Obesity, the Obesity Epidemic, and Metabolic Dysfunction: The Conundrum Presented by the Disconnect between Evolution and Modern Societies
Bibliographic record
Abstract
Currently, there is an obesity epidemic in the developed world, with both adults and children being affected. The consequences of this epidemic on health and health outcomes have impact at multiple levels, and it is increasing. The basis for this epidemic, which appears to have emerged with significance ~40 - 50 years ago, is unknown but is believed by many to have much of its basis in poor diets and inactivity/sedentary behaviour. Analysis of the human genome has revealed >100 loci which exhibit risk for development of obesity. Why there are so many loci, and how they benefited humans evolutionarily are unknown. In spite of these limitations, there are urgent needs for effective short-term interventions to assist those with obesity, as well as longer-term needs to effectively prevent development of obesity. For the former, personalized exercise programs, use of prebiotics, optimal nutrition and surgical interventions can be effective for some individuals but more interventions that address cause are also needed. For longer term solutions more detailed genetic and epigenetic understanding of risk will be required. An attractive speculation is that the genomic risk factors for obesity (>100 identified) have been retained evolutionarily to address acute metabolic needs and current conditions have converted such risks to a chronic state, making reversal more difficult and with more consequences, including possible epigenetic modifications of risk genes. Other contributing factors to chronic obesity could also relate to chemical disruptors in the environment over the past 50+ years which may impact metabolic regulation via the established risk genomic risk factors or new variants. Therefore, to effectively control this high impact epidemic of obesity likely requires a more detailed genetic and epigenetic analysis of families with obesity and analysis of isolated populations, as well as a more thorough investigation of chemicals capable of being metabolic disruptors in this regard. Thus, the long-term solution(s) to the obesity epidemic will require a concerted multidisciplinary approach that may be more complex than just becoming more active and avoiding sedentary behavior.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".