Shannon C Conrey^1,2, PhD, Allison R Burrell^1,2, BSN, Cole Brokamp^1,3, PhD, Rachel M Burke⁴, PhD, Sarah C Couch⁵, PhD, RD, Liang Niu¹, PhD, Claire P Mattison^4,6, MPH, Daniel C Payne7, PhD, Mary A Staat^1,2, MD, MPH, and Ardythe L Morrow^1,2, PhD
¹University of Cincinnati College of Medicine, Department of Environmental and Public Health Sciences, Cincinnati, Ohio, United States of America
²Cincinnati Children’s Hospital Medical Center, Department of Infectious Disease, Cincinnati, Ohio, United States of America
³Cincinnati Children’s Hospital Medical Center, Department of Biostatistics and Epidemiology, Cincinnati, Ohio, United States of America
⁴Centers for Disease Control and Prevention, Division of Viral Diseases, Atlanta, Georgia, United States of America
⁵University of Cincinnati College of Allied Health Sciences, Department of Rehabilitation, Exercise and Nutrition Science, Cincinnati, Ohio, United States of America
⁶Cherokee Nation Assurance, Arlington, Virginia, United States of America
⁷Centers for Disease Control and Prevention, Division of Foodborne, Waterborne, and Environmental Diseases, Atlanta, Georgia, United States of America

Chapter DOI: https://doi.org/10.52305/NZMV3463

Part of the book: Environmental Health: Poverty, Race and Child Health in the Time of COVID-19

Abstract

Nearly 14% of American children aged 2–5 have obesity, with higher rates in children from lower-income and Black families. While evidence connects neighborhood socio-economic environment (SEE) and obesity in adults and adolescents, little is known of this relationship in young children. We compared measures of SEE and family-level socio[1]demographic factors as predictors of obesity at age two. Methods: Family-level data from the PREVAIL Cohort, a CDC-funded birth cohort in Cincinnati, Ohio, were collected prenatally from the mothers. Residential addresses were geocoded and assigned validated measures of census tract-level SEE, including USDA food desert indicators and the Deprivation Index. Family-level and ecological SEE were compared as predictors of obesity (BMIz ≥1.65) at age two in terms of proportional differences, relative risk, and model fit statistics. Results: Residing outside of Deprivation Index High SEE neighborhoods was significantly associated with higher proportion (20.0% vs 5.9%; χ2=4.36, p=0.037) and increased risk of obesity in univariable (RR = 3.4, 95%CI: 1.26–13.86) and multivariable models (RR = 3.5, 95%CI: 1.06–11.71). There were no differences in proportion or risk of obesity by USDA food desert indicators or family-level factors. Models using categorical Deprivation Index performed better than the family-level and the USDA food desert variables in terms of model fit. Conclusion: In the PREVAIL Cohort, only category of Deprivation Index was a significant predictor of obesity in two-year-old children. Future studies are needed to evaluate the Deprivation Index as a generalizable tool to identify neighborhoods at higher risk for obesity.

References

[1] Kelsey MM, Zaepfel A, Bjornstad P, Nadeau KJ. Age-related consequences of
childhood obesity. Gerontology 2014;60(3):222-8.
[2] Llewellyn A, Simmonds M, Owen CG, Woolacott N. Childhood obesity as a
predictor of morbidity in adulthood: a systematic review and meta-analysis. Obes
Rev 2016;17(1):56-67.
[3] Ogden C, Fryar C, Martin C, Freedman D, Carroll M, Gu Q, et al. Trends in obesity
prevalence by race and Hispanic origin—1999–2000 to 2017–2018. JAMA
2020;324(12):1208-10.
[4] Hales C, Carroll M, Fryar C, Ogden C. Prevalence of obesity and severe obesity
among adults: United States, 2017–2018. NCHS Data Brief. Hyattsville, MD:
National Center for Health Statistics, 2020:360.
[5] Ogden C, Carroll M, Fakhouri T, Hales C, Fryar C, Li X, et al. Prevalence of obesity
among youths by household income and education level of head of household —
United States 2011–2014. MMWR 2018;67:186-9.
[6] Vargas CM, Stines EM, Granado HS. Health-equity issues related to childhood
obesity: a scoping review. J Public Health Dent 2017;77(S1):S32-42.
[7] Duncan DT, Sharifi M, Melly SJ, Marshall R, Sequist TD, Rifas-Shiman SL, et al.
Characteristics of walkable built environments and BMI z-scores in children:
evidence from a large electronic health record database. Environ Health Perspect
2014;122(12):1359-65.
[8] Carroll-Scott A, Gilstad-Hayden K, Rosenthal L, Peters SM, McCaslin C, Joyce R,
et al. Disentangling neighborhood contextual associations with child body mass
index, diet, and physical activity: the role of built, socioeconomic, and social
environments. Soc Sci Med 2013;95:106-14.
[9] Johnson KA, Showell NN, Flessa S, Janssen M, Reid N, Cheskin LJ, et al. Do
neighborhoods matter? A systematic review of modifiable risk factors for obesity
among low socio-economic status Black and Hispanic children. Child Obes
2019;15(2):71-86.
[10] Fiechtner L, Sharifi M, Sequist T, Block J, Duncan DT, Melly SJ, et al. Food
environments and childhood weight status: effects of neighborhood median income.
Child Obes 2015;11(3):260.
[11] Do DP, Frank R, Iceland J. Black-white metropolitan segregation and self-rated
health: Investigating the role of neighborhood poverty. Soc Sci Med 2017;187:85-92.
[12] Davison KK, Birch LL. Childhood overweight: A contextual model and
recommendations for future research. Obes Rev 2001;2(3):159-71.
[13] Saelens BE, Sallis JF, Frank LD, Couch SC, Zhou C, Colburn T, et al. Obesogenic
neighborhood environments, child and parent obesity: The Neighborhood Impact on
Kids study. Am J Prev Med 2012;42(5):e57.
[14] Kang Sim DE, Strong DR, Manzano MA, Rhee KE, Boutelle KN. Evaluation of
dyadic changes of parent-child weight loss patterns during a family-based
behavioral treatment for obesity. Pediatr Obes 2020;15(6):e12622.
[15] Quillian L. Segregation and poverty concentration: The role of three segregations.
Am Sociol Rev 2012;77(3):354-79.
[16] Massey DS, Denton NA. American apartheid: segregation and the making of the
underclass. Cambridge, MA: Harvard University Press,1993.
[17] Cobb LK, Appel LJ, Franco M, Jones-Smith JC, Nur A, Anderson CAM. The
relationship of the local food environment with obesity: A systematic review of
methods, study quality, and results. Obesity 2015;23(7):1331-44.
[18] Mei K, Huang H, Xia F, Hong A, Chen X, Zhang C, et al. State-of-the-art of
measures of the obesogenic environment for children. Obes Rev 2020 Jul 28.
[19] American Community Survey. URL: https://www.census.gov/programssurveys/acs.
[20] Food Access Research Atlas. URL: https://www.ers.usda.gov/data-products/foodaccess-research-atlas/.
[21] Brokamp C, Beck AF, Goyal NK, Ryan P, Greenberg JM, Hall ES. Material
community deprivation and hospital utilization during the first year of life: an urban
population–based cohort study. Ann Epidemiol 2019;30:37-43.
[22] Woodruff RC, Haardörfer R, Raskind IG, Hermstad A, Kegler MC. Comparing food
desert residents with non-food desert residents on grocery shopping behaviours, diet
and BMI: results from a propensity score analysis. Public Health Nutr 2020;23(5):806-11.
[23] Thomsen MR, Nayga RM, Alviola PA, Rouse HL. The effect of food deserts on the
body mass index of elementary schoolchildren. Am J Agric Econ 2016;98(1):1-18.
[24] Briggs AC, Black AW, Lucas FL, Siewers AE, Fairfield KM. Association between
the food and physical activity environment, obesity, and cardiovascular health
across Maine counties. BMC Public Health 2019;19(1):374-9.
[25] MacNell L. A geo-ethnographic analysis of low-income rural and urban women’s
food shopping behaviors. Appetite 2018;128:311-20.
[26] Santorelli ML, Okeke JO. Evaluating community measures of healthy food access.
J Commun Health 2017;42(5):991-7.
[27] Block JP, Subramanian SV. Moving beyond “food deserts”: Reorienting United
States policies to reduce disparities in diet quality. PLoS Med 2015;12(12):e1001914.
[28] Kimbro RT, Denney JT. Neighborhood context and racial/ethnic differences in
young children’s obesity: structural barriers to interventions. Soc Sci Med 2013;95:97.
[29] Phillips RL, Liaw W, Crampton P, Exeter DJ, Bazemore A, Vickery KD, et al. How
other countries use deprivation indices-and why the United States desperately needs
one. Health Aff (Millwood) 2016;35(11):1991-8.
[30] Brokamp C, Jandarov R, Rao MB, LeMasters G, Ryan P. Exposure assessment
models for elemental components of particulate matter in an urban environment: A
comparison of regression and random forest approaches. Atmos Environ 2017;151:1-11.
[31] Brokamp C, LeMasters GK, Ryan PH. Residential mobility impacts exposure
assessment and community socioeconomic characteristics in longitudinal
epidemiology studies. J Expo Sci Environ Epidemiol 2016;26(4):428-34.
[32] Morrow AL, Staat MA, DeFranco EA, McNeal MM, Cline AR, Conrey SC, et al.
Pediatric respiratory and enteric virus acquisition and immunogenesis in US
mothers and children aged 0-2: PREVAIL Cohort Study. JMIR Res Protoc 2021;12;10(2):e22222.
[33] Overweight and obesity. URL: https://www.cdc.gov/obesity/data/adult.html.
[34] Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research
electronic data capture (REDCap) – A metadata-driven methodology and workflow
process for providing translational research informatics support. J Biomed Inform 2009;42(2):377-81.
[35] Brokamp C. DeGAUSS: Decentralized Geomarker Assessment for Multi-Site
Studies. J Open Source Software 2018;3(30):812.
[36] Growth charts-Z score data files. URL: https://www.cdc.gov/growthcharts/zscore.htm.
[37] Data, trend and maps. URL: https://www.cdc.gov/nccdphp/dnpao/data-trendsmaps/index.html.
[38] R Core Team. R: A language and environment for statistical computing. Vienna,
Austria: R Foundation for Statistical Computing, 2018. URL: https://www.Rproject.org/.
[39] Anderson KF. Racial residential segregation and the distribution of health-related
organizations in urban neighborhoods. Social Problems 2017;64(2):256-76.
[40] Metallinos-Katsaras, Elizabeth, PhD, RD, Must A, PhD, Gorman K, PhD. A
longitudinal study of food insecurity on obesity in preschool children. J Acad Nutr Diet 2012;112(12):1949-58.
[41] Kim Y, Cubbin C, Oh S. A systematic review of neighbourhood economic context
on child obesity and obesity-related behaviours. Obes Rev 2019;20(3):420-31