A Proposed Strategy against Obesity: How Government Policy Can Counter the Obesogenic Environment
Bibliographic record
Abstract
An epidemic of obesity emerged in the USA in 1976-1980. The epidemic then spread to many other Westernized nations. Many interventions have been carried out with the goal of lowering the prevalence of obesity. These have mostly taken the form of various types of health promotion (i.e., providing people with education, advice, and encouragement). These actions have achieved, at most, only limited success. A strategy with a better chance of success starts with the recognition that the fundamental cause of obesity is that we live in an obesogenic environment. It is therefore necessary to change the environment so that it fosters a generally healthy lifestyle, thereby leading to enhanced health for the population, including improved weight control. A major goal is to increase the intake of healthy foods (especially fruit, vegetables, and whole grains), while decreasing intake of unhealthy foods (especially ultra-processed foods such as sugar). This will require major changes of many government policies. Some of the required policies are as follows. Schools should implement policies that create a healthy environment for children. For example, they should adopt a policy that only foods of high nutritional quality are sold in vending machines or given to students within school meals. Policies need to go well beyond the school setting; a broad strategy is needed that creates a healthy environment for children. Another important policy is the manipulation of food prices in order to shift the diet toward healthy foods. This requires using subsidies to lower the price of healthy foods, while adding a tax to less healthy foods to increase the price. This policy has been implemented in many cities and countries in the form of a tax on sugar-sweetened beverages (SSBs). The advertising of unhealthy foods (including fast-food restaurants) should be banned, especially where children and adolescents are the major target. Such a ban could be extended to a complete ban on all advertising for unhealthy foods, including that directed at adults. The proposed policy measures are likely to be strongly opposed by food corporations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".