Factors Associated with Maternal Serum Levels of Perfluoroalkyl Substances and Organochlorines: A Descriptive Study of Parous Women in Norway and Sweden
Bibliographic record
Abstract
INTRODUCTION: Perfluoroalkyl substances (PFASs) and organochlorines (OCs) are ubiquitous and persistent in the environment and proposed endocrine disrupting chemicals (EDCs). They can be transferred across the placenta during pregnancy, and studies suggest that the prenatal period may be particularly sensitive for influences on fetal growth and development. Several studies have investigated socio-demographic and pregnancy related factors associated with maternal serum PFAS and OC levels, but few studies have been conducted in time periods with increasing emissions of PFASs and recent emissions of OCs. METHODS: Serum from 424 pregnant women participating in the NICHD Scandinavian Successive Small-for-gestational Age (SGA) births study was collected in 1986-1988, and analyses of two PFASs and six OCs were conducted. Associations between EDCs and geographic, time dependent, socio-demographic and pregnancy related variables were evaluated by using multivariable linear regression models. RESULTS: Previous breastfeeding duration, time since last breastfeeding period, sampling date and country of residence were important factors associated with serum levels of PFOS and PFOA. Smoking status and pre-pregnancy BMI were negatively associated with PFOS, and maternal height was borderline negatively associated with PFOS and PFOA. Glomerular filtration rate (GFR) was negatively associated with PFOS in a sub-sample. Maternal serum levels of OCs were positively associated with maternal age, and negatively associated with previous breastfeeding duration and sampling date. Smoking had a consistently negative association with PCB 118 in a dose-dependent manner. Education level, pre-pregnancy BMI and alcohol consumption varied in importance according to the compound under study. CONCLUSIONS: Several maternal factors, including potentially modifiable factors, markers of pregnancy physiology and factors also related to perinatal outcomes were associated with EDC levels. Results from this study are relevant to populations with still high PFAS and OC levels, i.e. developing countries. Moreover, we can use this knowledge about associated factors on emerging EDCs with similar properties.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".