Edwin A Mitchell1, Xiaohan Yan2, Shirley You Ren2, Tatiana M Anderson3, Jan-Marino Ramirez4, Juan M Lavista Ferres2, Richard Johnston2. 1. Department of Paediatrics, Child and Youth Health, University of Auckland, Auckland, New Zealand. 2. AI For Good Research Lab, Microsoft, Redmond, WA. 3. Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA. 4. Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA; Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA; Department of Pediatrics, University of Washington School of Medicine, Seattle, WA.
Abstract
OBJECTIVES: To assess the geographic variation of sudden unexpected infant death (SUID) and test if variation in geographic factors, such as state, latitude, and longitude, play a role in SUID risk across the US. STUDY DESIGN: We analyzed the Centers for Disease Control and Prevention's Cohort Linked Birth/Infant Death dataset (2005-2010; 22 882 SUID cases, 25 305 837 live births, rate 0.90/1000). SUID was defined as infant deaths (ages 7-364 days) that included sudden infant death syndrome, ill-defined and unknown cause of mortality, and accidental suffocation and strangulation in bed. SUID geographic variation was analyzed using 2 statistical models, logistic regression and generalized additive model (GAM). RESULTS: Both models produced similar results. Without adjustment, there was marked geographic variation in SUID rates, but the variation decreased after adjusting for covariates including known risk factors for SUID. After adjustment, nine states demonstrated significantly higher or lower SUID mortality than the national average. Geographic contribution to SUID risk in terms of latitude and longitude were also attenuated after adjustment for covariates. CONCLUSION: Understanding why some states have lower SUID rates may enhance SUID prevention strategies.
OBJECTIVES: To assess the geographic variation of sudden unexpected infantdeath (SUID) and test if variation in geographic factors, such as state, latitude, and longitude, play a role in SUID risk across the US. STUDY DESIGN: We analyzed the Centers for Disease Control and Prevention's Cohort Linked Birth/InfantDeath dataset (2005-2010; 22 882 SUID cases, 25 305 837 live births, rate 0.90/1000). SUID was defined as infantdeaths (ages 7-364 days) that included sudden infant death syndrome, ill-defined and unknown cause of mortality, and accidental suffocation and strangulation in bed. SUID geographic variation was analyzed using 2 statistical models, logistic regression and generalized additive model (GAM). RESULTS: Both models produced similar results. Without adjustment, there was marked geographic variation in SUID rates, but the variation decreased after adjusting for covariates including known risk factors for SUID. After adjustment, nine states demonstrated significantly higher or lower SUID mortality than the national average. Geographic contribution to SUID risk in terms of latitude and longitude were also attenuated after adjustment for covariates. CONCLUSION: Understanding why some states have lower SUID rates may enhance SUID prevention strategies.
Authors: Ali H Mokdad; Katherine Ballestros; Michelle Echko; Scott Glenn; Helen E Olsen; Erin Mullany; Alex Lee; Abdur Rahman Khan; Alireza Ahmadi; Alize J Ferrari; Amir Kasaeian; Andrea Werdecker; Austin Carter; Ben Zipkin; Benn Sartorius; Berrin Serdar; Bryan L Sykes; Chris Troeger; Christina Fitzmaurice; Colin D Rehm; Damian Santomauro; Daniel Kim; Danny Colombara; David C Schwebel; Derrick Tsoi; Dhaval Kolte; Elaine Nsoesie; Emma Nichols; Eyal Oren; Fiona J Charlson; George C Patton; Gregory A Roth; H Dean Hosgood; Harvey A Whiteford; Hmwe Kyu; Holly E Erskine; Hsiang Huang; Ira Martopullo; Jasvinder A Singh; Jean B Nachega; Juan R Sanabria; Kaja Abbas; Kanyin Ong; Karen Tabb; Kristopher J Krohn; Leslie Cornaby; Louisa Degenhardt; Mark Moses; Maryam Farvid; Max Griswold; Michael Criqui; Michelle Bell; Minh Nguyen; Mitch Wallin; Mojde Mirarefin; Mostafa Qorbani; Mustafa Younis; Nancy Fullman; Patrick Liu; Paul Briant; Philimon Gona; Rasmus Havmoller; Ricky Leung; Ruth Kimokoti; Shahrzad Bazargan-Hejazi; Simon I Hay; Simon Yadgir; Stan Biryukov; Stein Emil Vollset; Tahiya Alam; Tahvi Frank; Talha Farid; Ted Miller; Theo Vos; Till Bärnighausen; Tsegaye Telwelde Gebrehiwot; Yuichiro Yano; Ziyad Al-Aly; Alem Mehari; Alexis Handal; Amit Kandel; Ben Anderson; Brian Biroscak; Dariush Mozaffarian; E Ray Dorsey; Eric L Ding; Eun-Kee Park; Gregory Wagner; Guoqing Hu; Honglei Chen; Jacob E Sunshine; Jagdish Khubchandani; Janet Leasher; Janni Leung; Joshua Salomon; Jurgen Unutzer; Leah Cahill; Leslie Cooper; Masako Horino; Michael Brauer; Nicholas Breitborde; Peter Hotez; Roman Topor-Madry; Samir Soneji; Saverio Stranges; Spencer James; Stephen Amrock; Sudha Jayaraman; Tejas Patel; Tomi Akinyemiju; Vegard Skirbekk; Yohannes Kinfu; Zulfiqar Bhutta; Jost B Jonas; Christopher J L Murray Journal: JAMA Date: 2018-04-10 Impact factor: 56.272
Authors: Juan M Lavista Ferres; Tatiana M Anderson; Richard Johnston; Jan-Marino Ramirez; Edwin A Mitchell Journal: Pediatrics Date: 2019-12-09 Impact factor: 7.124
Authors: Lisa M Bodnar; Lara L Siminerio; Katherine P Himes; Jennifer A Hutcheon; Timothy L Lash; Sara M Parisi; Barbara Abrams Journal: Obesity (Silver Spring) Date: 2015-11-17 Impact factor: 5.002