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• W2570290461 abstract "Understanding the relationships between obesity and socioeconomic status (SES) among school children and the spatial variation of such relationship is essential for developing appropriate intervention strategies. In this study, we employed Local Entropy Map (LEM) to explore the spatial patterns of the relationship at school district level in Texas. Children's obesity was measured by Body Mass Index (BMI). The BMI data for this study were obtained from Physical Fitness Assessment Initiative (PFAI) program that has been coordinated by Texas Education Agency (TEA). SES was described by six variables, which were further reduced into two factors, namely Household SES and Neighborhood SES. The study period was 2012–2013 academic year. LEM analyses revealed clear spatial variation of the relationship between obesity and SES at school-district level. In particular, the prevalence of obesity among school children was found to be significantly related to Household SES and Neighborhood SES in four regions in Texas. These four regions are centered in major metropolitan areas in Texas, including San Antonio, Dallas-Fort Worth, Houston, and Lubbock. Further regression analyses showed variation of the relationship across these four regions. Obesity among school children in Texas was found to be more related to Household SES than Neighborhood SES; the relationship was strongest in San Antonio region. These findings may suggest the presence of obesogenic environment in the low SES school districts in these regions. Further studies to examine the particular nature of the obesogenic environment in these school districts are needed in order to support the development of regionalized policy and practice that can be more effective in addressing locale specifics." @default.
• W2570290461 created "2017-01-13" @default.
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• W2570290461 date "2017-02-01" @default.
• W2570290461 modified "2023-09-26" @default.
• W2570290461 title "The relationship between obesity and socioeconomic status among Texas school children and its spatial variation" @default.
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• W2570290461 doi "https://doi.org/10.1016/j.apgeog.2016.12.008" @default.
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