Food Environment around School and Students' Weight Status: A Study of Four New Jersey Low-Income Communities
Bibliographic record
Abstract
abstract: Childhood obesity has been on the rise for the past decade, and it has been hypothesized that students' food choices may be influenced by easy access to food outlets near their schools that provide unhealthful options. But the results of recent studies on the relationship between the food environment around schools and student weight status are mixed and often contradictory. Most studies have used measures of weight and height that were self-reported by students, or have relied on data from a relatively small sample of students. I examine the association between weight status among school students and the food environment surrounding their schools using professionally-measured, student-level data across the full school-age spectrum. De-identified data were obtained for over 30,000 K-12 students in 79 public schools located in four New Jersey cities. Locations of alternative food-outlets (specifically, supermarkets, convenience stores, small grocery stores, and limited-service restaurants) were obtained from commercial sources and geocoded to develop proximity measures. A simplified social-ecological framework was used to conceptualize the multi-level the association between students' BMI and school proximity to food outlets and multivariate analyses were used to estimate this relationship controlling for student- and school-level factors. Over twenty percent of the students were obese, compared to the national average at 17% (Ogden, Carroll, Kit, & Flegal, 2012). On average, students had 2.6 convenience stores, 2.9 limited-service restaurants, and 0.1 supermarkets within a quarter mile of their school. This study suggests that easy access to small grocery stores (which this study uniquely examines as a separate food outlet category) that offer healthy choices including five types of fresh vegetable, five types of fresh fruits, low-fat dairy, and lean meats is associated with lower BMI z score and lower probability of being obese for middle and high school students. This suggests that improving access to such small food outlets may be a promising area for future investigation in obesity mitigation research. Also, this study separates students of pre-schools, kindergartens and elementary schools (neighborhood schools) from that of the middle and high schools (non-neighborhood) schools because the two groups of schools have different neighborhood characteristics, as well as open-school and bussing policies that result in different levels of exposure that students have to the food outlets around the schools. The result of this study suggests that the relationship between students' weight outcomes and food environment around schools is different in the two groups of schools.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".