Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes
Por:
Serrano-Lomelin J., Nielsen C.C., Jabbar M.S.M., Wine O., Bellinger C., Villeneuve P.J., Stieb D., Aelicks N., Aziz K., Buka I., Chandra S., Crawford S., Demers P., Erickson A.C., Hystad P., Kumar M., Phipps E., Shah P.S., Yuan Y., Zaiane O.R., Osornio-Vargas A.R.
Publicada:
1 ene 2019
Categoría:
Environmental science (miscellaneous)
Resumen:
Background: Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches. Objective: We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO. Methods: We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006–2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density. Results: From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses. Conclusion: This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes. © 2019 The Authors
Filiaciones:
Serrano-Lomelin J.:
School of Public Health, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Department of Obstetrics & Gynecology, University of Alberta, Royal Alexandra Hospital, 10240 Kingsway Avenue, Edmonton, Alberta T5H 3V9, Canada
Nielsen C.C.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Department of Earth and Atmospheric Sciences, University of Alberta, 1-26 Earth Science Building, Edmonton, Alberta T6G 2E3, Canada
Jabbar M.S.M.:
Department of Computing Science, University of Alberta, 32 Athabasca Hall, Edmonton, Alberta T6G 2E8, Canada
Wine O.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Bellinger C.:
Department of Computing Science, University of Alberta, 32 Athabasca Hall, Edmonton, Alberta T6G 2E8, Canada
Villeneuve P.J.:
Department of Health Sciences, Carleton University, Herzberg Building, Room 5413, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
Stieb D.:
Environmental Health Science and Research Bureau, Health Canada, 50 Colombine Driveway, Ottawa, Ontario K1A 0K9, Canada
Aelicks N.:
Alberta Health Services, Alberta Perinatal Health Program, Suite 310, 1403-29 Street NW, Calgary, Alberta T2N 2T9, Canada
Aziz K.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Buka I.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Chandra S.:
Department of Obstetrics & Gynecology, University of Alberta, Royal Alexandra Hospital, 10240 Kingsway Avenue, Edmonton, Alberta T5H 3V9, Canada
Crawford S.:
Alberta Health Services, Alberta Perinatal Health Program, Suite 310, 1403-29 Street NW, Calgary, Alberta T2N 2T9, Canada
Demers P.:
CAREX Canada, Faculty of Health Sciences, Simon Fraser University, 105-515 West Hastings St, Vancouver, BC V6B 5K3, Canada
Erickson A.C.:
School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC V6T 1Z3, Canada
Hystad P.:
School of Biological and Population Health Sciences, Oregon State University, 101 Milam Hall, Corvallis, OR 97331, United States
Kumar M.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Phipps E.:
Canadian Partnership for Children's Health & Environment, 1500-55 University Avenue, Toronto, Ontario M5J 2H7, Canada
Shah P.S.:
Department of Pediatrics and Institute of Health Policy, Management, and Evaluation, University of Toronto, Mount Sinai Hospital, 600 University Avenue, Room 19-231A, Toronto, Ontario M5G 1X5, Canada
Yuan Y.:
School of Public Health, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Zaiane O.R.:
Department of Computing Science, University of Alberta, 32 Athabasca Hall, Edmonton, Alberta T6G 2E8, Canada
Osornio-Vargas A.R.:
Department of Pediatrics, University of Alberta, Edmonton Clinic Health Academy, 11405 87 Avenue, Edmonton, Alberta T6G 1C9, Canada
Gold
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