Do phthalates act as obesogens in humans? A systematic review of the epidemiological literature
Bibliographic record
Abstract
INTRODUCTION: Phthalates, a class of commonly used compounds with widespread human exposure, have been described as obesogens, or chemicals that disrupt lipid metabolism and produce metabolic changes leading to increased risk of type 2 diabetes mellitus (DM) and cardiovascular disease (CVD). This communication provides a systematic review of the available epidemiologic evidence on associations between phthalate ester metabolites in urine or blood and various health endpoints related to overweight/obesity, DM or CVD. METHODS: We followed the current methodological guidelines for systematic reviews to identify, retrieve and summarize the relevant epidemiological literature on the relation between phthalates and overweight/obesity, DM, CVD or related biomarkers. Each eligible paper was summarized with respect to methods and results with particular attention to study design and exposure assessment. As quantitative meta-analysis was not feasible, the study results were assessed qualitatively for inter- and intra-study consistency. RESULTS: We identified 26 publications of epidemiologic studies that assessed associations between either urinary or serum phthalate metabolites and outcomes of interest. These studies represented 18 independent data sources. We found no inter- or intra-study consistency for any phthalate metabolite for any of the indicators of overweight/obesity, DM or CVD in children or adults. Most reported associations were not statistically significantly different from the null, some were positive, and others were inverse. All studies except two used cross-sectional analyses and for this reason could not be used to test causal hypotheses. CONCLUSION: The current epidemiological data do not support or refute the hypothesis that phthalates act as obesogens in humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".