Physical inactivity prevalence and trends among Mexican adults: results from the National Health and Nutrition Survey (ENSANUT) 2006 and 2012
Bibliographic record
Abstract
BACKGROUND: Lifestyles such as unhealthy diets and the lack of physical activity have been contributed to the increased prevalence of obesity. In 2012, the world health organization published the first global recommendation for physical activity and health. People who do not meet at least 150 minutes of moderate-to-vigorous physical activity are considered to be physically inactive. The prevalence of physical inactivity worldwide is 31%, however there is insufficient data from prevalence and trends of physical inactivity in Mexican population. The purposes of this study are to describe the physical inactivity prevalence and recent trends in Mexican adults and to examine the association between physical inactivity with biologic and sociodemographic characteristics. METHODS: Representative samples of 17,183 and 10,729 adults (aged 20 to 69 years) who participated in the National Health and Nutrition Survey (ENSANUT) in 2006 and 2012, respectively. Moderate-to-vigorous physical activity (MVPA) was assessed using the short form version of the International Physical Activity Questionnaire (IPAQ), which was administered in face-to-face interviews. Self-reported IPAQ MVPA levels were adjusted using an equation derived from a previous validation study. Participants were considered inactive if they engaged in <150-minutes/week of moderate physical activity or <75 minutes/week of vigorous physical activity according to WHO classification criteria. RESULTS: The prevalence of physical inactivity was significantly higher in 2012 (19.4%, 95% CI: 18.1, 20.7) than in 2006 (13.4%, 95% CI: 12.5, 14.5). Adults in the obese category, 60-69 age group, and those in the highest socioeconomic status tertile were more likely to be physically inactive. CONCLUSIONS: The proportion of the Mexican adult population who do not meet the minimum WHO physical activity criteria has increased by 6% points between 2006 and 2012. Given the increasing prevalence of obesity, the aging of the population, and the shift in socioeconomic status in Mexico, physical inactivity could continue to increase in the coming years unless effective public health interventions are implemented.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".