Risk Factors for Adult Overweight and Obesity: The Importance of Looking Beyond the ‘Big Two’
Bibliographic record
Abstract
OBJECTIVE: To compare two traditional (high dietary lipid intake and non-participation in high-intensity physical exercise, namely the 'Big Two' factors) versus three nontraditional (short sleep duration, high disinhibition eating behavior, and low dietary calcium intake) risk factors as predictors of excess body weight and overweight/obesity development. METHOD: Adult participants aged 18-64 years of the Quebec Family Study were selected for cross-sectional (n = 537) and longitudinal (n = 283; 6-year follow-up period) analyses. The main outcome measure was overweight/obesity, defined as a BMI ≥ 25 kg/m(2). RESULTS: We observed that both the prevalence and incidence of overweight/obesity was best predicted by a combination of risk factors. However, short sleep duration, high disinhibition eating behavior and low dietary calcium intake seemed to contribute more to the risk of overweight and obesity than high dietary lipid intake and non-participation in high-intensity physical exercise. Globally, the risk of being overweight or obese was two-fold higher for individuals having the three nontraditional risk factors combined (OR 6.05; 95% CI 4.26-7.88) compared to those reporting a high percentage of lipids in their diet together with no vigorous physical activity in their daily schedule (OR 2.95; 95% CI 2.18-3.73). Furthermore, the risk of overweight/obesity was also higher for the combination of any two of the nontraditional risk factors than for the combination of the 'Big Two' factors. CONCLUSION: These results are concordant with previous reports showing that obesity is a multifactorial condition, and emphasize the importance of looking beyond reported measures of the 'Big Two' factors.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".