Bisphenol A and indicators of obesity, glucose metabolism/type 2 diabetes and cardiovascular disease: A systematic review of epidemiologic research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Bisphenol A (BPA), a high-volume chemical with weak estrogenic properties, has been linked to obesity, cardiovascular diseases (CVD) and diabetes mellitus (DM). This review evaluates both the consistency and the quality of epidemiological evidence from studies testing the hypothesis that BPA exposure is a risk factor for these health outcomes. METHODS: We followed the current methodological guidelines for systematic reviews by using two independent researchers to identify, review and summarize the relevant epidemiological literature on the relation of BPA to obesity, CVD, DM, or related biomarkers. Each paper was summarized with respect to its methods and results with particular attention to study design and exposure assessment, which have been cited as the main areas of weakness in BPA epidemiologic research. As quantitative meta-analysis was not feasible, the study results were categorized qualitatively as positive, inverse, null, or mixed. RESULTS: Nearly all studies on BPA and obesity-, DM- or CVD-related health outcomes used a cross-sectional design and relied on a single measure of BPA exposure, which may result in serious exposure misclassification. For all outcomes, results across studies were inconsistent. Although several studies used the same data and the same or similar statistical methods, when the methods varied slightly, even studies that used the same data produced different results. CONCLUSION: Epidemiological study design issues severely limit our understanding of health effects associated with BPA exposure. Considering the methodological limitations of the existing body of epidemiology literature, assertions about a causal link between BPA and obesity, DM, or CVD are unsubstantiated.
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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 | 0.014 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 | 0.000 |
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 it