The spatial association between community air pollution and mortality: a new method of analyzing correlated geographic cohort data

A Community-Integrated Geographic Information System Study of Air Pollution Exposure Impacts in Colfax, LA

A community-integrated geographic information systems (CIGIS) study assimilating qualitative and quantitative information about human exposures and health was conducted in Colfax, Louisiana, which hosts a commercial open burn/open detonation thermal treatment (TT) facility that destroys waste from Superfund sites, explosives, military ordnances, and propellants. Fifty-eight percent of residents identified as Black, and median annual income was $16,318, with 90% of the population living below the poverty line. We conducted oral history interviews of twenty-nine residents and mined public records to document the community's experiences. Interviews focused on themes of Colfax's history, changing community fabric, resident health, and air pollution. The oral histories and public comments by community members provided information about lived experiences, including several health conditions, toleration of noise and vibration, property damage, and resulting changes to activity levels. These statements provided insight into the extent of suffering experienced by the local community. We also ran dispersion models for dates in 2020 when the waste stream composition, mass, and burn/smoldering times were provided in the facility's public records. The dispersion models placed the air pollution at the homes of residents during some of the time, and waste stream records from the TT facility agree with community testimony about health effects based on the known health effects of those compounds. CIGIS integration of our community-based qualitative data and maps with quantitative air pollution dispersion model output illustrated alignment between community complaints of impacts to health and property, known toxicological information about waste stream compounds, and dispersion model output.

A New Method of Removing Fine Particulates Using an Electrostatic Force

Many studies have found that the concentration of fine particulates in the atmosphere has increased. In particular, when using the bus, the situation in which people are exposed to relatively high concentrations of fine particulates is increasing. The purpose of this study is to reduce exposure to these potentially harmful particulates by introducing open shelters at outdoor bus stops. In order to use it as an outdoor fine particulates reduction device, a brush filter using electrostatic force (EF) was used on an experimental scale and the generation of electrostatic force, according to the material, was examined. As electrostatic force was generated, the fine particulates collection performance was about 90% efficiency. In addition, it was confirmed that the efficiency of each particle size was improved by 57% through structural improvement. Finally, through experimentation, it was confirmed that the brush module can be used for about 70 days.

A Study on Characteristic Emission Factors of Exhaust Gas from Diesel Locomotives

Use of diesel locomotives in transport is gradually decreasing due to electrification and the introduction of high-speed electric rail. However, in Korea, up to 30% of the transportation of passengers and cargo still uses diesel locomotives and diesel vehicles. Many studies have shown that exhaust gas from diesel locomotives poses a threat to human health. This study examined the characteristics of particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbons in diesel locomotive engine exhaust. Emission concentrations were evaluated and compared with the existing regulations. In the case of PM and NOx, emission concentrations increased as engine output increased. High concentrations of CO were detected at engine start and acceleration, while hydrocarbons showed weakly increased concentrations regardless of engine power. Based on fuel consumption and engine power, the emission patterns of PM and gaseous substances observed in this study were slightly higher than the U.S. Environmental Protection Agency Tier standard and the Korean emission standard. Continuous monitoring and management of emissions from diesel locomotives are required to comply with emission standards. The findings of this study revealed that emission factors varied based on fuel consumption, engine power, and actual driving patterns. For the first time, a portable emission measurement system (PEMS), normally used to measure exhaust gas from diesel vehicles, was used to measure exhaust gas from diesel locomotives, and the data acquired were compared with previous results. This study is meaningful as the first example of measuring the exhaust gas concentration by connecting a PEMS to a diesel locomotive, and in the future, a study to measure driving characteristics and exhaust gas using a PEMS should be conducted.

Cancer Mortality Risks from Long-term Exposure to Ambient Fine Particle

BACKGROUND

Few studies have assessed long-term effects of particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) on mortality for causes of cancer other than the lung; we assessed the effects on multiple causes. In Hong Kong, most people live and work in urban or suburban areas with high-rise buildings. This facilitates the estimation of PM2.5 exposure of individuals, taking into account the height of residence above ground level for assessment of the long-term health effects with sufficient statistical power.

METHODS

We recruited 66,820 persons who were ≥65 in 1998 to 2001 and followed up for mortality outcomes until 2011. Annual concentrations of PM at their residential addresses were estimated using PM2.5 concentrations measured at fixed-site monitors, horizontal-vertical locations, and satellite data. We used Cox regression model to assess the HR of mortality for cancer per 10 μg/m(3) increase of PM2.5 RESULTS: PM2.5 was associated with increased risk of mortality for all causes of cancer [HR, 1.22 (95% CI, 1.11-1.34)] and for specific cause of cancer in upper digestive tract [1.42 (1.06-1.89)], digestive accessory organs [1.35 (1.06-1.71)] in all subjects; breast [1.80 (1.26-2.55)] in females; and lung [1.36 (1.05-1.77)] in males.

CONCLUSIONS

Long-term exposures to PM2.5 are associated with elevated risks of cancer in various organs.

IMPACT

This study is particularly timely in China, where compelling evidence is needed to support the pollution control policy to ameliorate the health damages associated with economic growth. Cancer Epidemiol Biomarkers Prev; 25(5); 839-45. ©2016 AACR.

Acute Effects of Nitrogen Dioxide on Cardiovascular Mortality in Beijing: An Exploration of Spatial Heterogeneity and the District-specific Predictors

The exploration of spatial variation and predictors of the effects of nitrogen dioxide (NO₂) on fatal health outcomes is still sparse. In a multilevel case-crossover study in Beijing, China, we used mixed Cox proportional hazard model to examine the citywide effects and conditional logistic regression to evaluate the district-specific effects of NO₂ on cardiovascular mortality. District-specific predictors that could be related to the spatial pattern of NO₂ effects were examined by robust regression models. We found that a 10 μg/m³ increase in daily mean NO₂ concentration was associated with a 1.89% [95% confidence interval (CI): 1.33–2.45%], 2.07% (95% CI: 1.23–2.91%) and 1.95% (95% CI: 1.16–2.72%) increase in daily total cardiovascular (lag03), cerebrovascular (lag03) and ischemic heart disease (lag02) mortality, respectively. For spatial variation of NO₂ effects across 16 districts, significant effects were only observed in 5, 4 and 2 districts for the above three outcomes, respectively. Generally, NO₂ was likely having greater adverse effects on districts with larger population, higher consumption of coal and more civilian vehicles. Our results suggested independent and spatially varied effects of NO₂ on total and subcategory cardiovascular mortalities. The identification of districts with higher risk can provide important insights for reducing NO₂ related health hazards.

Satellite-Based Estimates of Long-Term Exposure to Fine Particles and Association with Mortality in Elderly Hong Kong Residents

BACKGROUND

A limited number of studies on long-term effects of particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) on health suggest it can be an important cause of morbidity and mortality. In Asia where air quality is poor and deteriorating, local data on long-term effects of PM2.5 to support policy on air quality management are scarce.

OBJECTIVES

We assessed long-term effects of PM2.5 on the mortality in a single Asian city.

METHODS

For 10-13 years, we followed up a cohort of 66,820 participants ≥ 65 years of age who were enrolled and interviewed in all 18 Elderly Health Centres of the Department of Health, Hong Kong, in 1998-2001. Their residential addresses were geocoded into x- and y-coordinates, and their proxy exposures to PM2.5 at their addresses in 1 × 1 km grids were estimated from the U.S. National Aeronautics and Space Administration (NASA) satellite data. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5.

RESULTS

Mortality HRs per 10-μg/m3 increase in PM2.5 were 1.14 (95% CI: 1.07, 1.22) for all natural causes, 1.22 (95% CI: 1.08, 1.39) for cardiovascular causes, 1.42 (95% CI: 1.16, 1.73) for ischemic heart disease, 1.24 (95% CI: 1.00, 1.53) for cerebrovascular disease, and 1.05 (95% CI: 0.90, 1.22) for respiratory causes.

CONCLUSIONS

Our methods in using NASA satellite data provide a readily accessible and affordable approach to estimation of a sufficient range of individual PM2.5 exposures in a single city. This approach can expand the capacity to conduct environmental accountability studies in areas with few measurements of fine particles.

CITATION

Wong CM, Lai HK, Tsang H, Thach TQ, Thomas GN, Lam KB, Chan KP, Yang L, Lau AK, Ayres JG, Lee SY, Chan WM, Hedley AJ, Lam TH. 2015. Satellite-based estimates of long-term exposure to fine particles and association with mortality in elderly Hong Kong residents. Environ Health Perspect 123:1167-1172; http://dx.doi.org/10.1289/ehp.1408264.

Agricultural crop density and risk of childhood cancer in the midwestern United States: an ecologic study

BACKGROUND

There is limited evidence for an association between agricultural pesticide exposure and certain types of childhood cancers. Numerous studies have evaluated exposure to pesticides and childhood cancer and found positive associations. However, few studies have examined the density of agricultural land use as a surrogate for residential exposure to agricultural pesticides and results are mixed. We examined the association of county level agricultural land use and the incidence of specific childhood cancers.

METHODS

We linked county-level agricultural census data (2002 and 2007) and cancer incidence data for children ages 0-4 diagnosed between 2004 and 2008 from cancer registries in six Midwestern states. Crop density (percent of county area that was harvested) was estimated for total agricultural land, barley, dry beans, corn, hay, oats, sorghum, soybeans, sugar beets, and wheat. Rate ratios and 95% confidence intervals were estimated using generalized estimating equation Poisson regression models and were adjusted for race, sex, year of diagnosis, median household income, education, and population density.

RESULTS

We found statistically significant exposure-response relationships for dry beans and total leukemias (RR per 1% increase in crop density = 1.09, 95% CI = 1.03-1.14) and acute lymphoid leukemias (ALL) (RR = 1.10, 95% CI = 1.04-1.16); oats and acute myeloid leukemias (AML) (RR = 2.03, 95% CI = 1.25, 3.28); and sugar beets and total leukemias (RR = 1.11, 95% CI = 1.04, 1.19) and ALL (RR = 1.11, 95% CI = 1.02, 1.21). State-level analyses revealed some additional positive associations for total leukemia and CNS tumors and differences among states for several crop density-cancer associations. However, some of these analyses were limited by low crop prevalence and low cancer incidence.

CONCLUSIONS

Publicly available data sources not originally intended to be used for health research can be useful for generating hypotheses about environmental exposures and health outcomes. The associations observed in this study need to be confirmed by analytic epidemiologic studies using individual level exposure data and accounting for potential confounders that could not be taken into account in this ecologic study.

A study of adverse birth outcomes and agricultural land use practices in Missouri

BACKGROUND

Missouri is an agriculturally intensive state, primarily growing corn and soybeans with additional rice and cotton farming in some southeastern counties. Communities located in close proximity to pesticide-treated fields are known to have increased exposure to pesticides and may be at increased risk of adverse birth outcomes. The study aims were to assess the relationship between county-level measures of crop-specific agricultural production and adverse birth outcomes in Missouri and to evaluate the most appropriate statistical methodologies for doing so.

METHODS

Potential associations between county level data on the densities of particular crops and low birth weight and preterm births were examined in Missouri between 2004-2006. Covariates considered as potential confounders and effect modifiers included gender, maternal race/ethnicity, maternal age at delivery, maternal smoking, access to prenatal care, quarter of birth, county median household income, and population density. These data were analyzed using both standard Poisson regression models as well as models allowing for temporal and spatial correlation of the data.

RESULTS

There was no evidence of an association between corn, soybean, or wheat densities with low birth weight or preterm births. Significant positive associations between both rice and cotton density were observed with both low birth weight and preterm births. Model results were consistent using Poisson and alternative models accounting for spatial and temporal variability.

CONCLUSIONS

The associations of rice and cotton with low birth weight and preterm births warrant further investigation. Study limitations include the ecological study design and limited available covariate information.

Modelling environmental factors correlated with podoconiosis: a geospatial study of non-filarial elephantiasis

INTRODUCTION

The precise trigger of podoconiosis - endemic non-filarial elephantiasis of the lower legs - is unknown. Epidemiological and ecological studies have linked the disease with barefoot exposure to red clay soils of volcanic origin. Histopathology investigations have demonstrated that silicon, aluminium, magnesium and iron are present in the lower limb lymph node macrophages of both patients and non-patients living barefoot on these clays. We studied the spatial variation (variations across an area) in podoconiosis prevalence and the associated environmental factors with a goal to better understanding the pathogenesis of podoconiosis.

METHODS

Fieldwork was conducted from June 2011 to February 2013 in 12 kebeles (administrative units) in northern Ethiopia. Geo-located prevalence data and soil samples were collected and analysed along with secondary geological, topographic, meteorological and elevation data. Soil data were analysed for chemical composition, mineralogy and particle size, and were interpolated to provide spatially continuous information. Exploratory, spatial, univariate and multivariate regression analyses of podoconiosis prevalence were conducted in relation to primary (soil) and secondary (elevation, precipitation, and geology) covariates.

RESULTS

Podoconiosis distribution showed spatial correlation with variation in elevation and precipitation. Exploratory analysis identified that phyllosilicate minerals, particularly clay (smectite and kaolinite) and mica groups, quartz (crystalline silica), iron oxide, and zirconium were associated with podoconiosis prevalence. The final multivariate model showed that the quantities of smectite (RR = 2.76, 95% CI: 1.35, 5.73; p = 0.007), quartz (RR = 1.16, 95% CI: 1.06, 1.26; p = 0.001) and mica (RR = 1.09, 95% CI: 1.05, 1.13; p < 0.001) in the soil had positive associations with podoconiosis prevalence.

CONCLUSIONS

More quantities of smectite, mica and quartz within the soil were associated with podoconiosis prevalence. Together with previous work indicating that these minerals may influence water absorption, potentiate infection and be toxic to human cells, the present findings suggest that these particles may play a role in the pathogenesis of podoconiosis and acute adenolymphangitis, a common cause of morbidity in podoconiosis patients.

Effect of air pollution control on life expectancy in the United States: an analysis of 545 U.S. counties for the period from 2000 to 2007

BACKGROUND

In recent years (2000-2007), ambient levels of fine particulate matter (PM2.5) have continued to decline as a result of interventions, but the decline has been at a slower rate than previous years (1980-2000). Whether these more recent and slower declines of PM2.5 levels continue to improve life expectancy and whether they benefit all populations equally is unknown.

METHODS

We assembled a data set for 545 U.S. counties consisting of yearly county-specific average PM2.5, yearly county-specific life expectancy, and several potentially confounding variables measuring socioeconomic status, smoking prevalence, and demographic characteristics for the years 2000 and 2007. We used regression models to estimate the association between reductions in PM2.5 and changes in life expectancy for the period from 2000 to 2007.

RESULTS

A decrease of 10 μg/m in the concentration of PM2.5 was associated with an increase in mean life expectancy of 0.35 years (SD = 0.16 years, P = 0.033). This association was stronger in more urban and densely populated counties.

CONCLUSIONS

Reductions in PM2.5 were associated with improvements in life expectancy for the period from 2000 to 2007. Air pollution control in the last decade has continued to have a positive impact on public health.

Space-time confounding adjusted determinants of child HIV/TB mortality for large zero-inflated data in rural South Africa

South Africa is experiencing a major burden of HIV/TB. We used longitudinal data from the Agincourt sub-district in rural northeast South Africa over the years 2000 to 2005. A total of 187 HIV/TB deaths were observed among 16,844 children aged 1-5 years coming from 8,863 households. In this paper we used Bayesian models to assess risk factors for child HIV/TB mortality taking into account the presence of spatial correlation. Bayesian zero inflated spatiotemporal models were able to detect hidden patterns within the data. Our main finding was that maternal orphans experienced a threefold greater risk of HIV/TB death compared to those with living mothers (AHR=2.93, 95% CI[1.29;6.93]). Risk factor analyses which adjust for person, place and time provide evidence for policy makers that includes a spatial distribution of risk. Child survival is dependent on the mother's survival; hence programs that promote maternal survival are critical.

The importance of scale for spatial-confounding bias and precision of spatial regression estimators

Residuals in regression models are often spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When unmeasured confounding introduces spatial structure into the residuals, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual: one can reduce bias by fitting a spatial model only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals are independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Semi-continuous speciation analyses for ambient air particulate matter: an urgent need for health effects studies

One of the most urgent needs for future progress in reducing the substantial impacts of ambient air particulate matter (PM) on human health is to determine which of its components are having the greatest effects. The EPA's Speciation Trends Network (STN) has been operating since 2000. It generates 24-h average fine PM component concentrations for sulfate and nitrate ions, elemental and organic carbon (EC/OC), and many elements on an every third or sixth day basis for one or a few sites in most large US cities. To date, a small number of research studies, summarized in this paper, have used available STN and other supplemental data to identify and quantify the influences of specific components or source-related mixtures on measures of health-related impacts. These pioneering studies have demonstrated the potential utility of using such data in analyses that can provide a sound basis for guiding future research and control activities on those PM sources that have the greatest public health relevance. Unfortunately, the STN data collection methods used are expensive, and data have therefore been too sparse for studies of short-term health effects, where semi-continuous data, or at least daily 24-h concentration data are needed, as well as for regional concentration distributions that are needed for definitive analyses. Furthermore, because of cost considerations, there is virtually no prospect of collecting the data needed by the health researchers for more definitive analyses as long as there is continued reliance on current FRM sampling and analysis methodologies. At the second EPA-HEI Workshop on "Air Quality and Health Researchers Working Together" in RTP, NC on 16 and 17 April 2008, many participants concluded that it was both desirable, and possibly technically and economically feasible, to re-equip the STN sites with an automated system of semi-continuous monitors for sulfate, nitrate, EC, OC, and semi-continuous multistage PM samplers for non-volatile elements, providing continuous records of PM components with an averaging time of approximately 6 h for both thoracic coarse mode PM, fine PM, and perhaps ultrafine PM as well. The availability of such data would greatly accelerate the accumulation of knowledge on PM component exposure-response relationships that would provide a sound basis more targeted air quality standards and pollution control measures.

Spatial variation of volatile organic compounds in a "Hot Spot" for air pollution

The spatial variations of volatile organic compounds (VOCs) were characterized in the Village of Waterfront South neighborhood (WFS), a "hot spot" for air toxics in Camden, NJ. This was accomplished by conducting "spatial saturation sampling" for 11 VOCs using 3500 OVM passive samplers at 22 sites in WFS and 16 sites in Copewood/Davis Streets (CDS) neighborhood, an urban reference area located ∼1000 m east of the WFS. Sampling durations were 24 and 48 h. For all 3 sampling campaigns (2 in summer and 1 in winter), the spatial variations and median concentrations of toluene, ethylbenzene, and xylenes (TEX) were found significantly higher (p < 0.05) in WFS than in CDS, where the spatial distributions of these compounds were relatively uniform. The highest concentrations of methyl tert-butyl ether (MTBE) (maximum of 159 μg m(-3)) were always found at one site close to a car scrapping facility in WFS during each sampling campaign. The spatial variation of benzene in WFS was found to be marginally higher (p = 0.057) than in CDS during one sampling campaign, but similar in the other two sampling periods. The results obtained from the analyses of correlation among all species and the proximity of sampling site to source indicated that local stationary sources in WFS have significant impact on MTBE and BTEX air pollution in WFS, and both mobile sources and some of the stationary sources in WFS contributed to the ambient levels of these species measured in CDS. The homogenous spatial distributions (%RSD < 24%) and low concentrations of chloroform (0.02-0.23 μg m(-3)) and carbon tetrachloride (0.45-0.51 μg m(-3)) indicated no significant local sources in the study areas. Further, results showed that the sampling at the fixed monitoring site may under- or over-estimate air pollutant levels in a "hot spot" area, suggesting that the "spatial saturation sampling" is necessary for conducting accurate assessment of air pollution and personal exposure in a community with a high density of sources.

Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a medicare cohort

BACKGROUND

The American Cancer Society study and the Harvard Six Cities study are 2 landmark cohort studies for estimating the chronic effects of fine particulate air pollution (PM2.5) on mortality. Using Medicare data, we assessed the association of PM2.5 with mortality for the same locations included in these studies.

METHODS

We estimated the chronic effects of PM2.5 on mortality for the period 2000-2002 using mortality data for cohorts of Medicare participants and average PM2.5 levels from monitors in the same counties included in the 2 studies. We estimated mortality risk associated with air pollution adjusting for individual-level (age and sex) and area-level covariates (education, income level, poverty, and employment). We controlled for potential confounding by cigarette smoking by including standardized mortality ratios for lung cancer and chronic obstructive pulmonary disease.

RESULTS

Using the Medicare data, we estimated that a 10 microg/m increase in the yearly average PM2.5 concentration is associated with 10.9% (95% confidence interval = 9.0-12.8) and with 20.8% (14.8-27.1) increases in all-cause mortality for the American Cancer Society and Harvard Six Cities study counties, respectively. The estimates are somewhat higher than those reported by the original investigators.

CONCLUSION

Although Medicare data lack information on some potential confounding factors, we estimated risks similar to those in the previously published reports, which incorporated more extensive information on individual-level confounders. We propose that the Medicare files can be used to construct on-going cohorts for tracking the risk of air pollution over time.

Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France

STUDY OBJECTIVE

Most studies of place effects on health have followed the multilevel analytical approach that investigates geographical variations of health phenomena by fragmenting space into arbitrary areas. This study examined whether analysing geographical variations across continuous space with spatial modelling techniques and contextual indicators that capture space as a continuous dimension surrounding individual residences provided more relevant information on the spatial distribution of outcomes. Healthcare utilisation in France was taken as an illustrative example in comparing the spatial approach with the multilevel approach.

DESIGN

Multilevel and spatial analyses of cross sectional data.

PARTICIPANTS

10,955 beneficiaries of the three principal national health insurance funds, surveyed in 1998 and 2000 on continental France.

MAIN RESULTS

Multilevel models showed significant geographical variations in healthcare utilisation. However, the Moran's I statistic showed spatial autocorrelation unaccounted for by multilevel models. Modelling the correlation between people as a decreasing function of the spatial distance between them, spatial mixed models gave information not only on the magnitude, but also on the scale of spatial variations, and provided more accurate standard errors for risk factors effects. The socioeconomic level of the residential context and the supply of physicians were independently associated with healthcare utilisation. Place indicators better explained spatial variations in healthcare utilisation when measured across continuous space, rather than within administrative areas.

CONCLUSIONS

The kind of conceptualization of space during analysis influences the understanding of place effects on health. In many contextual studies, viewing space as a continuum may yield more relevant information on the spatial distribution of outcomes.

Comparison of a spatial perspective with the multilevel analytical approach in neighborhood studies: the case of mental and behavioral disorders due to psychoactive substance use in Malmo, Sweden, 2001

Most studies of neighborhood effects on health have used the multilevel approach. However, since this methodology does not incorporate any notion of space, it may not provide optimal epidemiologic information when modeling variations or when investigating associations between contextual factors and health. Investigating mental disorders due to psychoactive substance use among all 65,830 individuals aged 40-59 years in 2001 in Malmö, Sweden, geolocated at their place of residence, the authors compared a spatial analytical perspective, which builds notions of space into hypotheses and methods, with the multilevel approach. Geoadditive models provided precise cartographic information on spatial variations in prevalence independent of administrative boundaries. The multilevel model showed significant neighborhood variations in the prevalence of substance-related disorders. However, hierarchical geostatistical models provided information on not only the magnitude but also the scale of neighborhood variations, indicating a significant correlation between neighborhoods in close proximity to each other. The prevalence of disorders increased with neighborhood deprivation. Far stronger associations were observed when using indicators measured in spatially adaptive areas, centered on residences of individuals, smaller in size than administrative neighborhoods. In neighborhood studies, building notions of space into analytical procedures may yield more comprehensive information than heretofore has been gathered on the spatial distribution of outcomes.

Exploring bias in a generalized additive model for spatial air pollution data

During the past few years, the generalized additive model (GAM) has become a standard tool for epidemiologic analysis exploring the effect of air pollution on population health. Recently, the use of the GAM has been extended from time-series data to spatial data. Still more recently, it has been suggested that the use of GAMs to analyze time-series data results in air pollution risk estimates being biased upward and that concurvity in the time-series data results in standard error estimates being biased downward. We show that concurvity in spatial data can lead to underestimation of the standard error of the estimated air pollution effect, even when using an asymptotically unbiased standard error estimator. We also show that both the magnitude and direction of the bias in the air pollution effect depend, at least in part, on the nature of the concurvity. We argue that including a nonparametric function of location in a GAM for spatial epidemiologic data can be expected to result in concurvity. As a result, we recommend caution in using the GAM to analyze this type of data.

On the relationship between time-series studies, dynamic population studies, and estimating loss of life due to short-term exposure to environmental risks

There is a growing concern that short-term exposure to combustion-related air pollution is associated with increased risk of death. This finding is based largely on time-series studies that estimate associations between daily variations in ambient air pollution concentrations and in the number of nonaccidental deaths within a community. Because these results are not based on cohort or dynamic population designs, where individuals are followed in time, it has been suggested that estimates of effect from these time-series studies cannot be used to determine the amount of life lost because of short-term exposures. We show that results from time-series studies are equivalent to estimates obtained from a dynamic population when each individual's survival experience can be summarized as the daily number of deaths. This occurs when the following conditions are satisfied: a) the environmental covariates vary in time and not between individuals; b) on any given day, the probability of death is small; c) on any given day and after adjusting for known risk factors for mortality such age, sex, smoking habits, and environmental exposures, each subject of the at-risk population has the same probability of death; d) environmental covariates have a common effect on mortality of all members of at-risk population; and e) the averages of individual risk factors, such as smoking habits, over the at-risk population vary smoothly with time. Under these conditions, the association between temporal variation in the environmental covariates and the survival experience of members of the dynamic population can be estimated by regressing the daily number of deaths on the daily value of the environmental covariates, as is done in time-series mortality studies. Issues in extrapolating risk estimates based on time-series studies in one population to estimate the amount of life lost in another population are also discussed.

National maps of the effects of particulate matter on mortality: exploring geographical variation

In this paper, we present national maps of relative rates of mortality associated with short-term exposure to particulate matter < 10 micro m in aerodynamic diameter (PM(10)). We report results for 88 of the largest metropolitan areas in the United States from 1987 to 1994 for all-cause mortality, combined cardiovascular and respiratory deaths, and other causes of mortality. Maximum likelihood estimates of the relative rate of mortality associated with PM(10)and the degree of statistical uncertainty were obtained for each of the 88 cities by fitting a separate log-linear regression of the daily mortality rate on air pollution level and potential confounders. We obtained Bayesian estimates of the relative rates by fitting a hierarchical model that takes into account spatial correlation among the true city-specific relative rates. We found that daily variations of PM(10) are positively associated with daily variations of mortality. In particular, the relative rate estimates of cardiovascular and respiratory mortality associated with PM(10) are larger on average than the relative rate estimates of all-cause and other-cause mortality. The estimated increase in the relative rate of death from cardiovascular and respiratory mortality, all-cause mortality, and other-cause mortality were 0.31% (95% posterior interval, 0.15-0.5), 0.22% (95% posterior interval, 0.1-0.38), and 0.13% (95% posterior interval, -0.05 to 0.29), respectively. Bayesian estimates of the city-specific relative rates ranged from 0.23% to 0.35% for cardiovascular and respiratory mortality, from 0.18% to 0.27% for all causes, and from 0.10% to 0.20% for other causes of mortality. The spatial characterization of effects across cities offers the potential to identify factors that could influence the effect of PM(10) on health, including particle characteristics, offering insights into mechanisms by which PM(10) causes adverse health effects.

Urban residential environments and senior citizens' longevity in megacity areas: the importance of walkable green spaces

STUDY OBJECTIVES

To study the association between greenery filled public areas that are nearby a residence and easy to walk in and the longevity of senior citizens in a densely populated, developed megacity.

DESIGN

Cohort study.

METHODS

The authors analysed the five year survival of 3144 people born in 1903, 1908, 1913, or 1918 who consented to a follow up survey from the records of registered Tokyo citizens in relation to baseline residential environment characteristics in 1992.

MAIN RESULTS

The survival of 2211 and the death of 897 (98.9% follow up) were confirmed. The probability of five year survival of the senior citizens studied increased in accordance with the space for taking a stroll near the residence (p<0.01), parks and tree lined streets near the residence (p<0.05), and their preference to continue to live in their current community (p<0.01). The principal component analysis from the baseline residential environment characteristics identified two environment related factors: the factor of walkable green streets and spaces near the residence and the factor of a positive attitude to a person's own community. After controlling the effects of the residents' age, sex, marital status, and socioeconomic status, the factor of walkable green streets and spaces near the residence showed significant predictive value for the survival of the urban senior citizens over the following five years (p<0.01).

CONCLUSIONS

Living in areas with walkable green spaces positively influenced the longevity of urban senior citizens independent of their age, sex, marital status, baseline functional status, and socioeconomic status. Greenery filled public areas that are nearby and easy to walk in should be further emphasised in urban planning for the development and re-development of densely populated areas in a megacity. Close collaboration should be undertaken among the health, construction, civil engineering, planning, and other concerned sectors in the context of the healthy urban policy, so as to promote the health of senior citizens.

Urban residential environments and senior citizens' longevity in megacity areas: the importance of walkable green spaces

STUDY OBJECTIVES

To study the association between greenery filled public areas that are nearby a residence and easy to walk in and the longevity of senior citizens in a densely populated, developed megacity.

DESIGN

Cohort study.

METHODS

The authors analysed the five year survival of 3144 people born in 1903, 1908, 1913, or 1918 who consented to a follow up survey from the records of registered Tokyo citizens in relation to baseline residential environment characteristics in 1992.

MAIN RESULTS

The survival of 2211 and the death of 897 (98.9% follow up) were confirmed. The probability of five year survival of the senior citizens studied increased in accordance with the space for taking a stroll near the residence (p<0.01), parks and tree lined streets near the residence (p<0.05), and their preference to continue to live in their current community (p<0.01). The principal component analysis from the baseline residential environment characteristics identified two environment related factors: the factor of walkable green streets and spaces near the residence and the factor of a positive attitude to a person's own community. After controlling the effects of the residents' age, sex, marital status, and socioeconomic status, the factor of walkable green streets and spaces near the residence showed significant predictive value for the survival of the urban senior citizens over the following five years (p<0.01).

CONCLUSIONS

Living in areas with walkable green spaces positively influenced the longevity of urban senior citizens independent of their age, sex, marital status, baseline functional status, and socioeconomic status. Greenery filled public areas that are nearby and easy to walk in should be further emphasised in urban planning for the development and re-development of densely populated areas in a megacity. Close collaboration should be undertaken among the health, construction, civil engineering, planning, and other concerned sectors in the context of the healthy urban policy, so as to promote the health of senior citizens.

Association between mortality and indicators of traffic-related air pollution in the Netherlands: a cohort study

BACKGROUND

Long-term exposure to particulate matter air pollution has been associated with increased cardiopulmonary mortality in the USA. We aimed to assess the relation between traffic-related air pollution and mortality in participants of the Netherlands Cohort study on Diet and Cancer (NLCS), an ongoing study.

METHODS

We investigated a random sample of 5000 people from the full cohort of the NLCS study (age 55-69 years) from 1986 to 1994. Long-term exposure to traffic-related air pollutants (black smoke and nitrogen dioxide) was estimated for the 1986 home address. Exposure was characterised with the measured regional and urban background concentration and an indicator variable for living near major roads. The association between exposure to air pollution and (cause specific) mortality was assessed with Cox's proportional hazards models, with adjustment for potential confounders.

FINDINGS

489 (11%) of 4492 people with data died during the follow-up period. Cardiopulmonary mortality was associated with living near a major road (relative risk 1.95, 95% CI 1.09-3.52) and, less consistently, with the estimated ambient background concentration (1.34, 0.68-2.64). The relative risk for living near a major road was 1.41 (0.94-2.12) for total deaths. Non-cardiopulmonary, non-lung cancer deaths were unrelated to air pollution (1.03, 0.54-1.96 for living near a major road).

INTERPRETATION

Long-term exposure to traffic-related air pollution may shorten life expectancy.

Air pollution and health

The health effects of air pollution have been subject to intense study in recent years. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in mortality and hospital admissions due to respiratory and cardiovascular disease. These effects have been found in short-term studies, which relate day-to-day variations in air pollution and health, and long-term studies, which have followed cohorts of exposed individuals over time. Effects have been seen at very low levels of exposure, and it is unclear whether a threshold concentration exists for particulate matter and ozone below which no effects on health are likely. In this review, we discuss the evidence for adverse effects on health of selected air pollutants.

What's wrong with the National Ambient Air Quality Standard (NAAQS) for fine particulate matter (PM(2.5))?

Associations between airborne concentrations of fine particulate matter (PM(2.5)) and mortality rates have been investigated primarily by ecologic or semiecologic epidemiology studies. Many investigators and regulatory agencies have inferred that the weak, positive association often observed is causal, that it applies to all forms of airborne PM(2.5), and that current ambient levels of PM(2.5) require reduction. Before implementing stringent regulations of ambient PM(2.5), analysts should pause to consider whether the accumulated evidence is sufficient, and sufficiently detailed, to support the PM(2.5) National Ambient Air Quality Standard. We take two tacks. First, we analyze the toxicologic evidence, finding it inconsistent with the notion that current ambient concentrations of all forms of fine particulate matter should affect pulmonary, cardiac, or all-cause mortality rates. More generally, we note that the thousands of forms of PM(2.5) are remarkably diverse, yet the PM(2.5) NAAQS presumes them to be identical toxicologically, and presumes that reducing ambient concentrations of any form of PM(2.5) will improve public health. Second, we examine the epidemiologic evidence in light of two related examples of semiecologic associations, examples that both inform the PM-mortality association and have been called into question by individual-level data. Taken together, the toxicologic evidence and lessons learned from analogous epidemiologic associations should encourage further investigation of the association between particulate matter and mortality rates before additional regulation is implemented, and certainly before the association is characterized as causal and applicable to all PM(2.5).

Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution

CONTEXT

Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive.

OBJECTIVE

To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality.

DESIGN, SETTING, AND PARTICIPANTS

Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998.

MAIN OUTCOME MEASURE

All-cause, lung cancer, and cardiopulmonary mortality.

RESULTS

Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-microg/m(3) elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality.

CONCLUSION

Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.

Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution

CONTEXT

Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive.

OBJECTIVE

To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality.

DESIGN, SETTING, AND PARTICIPANTS

Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998.

MAIN OUTCOME MEASURE

All-cause, lung cancer, and cardiopulmonary mortality.

RESULTS

Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-microg/m(3) elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality.

CONCLUSION

Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.

Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution

CONTEXT

Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive.

OBJECTIVE

To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality.

DESIGN, SETTING, AND PARTICIPANTS

Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998.

MAIN OUTCOME MEASURE

All-cause, lung cancer, and cardiopulmonary mortality.

RESULTS

Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-microg/m(3) elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality.

CONCLUSION

Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.

Temporal and spatial relations between age specific mortality and ambient air quality in the United States: regression results for counties, 1960-97

OBJECTIVE

To investigate longitudinal and spatial relations between air pollution and age specific mortality for United States counties (except Alaska) from 1960 to the end of 1997.

METHODS

Cross sectional regressions for five specific periods using published data on mortality, air quality, demography, climate, socioeconomic status, lifestyle, and diet. Outcome measures are statistical relations between air quality and county mortalities by age group for all causes of death, other than AIDS and trauma.

RESULTS

A specific regression model was developed for each period and age group, using variables that were significant (p<0.05), not substantially collinear (variance inflation factor <2), and had the expected algebraic sign. Models were initially developed without the air pollution variables, which varied in spatial coverage. Residuals were then regressed in turn against current and previous air quality, and dose-response plots were constructed. The validity of this two stage procedure was shown by comparing a subset of results with those obtained with single stage models that included air quality (correlation=0.88). On the basis of attributable risks computed for overall mean concentrations, the strongest associations were found in the earlier periods, with attributable risks usually less than 5%. Stronger relations were found when mortality and air quality were measured in the same period and when the locations considered were limited to those of previous cohort studies (for PM(2.5) and SO(4)(2-)). Thresholds were suggested at 100-130 microg/m(3) for mean total suspended particulate (TSP), 7-10 microg/m(3) for mean sulfate, 10-15 ppm for peak (95th percentile) CO, 20-40 ppb for mean SO(2.) Contrary to expectations, associations were often stronger for the younger age groups (<65 y). Responses to PM, CO, and SO(2) declined over time; responses in elderly people to peak O(3) increased over time as did responses to NO(2) for the younger age groups. These results generally agreed with previous prospective cohort and ecological studies for comparable periods, age groups, and pollutants, but they also suggest that the results of those previous studies may no longer be applicable.

CONCLUSIONS

Spatially derived relations between air quality and mortality vary significantly by age group and period and may be sensitive to the locations included in the analysis.