Stephanie Hsieh1, Ann C Klassen2, Frank C Curriero3, Laura E Caulfield4, Lawrence J Cheskin5, Jaimie N Davis6, Michael I Goran7, Marc J Weigensberg8, Donna Spruijt-Metz9. 1. Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. Electronic address: shsieh@jhsph.edu. 2. Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Department of Community Health and Prevention, Drexel University School of Public Health, Drexel University, Philadelphia, Pennsylvania. 3. Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. 4. Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. 5. Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. 6. Department of Nutritional Sciences, University of Texas, Austin, Texas. 7. Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, California; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California; Department of Physiology & Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California. 8. Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, California. 9. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California.
Abstract
BACKGROUND: Evidence of associations between the built environment and obesity risk has been steadily building, yet few studies have focused on the relationship between the built environment and aspects of metabolism related to obesity's most tightly linked comorbidity, type 2 diabetes. PURPOSE: To examine the relationship between aspects of the neighborhood built environment and insulin resistance using accurate laboratory measures to account for fat distribution and adiposity. METHODS: Data on 453 Hispanic youth (aged 8-18 years) from 2001 to 2011 were paired with neighborhood built environment and 2000 Census data. Analyses were conducted in 2011. Walking-distance buffers were built around participants' residential locations. Body composition and fat distribution were assessed using dual x-ray absorptiometry and waist circumference. Variables for park space, food access, walkability, and neighborhood sociocultural aspects were entered into a multivariate regression model predicting insulin resistance as determined by the homeostasis model assessment. RESULTS: Independent of obesity measures, greater fast-food restaurant density was associated with higher insulin resistance. Increased park space and neighborhood linguistic isolation were associated with lower insulin resistance among boys. Among girls, park space was associated with lower insulin resistance, but greater neighborhood linguistic isolation was associated with higher insulin resistance. A significant interaction between waist circumference and neighborhood linguistic isolation indicated that the negative association between neighborhood linguistic isolation and insulin resistance diminished with increased waist circumference. CONCLUSIONS: Reducing access to fast food and increasing public park space may be valuable to addressing insulin resistance and type 2 diabetes, but effects may vary by gender.
BACKGROUND: Evidence of associations between the built environment and obesity risk has been steadily building, yet few studies have focused on the relationship between the built environment and aspects of metabolism related to obesity's most tightly linked comorbidity, type 2 diabetes. PURPOSE: To examine the relationship between aspects of the neighborhood built environment and insulin resistance using accurate laboratory measures to account for fat distribution and adiposity. METHODS: Data on 453 Hispanic youth (aged 8-18 years) from 2001 to 2011 were paired with neighborhood built environment and 2000 Census data. Analyses were conducted in 2011. Walking-distance buffers were built around participants' residential locations. Body composition and fat distribution were assessed using dual x-ray absorptiometry and waist circumference. Variables for park space, food access, walkability, and neighborhood sociocultural aspects were entered into a multivariate regression model predicting insulin resistance as determined by the homeostasis model assessment. RESULTS: Independent of obesity measures, greater fast-food restaurant density was associated with higher insulin resistance. Increased park space and neighborhood linguistic isolation were associated with lower insulin resistance among boys. Among girls, park space was associated with lower insulin resistance, but greater neighborhood linguistic isolation was associated with higher insulin resistance. A significant interaction between waist circumference and neighborhood linguistic isolation indicated that the negative association between neighborhood linguistic isolation and insulin resistance diminished with increased waist circumference. CONCLUSIONS: Reducing access to fast food and increasing public park space may be valuable to addressing insulin resistance and type 2 diabetes, but effects may vary by gender.
Authors: Tanya L Alderete; Rima Habre; Claudia M Toledo-Corral; Kiros Berhane; Zhanghua Chen; Frederick W Lurmann; Marc J Weigensberg; Michael I Goran; Frank D Gilliland Journal: Diabetes Date: 2017-01-30 Impact factor: 9.461