Heterogeneous effects of obesity on mental health: Evidence from Mexico
Bibliographic record
Abstract
Obesity can spread more easily if it is not perceived negatively. This issue may be more pronounced among the poor, a conjecture that we test in this paper. We start with general evidence on the concave relationship between income and obesity, both across countries and within Mexico, a country characterized by very unequal development levels and the highest obesity rate in the world. We suggest a general model that explains this stylized fact from a simple necessary condition, namely, the complementarity between nonfood consumption and health concerns. Then, we test the direct effect of overweight on mental health among Mexican women. We find a positive effect of obesity in the low consumption group and a depressing effect among the rich. This result is robust to the inclusion of a range of confounders (childhood conditions, lifestyle variables, food expenditure, and household shocks) and after instrumenting individual fatness by the variation in genetic predisposition. The complementarity between living standards and weight concerns may reflect different norms, different labor market penalties, or simply different returns to healthy time across the social spectrum.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".