Associations between Parabens and Measures of Metabolic Syndrome in the General Canadian Population
Bibliographic record
Abstract
Background: Metabolic syndrome (MetS) is a cluster of risk factors which increases the risk of developing several chronic diseases. It is defined as having any three of the following risk factors: abdominal obesity, elevated triglycerides, reduced high-density lipoprotein cholesterol, hypertension, and elevated fasting glucose. Parabens are preservative agents used ubiquitously in cosmetic and personal care products that may increase the risk of MetS due to their endocrine-disrupting properties. We examined if exposure to parabens was associated with MetS or component risk factors in the Canadian general population.Methods: Methyl, ethyl, propyl, and butyl paraben were measured in the urine of participants (n=2564, age 3-79) in Cycle 4 (2014 – 2015) of the Canadian Health Measures Survey (CHMS), a nationally representative biomonitoring survey in Canada. Linear and logistic regression were performed to investigate associations between each individual paraben and MetS, MetS components and related anthropometric measures, adjusted for age, sex, and household income.Results: Due to a high proportion of non-detectable measures for ethyl and butyl paraben (65% and 83%, respectively), only results for methyl and propyl paraben are reported here. Detection rates were high (92% and 79%) and geometric means were 17 ug/L and 2.5 ug/L for methyl and propyl paraben, respectively. Overall, parabens were associated with slightly decreased odds of MetS, and individual MetS components were generally inversely associated with paraben concentrations. However, among children and adolescents (age <18 years), parabens tended to be associated with higher BMI, though not statistically significant.Conclusions: In this cross-sectional analysis, there was little evidence that parabens are associated with MetS. Results considering paraben mixtures and interaction with triclosan will also be presented.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".