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PM10 Particulates: Are They the Major Determinant of Pediatric Respiratory Admissions in Utah County, Utah (1985-1989)
Abstract
A previous study examined temporal patterns of respiratory hospitalizations and PM10levels in Utah County, Utah, between April 1985 and February 1988. Statistically significant correlations were found between monthly PM1 0 levels and pediatric admissions for pneumoniapleurisy and bronchitis-asthma. We performed an expanded analysis and found strong, coherent evidence that the major determinant of elevated levels of pediatric respiratory hospitalizations was biological rather than chemical. Respiratory syncytial virus (RSV) activity was the single explanatory factor that consistently accounted for a statistically significant portion of the observed variations of pediatric respiratory hospitalizations. No coherent evidence of residual statistical associations between PM10 levels and hospitalizations was found for any age group or respiratory illnes.
... Vanadium has been frequently associated with boilermaker's bronchitis (Levy et al, 1984) and Ni has been classified as a human carcinogen (IARC, 1990) in addition to its sensitizing effects (Menne et al, 1989). Environmental PM collected in industrial areas has been noted to contain these toxic metals (Spengler and Thurston, 1983;Lamm et al., 1994). Respiratory diseases in humans have been associated with PM air pollutants in industrial areas emitting metallic PM (Lamm et al, 1994). ...
... Environmental PM collected in industrial areas has been noted to contain these toxic metals (Spengler and Thurston, 1983;Lamm et al., 1994). Respiratory diseases in humans have been associated with PM air pollutants in industrial areas emitting metallic PM (Lamm et al, 1994). However, the definitive role of metal versus other causative constituents has not been confirmed in epidemiologic studies associating PM air pollution with mortality of susceptible populations (Dockery et al, 1993;Schwartz, 1994). ...
Occupational exposure to residual oil fly ash (ROFA) particulate has been associated with adverse respiratory health effects in humans. We hypothesized that ROFA collected at different sites within an oil burning power plant, by virtue of its differing metal and sulfate composition, will induce differential lung injury. Ten ROFA samples collected at various sites within a power plant were analyzed for water- and 1.0 M HCl-leachable arsenic (As), beryllium (Be), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), vanadium (V), zinc (Zn), and sulfur by inductively coupled plasma-atomic emission spectroscopy. All ROFA samples contained variable amounts of leachable (water-extractable) and 1.0 M HCl-extractable Fe, V, and/or Ni. All other metals, except Zn (ROFA No. 1 contained 3.43 and No. 3, 6.35 micrograms/mg Zn), were present in negligible quantities (< 1.0 microgram/mg) in the water extract. In vivo pulmonary injury from exposure to whole saline suspensions of these ROFA was evaluated. Male, SD rats (60 days old) were intratracheally instilled with either saline or saline suspension of whole ROFA (< 3.0 mass median aerodynamic diameter) at three concentrations (0.833, 3.33, or 8.33 mg/kg). After 24 h, lungs were lavaged and bronchoalveolar lavage fluid (BALF) was analyzed for cellular influx and protein content as well as lactate dehydrogenase (LDH) and N-acetyl glucosaminidase (NAG) activity and total hemoglobin as indicators of lung injury. ROFA-induced increases in BALF protein and LDH, but not neutrophilic inflammation, were associated with its water-leachable total metal, Ni, Fe, and sulfate content. However, the neutrophilic response following ROFA exposure was positively correlated with its water-leachable V content. Modest lung injury was observed with the ROFA samples which contained the smallest amounts of water-leachable metals. The ability of ROFA to induce oxidative burst in alveolar macrophage (AM) was determined in vitro using a chemiluminescence (CL) assay. AM CL signals in vitro were greatest with ROFA containing primarily soluble V and were less with ROFA containing Ni plus V. In summary, ROFA-induced in vivo acute pulmonary inflammation appears to be associated with its water-leachable V content; however, protein leakage appears to be associated with its water-leachable Ni content. ROFA-induced in vitro activation of AM was highest with ROFA containing leachable V but not with Ni plus V, suggesting that the potency and the mechanism of pulmonary injury will differ between emissions containing V and Ni.
... An early study observed that the shutdown of the steel mill was associated with large reductions in PM pollution with accompanying large reductions in pediatric respiratory hospital admissions. 28 Although there was some controversy and debate regarding the interpretation of this study, 202,344 subsequent epidemiologic studies in the valley continued to observe PM associations with hospitalizations, 29 lung function and respiratory symptoms, 30 -32 school absences, 33 and mortality. 20 291 24-hr PM 10 90 elderly (8760 obs), Utah Valley 3-min m Peters et al. , 2000 Pollution episode 2681 adults, Augsburg, Germany 20-sec m Liao et al. 1999 294 24-hr PM 2.5 26 elderly (wk), Baltimore 6-min n n n Pope et al. 1999 295 1-or 2-day PM 10 310 1-to 4-hr PM 0.3-1 26 CHD/hypertensive patients in Taipei, Taiwan 5-min n n Notes: Positive PM-effect estimates are indicated by m, negative PM-effect estimates are indicated by n, no effects indicated by 3, multiple arrows indicate inconsistent mixed effects from different studies; CHD ϭ coronary heart disease. ...
Efforts to understand and mitigate the health effects of particulate matter (PM) air pollution have a rich and interesting history. This review focuses on six substantial lines of research that have been pursued since 1997 that have helped elucidate our understanding about the effects of PM on human health. There has been substantial progress in the evaluation of PM health effects at different timescales of exposure and in the exploration of the shape of the concentration-response function. There has also been emerging evidence of PM-related cardiovascular health effects and growing knowledge regarding interconnected general pathophysiological pathways that link PM exposure with cardiopulmonary morbidity and mortality. Despite important gaps in scientific knowledge and continued reasons for some skepticism, a comprehensive evaluation of the research findings provides persuasive evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonary health. Although much of this research has been motivated by environmental public health policy, these results have important scientific, medical, and public health implications that are broader than debates over legally mandated air quality standards.
... An early study observed that the shutdown of the steel mill was associated with large reductions in PM pollution with accompanying large reductions in pediatric respiratory hospital admissions. 28 Although there was some controversy and debate regarding the interpretation of this study, 202,344 subsequent epidemiologic studies in the valley continued to observe PM associations with hospitalizations, 29 lung function and respiratory symptoms, 30 -32 school absences, 33 and mortality. 20 291 24-hr PM 10 90 elderly (8760 obs), Utah Valley 3-min m Peters et al. , 2000 Pollution episode 2681 adults, Augsburg, Germany 20-sec m Liao et al. 1999 294 24-hr PM 2.5 26 elderly (wk), Baltimore 6-min n n n Pope et al. 1999 295 1-or 2-day PM 10 310 1-to 4-hr PM 0.3-1 26 CHD/hypertensive patients in Taipei, Taiwan 5-min n n Notes: Positive PM-effect estimates are indicated by m, negative PM-effect estimates are indicated by n, no effects indicated by 3, multiple arrows indicate inconsistent mixed effects from different studies; CHD ϭ coronary heart disease. ...
Efforts to understand and mitigate thehealth effects of particulate matter (PM) air pollutionhave a rich and interesting history. This review focuseson six substantial lines of research that have been pursued since 1997 that have helped elucidate our understanding about the effects of PM on human health. There hasbeen substantial progress in the evaluation of PM health effects at different time-scales of exposure and in the exploration of the shape of the concentration-response function. There has also been emerging evidence of PM-related cardiovascular health effects and growing knowledge regarding interconnected general pathophysiological pathways that link PM exposure with cardiopulmonary morbidiity and mortality. Despite important gaps in scientific knowledge and continued reasons for some skepticism, a comprehensive evaluation of the research findings provides persuasive evidence that exposure to fine particulate air pollution has adverse effects on cardiopulmonaryhealth. Although much of this research has been motivated by environmental public health policy, these results have important scientific, medical, and public health implications that are broader than debates over legally mandated air quality standards.
Utah has a rich history related to air pollution; however, it is not widely known or documented. This is despite air quality being a top issue of public concern for the state’s urban residents and acute episodes that feature some of the world’s worst short-term particulate matter exposure. As we discuss in this narrative review, the relationship between air pollution and the state’s residents has changed over time, as fuel sources shifted from wood to coal to petroleum and natural gas. Air pollution rose in prominence as a public issue in the 1880s as Utah’s urban areas grew. Since then, scientific advances have increased the understanding of air quality impacts on human health, groups of concerned citizens worked to raise public awareness, policy makers enacted legislation to improve air quality, and courts upheld rights to clean air. Utah’s air quality future holds challenges and opportunities and can serve as useful case for other urbanizing regions struggling with air quality concerns. Population growth and changing climate will exacerbate current air quality trends, but economically viable clean energy technologies can be deployed to reduce air pollution, bringing substantial public health and economic benefits to the state’s residents and other settings with similar public health concerns.
An aim of applied science in general and of epidemiology in particular is to draw sound causal inferences from observations. For public health policy analysts and epidemiologists, this includes drawing inferences about whether historical changes in exposures have actually caused the consequences predicted for, or attributed to, them. The example of the Dublin coal-burning ban mentioned in Chaps. 15 and 16 suggests that accurate evaluation of the effect of interventions is not always easy, even when data are plentiful. Students are taught to develop hypotheses about causal relations, devise testable implications of these causal hypotheses, carry out the tests, and objectively report and learn from the results to refute or refine the initial hypotheses. For at least the past two decades, however, epidemiologists and commentators on scientific methods and results have raised concerns that current practices too often lead to false-positive findings and to mistaken attributions of causality to mere statistical associations (Lehrer 2012; Sarewitz 2012; Ottenbacher 1998; Imberger et al. 2011). Formal training in epidemiology may be a mixed blessing in addressing these concerns. As discussed in Appendix C of Chap. 9, concepts such as “attributable risk,” “population attributable fraction,” “burden of disease,” “etiologic fraction,” and even “probability of causation” are solidly based on relative risks and related measures of statistical association; they do not necessarily reveal anything about predictive, manipulative, structural, or explanatory (mechanistic) causation (Greenland and Brumback 2002). Limitations of human judgment and inference, such as confirmation bias (finding what we expect to find), motivated reasoning (concluding what it pays us to conclude), and overconfidence (mistakenly believing that our own beliefs are more accurate than they really are), do not spare health effects investigators. Experts in the health effects of particular compounds are not always also experts in causal analysis, and published causal conclusions are often unwarranted, with a pronounced bias toward finding “significant” effects where none actually exists (false positives) (Lehrer 2012; Sarewitz 2012; Ioannidis 2005; The Economist 2013).
An aim of applied science in general, and of epidemiology in particular, is to draw sound causal inferences from observations. For public health policy analysts and epidemiologists, this includes drawing inferences about whether historical changes in exposures have actually caused the consequences predicted for, or attributed to, them. The example of the Dublin coal-burning ban introduced in Chap. 1 suggests that accurate evaluation of the effect of interventions is not always easy, even when data are plentiful. Students are taught to develop hypotheses about causal relations, devise testable implications of these causal hypotheses, carry out the tests, and objectively report and learn from the results to refute or refine the initial hypotheses. For at least the past two decades, however, epidemiologists and commentators on scientific methods and results have raised concerns that current practices too often lead to false-positive findings and to mistaken attributions of causality to mere statistical associations (Lehrer 2012; Sarewitz 2012; Ottenbacher 1998; Imberger et al. 2011). Formal training in epidemiology may be a mixed blessing in addressing these concerns. As discussed in Chap. 2, concepts such as “attributable risk,” “population attributable fraction,” “burden of disease,” “etiologic fraction,” and even “probability of causation” are solidly based on relative risks and related measures of statistical association; they do not necessarily reveal anything about predictive, manipulative, structural, or explanatory (mechanistic) causation (e.g., Cox 2013; Greenland and Brumback 2002). Limitations of human judgment and inference, such as confirmation bias (finding what we expect to find), motivated reasoning (concluding what it pays us to conclude), and overconfidence (mistakenly believing that our own beliefs are more accurate than they really are), do not spare health effects investigators. Experts in the health effects of particular compounds are not always also experts in causal analysis, and published causal conclusions are often unwarranted, as reviewed in Chap. 2, with a pronounced bias toward finding “significant” effects where none actually exists (false positives) (Lehrer 2012; Sarewitz 2012; Ioannidis 2005; The Economist 2013). © Springer International Publishing AG, part of Springer Nature 2018.
Acting effectively in an uncertain world requires two main skills: predicting the probable consequences of alternative courses of action and choosing actions that make preferred consequences more likely. Risk analysis supports and applies both skills. It provides a framework to enable its practitioners to assess the probable consequences of alternative choices (including the status quo), to communicate technical findings and remaining uncertainties effectively to different audiences, and to use the results to advise risk managers and policy makers about what to do next. These three core components of risk assessment, risk communication, and risk management are making risk analysis invaluable in widely diverse applications. Prominent application areas include project risk management, enterprise risk management, nuclear and aviation safety, community-based disaster preparation and planning, health effects research, drug development, product safety assessment, ecotoxicology, regulatory program evaluation, public health, and other areas of applied risk research and management.
Purpose:
Between 2000 and 2010, air pollutant levels in counties throughout the United States changed significantly, with fine particulate matter (PM2.5) declining over 30% in some counties and ozone (O3) exhibiting large variations from year to year. This history provides an opportunity to compare county-level changes in average annual ambient pollutant levels to corresponding changes in all-cause (AC) and cardiovascular disease (CVD) mortality rates over the course of a decade. Past studies have demonstrated associations and subsequently either interpreted associations causally or relied on subjective judgments to infer causation. This article applies more quantitative methods to assess causality.
Methods:
This article examines data from these "natural experiments" of changing pollutant levels for 483 counties in the 15 most populated US states using quantitative methods for causal hypothesis testing, such as conditional independence and Granger causality tests. We assessed whether changes in historical pollution levels helped to predict and explain changes in CVD and AC mortality rates.
Results:
A causal relation between pollutant concentrations and AC or CVD mortality rates cannot be inferred from these historical data, although a statistical association between them is well supported. There were no significant positive associations between changes in PM2.5 or O3 levels and corresponding changes in disease mortality rates between 2000 and 2010, nor for shorter time intervals of 1 to 3 years.
Conclusions:
These findings suggest that predicted substantial human longevity benefits resulting from reducing PM2.5 and O3 may not occur or may be smaller than previously estimated. Our results highlight the potential for heterogeneity in air pollution health effects across regions, and the high potential value of accountability research comparing model-based predictions of health benefits from reducing air pollutants to historical records of what actually occurred.
Improving Risk Analysis discusses and illustrates practical methods for assessing, communicating, and managing uncertain risks when the probabilities of consequences caused by alternative actions cannot be quantified with useful confidence, accuracy, and precision. This monograph demonstrates how to avoid these pitfalls by using improved techniques of risk analysis. Through these improved techniques of risk analysis, readers will better understand uncertain risks and be able to make more effective decisions about how to manage them.
The book is divided into three parts. Parts 1 and 2 explore the key principles on how high-quality risk analysis can greatly improve the clarity and effectiveness of decisions when the consequences of different choices are uncertain. Part 3 shows in greater detail how these introduced methods can be applied to health effects of air pollution, with emphasis on understanding and modeling causal relations between exposures and responses based on realistically limited and imperfect data. Throughout the book, real-world examples and case studies drawn from health, safety, environmental, and terrorism risk analysis are used and illustrate the practical application of techniques for improving risk analysis.
Using epidemiological meta studies for the health impacts of small particulate matter — PM10 — it is possible to predict the number of premature deaths and some morbidity impacts in the UK from prevailing ambient concentrations. The analysis suggests that as many as 12 000 deaths might be attributed to total concentrations, or perhaps 7000 deaths if only ‘anthropogenic’ PM10 is included. The nature of these premature deaths is unclear. They are almost certainly among the older population so that foreshortened lives may be measured in days, months or years. Morbidity effects can similarly be estimated, the main ones of policy concern being chronic bronchitis and ‘restricted activity days’. Unit economic values are applied to these health impacts in order to ‘collapse’ different impacts into a common unit. The end result is a premature mortality cost of about £11.1 billion (urban plus rural exposure) and a further £6.3 billion for urban morbidity.
The mechanisms by which increased mortality and morbidity occur in individuals with preexistent cardiopulmonary disease following acute episodes of air pollution are unknown. Studies involving air pollution effects on animal models of human cardiopulmonary diseases are both infrequent and difficult to interpret. Such models are, however, extensively used in studies of disease pathogenesis. Primarily they comprise those developed by genetic, pharmacologic, or surgical manipulations of the cardiopulmonary system. This review attempts a comprehensive description of rodent cardiopulmonary disease models in the context of their potential application to susceptibility studies of air pollutants regardless of whether the models have been previously used for such studies. The pulmonary disease models include bronchitis, emphysema, asthma/allergy, chronic obstructive pulmonary disease, interstitial fibrosis, and infection. The models of systemic hypertension and congestive heart failure include: those derived by genetics (spontaneously hypertensive, Dahl S. renin transgenic, and other rodent models); congestive heart failure models derived by surgical manipulations; viral myocarditis; and cardiomyopathy induced by adriamycin. The characteristic pathogenic features critical to understanding the susceptibility to inhaled toxicants are described. It is anticipated that this review will provide a ready reference for the selection of appropriate rodent models of cardiopulmonary diseases and identify not only their pathobiologic similarities and/or differences to humans but also their potential usefulness in susceptibility studies.
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Transition metals are components of airborne particles and have been implicated in adverse health effects. The relative inflammatory potential of these metals is usually inferred from separate studies that focus on only one or a few individual metals. Comparisons of relative potency among several metals from these separate studies can be difficult. In one comprehensive study, we measured the pulmonary effects of equimolar doses of six metals in soluble form. Our purpose was to compare inflammatory potential and pulmonary toxicity among individual transition metals. Rats received saline, 0.1 or 1.0 micromol/kg of vanadium, nickel, iron(II), copper, manganese, or zinc as sulfates. Bronchoalveolar lavage (BAL) was performed at 0, 4, 16, or 48 h postinstillation. All treatments except V showed increased lactate dehydrogenase activity in BAL fluid; Cu- and Ni-exposed animals had the highest levels. Protein levels in BAL fluid were more than five times higher in Cu-exposed animals compared to other metal treatments at 16 and 48 h. At the 0.1 micromol/kg dose, only Cu induced significant neutrophilia at 16 and 48 h. For the 1.0 micromol/kg dose, all metals tested induced significant neutrophilia, with mean neutrophil numbers for Cu and Mn significantly higher compared to the other metals. At 48 h, neutrophil numbers were still elevated in all metal exposures. Only Mn caused substantial eosinophilia. At the 1.0 micromol/kg dose, only Cu induced macrophage inflammatory protein-2 (MIP-2) mRNA at 4 h. By 48 h, induction of MIP-2 mRNA was observed for all metal exposures except Cu, which subsequently returned to baseline levels. On an equimolar basis, Cu was the most proinflammatory metal, followed by Mn and Ni, while V, Fe(II), and Zn induced similar levels of inflammation. Overall, there were many similarities in the pulmonary responses of the metals we tested. However, we also observed divergent, metal-specific responses. These differential responses suggest that metals induce pulmonary inflammation by differing pathways or combinations of signals.
Winter air pollution in Christchurch is dominated by particulate matter from solid fuel domestic heating. The aim of the study was to explore the relationship between particulate air pollution and admissions to hospital with cardio-respiratory illnesses.
Particulate air pollution statistics (PM10) were obtained from the Canterbury Regional Council monitoring station in the city. The New Zealand Health Information Service provided data on admissions to the Princess Margaret and Christchurch Hospitals for the period June 1988 through December 1998 for both adults and children with cardiac and respiratory disorders. The relationship between PM10 and admissions was explored using a time series analysis approach controlling for weather variables. Missing values were interpolated from carbon monoxide data for the same time period, as carbon monoxide and PM10 were highly correlated.
There was a significant association between PM10 levels and cardio-respiratory admissions. For all age groups combined there was a 3.37% increase in respiratory admissions for each interquartile rise in PM10 (interquartile value 14.8 mcg/m3). There was also a 1.26% rise in cardiac admissions for each interquartile rise in PM10. There was no relationship between PM10 and admissions for appendicitis, the control condition selected.
In keeping with overseas studies, there is evidence in Christchurch of a relationship between ambient particulate levels and admissions with cardiac and respiratory illnesses. The size of the effect is consistent with overseas data, with the greatest impact for respiratory disorders. Implications: These results indicate that measures to control ambient particulate levels have the potential to reduce hospital admissions for cardio-respiratory illnesses.
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).
I review the rationale for the Environmental Protection Agency's 1996 fine particle standard, which was based almost entirely on the epidemiological data with neither support from Toxicology nor understanding of mechanism. While many epidemiological papers available in 1996 reported associations between ambient particles and adverse effects on human health, many others did not and the evidence fell far short of supporting a causal association between particle mass concentration and human health. The literature appearing after 1996 further complicates the picture. The large studies that have appeared after 1996, such as National Mortality Morbidity and Air Pollution Study, and the reanalyses of the American Cancer Society II study, report risks that are substantially smaller than the risks reported in the 1996 Criteria Document and Staff Paper. Moreover, concerns about confounding by weather, temporal trends and co-pollutants remain unresolved. Other issues having to do with model choice have resurfaced as a result of reanalyses of critical data to address a glitch in a widely used software package for time-series epidemiology studies of air pollution. Finally, contemporary examples show that the results of observational epidemiology studies can be seriously biased, particularly when estimated risks are small, as is the case with studies of air pollution. The Agency has largely ignored these issues. I conclude that a particle mass standard is not defensible on the basis of a causal association between ambient particle mass and adverse effects on human health. Such a standard may be justifiable on the basis of the precautionary principle, however. The Agency could argue that the Science raises concerns about current levels of air pollution, and that reduction of ambient fine particulate matter mass, if it could be achieved without an increase in the level of the ultrafines, could have positive effects on human health. If the Agency justifies a particulate matter mass standard on these grounds then the debate over the form and level of the standard will, for all practical purposes, belong strictly in the Policy arena.
Air pollution caused by motor vehicles is a major environmental problem in many Latin American urban centers. If appropriate measures are not taken soon, vehicular air pollution in the region is likely to worsen, posing a great threat to human health and welfare. This report analyzes the pollutants emitted by motor vehicles, their effects, and pollutant-control measures targeted at vehicles, fuels, and transport management. Case studies for Mexico City, Mexico, Santiago, Chile, São Paulo, Brazil, Belo Horizonte, Brazil, Buenos Aires, Argentina, Rio de Janeiro, Brazil, and Santafé de Bogotá, Colombia, illustrate how these measures have been used in the region and how they can be strengthened.
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