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The Exposure Uncertainty Analysis: The Association between Birth Weight and Trimester Specific Exposure to Particulate Matter (PM 2.5 vs. PM 10 )

View Article: PubMed Central - PubMed

ABSTRACT

Often spatiotemporal resolution/scale of environmental and health data do not align. Therefore, researchers compute exposure by interpolation or by aggregating data to coarse spatiotemporal scales. The latter is often preferred because of sparse geographic coverage of environmental monitoring, as interpolation method cannot reliably compute exposure using the small sample of sparse data points. This paper presents a methodology of diagnosing the levels of uncertainty in exposure at a given distance and time interval, and examines the effects of particulate matter (PM) ≤2.5 µm and ≤10 µm in diameter (PM2.5 and PM10, respectively) on birth weight (BW) and low birth weight (LBW), i.e., birth weight <2500 g in Chicago (IL, USA), accounting for exposure uncertainty. Two important findings emerge from this paper. First, uncertainty in PM exposure increases significantly with the increase in distance from the monitoring stations, e.g., 50.6% and 38.5% uncertainty in PM10 and PM2.5 exposure respectively for 0.058° (~6.4 km) distance from the monitoring stations. Second, BW was inversely associated with PM2.5 exposure, and PM2.5 exposure during the first trimester and entire gestation period showed a stronger association with BW than the exposure during the second and third trimesters. But PM10 did not show any significant association with BW and LBW. These findings suggest that distance and time intervals need to be chosen with care to compute exposure, and account for the uncertainty to reliably assess the adverse health risks of exposure.

No MeSH data available.


An example of PM2.5 monitoring sites and inclusion of subjects within 3 and 6 mile distance radius.
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ijerph-13-00906-f001: An example of PM2.5 monitoring sites and inclusion of subjects within 3 and 6 mile distance radius.

Mentions: The geocoded births were census track centroid point locations i = 1, …, N. There were several monitoring stations in some Census Tracts and none within 3 mile or 6 mile distance from the centroid of many Census Tracts (Figure 1). Exposure was computed using only 3 and 6 miles interval between mother’s residence tract and PM monitoring sites. The time interval for exposure computation remained constant for different trimesters and entire pregnancy for each mother. Let Akt denote PM monitored on days t = (1, …, T) at spatially dispersed sites k = (1, …, K) then the daily average PM exposure of mothers (Aim(t−L)) at location i = (1, …, N) who gave births on tth day and lived in census tract m = (1, …, m) during the gestational length (L, measured in days) can be calculated as:(4)Aim(t−L)=1∑l∈L∑k∈K∀jk∑l∈L∑k∈KAk(t−l)∀jkwhere l = days before the birth date (t); = 1 if the distance between jth census tract centroid and kth monitoring site was ≤ s, 0 otherwise.


The Exposure Uncertainty Analysis: The Association between Birth Weight and Trimester Specific Exposure to Particulate Matter (PM 2.5 vs. PM 10 )
An example of PM2.5 monitoring sites and inclusion of subjects within 3 and 6 mile distance radius.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036739&req=5

ijerph-13-00906-f001: An example of PM2.5 monitoring sites and inclusion of subjects within 3 and 6 mile distance radius.
Mentions: The geocoded births were census track centroid point locations i = 1, …, N. There were several monitoring stations in some Census Tracts and none within 3 mile or 6 mile distance from the centroid of many Census Tracts (Figure 1). Exposure was computed using only 3 and 6 miles interval between mother’s residence tract and PM monitoring sites. The time interval for exposure computation remained constant for different trimesters and entire pregnancy for each mother. Let Akt denote PM monitored on days t = (1, …, T) at spatially dispersed sites k = (1, …, K) then the daily average PM exposure of mothers (Aim(t−L)) at location i = (1, …, N) who gave births on tth day and lived in census tract m = (1, …, m) during the gestational length (L, measured in days) can be calculated as:(4)Aim(t−L)=1∑l∈L∑k∈K∀jk∑l∈L∑k∈KAk(t−l)∀jkwhere l = days before the birth date (t); = 1 if the distance between jth census tract centroid and kth monitoring site was ≤ s, 0 otherwise.

View Article: PubMed Central - PubMed

ABSTRACT

Often spatiotemporal resolution/scale of environmental and health data do not align. Therefore, researchers compute exposure by interpolation or by aggregating data to coarse spatiotemporal scales. The latter is often preferred because of sparse geographic coverage of environmental monitoring, as interpolation method cannot reliably compute exposure using the small sample of sparse data points. This paper presents a methodology of diagnosing the levels of uncertainty in exposure at a given distance and time interval, and examines the effects of particulate matter (PM) ≤2.5 µm and ≤10 µm in diameter (PM2.5 and PM10, respectively) on birth weight (BW) and low birth weight (LBW), i.e., birth weight <2500 g in Chicago (IL, USA), accounting for exposure uncertainty. Two important findings emerge from this paper. First, uncertainty in PM exposure increases significantly with the increase in distance from the monitoring stations, e.g., 50.6% and 38.5% uncertainty in PM10 and PM2.5 exposure respectively for 0.058° (~6.4 km) distance from the monitoring stations. Second, BW was inversely associated with PM2.5 exposure, and PM2.5 exposure during the first trimester and entire gestation period showed a stronger association with BW than the exposure during the second and third trimesters. But PM10 did not show any significant association with BW and LBW. These findings suggest that distance and time intervals need to be chosen with care to compute exposure, and account for the uncertainty to reliably assess the adverse health risks of exposure.

No MeSH data available.