Nutritional Challenges of Incretin-Based Obesity Management Medications: Implications for Clinical Practice
Bibliographic record
Abstract
Several novel incretin-based obesity management medications (OMMs) have recently been approved for chronic weight management in adults with obesity or overweight. These agents have demonstrated substantial weight reduction effects alongside glucoregulatory and cardioprotective benefits. However, the use of incretin-based OMMs presents nutritional challenges that remain insufficiently addressed. These include side effects such as gastrointestinal disturbances and loss of lean body mass, which may compromise nutritional status, reduce energy expenditure, and heighten risk of rebound weight gain, sarcopenia, and frailty. Moreover, although these medications effectively suppress energy intake and reduce food quantity, they may also have unintended effects on diet quality, potentially influencing macronutrient distribution, ultraprocessed food consumption, risk of vitamin and mineral deficiencies, and disordered eating behaviors, which could undermine long-term weight maintenance and the cardiometabolic benefits achieved through these pharmacotherapy agents. Emerging evidence suggests that specific dietary and behavioral strategies, such as higher protein intake, resistance training, nutrient-dense eating patterns, and fostering adaptive eating behaviors, may help mitigate nutritional challenges and physiologic deterioration during significant weight reduction while also supporting cardiometabolic health maintenance. However, the application of these strategies as adjunct treatments alongside the new OMMs remains unclear. This narrative review summarizes the current literature on these issues and proposes dietary interventions and behavioral modification strategies aimed at mitigating the adverse effects that can be associated with incretin-based OMMs. These considerations are increasingly important given the expanding use of these medications, the degree of weight reduction they induce, and the implications for specific at-risk groups, including aging populations prone to muscle and functional decline and individuals with pre-existing conditions of nutritional deficiencies, chronic diseases, and disordered eating patterns.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".