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Fine particulate matter pollution linked to respiratory illness in infants and increased hospital costs.

ABSTRACT: There has been little research to date on the linkages between air pollution and infectious respiratory illness in children, and the resulting health care costs. In this study we used data on air pollutants and national hospitalizations to study the relationship between fine particulate air pollution and health care charges and costs for the treatment of bronchiolitis, an acute viral infection of the lungs. We found that as the average exposure to fine particulate matter over the lifetime of an infant increased, so did costs for the child's health care. If the United States were to reduce levels of fine particulate matter to 7 percent below the current annual standard, the nation could save $15 million annually in reduced health care costs from hospitalizations of children with bronchiolitis living in urban areas. These findings reinforce the need for ongoing efforts to reduce levels of air pollutants. They should trigger additional investigation to determine if the current standards for fine-particulate matter are sufficiently protective of children's health.

SUBMITTER: Sheffield P

PROVIDER: S-EPMC6643957 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Fine particulate matter pollution linked to respiratory illness in infants and increased hospital costs.

Sheffield Perry P Roy Angkana A Wong Kendrew K Trasande Leonardo L

Health affairs (Project Hope) 20110504 5

There has been little research to date on the linkages between air pollution and infectious respiratory illness in children, and the resulting health care costs. In this study we used data on air pollutants and national hospitalizations to study the relationship between fine particulate air pollution and health care charges and costs for the treatment of bronchiolitis, an acute viral infection of the lungs. We found that as the average exposure to fine particulate matter over the lifetime of an ...[more]

PMID: 21543422

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Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Project description:Objective: To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM2.5) for 214 mutually exclusive disease groups.Design: Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.Setting: Medicare inpatient hospital claims in the United States, 2000-12 (n=95?277?169).Participants: All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.Main outcome measures: Risk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups.Results: Positive associations between short term exposure to PM2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson's disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM2.5. For the rarely studied diseases, each 1 µg/m3 increase in short term PM2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12?216 days in hospital (11?358 to 13?075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m3 increase in short term exposure to PM2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20?098 days in hospital (18?950 to 21?247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life.Conclusions: New causes and previously identified causes of hospital admission associated with short term exposure to PM2.5 were found. These associations remained even at a daily PM2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM2.5.

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Fine particulate matter pollution linked to respiratory illness in infants and increased hospital costs.

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Fine particulate matter pollution linked to respiratory illness in infants and increased hospital costs.

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