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Environmental Factors and Risk of Childhood Obesity Sharon Kandris, MA 1 & Gilbert Liu, MD,MS 2 1 The Polis Center at Indiana University-Purdue University.

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Presentation on theme: "Environmental Factors and Risk of Childhood Obesity Sharon Kandris, MA 1 & Gilbert Liu, MD,MS 2 1 The Polis Center at Indiana University-Purdue University."— Presentation transcript:

1 Environmental Factors and Risk of Childhood Obesity Sharon Kandris, MA 1 & Gilbert Liu, MD,MS 2 1 The Polis Center at Indiana University-Purdue University at Indianapolis 2 Children’s Health Services Research, Department of Pediatrics at Indiana University

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11 Background Environmental factors that increase caloric intake and decrease energy expenditure seem to underlie the rapid increases in obesity prevalence Environmental factors that increase caloric intake and decrease energy expenditure seem to underlie the rapid increases in obesity prevalence The current U.S. environment is characterized by an essentially unlimited supply of convenient, inexpensive, palatable, energy-dense foods coupled with a lifestyle requiring negligible amounts of physical activity for subsistence. The current U.S. environment is characterized by an essentially unlimited supply of convenient, inexpensive, palatable, energy-dense foods coupled with a lifestyle requiring negligible amounts of physical activity for subsistence.

12 1970’s obesity was associated with higher socioeconomic status in early childhood, and lower SES in adolescent females 1980’s very disparate reporting on the relationship between SES and obesity 1990’s 2.2-fold increased incidence of childhood obesity in children living in dilapidated living conditions. 2000’s children from low income families had an almost threefold increased risk of developing obesity.Background

13 Hypothesis Controlling for individual demographics, childhood obesity is more prevalent in regions where the social milieu does not support healthy lifestyles

14 Social Milieu Factors Related to Healthy Lifestyle Lower Median Income Decreased Physical Activity Less access to facilities for physical activity Less access to facilities for physical activity Less leisure time for physical activity Less leisure time for physical activity Less Healthful Diet Greater use of high-calorie convenience foods Greater use of high-calorie convenience foods Lower consumption of fruits and vegetables Lower consumption of fruits and vegetables Lower Educational Attainment More Single-parent households Higher Crime A perception of one’s neighborhood as unsafe poses a barrier to physical activity

15 Approach 1. Study design: Cross-sectional 2. Regenstrief Medical Record System, Indiana University Medical Group 3. Patients ages 4-18y who had simultaneously documented heights and weights in calendar years 1996 – 2000 4. Categorized by BMI percentiles into overweight (>85 th – 95 th percentile for age-adjusted norms) and obese (>95 th percentile) 5. Using GIS, we linked study subjects with community- level socioeconomic data (2000 U.S. Census) using census block groups as the index

16 Statistical Analysis Logistic regression examining association between obesity and: Individual-level variables 1.Age 2.Gender 3.Ethnicity Community-level variables 1.Median family income Extremely low, Very low, Low, Middle, Moderate & Upper* Extremely low, Very low, Low, Middle, Moderate & Upper* 2.Proportion of adults without HS degree 3.Proportion of single-parent households 4.Crime rate per square mile 5.Linguistic isolation *[HUD definitions adjusted for Indianapolis median family incomes]

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18 Distribution of BMI (n=17,871) Normal weight……………..11,133 (62%) Overweight………………….2,893 (16%) Obese………………………..3,845 (22%)

19 Distribution of BMI by Gender (n=17,871) Total (%) Boy Normal Overweight Obese 8455 (47) 5396 (64) 1296 (15) 1763 (21) Girl Normal Overweight Obese 9416 (53) 5737 (61) 1597 (17) 2082 (22) Total Normal Overweight Obese 11133 (62) 2893 (16) 3845 (22)

20 Distributions of BMI by Ethnicity and Gender (n=17,871) Black (%)White (%)Hispanic (%) Other (%) Male Normal Overweight Obese 3246 (65) 734 (15) 1021 (20) 1820 (63) 450 (16) 620 (21) 198 (54) 76 (21) 94 (16) 132 (67) 36 (18) 28 (14) Female Normal Overweight Obese 3396 (60) 996 (17) 1302 (23) 2041 (63) 519 (16) 660 (21) 185 (57) 55 (17) 82 (26) 115 (64) 27 (15) 38 (21)

21 Summary Statistics on Age and Census Block Group Indicators Mean & Standard Deviation Age 10.4 ± 4.2 Median Family Income $32,561 ± 12,406 Proportion of Adults without HS diploma 29.3% ± 14.7 Proportion of single-parent households 28.9% ± 14.3 Crime rate per square mile 604.1 ± 428.6

22 Distribution of Obesity by Age

23 Distribution of Obesity by Income Level

24 FactorEstimate95% Confidence Interval Ethnic and Gender Subgroups White Male White Female Hispanic Male Hispanic Female Black Male Black Female Others Male Others Female 1.000 0.931 1.374 1.437 0.955 1.059 0.654 1.097 Reference Group (0.822, 1.055) (1.050, 1.799) (1.114, 1.852) (0.852, 1.070) (0.948, 1.184) (0.433, 0.987) (0.756, 1.592) Point Estimates and 95% Confidence Intervals for Odds Ratios by Ethnicity and Gender

25 FactorEstimate95% Confidence Interval Income categories Extremely low income Very low income Low income Moderate income Middle income Upper income 1.441 1.550 1.471 1.345 1.335 1.000 (1.104, 1.881) (1.265, 1.898) (1.212, 1.785) (1.078, 1.677) (1.071, 1.664) Reference Group Point Estimates and 95% Confidence Intervals for Odds Ratios by Income Levels

26 Summary of Findings 1. Inverse association between the median family income of a census block group and the incidence of obese children in the census block group 2. A child’s risk of obesity differs according to individual characteristics such as age, race and gender.

27  Used Geographic Information Systems (GIS)  Observed spatial relationship between obesity and environmental variables  Compared block groups with high prevalence of obesity to those with low and mapped against environmental variables  Identified “High-Risk” Areas Spatial Analysis

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32 High Risk Neighborhoods

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34 In General:  Near Industry  Poor Access to Open Space  Few Grocery Stores  Impoverished  Large Hispanic population

35 Next Steps New Variables Environmental  Land use type  Air and water quality  Hazardous Substances  Grocery Stores  Ethnic Food Stores  Fast Food Density Individual-level: Individual-level:  Insurance Status New Analysis Methods  Year-by-year  Geostatistical Analysis  Advanced Spatial Analysis

36 Next Steps Develop Education and/or Intervention Strategies Through Continued Involvement in Community Initiatives »P.E. for the 21 st Century Charter School, Indianapolis, IN »Youth Movement Initiative

37 Community Initiatives National –Pediatric Academic Societies –American College of Sports Medicine –National Association of State High School Associations Local –Strategic Thinking on Obesity Coalition –West Side Community Organization –Additional Funding Support (NIH) »Indiana State Department of Health »State Toxicologist »Local Researchers

38 Contact Us Sharon Kandris skandris@iupui.edu 317.278.2944 Gil Liu gcliu@iupui.edu 317.278.0552


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