Individual time preferences and obesity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Behavioral economic analysis of health-related behavior is a potentially useful approach to study and control non-communicable diseases. The purpose of this paper is to explore the time preferences of individuals and its impact on obesity in an adult population of Iran. Design/methodology/approach A structured questionnaire was completed by 792 individuals who were randomly selected from the participants of an ongoing national Prospective Epidemiological Research Studies in IrAN cohort study in West of Iran. The quasi-hyperbolic discounting model was used to estimate the parameters of time preferences and a probit regression model was used to explore the correlation between obesity and time preferences. Findings There was a statistically significant correlation between obesity and both the long-run patience and present-biased preferences of participants. Individuals with a low level of long-run patience were 10.2 percentage points more likely to be obese compared to individuals with a high level of long-run patience. The probability of being obese increased by 11 percentage points in present-biased individuals compared to future biased individuals. Originality/value The long-run patience and time inconsistent preferences were significant determinants of obesity. Considering the time-inconsistent preferences in the development of policies to change obesity-related behavior among adults might increase the success rate of the interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it