Diet and acne: A systematic review
Bibliographic record
Abstract
Background: Acne vulgaris is a common cutaneous disorder. Diet and metabolism, specifically glycemic content and dairy, influence hormones such as insulin, insulin-like growth factor 1, and androgens, which affect acnegenesis. Objective: To systematically review high-quality evidence regarding the association of dietary glycemic and dairy intake with acnegenesis. Methods: A comprehensive literature search, without timeline restriction, of MEDLINE (completed between October and November 2021) for English-language papers that examined the association between diet and acne was conducted. The evidence quality was assessed using the Ottawa quality assessment scale. Results: The literature search yielded 410 articles, of which 34 articles met the inclusion criteria. The literature on whether dairy product intake is associated with acnegenesis is mixed and may be dependent on sex, ethnicity, and cultural dietary habits. High glycemic index and increased daily glycemic load intake were positively associated with acnegenesis and acne severity, an observation supported by randomized controlled trials. Conclusion: High glycemic index, increased glycemic load, and carbohydrate intake have a modest yet significant proacnegenic effect. Increased dairy consumption may have been proacnegenic in select populations, such as those in which a Western diet is prevalent. The impact of diet on acnegenesis is likely dependent on sex and ethnicity. Further randomized trials are necessary to fully characterize the potential associations.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".