The use of alternative pollutant metrics in time-series studies of ambient air pollution and respiratory emergency department visits.
ABSTRACT: Various temporal metrics of daily pollution levels have been used to examine the relationships between air pollutants and acute health outcomes. However, daily metrics of the same pollutant have rarely been systematically compared within a study. In this analysis, we describe the variability of effect estimates attributable to the use of different temporal metrics of daily pollution levels. We obtained hourly measurements of ambient particulate matter (PM?.?), carbon monoxide (CO), nitrogen dioxide (NO?), and ozone (O?) from air monitoring networks in 20-county Atlanta for the time period 1993-2004. For each pollutant, we created (1) a daily 1-h maximum; (2) a 24-h average; (3) a commute average; (4) a daytime average; (5) a nighttime average; and (6) a daily 8-h maximum (only for O?). Using Poisson generalized linear models, we examined associations between daily counts of respiratory emergency department visits and the previous day's pollutant metrics. Variability was greatest across O? metrics, with the 8-h maximum, 1-h maximum, and daytime metrics yielding strong positive associations and the nighttime O? metric yielding a negative association (likely reflecting confounding by air pollutants oxidized by O?). With the exception of daytime metric, all of the CO and NO? metrics were positively associated with respiratory emergency department visits. Differences in observed associations with respiratory emergency room visits among temporal metrics of the same pollutant were influenced by the diurnal patterns of the pollutant, spatial representativeness of the metrics, and correlation between each metric and copollutant concentrations. Overall, the use of metrics based on the US National Ambient Air Quality Standards (for example, the use of a daily 8-h maximum O? as opposed to a 24-h average metric) was supported by this analysis. Comparative analysis of temporal metrics also provided insight into underlying relationships between specific air pollutants and respiratory health.
Project description:Most studies of short-term particulate matter (PM) exposure use 24-hour averages. However, other pollutants have stronger effects at shorter timeframes, which has influenced policy (e.g., ozone 8-hour maximum). Selecting appropriate exposure timeframes is important for effective regulation. The U.S. EPA identified health effects for sub-daily PM exposures as a critical research need. Unlike most areas, Seoul, Korea has hourly measurements of PM10, although not PM2.5. We investigated PM10 and mortality (total, cardiovascular, respiratory) in Seoul (1999-2009) considering sub-daily exposures: 24-hour, daytime (7am-8pm), morning (7-10am), nighttime (8pm-7am), and 1-hour daily maximum. We applied Poisson generalized linear modeling adjusting for temporal trends and meteorology. All PM10 metrics were significantly associated with total mortality. Compared to other exposure timeframes, morning exposure had the most certain effect with total mortality (based on statistical significance). A 10µg/m3 increase in 24-hour, daytime, morning, nighttime, and 1-hour maximum PM10 was associated with a 0.15% (95% confidence interval 0.02-0.28%), 0.14% (0.01-0.27%), 0.10% (0.03-0.18%), 0.12% (0.03-0.22%), and 0.10% (0.00-0.21%) increase in total mortality, respectively. PM10 was significantly associated with cardiovascular mortality for 24-hour, morning, and nighttime exposures. We did not identify significant associations with respiratory mortality. Results support use of a 24-hour averaging time as an appropriate metric for health studies and regulation, particularly for PM10 and mortality.
Project description:Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 ?g/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.
Project description:In this study, we estimated the short-term effects of ambient air pollution on respiratory disease hospitalization in Taiyuan, China. Daily data of respiratory disease hospitalization, daily concentration of ambient air pollutants and meteorological factors from 1 October 2014 to 30 September 2017 in Taiyuan were included in our study. We conducted a time-series study design and applied a generalized additive model to evaluate the association between every 10-?g/m³ increment of air pollutants and percent increase of respiratory disease hospitalization. A total of 127,565 respiratory disease hospitalization cases were included in this study during the present period. In single-pollutant models, the effect values in multi-day lags were greater than those in single-day lags. PM2.5 at lag02 days, SO? at lag03 days, PM10 and NO? at lag05 days were observed to be strongly and significantly associated with respiratory disease hospitalization. No significant association was found between O? and respiratory disease hospitalization. SO? and NO? were still significantly associated with hospitalization after adjusting for PM2.5 or PM10 into two-pollutant models. Females and younger population for respiratory disease were more vulnerable to air pollution than males and older groups. Therefore, some effective measures should be taken to strengthen the management of the ambient air pollutants, especially SO? and NO?, and to enhance the protection of the high-risk population from air pollutants, thereby reducing the burden of respiratory disease caused by ambient air pollution.
Project description:Vehicles are major sources of air pollutant emissions, and individuals living near large roads endure high exposures and health risks associated with traffic-related air pollutants. Air pollution epidemiology, health risk, environmental justice, and transportation planning studies would all benefit from an improved understanding of the key information and metrics needed to assess exposures, as well as the strengths and limitations of alternate exposure metrics. This study develops and evaluates several metrics for characterizing exposure to traffic-related air pollutants for the 218 residential locations of participants in the NEXUS epidemiology study conducted in Detroit (MI, USA). Exposure metrics included proximity to major roads, traffic volume, vehicle mix, traffic density, vehicle exhaust emissions density, and pollutant concentrations predicted by dispersion models. Results presented for each metric include comparisons of exposure distributions, spatial variability, intraclass correlation, concordance and discordance rates, and overall strengths and limitations. While showing some agreement, the simple categorical and proximity classifications (e.g., high diesel/low diesel traffic roads and distance from major roads) do not reflect the range and overlap of exposures seen in the other metrics. Information provided by the traffic density metric, defined as the number of kilometers traveled (VKT) per day within a 300 m buffer around each home, was reasonably consistent with the more sophisticated metrics. Dispersion modeling provided spatially- and temporally-resolved concentrations, along with apportionments that separated concentrations due to traffic emissions and other sources. While several of the exposure metrics showed broad agreement, including traffic density, emissions density and modeled concentrations, these alternatives still produced exposure classifications that differed for a substantial fraction of study participants, e.g., from 20% to 50% of homes, depending on the metric, would be incorrectly classified into "low", "medium" or "high" traffic exposure classes. These and other results suggest the potential for exposure misclassification and the need for refined and validated exposure metrics. While data and computational demands for dispersion modeling of traffic emissions are non-trivial concerns, once established, dispersion modeling systems can provide exposure information for both on- and near-road environments that would benefit future traffic-related assessments.
Project description:Epidemiologic literature suggests that exposure to air pollutants is associated with fetal development.We investigated maternal exposures to air pollutants during weeks 2-8 of pregnancy and their associations with congenital heart defects.Mothers from the National Birth Defects Prevention Study, a nine-state case-control study, were assigned 1-week and 7-week averages of daily maximum concentrations of carbon monoxide, nitrogen dioxide, ozone, and sulfur dioxide and 24-hr measurements of fine and coarse particulate matter using the closest air monitor within 50 km to their residence during early pregnancy. Depending on the pollutant, a maximum of 4,632 live-birth controls and 3,328 live-birth, fetal-death, or electively terminated cases had exposure data. Hierarchical regression models, adjusted for maternal demographics and tobacco and alcohol use, were constructed. Principal component analysis was used to assess these relationships in a multipollutant context.Positive associations were observed between exposure to nitrogen dioxide and coarctation of the aorta and pulmonary valve stenosis. Exposure to fine particulate matter was positively associated with hypoplastic left heart syndrome but inversely associated with atrial septal defects. Examining individual exposure-weeks suggested associations between pollutants and defects that were not observed using the 7-week average. Associations between left ventricular outflow tract obstructions and nitrogen dioxide and between hypoplastic left heart syndrome and particulate matter were supported by findings from the multipollutant analyses, although estimates were attenuated at the highest exposure levels.Using daily maximum pollutant levels and exploring individual exposure-weeks revealed some positive associations between certain pollutants and defects and suggested potential windows of susceptibility during pregnancy.
Project description:The objective of this study was to investigate the potential association between air pollutants and respiratory diseases (RDs). Generalized additive models were used to analyze the effect of air pollutants on mortalities or outpatient visits. The average concentrations of air pollutants in Hangzhou (HZ) were 1.6-2.8 times higher than those in Zhoushan (ZS), except for O3. In a single pollutant model, the increased concentrations of PM2.5, NO2, and SO2 were strongly associated with deaths caused by RD in HZ, while PM2.5 and O3 were associated with deaths caused by RD in ZS. All air pollutants (PM2.5, NO2, SO2, and O3) were strongly associated with outpatient visits for RD in both HZ and ZS. In multiple pollutant models, a significant association was only observed between PM2.5 and the mortality rate of RD patients in both HZ and in ZS. Moreover, strong associations between SO2, NO2, and outpatient visits for RD were observed in HZ and ZS. This study has provided evidence that both the mortality rates and outpatient visits for RD were significantly associated with air pollutants. Furthermore, the results showed that different air pollutant levels lead to regional differences between mortality rates and outpatient visits.
Project description:Few studies have compared different methods when exploring the short-term effects of air pollutants on respiratory disease mortality in Wuhan, China. This study assesses the association between air pollutants and respiratory disease mortality with both time-series and time-stratified-case-crossover designs. The generalized additive model (GAM) and the conditional logistic regression model were used to assess the short-term effects of air pollutants on respiratory disease mortality. Stratified analyses were performed by age, sex, and diseases. A 10??g/m3 increment in SO2 level was associated with an increase in relative risk for all respiratory disease mortality of 2.4% and 1.9% in the case-crossover and time-series analyses in single pollutant models, respectively. Strong evidence of an association between NO2 and daily respiratory disease mortality among men or people older than 65 years was found in the case-crossover study. There was a positive association between air pollutants and respiratory disease mortality in Wuhan, China. Both time-series and case-crossover analyses consistently reveal the association between three air pollutants and respiratory disease mortality. The estimates of association between air pollution and respiratory disease mortality from the case-crossover analysis displayed greater variation than that from the time-series analysis.
Project description:Concerns regarding the health impact of urban air pollution on asthmatic children are pronounced along the U.S.-Mexico border because of rapid population growth near busy border highways and roads.We conducted the first binational study of the impacts of air pollution on asthmatic children in Ciudad Juarez, Mexico, and El Paso, Texas, USA, and compared different exposure metrics to assess acute respiratory response.We recruited 58 asthmatic children from two schools in Ciudad Juarez and two schools in El Paso. A marker of airway inflammation [exhaled nitric oxide (eNO)], respiratory symptom surveys, and pollutant measurements (indoor and outdoor 48-hr size-fractionated particulate matter, 48-hr black carbon, and 96-hr nitrogen dioxide) were collected at each school for 16 weeks. We examined associations between the pollutants and respiratory response using generalized linear mixed models.We observed small but consistent associations between eNO and numerous pollutant metrics, with estimated increases in eNO ranging from 1% to 3% per interquartile range increase in pollutant concentrations. Effect estimates from models using school-based concentrations were generally stronger than corresponding estimates based on concentrations from ambient air monitors. Both traffic-related and non-traffic-related particles were typically more robust predictors of eNO than was nitrogen dioxide, for which associations were highly sensitive to model specification. Associations differed significantly across the four school-based cohorts, consistent with heterogeneity in pollutant concentrations and cohort characteristics. Models examining respiratory symptoms were consistent with the null.The results indicate adverse effects of air pollution on the subclinical respiratory health of asthmatic children in this region and provide preliminary support for the use of air pollution monitors close to schools to track exposure and potential health risk in this population.
Project description:Several exposure metrics have been applied in health research and policy settings to represent ozone exposure, such as the 24 h average and daily 8 h maximum. Frequently, results calculated using one exposure metric are converted using a simple ratio to compare or combine findings with results using a different metric. This conversion, however, assumes that such a ratio is constant across locations and time periods. We investigated the appropriateness of this conversion method by examining the relationships among various forms of ozone concentrations (24 h average, daily 1 h maximum, and daily 8 h maximum) within and between communities for 78 US communities from 2000 to 2004 and compared results to commonly used conversion ratios. We explored whether the relationships between ozone exposure metrics differ by region, weather, season, and city-specific characteristics. Analysis revealed variation in the relationship among ozone metrics, both across communities and across time within individual communities, indicating that conversion of ozone exposure metrics with a standard ratio introduces uncertainty. For example, the average ratio of the daily 8 h maximum to the daily concentration ranged from 1.23 to 1.83. Within a community, days with higher ozone levels had lower ratios. Relationships among metrics within a community were associated with daily temperature. The community-average exposure metric ratios were lower for communities with higher long-term ozone levels. Ozone metric ratios differed by season because of the different rate of change of ozone metrics throughout the year. We recommend that health effects studies present results from multiple ozone exposure metrics, if possible. When conversions are necessary, more accurate estimates can be obtained using summaries of data for a given location and time period if available, or by basing conversion ratios on data from a similar city and season, such as the results provided in this study.
Project description:In time-series studies of ambient air pollution and health in large urban areas, measurement errors associated with instrument precision and spatial variability vary widely across pollutants. In this paper, we characterize these errors for selected air pollutants and estimate their impacts on epidemiologic results from an ongoing study of air pollution and emergency department visits in Atlanta. Error was modeled for daily measures of 12 air pollutants using collocated monitor data to characterize instrument precision and data from multiple study area monitors to estimate population-weighted spatial variance. Time-series simulations of instrument and spatial error were generated for each pollutant, added to a reference pollutant time-series, and used in a Poisson generalized linear model of air pollution and cardiovascular emergency department visits. Reductions in risk ratio due to instrument precision error were less than 6%. Error due to spatial variability resulted in average risk ratio reductions of less than 16% for secondary pollutants (O(3), PM(2.5) sulfate, nitrate and ammonium) and between 43% and 68% for primary pollutants (NO(x), NO(2), SO(2), CO, PM(2.5) elemental carbon); pollutants of mixed origin (PM(10), PM(2.5), PM(2.5) organic carbon) had intermediate impacts. Quantifying impacts of measurement error on health effect estimates improves interpretation across ambient pollutants.