Does the sex of one’s co-twin affect height and BMI in adulthood? A study of dizygotic adult twins from 31 cohorts
Bibliographic record
Abstract
BACKGROUND: The comparison of traits in twins from opposite-sex (OS) and same-sex (SS) dizygotic twin pairs is considered a proxy measure of prenatal hormone exposure. To examine possible prenatal hormonal influences on anthropometric traits, we compared mean height, body mass index (BMI), and the prevalence of being overweight or obese between men and women from OS and SS dizygotic twin pairs. METHODS: The data were derived from the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) database, and included 68,494 SS and 53,808 OS dizygotic twin individuals above the age of 20 years from 31 twin cohorts representing 19 countries. Zygosity was determined by questionnaires or DNA genotyping depending on the study. Multiple regression and logistic regression models adjusted for cohort, age, and birth year with the twin type as a predictor were carried out to compare height and BMI in twins from OS pairs with those from SS pairs and to calculate the adjusted odds ratios and 95% confidence intervals for being overweight or obese. RESULTS: OS females were, on average, 0.31 cm (95% confidence interval (CI) 0.20, 0.41) taller than SS females. OS males were also, on average, taller than SS males, but this difference was only 0.14 cm (95% CI 0.02, 0.27). Mean BMI and the prevalence of overweight or obesity did not differ between males and females from SS and OS twin pairs. The statistically significant differences between OS and SS twins for height were small and appeared to reflect our large sample size rather than meaningful differences of public health relevance. CONCLUSIONS: We found no evidence to support the hypothesis that prenatal hormonal exposure or postnatal socialization (i.e., having grown up with a twin of the opposite sex) has a major impact on height and BMI in adulthood.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".