Exploring the Relationship Between Body Mass Index, Obesity, and Gambling Level Across Different Gambling Types
Bibliographic record
Abstract
Individuals’ body weight, measured in terms of body mass index (BMI), has been linked to various health issues in the literature. Recently, a positive relationship has been found between obesity and the level of problem gambling. In this exploratory study, we investigate the association between BMI, obesity, and gambling frequency across multiple types of leisure gambling. Data collected by the Pew Research Center among 1,473 gamblers was used to tests the links between BMI and gambling frequency for 16 types of leisure gambling activities. After we accounted for the effects of age, educational level, and family income and corrected for multiple comparisons, the results showed that obese participants (BMI ³ 30) conducted significantly more gambling activities in two types of gambling, namely, playing bingo for money and buying state lottery tickets. Moreover, among female gamblers only, BMI was positively associated with frequency of gambling related to casinos, college basketball, and video poker machines. The findings of this exploratory study allow a better understanding of the potential risk factors of obesity and may be of value to public policy makers.Dans diverses études antérieures, le poids corporel des personnes, mesuré en termes d’indice de masse corporelle (IMC), a été lié à divers problèmes de santé. Récemment, un lien positif a été constaté entre l’obésité et le niveau de jeu compulsif. Dans cette étude exploratoire, nous examinons la relation entre l’indice de masse corporelle, l’obésité et la fréquence du jeu, en nous basant sur divers types de jeux de hasard récréatifs. À l’aide de données recueillies par Pew Research Center auprès de 1 473 joueurs, l’étude sonde les liens entre l’IMC et la fréquence du jeu dans le cas de seize types de jeux récréatifs. Les résultats montrent qu’après avoir tenu compte de l’effet de l’âge, du niveau d’instruction et du revenu familial, ainsi que de la correction de comparaisons multiples, les participants obèses (IMC ≧ 30) ont mené beaucoup plus d’activités de jeu dans deux types de jeux, à savoir le bingo lucratif et l’achat d’une loterie d’État. De plus, seulement chez les joueurs de sexe féminin, l’IMC est positivement associé à la fréquence du jeu dans les cas du casino, du basketball universitaire et de la machine de vidéo poker. Les résultats de cette étude exploratoire nous permettent de mieux comprendre les facteurs de risque éventuels de l’obésité et peuvent être utiles aux décideurs publics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".