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Evaluation of a spatially resolved forest fire smoke model for population-based epidemiologic exposure assessment.

Yao J, Eyamie J, Henderson SB - J Expo Sci Environ Epidemiol (2014)

Bottom Line: Exposure to forest fire smoke (FFS) is associated with multiple adverse health effects, mostly respiratory.We then used meta-regression to estimate the overall effects.Effects on cardiovascular outcomes were only significant using model estimates in all LHAs during extreme fire days.

View Article: PubMed Central - PubMed

Affiliation: Environmental Health Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada.

ABSTRACT
Exposure to forest fire smoke (FFS) is associated with multiple adverse health effects, mostly respiratory. Findings for cardiovascular effects have been inconsistent, possibly related to the limitations of conventional methods to assess FFS exposure. In previous work, we developed an empirical model to estimate smoke-related fine particulate matter (PM2.5) for all populated areas in British Columbia (BC), Canada. Here, we evaluate the utility of our model by comparing epidemiologic associations between modeled and measured PM2.5. For each local health area (LHA), we used Poisson regression to estimate the effects of PM2.5 estimates and measurements on counts of medication dispensations and outpatient physician visits. We then used meta-regression to estimate the overall effects. A 10 μg/m(3) increase in modeled PM2.5 was associated with increased sabutamol dispensations (RR=1.04, 95% CI 1.03-1.06), and physician visits for asthma (1.06, 1.04-1.08), COPD (1.02, 1.00-1.03), lower respiratory infections (1.03, 1.00-1.05), and otitis media (1.05, 1.03-1.07), all comparable to measured PM2.5. Effects on cardiovascular outcomes were only significant using model estimates in all LHAs during extreme fire days. This suggests that the exposure model is a promising tool for increasing the power of epidemiologic studies to detect the health effects of FFS via improved spatial coverage and resolution.

No MeSH data available.


Related in: MedlinePlus

Map of local health areas (LHAs) in British Columbia, Canada. Background is color coded according to LHA population. Green dots indicate monitoring stations and crosses indicate large fires with fire radiative power of >1500 MW during the study period.
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fig1: Map of local health areas (LHAs) in British Columbia, Canada. Background is color coded according to LHA population. Green dots indicate monitoring stations and crosses indicate large fires with fire radiative power of >1500 MW during the study period.

Mentions: BC is located on the west coast of Canada, with an area of 944,735 km2 and a population of 4,243,580 in the census year of 2006. The province is divided into 89 local health areas (LHAs) for the purposes of health administration, and their 2006 populations ranged from 542 to 352,783 individuals. The study period covers the forest fire seasons (1 April to 30 September) of 2003 through 2010, during which the annual area burned averaged 1608 km2 and ranged from 132 to 3371 km2. The central and southern interior areas are most prone to forest fires, especially following damage done by an extensive infestation of the mountain pine beetle.24 The province has a dense air quality monitoring network relative to the size of its population (Figure 1).


Evaluation of a spatially resolved forest fire smoke model for population-based epidemiologic exposure assessment.

Yao J, Eyamie J, Henderson SB - J Expo Sci Environ Epidemiol (2014)

Map of local health areas (LHAs) in British Columbia, Canada. Background is color coded according to LHA population. Green dots indicate monitoring stations and crosses indicate large fires with fire radiative power of >1500 MW during the study period.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835685&req=5

fig1: Map of local health areas (LHAs) in British Columbia, Canada. Background is color coded according to LHA population. Green dots indicate monitoring stations and crosses indicate large fires with fire radiative power of >1500 MW during the study period.
Mentions: BC is located on the west coast of Canada, with an area of 944,735 km2 and a population of 4,243,580 in the census year of 2006. The province is divided into 89 local health areas (LHAs) for the purposes of health administration, and their 2006 populations ranged from 542 to 352,783 individuals. The study period covers the forest fire seasons (1 April to 30 September) of 2003 through 2010, during which the annual area burned averaged 1608 km2 and ranged from 132 to 3371 km2. The central and southern interior areas are most prone to forest fires, especially following damage done by an extensive infestation of the mountain pine beetle.24 The province has a dense air quality monitoring network relative to the size of its population (Figure 1).

Bottom Line: Exposure to forest fire smoke (FFS) is associated with multiple adverse health effects, mostly respiratory.We then used meta-regression to estimate the overall effects.Effects on cardiovascular outcomes were only significant using model estimates in all LHAs during extreme fire days.

View Article: PubMed Central - PubMed

Affiliation: Environmental Health Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada.

ABSTRACT
Exposure to forest fire smoke (FFS) is associated with multiple adverse health effects, mostly respiratory. Findings for cardiovascular effects have been inconsistent, possibly related to the limitations of conventional methods to assess FFS exposure. In previous work, we developed an empirical model to estimate smoke-related fine particulate matter (PM2.5) for all populated areas in British Columbia (BC), Canada. Here, we evaluate the utility of our model by comparing epidemiologic associations between modeled and measured PM2.5. For each local health area (LHA), we used Poisson regression to estimate the effects of PM2.5 estimates and measurements on counts of medication dispensations and outpatient physician visits. We then used meta-regression to estimate the overall effects. A 10 μg/m(3) increase in modeled PM2.5 was associated with increased sabutamol dispensations (RR=1.04, 95% CI 1.03-1.06), and physician visits for asthma (1.06, 1.04-1.08), COPD (1.02, 1.00-1.03), lower respiratory infections (1.03, 1.00-1.05), and otitis media (1.05, 1.03-1.07), all comparable to measured PM2.5. Effects on cardiovascular outcomes were only significant using model estimates in all LHAs during extreme fire days. This suggests that the exposure model is a promising tool for increasing the power of epidemiologic studies to detect the health effects of FFS via improved spatial coverage and resolution.

No MeSH data available.


Related in: MedlinePlus