TY - JOUR
T1 - Space-time hot spots of critically ill small for gestational age newborns and industrial air pollutants in major metropolitan areas of Canada
AU - Canadian Neonatal Network
AU - DoMiNO Tea
AU - Nielsen, Charlene C.
AU - Amrhein, Carl G.
AU - Shah, Prakesh S.
AU - Stieb, David M.
AU - Osornio-Vargas, Alvaro R.
N1 - Funding Information:
This study was funded by Canadian Institutes of Health Research/Natural Sciences and Engineering Research Council (CIHR/NSERC) Funding Reference Number (FRN) 127789 entitled “Spatial data mining exploring co-location of adverse birth outcomes and environmental variables.” Ethics approval was obtained from the Research Ethics Board at the University of Alberta, ID Pro00039545 and approval from the Alberta Perinatal Health Program (APHP) and the Canadian Neonatal Network (CNN) coordinating center and MiCare in Toronto. MiCare is supported by a team grant from the Canadian Institutes of Health Research (CTP 87518), the Ontario Ministry of Health, and in-kind support from Mount Sinai Hospital.
Funding Information:
This study was funded by Canadian Institutes of Health Research/Natural Sciences and Engineering Research Council ( CIHR / NSERC ) Funding Reference Number (FRN) 127789 entitled “Spatial data mining exploring co-location of adverse birth outcomes and environmental variables.” Ethics approval was obtained from the Research Ethics Board at the University of Alberta , ID Pro00039545 and approval from the Alberta Perinatal Health Program (APHP) and the Canadian Neonatal Network (CNN) coordinating center and MiCare in Toronto. MiCare is supported by a team grant from the Canadian Institutes of Health Research ( CTP 87518 ), the Ontario Ministry of Health , and in-kind support from Mount Sinai Hospital.
Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2020/7
Y1 - 2020/7
N2 - We assessed the association of spatiotemporal hot spots of critically ill small for gestational age (ciSGA) newborns and industrial air emissions. Using neonatal admission data from the Canadian Neonatal Network between 2006 and 2010 (n = 32,836 infants), we aggregated maternal residential postal codes from nineteen census metropolitan areas (CMA) into space-time cubes and applied emerging hot spot analyses. Using National Pollutant Release Inventory data (n = 161 chemicals) and Environment Canada weather station data (n = 19 sites), we estimated monthly wind-dispersion of air emissions and calculated hot spots. We associated the patterns using logistic regression, with covariates for low socioeconomic status, NO2 pollution, and number of infants. A total of 5465 infants were identified as ciSGA and the larger CMAs had more and larger hot spots (i.e. accumulation of events in space and time). Seventy-eight industrial chemical hot spots were associated with ciSGA hot spots. The highest number of positive associations were for 28 different pollutants, which differed by CMA. Twenty-one were known or suspected developmental toxicants, such as particulate matter, carbon monoxide, heavy metals, and volatile organic compounds. Associations with hot spots of industrial chemical emissions were geographically specific and may help explain the space-time trends of ciSGA.
AB - We assessed the association of spatiotemporal hot spots of critically ill small for gestational age (ciSGA) newborns and industrial air emissions. Using neonatal admission data from the Canadian Neonatal Network between 2006 and 2010 (n = 32,836 infants), we aggregated maternal residential postal codes from nineteen census metropolitan areas (CMA) into space-time cubes and applied emerging hot spot analyses. Using National Pollutant Release Inventory data (n = 161 chemicals) and Environment Canada weather station data (n = 19 sites), we estimated monthly wind-dispersion of air emissions and calculated hot spots. We associated the patterns using logistic regression, with covariates for low socioeconomic status, NO2 pollution, and number of infants. A total of 5465 infants were identified as ciSGA and the larger CMAs had more and larger hot spots (i.e. accumulation of events in space and time). Seventy-eight industrial chemical hot spots were associated with ciSGA hot spots. The highest number of positive associations were for 28 different pollutants, which differed by CMA. Twenty-one were known or suspected developmental toxicants, such as particulate matter, carbon monoxide, heavy metals, and volatile organic compounds. Associations with hot spots of industrial chemical emissions were geographically specific and may help explain the space-time trends of ciSGA.
KW - Exposome
KW - Small for gestational age
KW - Space-time pattern mining
KW - Wind-directed emissions
UR - http://www.scopus.com/inward/record.url?scp=85082927691&partnerID=8YFLogxK
U2 - 10.1016/j.envres.2020.109472
DO - 10.1016/j.envres.2020.109472
M3 - Article
C2 - 32298842
AN - SCOPUS:85082927691
SN - 0013-9351
VL - 186
JO - Environmental Research
JF - Environmental Research
M1 - 109472
ER -
