TY - JOUR
T1 - Uncertainty in the relationship between criteria pollutants and low birth weight in Chicago
AU - Kumar, Naresh
N1 - Funding Information:
The author would like to thank two anonymous referees for their thoughtful comments and suggestions, and Dr. Kirsti Bocskay, Chicago Department of Public Health, Chicago, for providing birth data, and Kevin Gibbs for geocoding these data. This work was partly funded by NIH/NIEHS – 1 R21 ES014004-01A and NIH/NICHD – 1 R21 HD046571-01A1 grants.
PY - 2012/3
Y1 - 2012/3
N2 - Using the data on all live births (~400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3miles distance of the monitoring stations the odds of LBW (births <2500g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM 10 (in μgm -3) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6miles distance of air pollution monitoring stations. The effect of PM 10 exposure on LBW became null when controlled for confounders. But PM 2.5 exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM 10 that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. While this paper challenges the findings of pervious epidemiological studies that have relied on coarse resolution air pollution data (such as county level aggregated data), the paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation.
AB - Using the data on all live births (~400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3miles distance of the monitoring stations the odds of LBW (births <2500g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM 10 (in μgm -3) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6miles distance of air pollution monitoring stations. The effect of PM 10 exposure on LBW became null when controlled for confounders. But PM 2.5 exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM 10 that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. While this paper challenges the findings of pervious epidemiological studies that have relied on coarse resolution air pollution data (such as county level aggregated data), the paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation.
KW - Exposure uncertainty
KW - Health risks
KW - Spatiotemporal misalignment
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U2 - 10.1016/j.atmosenv.2011.12.001
DO - 10.1016/j.atmosenv.2011.12.001
M3 - Article
AN - SCOPUS:84856546749
VL - 49
SP - 171
EP - 179
JO - Atmospheric Environment
JF - Atmospheric Environment
SN - 1352-2310
ER -
