Contraceptive Options and Their Associated Estrogenic Environmental Loads: Relationships and Trade-Offs
Bibliographic record
Abstract
This work explores the relationships between a user's choice of a given contraceptive option and the load of steroidal estrogens that can be associated with that choice. Family planning data for the USA served as a basis for the analysis. The results showed that collectively the use of contraception in the USA conservatively averts the release of approximately 4.8 tonnes of estradiol equivalents to the environment. 35% of the estrogenic load released over the course of all experienced pregnancies events and 34% the estrogenic load represented by all resultant legacies are a result of contraception failure and the non-use of contraception. A scenario analysis conducted to explore the impacts of discontinuing the use of ethinylestradiol-based oral contraceptives revealed that this would not only result in a 1.7-fold increase in the estrogenic loading of the users, but the users would also be expected to experience undesired family planning outcomes at a rate that is 3.3 times higher. Additional scenario analyses in which ethinylestradiol-based oral contraceptive users were modeled as having switched entirely to the use of male condoms, diaphragms or copper IUDs suggested that whether a higher or lower estrogenic load can be associated with the switching population depends on the typical failure rates of the options adopted following discontinuation. And, finally, it was estimated that, in the USA, at most 13% of the annual estrogenic load can be averted by fully meeting the contraceptive needs of the population. Therefore, while the issue of estrogen impacts on the environment cannot be addressed solely by meeting the population's contraceptive needs, a significant fraction of the estrogenic mass released to environment can be averted by improving the level with which their contraceptive needs are met.
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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".