Hongtai Huang1, Tracey J Woodruff2, Rebecca J Baer3, Komal Bangia4, Laura M August4, Laura L Jellife-Palowski5, Amy M Padula2, Marina Sirota6. 1. Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA; Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA, USA. Electronic address: Hongtai.Huang@ucsf.edu. 2. Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA, USA. 3. Department of Pediatrics, University of California, San Diego, CA, USA; California Preterm Birth Initiative, University of California, San Francisco, CA, USA. 4. Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, Sacramento, CA, USA. 5. California Preterm Birth Initiative, University of California, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA. 6. Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA; Department of Pediatrics, University of California, San Francisco, CA, USA. Electronic address: Marina.Sirota@ucsf.edu.
Abstract
BACKGROUND: Preterm birth (PTB),2 defined as birth at gestational age <37 weeks, is a major public health concern. Infants born prematurely, comprising of about 10% of the US newborns, have elevated risks of neonatal mortality and a wide array of health problems. Although numerous clinical, genetic, environmental and socioeconomic factors have been implicated in PTB, very few studies investigate the impacts of multiple pollutants and social factors on PTB using large scale datasets. OBJECTIVES: To evaluate association between environmental and socioeconomic factors and PTB in California. METHODS: We linked the birth cohort file maintained by the California Office of Statewide Health Planning and Development from 2009 to 2012 years across 1.8 million births and the CalEnviroScreen 3.0 dataset from California Communities Environmental Health Screening Tool at the census tract level for 56 California counties. CalEnviroScreen contains 7 exposure and 5 environmental effects variables that constitute the Pollution Burden variable, and 5 socioeconomic variables. We evaluated relationships between environmental exposures and the risk of PTB using hierarchical clustering analyses and GIS-based visualization. We also used logistic regression to evaluate the relationship between specific pollutant and exposure indicators and PTB, accounted for socio-demographic determinants such as maternal race/ethnicity, maternal age, maternal education and payment of delivery costs. RESULTS: There exists geographic variability in PTB for groups of counties with similar environmental and social exposure profiles. We found an association between Pollution Burden, particulate matter ≤2.5 μm (PM2.5), and Drinking Water Scores and PTB (adjusted odds ratios were 1.03 (95% Confidence Interval (CI): 1.01, 1.04), 1.03 (95% CI: 1.02,1.04), and 1.04 (95% CI: 1.03,1.05), respectively). Additional findings suggest that certain drinking water contaminants such as arsenic and nitrate are associated with PTB in California. CONCLUSIONS: CalEnviroScreen data combined with birth records offer great opportunity for revealing novel exposures and evaluating cumulative exposures related to PTB by providing useful environmental and social information. Certain drinking water contaminants such as arsenic and nitrate are potentially associated with PTB in California and should be investigated further. Small association signals may involve sizeable population impacts.
BACKGROUND: Preterm birth (PTB),2 defined as birth at gestational age <37 weeks, is a major public health concern. Infants born prematurely, comprising of about 10% of the US newborns, have elevated risks of neonatal mortality and a wide array of health problems. Although numerous clinical, genetic, environmental and socioeconomic factors have been implicated in PTB, very few studies investigate the impacts of multiple pollutants and social factors on PTB using large scale datasets. OBJECTIVES: To evaluate association between environmental and socioeconomic factors and PTB in California. METHODS: We linked the birth cohort file maintained by the California Office of Statewide Health Planning and Development from 2009 to 2012 years across 1.8 million births and the CalEnviroScreen 3.0 dataset from California Communities Environmental Health Screening Tool at the census tract level for 56 California counties. CalEnviroScreen contains 7 exposure and 5 environmental effects variables that constitute the Pollution Burden variable, and 5 socioeconomic variables. We evaluated relationships between environmental exposures and the risk of PTB using hierarchical clustering analyses and GIS-based visualization. We also used logistic regression to evaluate the relationship between specific pollutant and exposure indicators and PTB, accounted for socio-demographic determinants such as maternal race/ethnicity, maternal age, maternal education and payment of delivery costs. RESULTS: There exists geographic variability in PTB for groups of counties with similar environmental and social exposure profiles. We found an association between Pollution Burden, particulate matter ≤2.5 μm (PM2.5), and Drinking Water Scores and PTB (adjusted odds ratios were 1.03 (95% Confidence Interval (CI): 1.01, 1.04), 1.03 (95% CI: 1.02,1.04), and 1.04 (95% CI: 1.03,1.05), respectively). Additional findings suggest that certain drinking water contaminants such as arsenic and nitrate are associated with PTB in California. CONCLUSIONS: CalEnviroScreen data combined with birth records offer great opportunity for revealing novel exposures and evaluating cumulative exposures related to PTB by providing useful environmental and social information. Certain drinking water contaminants such as arsenic and nitrate are potentially associated with PTB in California and should be investigated further. Small association signals may involve sizeable population impacts.
Authors: Juliana Stone; Pragna Sutrave; Emily Gascoigne; Matthew B Givens; Rebecca C Fry; Tracy A Manuck Journal: Am J Obstet Gynecol MFM Date: 2021-01-11
Authors: Zesemayat K Mekonnen; John W Oehlert; Brenda Eskenazi; Gary M Shaw; John R Balmes; Amy M Padula Journal: J Expo Sci Environ Epidemiol Date: 2021-04-15 Impact factor: 5.563
Authors: Anne L Dunlop; Alicynne Glazier Essalmi; Lyndsay Alvalos; Carrie Breton; Carlos A Camargo; Whitney J Cowell; Dana Dabelea; Stephen R Dager; Cristiane Duarte; Amy Elliott; Raina Fichorova; James Gern; Monique M Hedderson; Elizabeth Hom Thepaksorn; Kathi Huddleston; Margaret R Karagas; Ken Kleinman; Leslie Leve; Ximin Li; Yijun Li; Augusto Litonjua; Yunin Ludena-Rodriguez; Juliette C Madan; Julio Mateus Nino; Cynthia McEvoy; Thomas G O'Connor; Amy M Padula; Nigel Paneth; Frederica Perera; Sheela Sathyanarayana; Rebecca J Schmidt; Robert T Schultz; Jessica Snowden; Joseph B Stanford; Leonardo Trasande; Heather E Volk; William Wheaton; Rosalind J Wright; Monica McGrath Journal: PLoS One Date: 2021-01-08 Impact factor: 3.752