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The effect of dose and timing of dose on the association between airborne particles and survival.

Schwartz J, Coull B, Laden F, Ryan L - Environ. Health Perspect. (2008)

Bottom Line: Because the uncertainties around the resultant curve do not reflect the uncertainty in model choice, we also used model averaging as an alternative approach, where multiple models are fit explicitly and averaged, weighted by their probability of being correct given the data.We examined the lag relationship by model averaging across a range of unconstrained distributed lag models.Reduction in particle concentrations below U.S. EPA standards would increase life expectancy.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Health, Harvard School of Public Health, 401 Park Dr., Suite 415 W, P.O. Box 15698, Boston, MA 02215 USA. jschwrtz@hsph.harvard.edu <jschwrtz@hsph.harvard.edu>

ABSTRACT

Background: Understanding the shape of the concentration-response curve for particles is important for public health, and lack of such understanding was recently cited by U.S. Environmental Protection Agency (EPA) as a reason for not tightening the standards. Similarly, the delay between changes in exposure and changes in health is also important in public health decision making. We addressed these issues using an extended follow-up of the Harvard Six Cities Study.

Methods: Cox proportional hazards models were fit controlling for smoking, body mass index, and other covariates. Two approaches were used. First, we used penalized splines, which fit a flexible functional form to the concentration response to examine its shape, and chose the degrees of freedom for the curve based on Akaike's information criterion. Because the uncertainties around the resultant curve do not reflect the uncertainty in model choice, we also used model averaging as an alternative approach, where multiple models are fit explicitly and averaged, weighted by their probability of being correct given the data. We examined the lag relationship by model averaging across a range of unconstrained distributed lag models.

Results: We found that the concentration-response curve is linear, clearly continuing below the current U.S. standard of 15 microg/m3, and that the effects of changes in exposure on mortality are seen within two years.

Conclusions: Reduction in particle concentrations below U.S. EPA standards would increase life expectancy.

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Related in: MedlinePlus

The estimated concentration–response relation between PM2.5 and the risk of death in the Six Cities Study, based on averaging the 32 possible models fit under the an uninformative prior, and under a prior giving a linear no-threshold model only half the probability of all other models. There is little difference in the two curves.
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f3-ehp0116-000064: The estimated concentration–response relation between PM2.5 and the risk of death in the Six Cities Study, based on averaging the 32 possible models fit under the an uninformative prior, and under a prior giving a linear no-threshold model only half the probability of all other models. There is little difference in the two curves.

Mentions: Table 2 shows the results of the BMA analysis. It lists the six (of 32) models for dose response that had posterior probabilities (based on the BIC approximation) of > 1%, as well as those posterior probabilities. The linear, no-threshold model had the great bulk of the probability, at 86%. The other models with nontrivial probability had a single slope change, at 10, 15, 20, 25, or 30 μg/m3 PM2.5 concentration. In all but one of these, the slope change was negative, indicating a somewhat lower slope at higher concentrations. The concentration–response curve, using the weighted average of all 32 models, is shown in Figure 2. It differs little from the curve generated by the penalized spline approach (Figure 1). Figure 3 shows the results of the sensitivity analysis where the linear no-threshold model was given half the prior probability of all other models. The results are indistinguishable except at the extreme ranges of the data, where there are few observations, and the prior would be expected to have more influence.


The effect of dose and timing of dose on the association between airborne particles and survival.

Schwartz J, Coull B, Laden F, Ryan L - Environ. Health Perspect. (2008)

The estimated concentration–response relation between PM2.5 and the risk of death in the Six Cities Study, based on averaging the 32 possible models fit under the an uninformative prior, and under a prior giving a linear no-threshold model only half the probability of all other models. There is little difference in the two curves.
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2199297&req=5

f3-ehp0116-000064: The estimated concentration–response relation between PM2.5 and the risk of death in the Six Cities Study, based on averaging the 32 possible models fit under the an uninformative prior, and under a prior giving a linear no-threshold model only half the probability of all other models. There is little difference in the two curves.
Mentions: Table 2 shows the results of the BMA analysis. It lists the six (of 32) models for dose response that had posterior probabilities (based on the BIC approximation) of > 1%, as well as those posterior probabilities. The linear, no-threshold model had the great bulk of the probability, at 86%. The other models with nontrivial probability had a single slope change, at 10, 15, 20, 25, or 30 μg/m3 PM2.5 concentration. In all but one of these, the slope change was negative, indicating a somewhat lower slope at higher concentrations. The concentration–response curve, using the weighted average of all 32 models, is shown in Figure 2. It differs little from the curve generated by the penalized spline approach (Figure 1). Figure 3 shows the results of the sensitivity analysis where the linear no-threshold model was given half the prior probability of all other models. The results are indistinguishable except at the extreme ranges of the data, where there are few observations, and the prior would be expected to have more influence.

Bottom Line: Because the uncertainties around the resultant curve do not reflect the uncertainty in model choice, we also used model averaging as an alternative approach, where multiple models are fit explicitly and averaged, weighted by their probability of being correct given the data.We examined the lag relationship by model averaging across a range of unconstrained distributed lag models.Reduction in particle concentrations below U.S. EPA standards would increase life expectancy.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Health, Harvard School of Public Health, 401 Park Dr., Suite 415 W, P.O. Box 15698, Boston, MA 02215 USA. jschwrtz@hsph.harvard.edu <jschwrtz@hsph.harvard.edu>

ABSTRACT

Background: Understanding the shape of the concentration-response curve for particles is important for public health, and lack of such understanding was recently cited by U.S. Environmental Protection Agency (EPA) as a reason for not tightening the standards. Similarly, the delay between changes in exposure and changes in health is also important in public health decision making. We addressed these issues using an extended follow-up of the Harvard Six Cities Study.

Methods: Cox proportional hazards models were fit controlling for smoking, body mass index, and other covariates. Two approaches were used. First, we used penalized splines, which fit a flexible functional form to the concentration response to examine its shape, and chose the degrees of freedom for the curve based on Akaike's information criterion. Because the uncertainties around the resultant curve do not reflect the uncertainty in model choice, we also used model averaging as an alternative approach, where multiple models are fit explicitly and averaged, weighted by their probability of being correct given the data. We examined the lag relationship by model averaging across a range of unconstrained distributed lag models.

Results: We found that the concentration-response curve is linear, clearly continuing below the current U.S. standard of 15 microg/m3, and that the effects of changes in exposure on mortality are seen within two years.

Conclusions: Reduction in particle concentrations below U.S. EPA standards would increase life expectancy.

Show MeSH
Related in: MedlinePlus