Traci A Bekelman1, Dana Dabelea1, Jody M Ganiban2, Andrew Law3, Alexandra McGovern Reilly3, Keri N Althoff3, Noel Mueller3, Carlos A Camargo4, Cristiane S Duarte5, Anne L Dunlop6, Amy J Elliott7, Assiamira Ferrara8, Diane R Gold9, Irva Hertz-Picciotto10, Tina Hartert11, Alison E Hipwell12, Kathi Huddleston13, Christine C Johnson14, Margaret R Karagas15, Catherine J Karr16, Gurjit K Khurana Hershey17, Leslie Leve18, Somdat Mahabir19, Cindy T McEvoy20, Jenae Neiderhiser21, Emily Oken22, Andrew Rundle23, Sheela Sathyanarayana24, Christine Turley25,26, Frances A Tylavsky27, Sara E Watson28, Rosalind Wright29, Mingyu Zhang3, Edward Zoratti14. 1. Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA. 2. Department of Psychological and Behavioral Sciences, The George Washington University, Washington, DC, USA. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 4. Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. 5. Division of Child and Adolescent Psychiatry, Department of Psychiatry, Columbia University, New York, New York, USA. 6. Woodruff Health Sciences Center, School of Medicine and Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA. 7. Avera Research Institute, Sioux Falls, South Dakota, USA. 8. Division of Research, Kaiser Permanente Northern California, Oakland, California, USA. 9. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. 10. Department of Public Health Sciences, University of California, Davis, California, USA. 11. Vanderbilt University School of Medicine, Nashville, Tennessee, USA. 12. Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. 13. College of Health and Human Services, George Mason University, Fairfax, Virginia, USA. 14. Henry Ford Health System, Detroit, Michigan, USA. 15. Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA. 16. Department of Environmental and Occupational Health Sciences, Department of Pediatrics, University of Washington, Seattle, Washington, USA. 17. Cincinnati Children's Hospital, Cincinnati, Ohio, USA. 18. Prevention Science Institute, University of Oregon, Eugene, Oregon, USA. 19. National Cancer Institute, NIH, Bethesda, Maryland, USA. 20. Department of Pediatrics, Oregon Health & Science University, Portland, Oregon, USA. 21. Department of Psychology, Penn State University, Pennsylvania, Pennsylvania, USA. 22. Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA. 23. Mailman School of Public Health, Columbia University, New York, New York, USA. 24. University of Washington/Seattle Children's Research Institute, Seattle, Washington, USA. 25. University of South Carolina, Columbia, South Carolina, USA. 26. Atrium Health Levine Children's, Charlotte, North Carolina, USA. 27. Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA. 28. Department of Pediatrics, University of Louisville, Louisville, Kentucky, USA. 29. Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Abstract
OBJECTIVE: The aim of this study was to describe the association of individual-level characteristics (sex, race/ethnicity, birth weight, maternal education) with child BMI within each US Census region and variation in child BMI by region. METHODS: This study used pooled data from 25 prospective cohort studies. Region of residence (Northeast, Midwest, South, West) was based on residential zip codes. Age- and sex-specific BMI z scores were the outcome. RESULTS: The final sample included 14,313 children with 85,428 BMI measurements, 49% female and 51% non-Hispanic White. Males had a lower average BMI z score compared with females in the Midwest (β = -0.12, 95% CI: -0.19 to -0.05) and West (β = -0.12, 95% CI: -0.20 to -0.04). Compared with non-Hispanic White children, BMI z score was generally higher among children who were Hispanic and Black but not across all regions. Compared with the Northeast, average BMI z score was significantly higher in the Midwest (β = 0.09, 95% CI: 0.05 to 0.14) and lower in the South (β = -0.12, 95% CI: -0.16 to -0.08) and West (β = -0.14, 95% CI: -0.19 to -0.09) after adjustment for age, sex, race/ethnicity, and birth weight. CONCLUSIONS: Region of residence was associated with child BMI z scores, even after adjustment for sociodemographic characteristics. Understanding regional influences can inform targeted efforts to mitigate BMI-related disparities among children.
OBJECTIVE: The aim of this study was to describe the association of individual-level characteristics (sex, race/ethnicity, birth weight, maternal education) with child BMI within each US Census region and variation in child BMI by region. METHODS: This study used pooled data from 25 prospective cohort studies. Region of residence (Northeast, Midwest, South, West) was based on residential zip codes. Age- and sex-specific BMI z scores were the outcome. RESULTS: The final sample included 14,313 children with 85,428 BMI measurements, 49% female and 51% non-Hispanic White. Males had a lower average BMI z score compared with females in the Midwest (β = -0.12, 95% CI: -0.19 to -0.05) and West (β = -0.12, 95% CI: -0.20 to -0.04). Compared with non-Hispanic White children, BMI z score was generally higher among children who were Hispanic and Black but not across all regions. Compared with the Northeast, average BMI z score was significantly higher in the Midwest (β = 0.09, 95% CI: 0.05 to 0.14) and lower in the South (β = -0.12, 95% CI: -0.16 to -0.08) and West (β = -0.14, 95% CI: -0.19 to -0.09) after adjustment for age, sex, race/ethnicity, and birth weight. CONCLUSIONS: Region of residence was associated with child BMI z scores, even after adjustment for sociodemographic characteristics. Understanding regional influences can inform targeted efforts to mitigate BMI-related disparities among children.
Authors: Elsie M Taveras; Matthew W Gillman; Ken P Kleinman; Janet W Rich-Edwards; Sheryl L Rifas-Shiman Journal: JAMA Pediatr Date: 2013-08-01 Impact factor: 16.193
Authors: Frances A Tylavsky; Assiamira Ferrara; Diane J Catellier; Emily Oken; Xiuhong Li; Andrew Law; Dana Dabelea; Andrew Rundle; Diane Gilbert-Diamond; Marie-France Hivert; Carrie V Breton; Andrea E Cassidy-Bushrow; Noel T Mueller; Kelly J Hunt; S Sonia Arteaga; Tania Lombo; Somdat Mahabir; Doug Ruden; Katherine Sauder; Monique M Hedderson; Yeyi Zhu; Sarah Polk; Nicole L Mihalopoulos; Miriam Vos; Lee Pyles; Mary Roary; Judy Aschner; Margaret R Karagas; Leonardo Trasande Journal: Int J Obes (Lond) Date: 2019-10-24 Impact factor: 5.551