CHILDHOOD OBESITY PREVENTION INTERVENTION AND POLICY IN THE MEXICAN SCHOOL SYSTEM
Bibliographic record
Abstract
Overweight and obesity in Mexican children substantiates the need to identify effective strategies and policies to address this problem.Instituto Nacional de Salud Publica (INSP) designed and implemented a randomized control trial (RCT) to assess an ecologically-based intervention program to modify the school environment to promote healthy lifestyle behaviours in children.The objectives of this thesis are to describe the design and impact of this RCT, to examine the program content through an ecological approach, and to examine policy activities that have been informed by the RCT findings.Four manuscripts address these objectives.Manuscript one is Promoting a Healthful Diet and Physical Activity in the MexicanSchool System for the Prevention of Obesity in Children: Rationale, Design and Methods.It describes the rationale, design, and methods of the two-year INSP-Secretaria de Educacion Publica (Secretary of Public Education, SEP) RCT.Manuscript two is Impact of a School-based Intervention Program on Obesity Risk Factors in Mexican Children.It reports on the environmental impact of the INSP-SEP intervention by comparing 16 intervention schools with 11 non-intervention schools.Results showed increased availability and food intake of healthy foods with a concomitant decrease in unhealthy food availability in intervention schools/children.Manuscript three is An Ecological and Theoretical Deconstruction of a School-based Obesity Prevention Program in Mexico.It reports on an assessment of the integration of ecological principles and theoretical constructs in the school-based behavioural change/obesity prevention intervention carried out by the INSP-SEP.Results showed that 32 intervention strategies were implemented in the school setting to engage target-groups; the most used SCT construct was Reciprocal Determinism.Manuscript four is titled Quality and Implementation of the Nutrition and Physical Activity School Policy Guidelines in Mexico City.It assesses the quality and implementation conditions of a policy and reports on the implementation and the uptake of the national school policy to prevent obesity in Mexico city through a policy analysis, WHO School Policy Framework (SPF)and indicators informed by the national policy.Findings showed that not all of the 10 iii implementation pre-conditions were met; School Guidelines mostly complied with SPF but were not fully implemented within our sample.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".