Evidence map›Paper›PMID 39348340›Full record

ArticleHuman reproduction (Oxford, England)2024

Measuring non-events: infertility estimation using cross-sectional, population-based data from four countries in sub-Saharan Africa.

Suzanne O Bell, Caroline Moreau, Dana Sarnak, Simon P S Kibira, Philip Anglewicz, Peter Gichangi, Alexander C McLain, Marie Thoma

Abstract read
In one paragraph

Article in Human reproduction (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Suzanne O BellDepartment of Population Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-7650-5940
Caroline MoreauDepartment of Population Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-8637-6249
Dana SarnakDepartment of Population Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Simon P S KibiraDepartment of Community Health and Behavioral Sciences, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.
Philip AnglewiczDepartment of Population Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Peter GichangiDepartment of Public Health, Technical University of Mombasa, Mombasa, Kenya.
Alexander C McLainDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA.ORCID 0000-0002-5475-0670
Marie ThomaDepartment of Family Science, University of Maryland, College Park, MD, USA.

Funding

Sci-Tech Core-Maryland Population Research CenterP2CHD041041 · NICHD · UNIV OF MARYLAND, COLLEGE PARK · PI Susan W Parker · 2018 to 2026
$3.9M
Advancing Understanding and Measurement of Infertility, Related Fears and Stigma, and Associated Consequences in Low-Resource CountriesK01HD107172 · NICHD · JOHNS HOPKINS UNIVERSITY · PI Suzanne O'Dea Bell · 2022 to 2026
$702k
Gates Foundation INV-009639Gates Foundation INV009639National Institute of Child Health and Human Development K01HD107172NICHD NIH HHS K01 HD107172NICHD NIH HHS L60 HD113077NICHD NIH HHS P2C HD041041
6 · The paper itself

Abstract

study questionDoes the prevalence of 12-month infertility in Burkina Faso, Côte d'Ivoire, Kenya, and Uganda differ between women trying to conceive and the broader population of women exposed to unprotected sex, and how are prevalence estimates affected by model assumptions and adjustments? SUMMARY ANSWER: Estimates of 12-month infertility among tryers ranged from 8% in Burkina Faso to 30% in Côte d'Ivoire, increasing substantially among a larger population of women exposed to unprotected intercourse. WHAT IS KNOWN ALREADY: While having a child is a fundamental human experience, the extent to which women and couples experience infertility is a neglected area of research, particularly in sub-Saharan Africa. Existing estimates of infertility in this region vary widely from 2% to 32%, however, potential impacts of variability in study populations and model assumptions have not been well-examined. STUDY DESIGN, SIZE, DURATION: We used cross-sectional nationally representative survey data from Burkina Faso, Côte d'Ivoire, Kenya, and Uganda. We employed a multi-stage cluster random sampling design with probability proportional to the size selection of clusters within each country to produce representative samples of women aged 15-49. Samples ranged from 3864 in Côte d'Ivoire to 9489 in Kenya. PARTICIPANTS/MATERIALS, SETTING,

methodsWe created two analytic samples in each country-tryers and a broader sample of women exposed to unprotected sex-exploring differences in population characteristics and estimating the period prevalence of 12-month infertility using the current duration (CD) approach. We also examined the impact of several model assumptions within each of the two analytic samples, including adjustments for recent injectable contraceptive use, unrecognized pregnancy, infertility treatment, underreported contraceptive use, and sexual activity. MAIN RESULTS AND THE ROLE OF CHANCE: Employing the CD approach among tryers produced an overall 12-month infertility prevalence of 7.9% (95% CI 6.6-12.7) in Burkina Faso, 29.6% (95% CI 15.3-100.0) in Côte d'Ivoire, 24.5% (95% CI 16.5-34.6) in Kenya, and 14.7% (95% CI 8.1-22.4) in Uganda. Results among women exposed to unprotected intercourse indicated much higher levels of infertility, ranging from 22.4% (95% CI 18.6-30.8) in Uganda to 63.7% (95% CI 48.8-87.9) in Côte d'Ivoire. Sensitivity analyses suggest infertility estimates are particularly sensitive to adjustments around pregnancy recognition timing and sexual activity, with little impact of adjustments for recent injectable contraceptive use, infertility treatment, and underreporting of traditional and coital dependent contraceptive use. LIMITATIONS, REASONS FOR CAUTION: There was substantial digit preference in responses at 12 months, particularly among the tryers, which could introduce bias. Data quality concerns in the reproductive calendar may impact the accuracy of the CD approach among the broader sample of women exposed to unprotected sex, particularly with regard to underreported contraceptive use, induced and spontaneous abortions, and unrecognized pregnancies. Lastly, we lacked information on postpartum amenorrhea or abstinence. WIDER IMPLICATIONS OF THE

findingsUnderstanding the inconsistencies in definition and analytic approach and their implications for infertility estimation is important for reliably monitoring population-level infertility trends, identifying factors influencing infertility, improving prevention programs, and ensuring access to quality treatment and services. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by grants from the Bill & Melinda Gates Foundation (INV009639) and the National Institute of Child Health and Human Development (K01HD107172). The funders were not involved in the study design, analyses, manuscript writing, or the decision to publish. The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Indexed as

Infertility, FemaleAdolescentAdultAfrica South of the SaharaBurkina FasoCote d'IvoireCross-Sectional StudiesFemaleHumansInfertilityKenyaPrevalenceUgandaYoung Adultcurrent duration approachinfertilitymeasurementsub-Saharan Africasurvey research

Identifiers

PMID39348340
PMCPMC11629970

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.