A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution

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Abstract

The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models.

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Most cited references 19

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A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

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The Lancet, 380(9859), 2224-2260

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Michael Jerrett, Richard Burnett, C. Pope … (2009)

Although many studies have linked elevations in tropospheric ozone to adverse health outcomes, the effect of long-term exposure to ozone on air pollution-related mortality remains uncertain. We examined the potential contribution of exposure to ozone to the risk of death from cardiopulmonary causes and specifically to death from respiratory causes. Data from the study cohort of the American Cancer Society Cancer Prevention Study II were correlated with air-pollution data from 96 metropolitan statistical areas in the United States. Data were analyzed from 448,850 subjects, with 118,777 deaths in an 18-year follow-up period. Data on daily maximum ozone concentrations were obtained from April 1 to September 30 for the years 1977 through 2000. Data on concentrations of fine particulate matter (particles that are < or = 2.5 microm in aerodynamic diameter [PM(2.5)]) were obtained for the years 1999 and 2000. Associations between ozone concentrations and the risk of death were evaluated with the use of standard and multilevel Cox regression models. In single-pollutant models, increased concentrations of either PM(2.5) or ozone were significantly associated with an increased risk of death from cardiopulmonary causes. In two-pollutant models, PM(2.5) was associated with the risk of death from cardiovascular causes, whereas ozone was associated with the risk of death from respiratory causes. The estimated relative risk of death from respiratory causes that was associated with an increment in ozone concentration of 10 ppb was 1.040 (95% confidence interval, 1.010 to 1.067). The association of ozone with the risk of death from respiratory causes was insensitive to adjustment for confounders and to the type of statistical model used. In this large study, we were not able to detect an effect of ozone on the risk of death from cardiovascular causes when the concentration of PM(2.5) was taken into account. We did, however, demonstrate a significant increase in the risk of death from respiratory causes in association with an increase in ozone concentration. 2009 Massachusetts Medical Society

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Risk of Nonaccidental and Cardiovascular Mortality in Relation to Long-term Exposure to Low Concentrations of Fine Particulate Matter: A Canadian National-Level Cohort Study

Dan Crouse, Paul Peters, Aaron van Donkelaar … (2012)

Background: Few cohort studies have evaluated the risk of mortality associated with long-term exposure to fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)]. This is the first national-level cohort study to investigate these risks in Canada. Objective: We investigated the association between long-term exposure to ambient PM2.5 and cardiovascular mortality in nonimmigrant Canadian adults. Methods: We assigned estimates of exposure to ambient PM2.5 derived from satellite observations to a cohort of 2.1 million Canadian adults who in 1991 were among the 20% of the population mandated to provide detailed census data. We identified deaths occurring between 1991 and 2001 through record linkage. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for available individual-level and contextual covariates using both standard Cox proportional survival models and nested, spatial random-effects survival models. Results: Using standard Cox models, we calculated HRs of 1.15 (95% CI: 1.13, 1.16) from nonaccidental causes and 1.31 (95% CI: 1.27, 1.35) from ischemic heart disease for each 10-μg/m3 increase in concentrations of PM2.5. Using spatial random-effects models controlling for the same variables, we calculated HRs of 1.10 (95% CI: 1.05, 1.15) and 1.30 (95% CI: 1.18, 1.43), respectively. We found similar associations between nonaccidental mortality and PM2.5 based on satellite-derived estimates and ground-based measurements in a subanalysis of subjects in 11 cities. Conclusions: In this large national cohort of nonimmigrant Canadians, mortality was associated with long-term exposure to PM2.5. Associations were observed with exposures to PM2.5 at concentrations that were predominantly lower (mean, 8.7 μg/m3; interquartile range, 6.2 μg/m3) than those reported previously.

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Author and article information

Contributors

Mieczysław Szyszkowicz: (613) 762-1830 , mietek.szyszkowicz@hc-sc.gc.ca

Journal

Journal ID (nlm-ta): Air Qual Atmos Health

Journal ID (iso-abbrev): Air Qual Atmos Health

Title: Air Quality, Atmosphere, & Health

Publisher: Springer Netherlands (Dordrecht )

ISSN (Print): 1873-9318

ISSN (Electronic): 1873-9326

Publication date (Electronic): 2 March 2016

Publication date PMC-release: 2 March 2016

Publication date (Print): 2016

Volume: 9

Issue: 8

Pages: 961-972

Affiliations

[1 ]Environmental Health Science and Research Bureau, Health Canada, 200 Eglantine Driveway, Ottawa, Ontario K1A 0K9 Canada

[2 ]Public Health Ontario, Oakville, Ontario Canada

[3 ]McLaughlin Centre for Population Health Risk Assessment, Institute of Population Health, University of Ottawa, Ottawa, Ontario Canada

[4 ]Centre for Research in Environmental Epidemiology (CREAL), Madrid, Spain

[5 ]Universitat Pompeu Fabra (UPF), Barcelona, Spain

[6 ]CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

[7 ]Department of Environmental Health Sciences, University of California at Los Angeles, Los Angeles, CA USA

[8 ]Department of Economics, Brigham Young University, Provo, UT USA

[9 ]United States Environmental Protection Agency, Research Triangle Park, Durham, NC USA

[10 ]Health Effects Institute, Boston, MA USA

[11 ]Epidemiology Research Program, American Cancer Society, Atlanta, GA USA

[12 ]Institute of Health Metrics and Evaluation, Seattle, WA USA

[13 ]Institute of Health and Environment, Seoul National University, Seoul, South Korea

[14 ]Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA USA

Article

Publisher ID: 398

DOI: 10.1007/s11869-016-0398-z

PMC ID: 5093184

PubMed ID: 27867428

SO-VID: 20b7c86c-cd36-4988-a7ec-19c5b06086c8

License:

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.