Measuring neighborhood deprivation for childhood health and development - scale implications in rural and urban context

Abstract

Neighborhood deprivation plays an important role in childhood health and development, but defining the appropriate neighborhood definition presents theoretical as well as practical challenges. Few studies have compared neighborhood definitions outside of highly urbanized settings. The purpose of the current study was to evaluate how various administrative and ego-centric neighborhood definitions may impact measured exposure to deprivation across the urban-rural continuum. We do so using the Family Life Project, a prospective longitudinal population-based sample of families living in North Carolina and Pennsylvania (USA), which also sets the stage for future investigations of neighborhood impacts on childhood health and development. To measure neighborhood deprivation, a standardized index of socioeconomic deprivation was calculated using data from the 2007-2011 American Community Survey. Families’ residential addresses when children were 2 months of age (n=1036) were geocoded and overlaid onto a deprivation index layer created at the census block group level to construct multiple administrative and ego-centric neighborhood definitions. Friedman tests were used to compare distributions of neighborhood deprivation across these neighborhood definitions within urbanized areas, urban clusters, and rural areas. Results indicated differences in urbanized areas (Chisquare= 897.75, P<0.001) and urban clusters (Chi-square=687.83, P<0.001), but not in rural areas (Chi-square=13.52, P=0.332). Findings imply that in urban areas, choice of neighborhood definition impacts measured exposure to neighborhood deprivation. Although exposure to neighborhood deprivation appears to be less sensitive to neighborhood definition in rural areas, researchers should apply theoretical reasoning to choose appropriate definitions of children’s neighborhood.

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References

Baud I, Kuffer M, Pfeffer K, Sliuzas R, Karuppannan S, 2010. Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing sub-standard residential areas. Int J Appl Earth Obs Geoinf 12:359-74. DOI: https://doi.org/10.1016/j.jag.2010.04.008

Beyer HL, 2012. Geo-spatial modelling environment [Computer software] (Version 0.7.2.* RC2). Available from: http://www.spatialecology.com/gme/

Cabrera-Barona P, Wei CZ, Hagenlocher M, 2016. Multiscale evaluation of an urban deprivation index: Implications for quality of life and healthcare accessibility planning. Appl Geogr 70:1-10. DOI: https://doi.org/10.1016/j.apgeog.2016.02.009

Chambers T, Pearson AL, Kawachi I, Rzotkiewicz Z, Stanley J, Smith M, Barr M, Ni Mhurchu C, Signal L, 2017. Kids in space: Measuring children’s residential neighborhood s and other destinations using activity space GPS and wearable camera data. Soc Sci Med 193:41-50. DOI: https://doi.org/10.1016/j.socscimed.2017.09.046

Crawford TW, Jilcott Pitts SB, McGuirt JT, Keyserling TC, Ammerman AS, 2014. Conceptualizing and comparing neighborhood and activity space measures for food environment research. Health Place 30:215-25. DOI: https://doi.org/10.1016/j.healthplace.2014.09.007

De Marco A, De Marco M, 2010. Conceptualization and measurement of the neighborhood in rural settings: a systematic review of the literature. J Community Psychol 38:99-114. DOI: https://doi.org/10.1002/jcop.20354

Diez Roux AV, Mair C, 2010. Neighborhood s and health. Ann N Y Acad Sci 1186:125-45. DOI: https://doi.org/10.1111/j.1749-6632.2009.05333.x

Dumedah G, Schuurman N, Yang WH, 2008. Minimizing effects of scale distortion for spatially grouped census data using rough sets. J Geogr Syst 10:47-69. DOI: https://doi.org/10.1007/s10109-007-0056-y

Duncan DT, Kawachi I, Subramanian SV, Aldstadt J, Melly SJ, Williams DR, 2014. Examination of how neighborhood definition influences measurements of youths’ access to tobacco retailers: A methodological note on spatial misclassification. Am J Epidemiol 179:373-81. DOI: https://doi.org/10.1093/aje/kwt251

Duncan DT, Regan SD, Chaix B, 2018. Operationalizing neighborhood definitions in health research: spatial misclassification and other issues. In: D.T. Duncan and I. Kawachi (Eds.), Neighborhoods and health. Oxford University Press, Oxford, UK, pp. 19-56. DOI: https://doi.org/10.1093/oso/9780190843496.003.0002

Environmental Systems Research Institute (ESRI), 2019. ArcGIS Release 10.7.1 Redlands, CA, USA.

Finegood ED, Rarick JRD, Blair C, Family Life Project Investigators, 2017. Exploring longitudinal associations between neighborhood disadvantage and cortisol levels in early childhood. Dev Psychopathol 29:1649-62. DOI: https://doi.org/10.1017/S0954579417001304

Fortney J, Rost K, Warren J, 2000. Comparing alternative methods of measuring geographic access to health services. Health Serv Outcomes Res Methodol 1:173-84. DOI: https://doi.org/10.1023/A:1012545106828

Fowler CS, Jensen L, 2020. Bridging the gap between geographic concept and the data we have: The case of labor markets in the USA. Environ Plan A 0308518X20906154. [Epub ahead of print].

Hobbs M, Griffiths C, Green MA, Jordan H, Saunders J, McKenna J, 2018. Neighborhood typologies and associations with body mass index and obesity: a cross-sectional study. Prev Med 111:351-7. DOI: https://doi.org/10.1016/j.ypmed.2017.11.024

Hotchkiss M, Phelan J, 2017. Uses of Census Bureau data in federal funds distribution. Available from: https://www2.census.gov/programs-surveys/decennial/2020/programmanagement/working-papers/Uses-of-Census-Bureau-Data-in-Federal-Funds-Distribution.pdf

Kramer MR, 2018. Residential segregation and health, neighborhoods and health. Oxford University Press, Oxford, UK, pp. 321-356. DOI: https://doi.org/10.1093/oso/9780190843496.003.0012

Kwan MP, 2013. Beyond space (as we knew it): toward temporally integrated geographies of segregation, health, and accessibility: space-time integration in geography and GIScience. Ann Am Assoc Georgr 103:1078-86. DOI: https://doi.org/10.1080/00045608.2013.792177

Leventhal T, 2018. Neighborhood context and children’s development: when do neighborhoods matter most? Child Dev Perspect 12:258-63. DOI: https://doi.org/10.1111/cdep.12296

Lian M, Struthers J, Liu Y, 2016. Statistical assessment of neighborhood socioeconomic deprivation environment in spatial epidemiologic studies. Open J Stat 6:436-42. DOI: https://doi.org/10.4236/ojs.2016.63039

Lin VK, Madill R, 2019. Incorporating spatial analyses into early care and education research. OPRE Research Brief #2019-88. Washington, D.C.: Office of Planning, Research, and Evaluation, Administration for Children and Families. Available from: https://files.eric.ed.gov/fulltext/ED602065.pdf

Malik R, Hamm K, 2017. Mapping America’s child care deserts. Available from: https://www.americanprogress.org/issues/early-childhood/reports/2017/08/30/437988/mapping-americas-child-care-deserts/

Matthews SA, 2011. Spatial polygamy and the heterogeneity of place: studying people and place via egocentric methods. Communities, neighborhoods, and health. Springer, Berlin, Germany, pp. 35-55. DOI: https://doi.org/10.1007/978-1-4419-7482-2_3

Messer LC, Laraia BA, Kaufman JS, Eyster J, Holzman C, Culhane J, Elo I, Burke JG, O’Campo P, 2006. The development of a standardized neighborhood deprivation index. J Urban Health 83:1041-62. DOI: https://doi.org/10.1007/s11524-006-9094-x

Minh A, Muhajarine N, Janus M, Brownell M, Guhn M, 2017. A review of neighborhood effects and early child development: How, where, and for whom, do neighborhood s matter? Health Place 46:155-74. DOI: https://doi.org/10.1016/j.healthplace.2017.04.012

Mitchell B, Franco J, 2018. HOLC “Redlining” maps: The persistent structure of segregation and economic inequality; Washington, DC, USA. Available from: https://ncrc.org/wp-content/uploads/dlm_uploads/2018/02/NCRC-Research-HOLC-10.pdf

O’Campo, 2003. Invited commentary: advancing theory and methods for multilevel models of residential neighborhood s and health. Am J Epidemiol 157:9-13. DOI: https://doi.org/10.1093/aje/kwf171

Östh J, Clark WA, Malmberg B, 2015. Measuring the scale of segregation using k‐nearest neighbor aggregates. Geogr Anal 47:34-49. DOI: https://doi.org/10.1111/gean.12053

Perchoux C, Chaix B, Brondeel R, Kestens Y, 2016. Residential buffer, perceived neighborhood, and individual activity space: New refinements in the definition of exposure areas - The RECORD cohort study. Health Place 40:116-22. DOI: https://doi.org/10.1016/j.healthplace.2016.05.004

R Core Team, 2017. A language and environment for statistical computing. R Foundation for Statistical. Vienna, Austria. Available from: https://www.r-project.org/

Richards MP, 2014. The gerrymandering of school attendance zones and the segregation of public schools: A geospatial analysis. Am J Educ Res 51:1119-57. DOI: https://doi.org/10.3102/0002831214553652

Ripley BD, 1981. Spatial statistics. Wiley, New York, NY, USA. DOI: https://doi.org/10.1002/0471725218

Sadler RC, Clark AF, Wilk P, O’Connor C, Gilliland JA, 2016. Using GPS and activity tracking to reveal the influence of adolescents’ food environment exposure on junk food purchasing. Can J Public Health 107:eS14-20. DOI: https://doi.org/10.17269/CJPH.107.5346

Schuurman N, Bell N, Dunn JR, Oliver L, 2007. Deprivation indices, population health and geography: an evaluation of the spatial effectiveness of indices at multiple scales. J Urban Health 84:591-603. DOI: https://doi.org/10.1007/s11524-007-9193-3

Sluiter R, Tolsma J, Scheepers P, 2015. At which geographic scale does ethnic diversity affect intra-neighborhood social capital?. Soc Sci Res 54:80-95. DOI: https://doi.org/10.1016/j.ssresearch.2015.06.015

Stewart O, 2011. Findings from research on active transportation to school and implications for safe routes to school programs. J Plan Lit 26:127-50. DOI: https://doi.org/10.1177/0885412210385911

Thatcher E, Johnson C, Zenk SN, Kulbok P, 2017. Retail food store access in rural Appalachia: A mixed methods study. Public Health Nurs 34:245-55. DOI: https://doi.org/10.1111/phn.12302

US Census Bureau, April 2009. Design and methodology: American Community Survey. Available from: https://www2.census.gov/programssurveys/acs/methodology/design_and_methodology/acs_design_methodology_previous.pdf

US Census Bureau, February 2020. Urban and rural. Available from: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html

Vallée J, Shareck M, 2014. Re: “Examination of how neighborhood definition influences measurements of youths’ access to tobacco retailers: A methodological note on spatial misclassification”. Am J Epidemiol 179:660-1. DOI: https://doi.org/10.1093/aje/kwt436

Vernon-Feagans L, Cox M, Family Life Project Key Investigators, 2013. The Family Life Project: an epidemiological and developmental study of young children living in poor rural communities. Monogr Soc Res Child Dev 78:1-150.

Wan C, Su SL, 2016. Neighborhood housing deprivation and public health: Theoretical linkage, empirical evidence, and implications for urban planning. Habitat Int 57:11-23. DOI: https://doi.org/10.1016/j.habitatint.2016.06.010

Willoughby M, Burchinal M, Garrett-Peters P, Mills-Koonce R, Vernon-Feagans L, Cox M, 2013. The Family Life Project: An epidemiological and developmental study of young children living in poor rural communities: II. Recruitment of the Family Life Project sample. Monogr Soc Res Child Dev 78:24-35. DOI: https://doi.org/10.1111/mono.12048

Xu H, Logan JR, Short SE, 2014. Integrating space with place in health research: a multilevel spatial investigation using child mortality in 1880 Newark, New Jersey. Demography 51:811-34. DOI: https://doi.org/10.1007/s13524-014-0292-y

Yaemsiri S, Alfier JM, Moy E, Rossen LM, Bastian B, Bolin J, Ferdinand AO, Callaghan T, Heron M, 2019. Healthy people 2020: Rural areas lag in achieving targets for major causes of death. Health Aff 38:2027-31. DOI: https://doi.org/10.1377/hlthaff.2019.00915

Zenk SN, Schulz AJ, Matthews SA, Odoms-Young A, Wilbur J, Wegrzyn L, Gibbs K, Braunschweig C, Stokes C, 2011. Activity space environment and dietary and physical activity behaviors: A pilot study. Health Place 17:1150-61. DOI: https://doi.org/10.1016/j.healthplace.2011.05.001

Published
2021-03-11
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Original Articles
Keywords:
Rural, neighborhood deprivation, neighborhood definition.
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How to Cite
Ursache, A., Regan, S., De Marco, A., Duncan, D. T., & The Family Life Project Key Investigators. (2021). Measuring neighborhood deprivation for childhood health and development - scale implications in rural and urban context. Geospatial Health, 16(1). https://doi.org/10.4081/gh.2021.926