Regionalization of school youth obesity and overweight in Texas by considering both body mass index and socioeconomic status
- 95 Downloads
We employed a regionalization algorithm called regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) to analyze the Body Mass Index (BMI) of school students in Texas and its association with social economic status (SES). The study includes 741 school districts in Texas. BMI data were extracted from the Physical Fitness Assessment Initiative program managed by Texas Education Agency. SES was described using six variables that cover two aspects, Household SES and Neighborhood SES. The study period was the 2012–2013 academic year. We used three REDCAP algorithms to delineate regions considering both spatial contiguity and attribute homogeneity. The result shows that Full-order-CLK algorithm of REDCAP is most effective in producing regions to delineate the patterns of Texas students’ BMI and its relationship with SES. Moreover, two- and six -class regions are the optimal numbers for such a regionalization. Our study reveals the regional patterns of school youth obesity in Texas when connecting to SES—particularly in regions with high rate of obesity and low SES, such as the regions in South and West Texas, and the three school districts in San Antonio. The findings can provide guidance for regionalized policy and practice to fight against school youth obesity in Texas.
KeywordsHeterogeneity Obesity REDCAP Regionalization Spatial contiguity
Compliance with ethical standards
Conflict of interest statement
The authors declare that they have no conflict of interest.
- Adu-Prah, S., & Oyana, T. J. (2015). Regionalization of youth and adolescent weight metrics for the continental united states using contiguity-constrained clustering and partitioning. Cartographica: The International Journal for Geographic Information and Geovisualization, 50(2), 61–70.CrossRefGoogle Scholar
- Benassi, F., Bocci, C., & Petrucci, A. (2010). Spatial data mining for clustering: From the literature review to an application using RedCap. Working paper 2010/2011, Università degli Studi di Firenze.Google Scholar
- Chalkias, C., Papadopoulos, A. G., Kalogeropoulos, K., Tambalis, K., Psarra, G., & Sidossis, L. (2013). Geographical heterogeneity of the relationship between childhood obesity and socio-environmental status: Empirical evidence from athens, greece. Applied Geography, 37, 34–43.CrossRefGoogle Scholar
- Escarce, J., Morales, L., & Rumbaut, R. (2006). The health status and health behaviors of Hispanics. In M. Tienda & F. Mitchell (Eds.), Hispanics and the future of America (pp. 362– 409). Washington, DC: National Academies Press.Google Scholar
- Index, B. M. (2008). About BMI for adults. Atlanta: Department of Health and Human Services,Centers for Disease Control and Prevention.Google Scholar
- Lenihan, P. (2008). Regionalization in local public health departments: The northern illinois public health consortium. Public Health Reports, 123(4), 1–13.Google Scholar
- Low, S., Chin, M. C., & Deurenberg-Yap, M. (2009). Review on epidemic of obesity. Annals Academy of Medicine Singapore, 38(1), 57.Google Scholar
- Martikainen, P. T., & Marmot, M. G. (1999). Socioeconomic differences in weight gain and determinants and consequences of coronary risk factors. The American Journal of Clinical Nutrition, 69(4), 719–726.Google Scholar
- Parker, L., Burns, A. C., & Nyberg, K. (2010). Childhood obesity prevention in texas: Workshop summary. New York: National Academies Press.Google Scholar
- Robert, L. K. (2013). Constructing geographic areas for homicide research: A case study of New Orleans, LouisianaGoogle Scholar
- Salvador, S., & Chan, P. (2004). Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms. Paper presented at the tools with artificial intelligence, 2004. ICTAI 2004. 16th IEEE International Conference On, pp. 576–584.Google Scholar
- Texas Education Agency (2014). Physical fitness assessment initiative. Retrieved from http://tea.texas.gov/Texas_Schools/Safe_and_Healthy_Schools/Physical_Fitness_Assessment_Initiative/
- Wang, Y., & Lim, H. (2012). The global childhood obesity epidemic and the association between socio-economic status and childhood obesity. International Review Of Psychiatry, 24(3), 176–188. https://doi.org/10.3109/09540261.2012.688195.