51 research outputs found
Air Pollution Exposure Assessment for Epidemiologic Studies of Pregnant Women and Children: Lessons Learned from the Centers for Childrenâs Environmental Health and Disease Prevention Research
The National Childrenâs Study is considering a wide spectrum of airborne pollutants that are hypothesized to potentially influence pregnancy outcomes, neurodevelopment, asthma, atopy, immune development, obesity, and pubertal development. In this article we summarize six applicable exposure assessment lessons learned from the Centers for Childrenâs Environmental Health and Disease Prevention Research that may enhance the National Childrenâs Study: a) Selecting individual study subjects with a wide range of pollution exposure profiles maximizes spatial-scale exposure contrasts for key pollutants of study interest. b) In studies with large sample sizes, long duration, and diverse outcomes and exposures, exposure assessment efforts should rely on modeling to provide estimates for the entire cohort, supported by subject-derived questionnaire data. c) Assessment of some exposures of interest requires individual measurements of exposures using snapshots of personal and microenvironmental exposures over short periods and/or in selected microenvironments. d) Understanding issues of spatialâtemporal correlations of air pollutants, the surrogacy of specific pollutants for components of the complex mixture, and the exposure misclassification inherent in exposure estimates is critical in analysis and interpretation. e) âUsualâ temporal, spatial, and physical patterns of activity can be used as modifiers of the exposure/outcome relationships. f) Biomarkers of exposure are useful for evaluation of specific exposures that have multiple routes of exposure. If these lessons are applied, the National Childrenâs Study offers a unique opportunity to assess the adverse effects of air pollution on interrelated health outcomes during the critical early life period
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Evidence Synthesis of Observational Studies in Environmental Health: Lessons Learned from a Systematic Review on Traffic-Related Air Pollution.
BACKGROUND: There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE. METHODS: We applied a modified OHAT approach and a broader narrative assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes. DISCUSSION: We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, narrative evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532
Near-Roadway Air Pollution and Coronary Heart Disease: Burden of Disease and Potential Impact of a Greenhouse Gas Reduction Strategy in Southern California
Background: Several studies have estimated the burden of coronary heart disease (CHD) mortality from ambient regional particulate matter †2.5 Όm (PM2.5). The burden of near-roadway air pollution (NRAP) generally has not been examined, despite evidence of a causal link with CHD.
Objective: We investigated the CHD burden from NRAP and compared it with the PM2.5 burden in the California South Coast Air Basin for 2008 and under a compact urban growth greenhouse gas reduction scenario for 2035.
Methods: We estimated the population attributable fraction and number of CHD events attributable to residential traffic density, proximity to a major road, elemental carbon (EC), and PM2.5 compared with the expected disease burden if the population were exposed to background levels of air pollution.
Results: In 2008, an estimated 1,300 CHD deaths (6.8% of the total) were attributable to traffic density, 430 deaths (2.4%) to residential proximity to a major road, and 690 (3.7%) to EC. There were 1,900 deaths (10.4%) attributable to PM2.5. Although reduced exposures in 2035 should result in smaller fractions of CHD attributable to traffic density, EC, and PM2.5, the numbers of estimated deaths attributable to each of these exposures are anticipated to increase to 2,500, 900, and 2,900, respectively, due to population aging. A similar pattern of increasing NRAP-attributable CHD hospitalizations was estimated to occur between 2008 and 2035.
Conclusion: These results suggest that a large burden of preventable CHD mortality is attributable to NRAP and is likely to increase even with decreasing exposure by 2035 due to vulnerability of an aging population. Greenhouse gas reduction strategies developed to mitigate climate change offer unexploited opportunities for air pollution health co-benefits
Physics-Informed Deep Learning to Reduce the Bias in Joint Prediction of Nitrogen Oxides
Atmospheric nitrogen oxides (NOx) primarily from fuel combustion have
recognized acute and chronic health and environmental effects. Machine learning
(ML) methods have significantly enhanced our capacity to predict NOx
concentrations at ground-level with high spatiotemporal resolution but may
suffer from high estimation bias since they lack physical and chemical
knowledge about air pollution dynamics. Chemical transport models (CTMs)
leverage this knowledge; however, accurate predictions of ground-level
concentrations typically necessitate extensive post-calibration. Here, we
present a physics-informed deep learning framework that encodes
advection-diffusion mechanisms and fluid dynamics constraints to jointly
predict NO2 and NOx and reduce ML model bias by 21-42%. Our approach captures
fine-scale transport of NO2 and NOx, generates robust spatial extrapolation,
and provides explicit uncertainty estimation. The framework fuses
knowledge-driven physicochemical principles of CTMs with the predictive power
of ML for air quality exposure, health, and policy applications. Our approach
offers significant improvements over purely data-driven ML methods and has
unprecedented bias reduction in joint NO2 and NOx prediction
Temporal and Spatial Patterns of Ambient Endotoxin Concentrations in Fresno, California
BackgroundEndotoxins are found in indoor dust generated by human activity and pets, in soil, and adsorbed onto the surfaces of ambient combustion particles. Endotoxin concentrations have been associated with respiratory symptoms and the risk of atopy and asthma in children.ObjectiveWe characterized the temporal and spatial variability of ambient endotoxin in Fresno/Clovis, California, located in California's Central Valley, to identify correlates and potential predictors of ambient endotoxin concentrations in a cohort of children with asthma [Fresno Asthmatic Children's Environment Study (FACES)].MethodsBetween May 2001 and October 2004, daily ambient endotoxin and air pollutants were collected at the central ambient monitoring site of the California Air Resources Board in Fresno and, for shorter time periods, at 10 schools and indoors and outdoors at 84 residences in the community. Analyses were restricted to May-October, the dry months during which endotoxin concentrations are highest.ResultsDaily endotoxin concentration patterns were determined mainly by meteorologic factors, particularly the degree of air stagnation. Overall concentrations were lowest in areas distant from agricultural activities. Highest concentrations were found in areas immediately downwind from agricultural/pasture land. Among three other measured air pollutants [fine particulate matter, elemental carbon (a marker of traffic in Fresno), and coarse particulate matter (PMc)], PMc was the only pollutant correlated with endotoxin. Endotoxin, however, was the most spatially variable.ConclusionsOur data support the need to evaluate the spatial/temporal variability of endotoxin concentrations, rather than relying on a few measurements made at one location, in studies of exposure and and respiratory health effects, particularly in children with asthma and other chronic respiratory diseases
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Prenatal exposure to ambient air pollutants and early infant growth and adiposity in the Southern California Mother's Milk Study
Background
Prior epidemiological and animal work has linked in utero exposure to ambient air pollutants (AAP) with accelerated postnatal weight gain, which is predictive of increased cardiometabolic risk factors in childhood and adolescence. However, few studies have assessed changes in infant body composition or multiple pollutant exposures. Therefore, the objective of this study was to examine relationships between prenatal residential AAP exposure with infant growth and adiposity.
Methods
Residential exposure to AAP (particulate matter < 2.5 and 10 microns in aerodynamic diameter [PM2.5, PM10]; nitrogen dioxide [NO2]; ozone [O3]; oxidative capacity [Oxwt: redox-weighted oxidative potential of O3 and NO2]) was modeled by spatial interpolation of monitoring stations via an inverse distance-squared weighting (IDW2) algorithm for 123 participants from the longitudinal Mother’s Milk Study, an ongoing cohort of Hispanic mother-infant dyads from Southern California. Outcomes included changes in infant growth (weight, length), total subcutaneous fat (TSF; calculated via infant skinfold thickness measures) and fat distribution (umbilical circumference, central to total subcutaneous fat [CTSF]) and were calculated by subtracting 1-month measures from 6-month measures. Multivariable linear regression was performed to examine relationships between prenatal AAP exposure and infant outcomes. Models adjusted for maternal age, pre-pregnancy body mass index, socioeconomic status, infant age, sex, and breastfeeding frequency. Sex interactions were tested, and effects are reported for each standard deviation increase in exposure.
Results
NO2 was associated with greater infant weight gain (β = 0.14, p = 0.02) and TSF (β = 1.69, p = 0.02). PM10 and PM2.5 were associated with change in umbilical circumference (β = 0.73, p = 0.003) and TSF (β = 1.53, p = 0.04), respectively. Associations of Oxwt (pinteractions < 0.10) with infant length change, umbilical circumference, and CTSF were modified by infant sex. Oxwt was associated with attenuated infant length change among males (β = -0.60, p = 0.01), but not females (β = 0.16, p = 0.49); umbilical circumference among females (β = 0.92, p = 0.009), but not males (β = -0.00, p = 0.99); and CTSF among males (β = 0.01, p = 0.03), but not females (β = 0.00, p = 0.51).
Conclusion
Prenatal AAP exposure was associated with increased weight gain and anthropometric measures from 1-to-6 months of life among Hispanic infants. Sex-specific associations suggest differential consequences of in utero oxidative stress. These results indicate that prenatal AAP exposure may alter infant growth, which has potential to increase childhood obesity risk.
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Short-Term Effects of Air Pollution on Wheeze in Asthmatic Children in Fresno, California
BACKGROUND: Although studies have demonstrated that air pollution is associated with exacerbation of asthma symptoms in children with asthma, little is known about the susceptibility of subgroups, particularly those with atopy. OBJECTIVE: This study was designed to evaluate our a priori hypothesis that identifiable subgroups of asthmatic children are more likely to wheeze with exposure to ambient air pollution. METHODS: A cohort of 315 children with asthma, 6-11 years of age, was recruited for longitudinal follow-up in Fresno, California (USA). During the baseline visit, children were administered a respiratory symptom questionnaire and allergen skin-prick test. Three times a year, participants completed 14-day panels during which they answered symptom questions twice daily. Ambient air quality data from a central monitoring station were used to assign exposures to the following pollutants: particulate matter <= 2.5 mu m in aerodynamic diameter, particulate matter between 2.5 and 10 mu m in aerodynamic diameter (PM(10-2.5)), elemental carbon, nitrogen dioxide (NO(2)), nitrate, and O(3). RESULTS: For the group as a whole, wheeze was significantly associated with short-term exposures to NO(2) [odds ratio (OR) = 1.10 for 8.7-ppb increase; 95% confidence interval (CI), 1.02-1.20] and PM(10-2.5) (OR = 1.11 for 14.7-mu g/m(3) increase; 95% CI, 1.01-1.22). The association with wheeze was stronger for these two pollutants in children who were skin-test positive to cat or common fungi and in boys with mild intermittent asthma. CONCLUSION: A pollutant associated with traffic emissions, NO(2), and a pollutant with bioactive constituents, PM(10-2.5), were associated with increased risk of wheeze in asthmatic children living in Fresno, California. Children with atopy to cat or common fungi and boys with mild intermittent asthma were the subgroups for which we observed the largest associations
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Postnatal exposure to ambient air pollutants is associated with the composition of the infant gut microbiota at 6-months of age
Epidemiological studies in adults have shown that exposure to ambient air pollution (AAP) is associated with the composition of the adult gut microbiome, but these relationships have not been examined in infancy. We aimed to determine if 6-month postnatal AAP exposure was associated with the infant gut microbiota at 6 months of age in a cohort of Latino mother-infant dyads from the Southern California Mother’s Milk Study (n = 103). We estimated particulate matter (PM2.5 and PM10) and nitrogen dioxide (NO2) exposure from birth to 6-months based on residential address histories. We characterized the infant gut microbiota using 16S rRNA amplicon sequencing at 6-months of age. At 6-months, the gut microbiota was dominated by the phyla Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Our results show that, after adjusting for important confounders, postnatal AAP exposure was associated with the composition of the gut microbiota. As an example, PM10 exposure was positively associated with Dialister, Dorea, Acinetobacter, and Campylobacter while PM2.5 was positively associated with Actinomyces. Further, exposure to PM10 and PM2.5 was inversely associated with Alistipes and NO2 exposure was positively associated with Actinomyces, Enterococcus, Clostridium, and Eubacterium. Several of these taxa have previously been linked with systemic inflammation, including the genera Dialister and Dorea. This study provides the first evidence of significant associations between exposure to AAP and the composition of the infant gut microbiota, which may have important implications for future infant health and development.
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Economic Valuation of Ozone-Related School Absences in the South Coast Air Basin of California
Air quality in the South Coast Air Basin of southern California has improved significantly over the past decade, although pollution levels continue to exceed health-based standards on a significant number of days. This study estimates the decline in ozone-related school absences in southern California over the 1990s, reported as differences in the number of days of respiratory illness-related absences, the number of days of all illness-related absences, and the economic loss to families of those absences. The study reports differences in the number of these effects for the intervals 1990-92 to 1997-99, for rolling three-year intervals to 1997-99 across that period, and for expected future reductions in ozone. The baseline population is the cohort aged 5-18 residing in the South Coast Air Basin in 1998. For the interval 1990-92 to 1997-99, the economic value of fewer school absences ranges from 330 million annually, with a best estimate of 75, on average, for every school-age child in the region. (JEL "I10", "I12", "Q2", "Q25") Copyright 2003 Western Economic Association International.
Air pollution, health and economic benefits--Lessons from 20ĂÂ years of analysis
This paper reviews and compares two air quality benefit assessments completed for California's South Coast Air Basin in 1989 and 2008. Specifically, we separate the influence of changes in population and air quality from that of newer health concentration-response relationships and changing economic values. The dynamic interaction of key variables, including health and economic, as well as changes in population and air quality, lead to significant changes in results over time. Results show dramatic reductions in exposures to ozone and particulate concentrations between the two time periods, a continually evolving health literature, and in contrast, fairly constant real economic unit values assigned to adverse health outcomes. Such research is important because highly technical analyses of the expected benefits of proposed air quality regulatory programs have become an increasingly important component of many decision-making processes.Benefit estimation Valuation Air pollution Health
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