2019
DOI: 10.1002/oby.22663
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Childhood Obesity and the Food Environment: A Population‐Based Sample of Public School Children in New York City

Abstract: Objective This study aimed to examine the relationship between proximity to healthy and unhealthy food outlets around children’s homes and their weight outcomes. Methods A total of 3,507,542 student‐year observations of height and weight data from the 2009‐2013 annual FitnessGram assessment of New York City public school students were used. BMI z scores were calculated, student obesity or obesity/overweight was determined using Centers for Disease Control and Prevention growth charts, and these data were combi… Show more

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Cited by 24 publications
(15 citation statements)
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“…In the first stage, we conducted Mahalanobis distance matching with 1:5 matching and replacement using administrative student-level data, including gender, age, grade, race and ethnicity, poverty status (defined as whether the student ever qualified for free/reduced-price lunch, as a proxy for family income below 185% of the federal poverty level), special education status, weight, and height; and neighborhood food environment variables, including count of fast-food restaurants, wait-service restaurants, convenience stores, and supermarkets within 0.50 miles of students’ residences and distance to closest food outlet (by type) from students’ residences. Restaurant variables were derived from the NYC Department of Health and Mental Hygiene Restaurant Grading data, and food store variables were derived from the New York State Department of Agriculture and Markets Licensing and Inspection data . We used python package NetworkX 2.4 to calculate food outlet count variables and the network distance between residential addresses and food outlet addresses, including FRESH supermarket addresses.…”
Section: Methodsmentioning
confidence: 99%
“…In the first stage, we conducted Mahalanobis distance matching with 1:5 matching and replacement using administrative student-level data, including gender, age, grade, race and ethnicity, poverty status (defined as whether the student ever qualified for free/reduced-price lunch, as a proxy for family income below 185% of the federal poverty level), special education status, weight, and height; and neighborhood food environment variables, including count of fast-food restaurants, wait-service restaurants, convenience stores, and supermarkets within 0.50 miles of students’ residences and distance to closest food outlet (by type) from students’ residences. Restaurant variables were derived from the NYC Department of Health and Mental Hygiene Restaurant Grading data, and food store variables were derived from the New York State Department of Agriculture and Markets Licensing and Inspection data . We used python package NetworkX 2.4 to calculate food outlet count variables and the network distance between residential addresses and food outlet addresses, including FRESH supermarket addresses.…”
Section: Methodsmentioning
confidence: 99%
“…In the Elbel et al (8) analysis of a population-based sample of public school children in New York City, proximity of fast-food restaurants was found to be inversely related to childhood obesity in the city. The authors concluded that their finding supports a need to pivot public policy toward promoting outlets that "sell healthier foods" and restrict access to "outlets selling less healthy items.…”
Section: Obesitymentioning
confidence: 99%
“…Elbel et al(8) Height and weight data (a total of 3,507,542 student-year observations) from the 2009-2013 annual FitnessGram assessment of New York City public school students were used to evaluate the relationships between weight status outcomes and the distance to several food outlet types (including supermarket) in the city. Statistical analyses utilized ordinary least squares regression modeling.Living farther than 0.025 mile from the nearest fast-food restaurant was associated with lower obesity and obesity/ overweight risk and with lower BMIz scores as calculated using FitnessGram data.…”
mentioning
confidence: 99%
“…This happens to people who reside in the cities since restaurants and stalls almost everywhere offer fast food. This is different for those who live far removed from fast-food premises, (Elbel et al, 2020). A study in California found that residing around fast-food outlets contributes to the obesity problem among children compared to those who live far away, (Davis & Carpanter, 2009).…”
Section: Accessibilitymentioning
confidence: 99%