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In this prospective study, we recruited 1759 children (average age, 10 years) from schools in 12 southern California communities and measured lung function annually for eight years. The rate of attrition was approximately 10 percent per year. The communities represented a wide range of ambient exposures to ozone, acid vapor, nitrogen dioxide, and particulate matter. Linear regression was used to examine the relationship of air pollution to the forced expiratory volume in one second (FEV1) and other spirometric measures.

Published Sep 9, 2004

Tashkin, D. P., Celli, B., Senn, S., Burkhart, D., Kesten, S., Menjoge, S., Decramer, M., & Study, U. (2008). The Effect of Air Pollution on Lung Development from 10 to 18 Years of Age W. 359, 1543–1554.

Children’s exposure to air pollution is a special concern because their immune system and lungs are not fully developed when exposure begins, raising the possibility of different responses than seen in adults. In addition, children spend more time outside, where the concentrations of pollution from traffic, powerplants, and other combustion sources are generally higher. Although air pollution has long been thought to exacerbate minor acute illnesses, recent studies have suggested that air pollution, particularly traffic-related pollution, is associated with infant mortality and the development of asthma and atopy. Other studies have associated particulate air pollution with acute bronchitis in children and demonstrated that rates of bronchitis and chronic cough declined in areas where particle concentrations have fallen. More mixed results have been reported for lung function. Overall, evidence for effects of air pollution on children have been growing, and effects are seen at concentrations that are common today. Although many of these associations seem likely to be causal, others require and warrant additional investigation.

Published Apr 1, 2004

Schwartz, J. (2018). Air Pollution and Children’s Health. 113(4). https://pediatrics.aappublications.org/content/113/Supplement_3/1037.short?casa_token=eeWXA1BufMkAAAAA:6Q_CEn-v6CM1qMkByowBIByv3mSUI3Pap587m3SZ1iTiJFq6OpgOgwTFG9nFYk3754kH2A5n0A

This review explores which facility attributes affect academic outcomes the most and in what manner and degree. The research is examined in six categories: inddor air quality, ventilation, and thermal comfort; lighting; acoustics; building age and quality; school size; and class size. The review concludes that school facilities affect learning. Spatial configuration, noise, heat, cold, light, and air quality obviuosly bear on students; and teachers; ability to perform. Needed are clean air, good light, and quiet, comfortable, and safe learning environment. The review asserts that this can be and generally has been achieved within the limits of existing knowledge, technology, and materials; it simply requires adequate funding and competent design, construction, and maintenance.

Published Nov 1, 2002

Schneider, M. (2002). Do School Facilities Affect Academic Outcomes? In National Clearinghouse for Educational Facilities, Washington, DC (p. 26). https://doi.org/November 2002

Most North American school buses and transport trucks are powered by dieselfuelled engines. Diesel has become the fuel of choice because it is considered more economical. However, as evidence grows about the connection between diesel exhaust, air pollution and ill health, so does public pressure to use cleaner fuels and vehicles.

Published Sep 3, 2002

Weir, E. (2002). Diesel exhaust, school buses and children’s health. Cmaj, 167(5), 505. https://www.cmaj.ca/content/167/5/505.short

The widely used generalized additive models (GAM) method is a flexible and effective technique for conducting nonlinear regression analysis in time-series studies of the health effects of air pollution. When the data to which the GAM are being applied have two characteristics—1) the estimated regression coefficients are small and 2) there exist confounding factors that are modeled using at least two nonparametric smooth functions—the default settings in the gam function of the S-Plus software package (version 3.4) do not assure convergence of its iterative estimation procedure and can provide biased estimates of regression coefficients and standard errors. This phenomenon has occurred in time-series analyses of contemporary data on air pollution and mortality. To evaluate the impact of default implementation of the gam software on published analyses, the authors reanalyzed data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) using three different methods: 1) Poisson regression with parametric nonlinear adjustments for confounding factors; 2) GAM with default convergence parameters; and 3) GAM with more stringent convergence parameters than the default settings. The authors found that pooled NMMAPS estimates were very similar under the first and third methods but were biased upward under the second method. Am J Epidemiol 2002;156:193–203.

Published Aug 1, 2002

Dominici, F. (2002). On the Use of Generalized Additive Models in Time-Series Studies of Air Pollution and Health. American Journal of Epidemiology, 156(3), 193–203. https://doi.org/10.1093/aje/kwf062

Various epidemiologic investigations have shown that ambient air pollution levels are associated with acute increases in hospital admissions and mortality in the United States and abroad. The objectives of this investigation were a) to determine if racial minorities are more adversely affected by ambient air pollution than their white counterparts and b) to assess the contribution of socioeconomic status to any observed racial differences in pollution effect. Time-series regression methods were conducted to investigate these hypotheses for daily respiratory hospital admissions in New York City, New York. Pollutants considered included mean daily levels of particulate matter with a mass median aerodynamic diameter less than 10 microm (PM(10), ozone (O3), strong aerosol acidity (H+), and sulfates (SO4(2). The relative risk for respiratory hospital admission was calculated for each pollutant for a maximum minus mean increment in mean daily pollutant concentration. The greatest difference between the white and nonwhite subgroups was observed for O(3), where the white relative risk (RR) was 1.032 [95% confidence interval (CI): 0.977-1.089] and the nonwhite RR was 1.122 (95%CI: 1.074-1.172). Although not statistically different from each other, the various pollutants' RR estimates for the Hispanic nonwhite category in New York City were generally larger in magnitude than those for the non-Hispanic white group. When these analyses incorporated differences in the underlying respiratory hospitalization rates across races (that for nonwhites, was roughly twice that for whites), the disparities in attributable risks from pollution (in terms of excess admissions per day per million persons) were even larger for nonwhites versus whites. However, when insurance status was used as an indicator of socioeconomic/health coverage status, higher RRs were indicated for the poor/working poor (i.e., those on Medicaid and the uninsured) than for those who were economically better off (i.e., the privately insured), even among non-Hispanic whites. Thus, although potential racial differences in pollution exposures could not be explored as a factor, within-race analyses suggested that most of the apparent differences in air pollutant effects found across races were explained by socioeconomic and/or health care disparities.

Published Aug 1, 2001

Gwynn, R. C., & Thurston, G. D. (2001). The burden of air pollution: impacts among racial minorities. Environmental Health Perspectives, 109(suppl 4), 501–506. https://doi.org/10.1289/ehp.01109s4501

Over the past three decades, an array of legislation with attendant regulations has been implemented to enhance the quality of the environment and thereby improve the public's health. Despite the many beneficial changes that have followed, there remains a disproportionately higher prevalence of harmful environmental exposures, particularly air pollution, for certain populations. These populations most often reside in urban settings, have low socioeconomic status, and include a large proportion of ethnic minorities. The disparities between racial/ethnic minority and/or low-income populations in cities and the general population in terms of environmental exposures and related health risks have prompted the "environmental justice" or "environmental equity" movement, which strives to create cleaner environments for the most polluted communities. Achieving cleaner environments will require interventions based on scientific data specific to the populations at risk; however, research in this area has been relatively limited. To assess the current scientific information on urban air pollution and its health impacts and to help set the agenda for immediate intervention and future research, the American Lung Association organized an invited workshop on Urban Air Pollution and Health Inequities held 22-24 October 1999 in Washington, DC. This report builds on literature reviews and summarizes the discussions of working groups charged with addressing key areas relevant to air pollution and health effects in urban environments. An overview was provided of the state of the science for health impacts of air pollution and technologies available for air quality monitoring and exposure assessment. The working groups then prioritized research needs to address the knowledge gaps and developed recommendations for community interventions and public policy to begin to remedy the exposure and health inequities.

Published Jun 1, 2001

American Lung Association. (2001). Urban air pollution and health inequities: a workshop report. Environmental Health Perspectives, 109(suppl 3), 357–374. https://doi.org/10.1289/ehp.109-1240553

Context: Vehicle exhaust is a major source of ozone and other air pollutants. Although high ground-level ozone pollution is associated with transient increases in asthma morbidity, the impact of citywide transportation changes on air quality and childhood asthma has not been studied. The alternative transportation strategy implemented during the 1996 Summer Olympic Games in Atlanta, Ga, provided such an opportunity. Objective: To describe traffic changes in Atlanta, Ga, during the 1996 Summer Olympic Games and concomitant changes in air quality and childhood asthma events. Design: Ecological study comparing the 17 days of the Olympic Games (July 19-August 4, 1996) to a baseline period consisting of the 4 weeks before and 4 weeks after the Olympic Games. Setting and Subjects: Children aged 1 to 16 years who resided in the 5 central counties of metropolitan Atlanta and whose data were captured in 1 of 4 databases. Main Outcome Measures: Citywide acute care visits and hospitalizations for asthma (asthma events) and nonasthma events, concentrations of major air pollutants, meteorological variables, and traffic counts. Results: During the Olympic Games, the number of asthma acute care events decreased 41.6% (4.23 vs 2.47 daily events) in the Georgia Medicaid claims file, 44.1% (1.36 vs 0.76 daily events) in a health maintenance organization database, 11.1% (4.77 vs 4.24 daily events) in 2 pediatric emergency departments, and 19.1% (2.04 vs 1.65 daily hospitalizations) in the Georgia Hospital Discharge Database. The number of nonasthma acute care events in the 4 databases changed -3.1%, +1.3%, -2.1%, and +1.0%, respectively. In multivariate regression analysis, only the reduction in asthma events recorded in the Medicaid database was significant (relative risk, 0.48; 95% confidence interval, 0.44-0.86). Peak daily ozone concentrations decreased 27.9%, from 81.3 ppb during the baseline period to 58.6 ppb during the Olympic Games (P<.001). Peak weekday morning traffic counts dropped 22.5% (P<.001). Traffic counts were significantly correlated with that day's peak ozone concentration (average r=0.36 for all 4 roads examined). Meteorological conditions during the Olympic Games did not differ substantially from the baseline period. Conclusions: Efforts to reduce downtown traffic congestion in Atlanta during the Olympic Games resulted in decreased traffic density, especially during the critical morning period. This was associated with a prolonged reduction in ozone pollution and significantly lower rates of childhood asthma events. These data provide support for efforts to reduce air pollution and improve health via reductions in motor vehicle traffic.

Published Feb 1, 2001

Friedman, M. S., Powell, K. E., Hutwagner, L., Graham, L. R. M., & Teague, W. G. (2001). Impact of changes in transportation and commuting behaviors during the 1996 Summer Olympic Games in Atlanta on air quality and childhood asthma. Journal of the American Medical Association, 285(7), 897–905. https://doi.org/10.1001/jama.285.7.897

Background. Air pollution in cities has been linked to increased rates of mortality and morbidity in developed and developing countries. Although these findings have helped lead to a tightening of air-quality standards, their validity with respect to public health has been questioned. Methods. We assessed the effects of five major outdoor-air pollutants on daily mortality rates in 20 of the largest cities and metropolitan areas in the United States from 1987 to 1994. The pollutants were particulate matter that is less than 10 μm in aerodynamic diameter (PM10), ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide. We used a two-stage analytic approach that pooled data from multiple locations. Results After taking into account potential confounding by other pollutants, we found consistent evidence that the level of PM10 is associated with the rate of death from all causes and from cardiovascular and respiratory illnesses. The estimated increase in the relative rate of death from all causes was 0.51 percent (95 percent posterior interval, 0.07 to 0.93 percent) for each increase in the PM10 level of 10 μg per cubic meter. The estimated increase in the relative rate of death from cardiovascular and respiratory causes was 0.68 percent (95 percent posterior interval, 0.20 to 1.16 percent) for each increase in the PM10 level of 10 μg per cubic meter. There was weaker evidence that increases in ozone levels increased the relative rates of death during the summer, when ozone levels are highest, but not during the winter. Levels of the other pollutants were not significantly related to the mortality rate. Conclusions. There is consistent evidence that the levels of fine particulate matter in the air are associated with the risk of death from all causes and from cardiovascular and respiratory illnesses. These findings strengthen the rationale for controlling the levels of respirable particles in outdoor air. (C) 2000, Massachusetts Medical Society.

Published Dec 14, 2000

Samet, J. M., Dominici, F., Curriero, F. C., Coursac, I., & Zeger, S. L. (2000). Fine Particulate Air Pollution and Mortality in 20 U.S. Cities, 1987–1994. New England Journal of Medicine, 343(24), 1742–1749. https://doi.org/10.1056/NEJM200012143432401

Misclassification of exposure is a well-recognized inherent limitation of epidemiologic studies of disease and the environment. For many agents of interest, exposures take place over time and in multiple locations; accurately estimating the relevant exposures for an individual participant in epidemiologic studies is often daunting, particularly within the limits set by feasibility, participant burden, and cost. Researchers have taken steps to deal with the consequences of measurement error by limiting the degree of error through a study's design, estimating the degree of error using a nested validation study, and by adjusting for measurement error in statistical analyses. In this paper, we address measurement error in observational studies of air pollution and health. Because measurement error may have substantial implications for interpreting epidemiologic studies on air pollution, particularly the time-series analyses, we developed a systematic conceptual formulation of the problem of measurement error in epidemiologic studies of air pollution and then considered the consequences within this formulation. When possible, we used available relevant data to make simple estimates of measurement error effects. This paper provides an overview of measurement errors in linear regression, distinguishing two extremes of a continuum-Berkson from classical type errors, and the univariate from the multivariate predictor case. We then propose one conceptual framework for the evaluation of measurement errors in the log-linear regression used for time-series studies of particulate air pollution and mortality and identify three main components of error. We present new simple analyses of data on exposures of particulate matter < 10 microm in aerodynamic diameter from the Particle Total Exposure Assessment Methodology Study. Finally, we summarize open questions regarding measurement error and suggest the kind of additional data necessary to address them.

Published May 1, 2000

Bruno, L. (2019). 済無No Title No Title. Journal of Chemical Information and Modeling, 53(9), 1689–1699. https://doi.org/10.1017/CBO9781107415324.004