A Prospective Cohort Study of Seasonal Variation in Spontaneous Abortion
Bibliographic record
Abstract
BACKGROUND: Up to 30% of pregnancies end in spontaneous abortion, yet few risk factors have been identified. Examining seasonal patterns in risk of spontaneous abortion can generate new hypotheses regarding environmental and lifestyle determinants. METHODS: We used data from Pregnancy Study Online-a preconception cohort study of pregnancy planners from the United States and Canada-to examine seasonal variation in spontaneous abortion risk. We enrolled 12,197 women during 2013 to 2020, 6104 of whom reported a conception within 12 months of enrollment. On follow-up questionnaires, participants reported date of spontaneous abortion and weeks gestation at time of loss. We used periodic regression to estimate two aspects of seasonal occurrence: peak/low ratio-a measure of intensity of seasonal variation-and peak timing. We examined season at risk (from the date of each gestational week) in relation to spontaneous abortion; in a secondary analysis, we examined season of conception in relation to spontaneous abortion. We controlled for seasonal patterns in attempt initiation via month the pregnancy attempt began. RESULTS: Almost 20% of women experienced spontaneous abortion. Risk was highest in late August, with a peak/low ratio of 1.3 (95% confidence interval [CI] = 1.1, 1.6). This seasonal pattern was evident almost exclusively for spontaneous abortion at <8 weeks since the last menstrual period date (peak/low ratio = 1.4; 95% CI = 1.2, 1.8), and associations were stronger among women living in the Southern and Midwestern United States. CONCLUSIONS: Environmental or lifestyle factors more prevalent in late summer may be associated with increased risk of early spontaneous abortion.
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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 | 0.003 | 0.002 |
| 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".