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Obesity, Twin Pregnancy, and the Role of Assisted Reproductive Technology

2024· article· en· W4390778591 on OpenAlexafffundabout
Jeffrey N. Bone, K.S. Joseph, Laura A. Magee, Li Qing Wang, Sid John, Mohamed A. Bedaiwy, Chantal Mayer, Sarka Lisonkova

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsBC Children's HospitalChildren's & Women's Health Centre of British ColumbiaUniversity of British Columbia
FundersSick Kids FoundationBC Children's Hospital
KeywordsMedicineBody mass indexPregnancyOverweightObstetricsObesityGestationTwin PregnancyPopulationBirth weightCohort studyDemographyLive birthAssisted reproductive technologyGestational ageReproductive medicineGynecologyEnvironmental healthInternal medicineInfertility

Abstract

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Importance: The prevalence of overweight and obesity (body mass index [BMI] ≥25) has increased globally, and high BMI has been linked to higher rates of twin birth. However, evidence from large population-based studies is lacking; the issue needs careful study, as women with obesity are also more likely to use assisted reproductive technology (ART), which frequently results in twin pregnancy. Objective: To examine the association between BMI and twin birth and the role of ART as a potential mediator in this association. Design, Setting, and Participants: This retrospective cohort study included all live births and stillbirths with gestational age of 20 weeks or longer in British Columbia, Canada, from 2008 to 2020, using data from the British Columbia Perinatal Database Registry. Data analysis was conducted from November 2022 to June 2023. Exposures: Prepregnancy BMI, calculated as weight in kilograms divided by height in meters squared, and use of ART. Main Outcomes and Measures: The study assessed whether prepregnancy BMI is associated with the rate of twin vs singleton delivery and whether this association is explained by the differential use of ART in women with obesity. Results: A total of 524 845 deliveries at 20 weeks' or longer gestation occurred in British Columbia during the study period, and 392 046 women had complete data on prepregnancy BMI. The median (IQR) age was 31.4 (27.7-35.0) years, approximately half were nulliparous (243 443 [46.4%]) and less than 10% smoked during pregnancy (36 894 [7.1%]). Overall, 8295 women had a twin delivery (15.8 per 1000 deliveries), and rates per 1000 deliveries by prepregnancy BMI categories were 11.9 (underweight), 15.1 (normal), 16.0 (overweight), 16.0 (obesity class I), 16.7 (obesity class II), and 18.9 (obesity class III). After adjustment for other covariates, women with underweight had relatively 16% fewer twins compared with women with normal BMI (adjusted risk ratio [aRR], 0.84; 95% CI, 0.74-0.95), while women with overweight, class I obesity, class II obesity, and class III obesity had 14% (aRR, 1.14; 95% CI, 1.07-1.21), 16% (aRR, 1.16; 95% CI, 1.06-1.27), 17% (aRR, 1.17; 95% CI, 1.02-1.34), and 41% higher rates (aRR, 1.41; 95% CI, 1.19-1.66), respectively. The proportion of women who conceived by ART increased with increasing BMI, and ART was associated with nearly a 12-fold higher rate of twin delivery (aRR, 11.80; 95% CI 11.10-12.54). ART explained about a quarter of the association between obesity class I and II and twin delivery (eg, obesity class I, 23% mediated; 95% CI, 7%-39% mediated), but none of this association was mediated by ART in women with class III obesity. Conclusions and relevance: In this cohort study of 524 845 births, the rate of twin birth increased with increasing prepregnancy BMI. In women with a BMI between 30 and 40, approximately one-quarter of this association was explained by higher use of ART; however, there was no evidence of such mediation in women with BMI of 40 or greater.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.299
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2024
Admission routes3
Has abstractyes

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