Sonali Bose1, Kristie R Ross2, Maria J Rosa3, Yueh-Hsiu Mathilda Chiu3, Allan Just3, Itai Kloog4, Ander Wilson5, Jennifer Thompson6, Katherine Svensson3, Martha María Téllez Rojo7, Lourdes Schnaas8, Erika Osorio-Valencia8, Emily Oken6, Robert O Wright9, Rosalind J Wright10. 1. Division of Pulmonary and Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, United States of America; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, United States of America. 2. Department of Pediatrics, Rainbow Babies and Children's Hospital, Case Western Reserve University, Cleveland, OH, United States of America. 3. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, United States of America. 4. Department of Geography and Environmental Development, Ben-Gurion University of the Negev, BeerSheba, Israel. 5. Department of Statistics, Colorado State University, United States of America. 6. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States of America. 7. Instituto Nacional de Salud Pública Cuernavaca, Morelos, Mexico. 8. Department of Developmental Neurobiology, National Institute of Perinatology "Isidro Espinosa de los Reyes", Mexico City, Mexico. 9. Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, United States of America; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, United States of America; Institute for Exposomics Research, Icahn School of Medicine at Mount Sinai, New York, United States of America. 10. Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, United States of America; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, United States of America; Institute for Exposomics Research, Icahn School of Medicine at Mount Sinai, New York, United States of America. Electronic address: rosalind.wright@mssm.edu.
Abstract
BACKGROUND: The programming of sleep architecture begins in pregnancy and depends upon optimal in utero formation and maturation of the neural connectivity of the brain. Particulate air pollution exposure can disrupt fetal brain development but associations between fine particulate matter (PM2.5) exposure during pregnancy and child sleep outcomes have not been previously explored. METHODS: Analyses included 397 mother-child pairs enrolled in a pregnancy cohort in Mexico City. Daily ambient prenatal PM2.5 exposure was estimated using a validated satellite-based spatio-temporally resolved prediction model. Child sleep periods were estimated objectively using wrist-worn, continuous actigraphy over a 1-week period at age 4-5 years. Data-driven advanced statistical methods (distributed lag models (DLMs)) were employed to identify sensitive windows whereby PM2.5 exposure during gestation was significantly associated with changes in sleep duration or efficiency. Models were adjusted for maternal education, season, child's age, sex, and BMI z-score. RESULTS: Mother's average age was 27.7 years, with 59% having at least a high school education. Children slept an average of 7.7 h at night, with mean 80.1% efficiency. The adjusted DLM identified windows of PM2.5 exposure between 31 and 35 weeks gestation that were significantly associated with decreased sleep duration in children. In addition, increased PM2.5 during weeks 1-8 was associated with decreased sleep efficiency. In other exposure windows (weeks 39-40), PM2.5 was associated with increased sleep duration. CONCLUSION: Prenatal PM2.5 exposure is associated with altered sleep in preschool-aged children in Mexico City. Pollutant exposure during sensitive windows of pregnancy may have critical influence upon sleep programming.
BACKGROUND: The programming of sleep architecture begins in pregnancy and depends upon optimal in utero formation and maturation of the neural connectivity of the brain. Particulate air pollution exposure can disrupt fetal brain development but associations between fine particulate matter (PM2.5) exposure during pregnancy and child sleep outcomes have not been previously explored. METHODS: Analyses included 397 mother-child pairs enrolled in a pregnancy cohort in Mexico City. Daily ambient prenatal PM2.5 exposure was estimated using a validated satellite-based spatio-temporally resolved prediction model. Child sleep periods were estimated objectively using wrist-worn, continuous actigraphy over a 1-week period at age 4-5 years. Data-driven advanced statistical methods (distributed lag models (DLMs)) were employed to identify sensitive windows whereby PM2.5 exposure during gestation was significantly associated with changes in sleep duration or efficiency. Models were adjusted for maternal education, season, child's age, sex, and BMI z-score. RESULTS: Mother's average age was 27.7 years, with 59% having at least a high school education. Children slept an average of 7.7 h at night, with mean 80.1% efficiency. The adjusted DLM identified windows of PM2.5 exposure between 31 and 35 weeks gestation that were significantly associated with decreased sleep duration in children. In addition, increased PM2.5 during weeks 1-8 was associated with decreased sleep efficiency. In other exposure windows (weeks 39-40), PM2.5 was associated with increased sleep duration. CONCLUSION: Prenatal PM2.5 exposure is associated with altered sleep in preschool-aged children in Mexico City. Pollutant exposure during sensitive windows of pregnancy may have critical influence upon sleep programming.
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