Abstract 033: Does Persistent Poverty Elevate Risk for Obesity More Than Occasional Poverty in Youth? Evidence From a Quebec Birth Cohort
Bibliographic record
Abstract
Background: Childhood poverty heightens the risk of obesity in adulthood, but its effect during childhood is poorly understood. We analyzed the relationship between poverty trajectories across the ages of 6, 8, 10, and 12 years with BMI Z-scores and the risk of being overweight in a birth cohort of children. Methods: Data were from 703 participants in the 1998-2010 ″Quebec Longitudinal Study of Child Development″ (n=2,120) birth cohort. Household income was measured annually with poverty defined as income below the low-income thresholds established by Statistics Canada adjusted for household size and geographic region. Children’s height and weight at ages 6, 8, 10, and 12 years were measured by trained study staff. Body mass index (BMI) was converted to age- and sex- standardized BMI Z-scores and percentiles and were classified as overweight or obese (BMI percentile > 85th) based on CDC growth curves. Trajectories of poverty across the ages of 6, 8, 10, and 12 years were characterized with a latent class group analysis using maximum likelihood in a semiparametric mixture model. Multivariable linear regressions predicted BMI Z-scores at different ages, and logistic regression predicted the risk of being overweight or obese based on poverty trajectories after adjusting for sex. Because all children at ages 6 and 8 years were pre-pubertal, and all children at age 12 were in puberty, only the model for BMI at age 10 adjusted for puberty. Results: Poverty trajectories were fairly stable across time and fell into 1 lower exposure category (consistently low exposure (approximately 70%, n=487)) and 3 higher exposure categories (increasing: 8%, n=55; decreasing: 10%, n=70; or consistently high exposure: 13%, n=91)). After adjusting for covariates, compared to children experiencing lower exposure to poverty, BMI Z-scores of children with consistently high exposure to poverty were 0.05 (p=NS), 0.12 (p=NS), 0.37 (p=0.02), and 0.42 (p=0.003) higher at ages 6, 8, 10, and 12 years, respectively. After adjustment, children experiencing consistently high exposure to poverty were at a significantly increased risk for being overweight or obese at age 8 (OR: 2.0, 95% CI: 1.2-3.3, p=0.01), age 10 (OR: 2.1, CI: 1.2-3.5, p=0.005), and at age 12 years (OR: 2.8, CI: 1.7-4.7, p<0.001) compared to children experiencing lower exposure to poverty. Children experiencing decreasing exposure to poverty at all ages, or increasing exposure at age 10 and 12 years were at an increased risk for being overweight or obese, but the results were not statistically significant. Conclusion: Findings suggest that there is a latency period for the detrimental effects of poverty on weight, but that previous exposure can still impact future weight even at a young age. Whether the disparity in weight status according to poverty trajectories widens as the children continue to age should be investigated.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".