Lauren A Wise, Molly N Hoffman, Sharonda M Lovett, Ruth J Geller, Nina L Schrager, Ugochinyere Vivian Ukah, Amelia K Wesselink, Jasmine A Abrams, Renee Boynton-Jarrett, Wendy Kuohung, Andrea S Kuriyama, Matthew O Hunt, David R Williams, Collette N Ncube
{"title":"Racial and ethnic disparities in fecundability: a North American preconception cohort study","authors":"Lauren A Wise, Molly N Hoffman, Sharonda M Lovett, Ruth J Geller, Nina L Schrager, Ugochinyere Vivian Ukah, Amelia K Wesselink, Jasmine A Abrams, Renee Boynton-Jarrett, Wendy Kuohung, Andrea S Kuriyama, Matthew O Hunt, David R Williams, Collette N Ncube","doi":"10.1093/humrep/deaf067","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":13003,"journal":{"name":"Human reproduction","volume":"29 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human reproduction","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/humrep/deaf067","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Human Reproduction features full-length, peer-reviewed papers reporting original research, concise clinical case reports, as well as opinions and debates on topical issues.
Papers published cover the clinical science and medical aspects of reproductive physiology, pathology and endocrinology; including andrology, gonad function, gametogenesis, fertilization, embryo development, implantation, early pregnancy, genetics, genetic diagnosis, oncology, infectious disease, surgery, contraception, infertility treatment, psychology, ethics and social issues.