John Byrnes1, Richard Mahoney2, Cele Quaintance3, Jeffrey B Gould3, Suzan Carmichael3, Gary M Shaw3, Amy Showen4, Ciaran Phibbs3, David K Stevenson3, Paul H Wise5. 1. Artificial Intelligence Center, SRI International, San Diego, California. 2. Robotics Program, SRI International, Menlo Park, California. 3. 1] Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California [2] March of Dimes Center for Prematurity Research at Stanford, Stanford University School of Medicine, Stanford, California. 4. David Geffen School of Medicine, University of California, Los Angeles, California. 5. 1] Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California [2] March of Dimes Center for Prematurity Research at Stanford, Stanford University School of Medicine, Stanford, California [3] Center for Policy, Outcomes and Prevention, Center for Health Policy/Center for Primary Care and Outcomes Research, Stanford University, Stanford, California.
Abstract
BACKGROUND: Despite years of research, the etiologies of preterm birth remain unclear. In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset. METHODS: Data on 145 million US births in 3,000 counties from the Natality Files of the National Center for Health Statistics for 1971-2011 were examined. State trends in early (<34 wk) and late (34-36 wk) preterm birth rates were compared. K-means cluster analyses were conducted to identify gestational age distribution patterns for all US counties over time. RESULTS: A weak association was observed between state trends in <34 wk birth rates and the initial absolute <34 wk birth rate. Significant associations were observed between trends in <34 wk and 34-36 wk birth rates and between white and African American <34 wk births. Periodicity was observed in county-level trends in <34 wk birth rates. Cluster analyses identified periods of significant heterogeneity and homogeneity in gestational age distributional trends for US counties. CONCLUSION: The observed geographic and temporal patterns suggest periodicity and complex, shared influences among preterm birth rates in the United States. These patterns could provide insight into promising hypotheses for further research.
BACKGROUND: Despite years of research, the etiologies of preterm birth remain unclear. In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset. METHODS: Data on 145 million US births in 3,000 counties from the Natality Files of the National Center for Health Statistics for 1971-2011 were examined. State trends in early (<34 wk) and late (34-36 wk) preterm birth rates were compared. K-means cluster analyses were conducted to identify gestational age distribution patterns for all US counties over time. RESULTS: A weak association was observed between state trends in <34 wk birth rates and the initial absolute <34 wk birth rate. Significant associations were observed between trends in <34 wk and 34-36 wk birth rates and between white and African American <34 wk births. Periodicity was observed in county-level trends in <34 wk birth rates. Cluster analyses identified periods of significant heterogeneity and homogeneity in gestational age distributional trends for US counties. CONCLUSION: The observed geographic and temporal patterns suggest periodicity and complex, shared influences among preterm birth rates in the United States. These patterns could provide insight into promising hypotheses for further research.
Authors: Teresa Janevic; Jennifer A Hutcheon; Norm Hess; Laurie Navin; Elizabeth A Howell; Lisa Gittens-Williams Journal: Matern Child Health J Date: 2018-10
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