortality. We found no evidence of interaction between the effects of temperature and particulate air pollution.

CONCLUSIONS

High temperatures and particulate air pollution are independently associated with increased daily mortality in Christchurch. The fact that these results are consistent with those of similar studies in other countries strengthens the argument that the associations are likely to be causal.

IMPLICATIONS

These findings contribute to evidence of health consequences of fuel combustion, both in the short term (from local air pollution) and in the long term (from the global climatic effects of increased atmospheric CO2).

Short-term associations between outdoor air pollution and mortality in London 1992-4

OBJECTIVES

A previous study of the short term effects of air pollution in London from April 1987 to March 1992 found associations between all cause mortality and black smoke and ozone, but no clear evidence of specificity for cardiorespiratory deaths. London data from 1992 to 1994 were analysed to examine the consistency of results over time and to include particles with a mean aerodynamic diameter of 10 microns (PM10) and carbon monoxide.

METHODS

Poisson regression was used of daily mortality counts grouped by age and diagnosis, adjusting for trend, seasonality, calendar effects, deaths from influenza, meteorology, and serial correlation. The pollutants examined were particles (PM10 and black smoke), nitrogen dioxide, ozone, sulphur dioxide, and carbon monoxide with single and cumulative lags up to 3 days.

RESULTS

No significant associations were found between any pollutant and all cause mortality, but, with the exception of ozone, all estimates were positive. Each pollutant apart from ozone was significantly associated with respiratory mortality; PM10 showed the largest effect (4% increase in deaths of all ages for a 10th-90th percentile increment). The pollutants significantly associated with cardiovascular deaths were nitrogen dioxide, ozone, and black smoke but there was no evidence of an association with PM10. In two pollutant models of respiratory deaths, the effect of black smoke, which in London indicates fine particles of diesel origin, was independent of that of PM10, but not vice versa.

CONCLUSION

These results from a new data set confirm a previous report that there are associations between various air pollutants and daily mortality in London. This new study found greater specificity for associations with respiratory and cardiovascular deaths, and this increases the plausibility of a causal explanation. However, the effects of ozone found in the earlier study were not replicated. The fraction of PM10 which comprises black smoke accounted for much of the effect of PM10.

Does living near a constellation of petrochemical, steel, and other industries impair health?

OBJECTIVES

To investigate concern that local industrial air pollution in Teesside, England, was causing poor health, several areas there were compared with parts of the City of Sunderland.

METHODS

Populations in similar social and economic circumstances but varying in their proximity to major industries were compared. Study populations lived in 27 housing estates in Teesside and Sunderland, north east England, with some data from subsets of estates. The estates were aggregated into zones (designated as A, B, and C in Teesside where A is closest to and C furthest from industry, and S in Sunderland). Zone S provided a reference area. The hypothesis was that a health gradient both within Teesside (A > B > C) and between Teesside and Sunderland (ABC > S) would indicate a possible health effect of local industrial air pollution. Data presented were: mortality (1981-91) from 27 housing estates; population self completion questionnaire survey data (1993, 9115 subjects) from 15 housing estates; and general practitioner (GP) consultation data (1989-94) from 2201 subjects in 12 Teesside estates.

RESULTS

The populations in the four zones were comparable for indicators including smoking habits, residential histories, and unemployment. All cause and cause specific mortalities were high compared with England and Wales. Mortality in all Teesside zones (ABC) combined was mostly higher than in zone S. In people aged 0-64, lung cancer and respiratory disease showed gradients with highest mortality in areas closest to industry (A > B > C and ABC > S). The association was clearest for lung cancer in women (0-64 years old, trend across zones ABC, p = 0.07, directly standardised rate ratio relative to zone S was 169 (95% confidence interval (95% CI) 116-122)). There were no important, consistent gradients in the hypothesised direction between zones in consultation rates in general practice, and self reported respiratory and nonrespiratory health including asthma.

CONCLUSIONS

There was no clear evidence that living close to industry was associated with morbidity, including asthma, or for most measures of mortality. For lung cancer in women the gradients indicated a health effect of local industrial air pollution. In the age group 0-64 observed gradients in lung cancer in men and mortality from respiratory disease in men and women were consistent with the study hypothesis, although not significant. The reasons for the different patterns at different ages, and between men and women, remain a puzzle.

Air pollution, pollens, and daily admissions for asthma in London 1987-92

BACKGROUND

A study was undertaken to investigate the relationship between daily hospital admissions for asthma and air pollution in London in 1987-92 and the possible confounding and modifying effects of airborne pollen.

METHODS

For all ages together and the age groups 0-14, 15-64 and 65+ years, Poisson regression was used to estimate the relative risk of daily asthma admissions associated with changes in ozone, sulphur dioxide, nitrogen dioxide and particles (black smoke), controlling for time trends, seasonal factors, calendar effects, influenza epidemics, temperature, humidity, and autocorrelation. Independent effects of individual pollutants and interactions with aeroallergens were explored using two pollutant models and models including pollen counts (grass, oak and birch).

RESULTS

In all-year analyses ozone was significantly associated with admissions in the 15-64 age group (10 ppb eight hour ozone, 3.93% increase), nitrogen dioxide in the 0-14 and 65+ age groups (10 ppb 24 hour nitrogen dioxide, 1.25% and 2.96%, respectively), sulphur dioxide in the 0-14 age group (10 micrograms/m3 24 hour sulphur dioxide, 1.64%), and black smoke in the 65% age group (10 micrograms/m3 black smoke, 5.60%). Significant seasonal differences were observed for ozone in the 0-14 and 15-64 age groups, and in the 0-14 age group there were negative associations with ozone in the cool season. In general, cumulative lags of up to three days tended to show stronger and more significant effects than single day lags. In two-pollutant models these associations were most robust for ozone and least for nitrogen dioxide. There was no evidence that the associations with air pollutants were due to confounding by any of the pollens, and little evidence of an interaction between pollens and pollution except for synergism of sulphur dioxide and grass pollen in children (p < 0.01).

CONCLUSIONS

Ozone, sulphur dioxide, nitrogen dioxide, and particles were all found to have significant associations with daily hospital admissions for asthma, but there was a lack of consistency across the age groups in the specific pollutant. These associations were not explained by confounding by airborne pollens nor was there convincing evidence that the effects of air pollutants and airborne pollens interact in causing hospital admissions for asthma.

Socioeconomic and environmental covariates of premature mortality in Ontario

This paper contributes to debates on the broad determinants of health and on the policy shift from curative to preventive and protective interventions. It addresses empirically the relative importance of influences on health with a multiple regression analysis of ecologic data from the 49 counties of Ontario. One model achieved high predictive power (that is, Adj R2 > 75%, p < 0.0001). Educational levels were a strong predictor of population health, showing a consistent inverse relationship with premature mortality ratios for both sexes and it was the strongest predictor for females. A low income variable supplied the strongest prediction for male mortality. This variable displayed a positive association with male mortality. Municipal expenditures on environmental protection exerted a negative effect on male mortality. These findings raise questions about the current directions of health policy in Ontario where the provincial government has reduced funding to social and environmental programs, while promising to maintain health care funding.

Mortality in the elderly and ambient ozone concentration during the hot summer, 1994, in Belgium

Extensive investigations were carried out to study the relationship between daily mortality in the elderly, outdoor air temperature, and ozone concentration observed in Belgium during the hot summer, 1994. The two environmental variables were assessed through mean daily temperature and 24-hr ozone concentration, both measured the day before and averaged over the country. Data were stratified by terciles of mean daily temperature in order to reduce the degree of collinearity between the investigated environmental variables. In the first stratum, which ranged from 9.9 to 15.4 degrees C (41 days), mean daily temperature and 24-hr ozone concentration were not correlated while the mean number of daily deaths was higher when 24-hr ozone concentration increased from 45 to 55 micrograms/m3 (P < 0.05). In the second stratum, which ranged from 15.6 to 20.3 degrees C (42 days), mean daily temperature and 24-hr ozone concentration were strongly correlated (r = 0.54, P < 0.0001). In this stratum, the number of daily deaths did not depend on the mean daily temperature but increased linearly with 24-hr ozone concentration within the range 25 to 85.5 micrograms/m3 (P < 0.001). After having examined the possible confounding effect of sulfur dioxide, nitrogen dioxide, fine particulates, and humidity, ozone was found to be the only investigated variable contributing to the increased daily mortality. In the third stratum, which ranged from 20.4 to 27.6 degrees C (40 days), mean daily temperature and 24-hr ozone concentration were also strongly correlated (r = 0.71, P < 0.0001). Daily mortality, in this stratum, was correlated more with mean daily temperature (r = 0.68, P < 0.001) than with 24-hr ozone concentration (r = 0.55, P < 0.001). Nonparametric regression analyses were performed to model the number of daily deaths in the whole range of temperatures. These analyses confirmed the effect of 24-hr ozone concentration on daily mortality already uncovered by the least-squares regression analysis in the second stratum of mean daily temperature. In addition, at levels exceeding 20 degrees C, the effect of ozone concentration on daily mortality was enhanced by temperature owing to a positive interaction between these two variables. The present study thus demonstrated a statistical association between daily mortality, observed in the elderly during the hot summer, 1994, in Belgium, and ambient ozone concentration. This relationship was dependent on the range of temperatures.