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Record W4409534702 · doi:10.1093/humrep/deaf067

Racial and ethnic disparities in fecundability: a North American preconception cohort study

2025· article· en· W4409534702 on OpenAlexaffabout
Lauren A. Wise, Molly N. Hoffman, Sharonda M. Lovett, Ruth J. Geller, Nina L. Schrager, Ugochinyere Vivian Ukah, Amelia K. Wesselink, Jasmine A. Abrams, Renée Boynton‐Jarrett, Wendy Kuohung, Andrea S. Kuriyama, Matthew O. Hunt, David R. Williams, Collette N. Ncube

Bibliographic record

VenueHuman Reproduction · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsMcGill University
FundersPrecursory Research for Embryonic Science and TechnologyNational Institute on Minority Health and Health DisparitiesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBill and Melinda Gates Foundation
KeywordsDemographyFertilityEthnic groupMedicineNational Survey of Family GrowthPregnancyInfertilityCohortCohort studyProspective cohort studyGynecologyPopulationEnvironmental healthFamily planningPolitical scienceInternal medicineBiology

Abstract

fetched live from OpenAlex

STUDY QUESTION: To what extent are there racial and ethnic disparities in fecundability in North America? SUMMARY ANSWER: In a North American preconception cohort study, we observed large differences in fecundability across racial and ethnic groups. WHAT IS KNOWN ALREADY: Several studies in the United States (USA) have shown that Black women tend to wait longer for fertility treatment and are less likely to seek medical care for infertility than White women. Among those who seek infertility treatment, there are large racial disparities in access to treatment and treatment success rates. However, research has been limited and conflicting on the extent to which fertility measures such as fecundability (per-cycle probability of conception) vary by race and ethnicity. STUDY DESIGN, SIZE, DURATION: We examined the associations of race and ethnicity with fecundability in Pregnancy Study Online (PRESTO), a prospective preconception cohort study of US and Canadian residents aged 21-45 years who were actively trying to conceive without the use of fertility treatment at enrollment (2013-2024). We restricted the analysis to 18 573 participants with fewer than 12 cycles of pregnancy attempt time at enrollment. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants self-reported data on race and ethnicity on a baseline questionnaire and completed bimonthly follow-up questionnaires for up to 12 months to update data on pregnancy status. We estimated fecundability ratios (FRs) and 95% confidence intervals (CI) using proportional probabilities regression models. We stratified by pregnancy attempt time at enrollment, reproductive history, country of residence, age, and educational attainment. In sensitivity analyses, we applied inverse probability of continuation weights to account for differential loss-to-follow-up. We also calculated the cumulative incidence of infertility during 12 cycles of attempt time by race and ethnicity using life-table methods to account for censoring. MAIN RESULTS AND THE ROLE OF CHANCE: Compared with non-Hispanic White participants, fecundability was appreciably lower among participants who identified as non-Hispanic Black (FR = 0.60, 95% CI: 0.52-0.70), non-Hispanic American Indian/Alaskan Native/Indigenous (FR = 0.70, 95% CI: 0.44-1.11), non-Hispanic multiracial (FR = 0.89, 95% CI: 0.81-0.99), or Hispanic other/unknown race (FR = 0.77, 95% CI: 0.65-0.90). Results were similar when we performed various sensitivity analyses including: application of inverse probability of continuation weights to account for differential loss-to-follow-up; stratification by age and educational attainment; and restriction of analyses to (i) participants with <3 cycles of pregnancy attempt time at enrollment, (ii) nulligravid participants without an infertility history, and (iii) US residents. The 12-cycle cumulative incidence of infertility (i.e. clinical definition) among participants with <2 cycles of attempt time at entry also differed meaningfully by race and ethnicity (33.2% among non-Hispanic Black participants and 29.7% among Hispanic other/unknown race participants vs 16.4% among non-Hispanic White participants). LIMITATIONS, REASONS FOR CAUTION: Due to limited numbers, we grouped participants into broad racial and ethnic groups within which there is considerable heterogeneity. Such groupings will obscure any differences in fecundability that exist between subgroups. Differential loss-to-follow-up was an important source of selection bias, though findings did not vary appreciably when we applied inverse probability of continuation weights. PRESTO is an internet-based convenience sample of pregnancy planners of higher-than-average socioeconomic status and is, therefore, not representative of all individuals who conceive, which may limit generalizability. WIDER IMPLICATIONS OF THE FINDINGS: These descriptive data indicate the strong need for additional studies to carefully measure and better understand the mechanisms underlying disparities in fecundability, including the effects of structural racism and discrimination, as well as programs and policies to advance reproductive health equity. As more research is conducted on the drivers of these disparities, greater efforts should be made to increase fertility awareness, enhance preconception health, expand access to fertility treatments, and improve patient care among underserved populations to reduce the burden of subfertility among those affected. STUDY FUNDING/COMPETING INTEREST(S): This work was funded by the Eunice Kennedy Shriver National Institute for Child Health and Human Development (R01-HD086742; T32-HD052458) and the National Institute on Minority Health and Health Disparities (K01-MD013911). In the past three years, L.A.W. served as a consultant for AbbVie, Inc. and the Gates Foundation. She was also a member of the steering committee for AbbVie on Abnormal Uterine Bleeding and Fibroids, where payments were made to Dr Wise. Her study, PRESTO, received in-kind donations from Kindara.com (fertility apps) and Swiss Precision Diagnostics (home pregnancy tests). C.N. received payments to her institution from the National Institute on Minority Health and Health Disparities K01-MD013911. The other authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.036
GPT teacher head0.378
Teacher spread0.342 · 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".

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Citations5
Published2025
Admission routes2
Has abstractyes

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