Evidence map›Paper›PMID 36804033›Full record

ArticleBMC women's health2023

Menstrual regulation: examining the incidence, methods, and sources of care of this understudied health practice in three settings using cross-sectional population-based surveys.

Suzanne O Bell, Mridula Shankar, Funmilola OlaOlorun, Elizabeth Omoluabi, Anoop Khanna, Danish Ahmad, Georges Guiella, Caroline Moreau

Open access · goldAbstract read
In one paragraph

Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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 at 6 institutions in 6 countries.

Suzanne O BellDepartment of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University, 615 N. Wolfe St. Suite W4041, Baltimore, MD, 21205, USA. suzannebell@jhu.edu.
Mridula ShankarDepartment of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University, 615 N. Wolfe St. Suite W4041, Baltimore, MD, 21205, USA.
Funmilola OlaOlorunCollege of Medicine, University of Ibadan, Ibadan, Nigeria.
Elizabeth OmoluabiCenter for Research, Evaluation Resources and Development, Ile-Ife, Nigeria.
Anoop KhannaIndian Institute of Health Management Research, Jaipur, India.
Danish AhmadIndian Institute of Health Management Research, Jaipur, India.
Georges GuiellaInstitut Supérieur Des Sciences de La Population (ISSP), Université of Ouagadougou, Ouagadougou, Burkina Faso.
Caroline MoreauDepartment of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University, 615 N. Wolfe St. Suite W4041, Baltimore, MD, 21205, USA.
IIHMR University · INJohns Hopkins University · USDevelopment Research and Projects Centre · NGInserm · FRInstitut Superieur Des Sciences De La Population · BFUniversity of Ibadan · NG

Funding

Anonymous Donor 127941Bill & Melinda Gates Foundation OPP10709004FIC NIH HHS L60 TW012222
6 · The paper itself

Abstract

backgroundMenstrual regulation is a practice that may exist within the ambiguity surrounding one's pregnancy status and has been the subject of limited research. The aim of this study is to measure the annual rate of menstrual regulation in Nigeria, Cote d'Ivoire, and Rajasthan, India, overall and by background characteristics and to describe the methods and sources women use to bring back their period.

methodsData come from population-based surveys of women aged 15-49 in each setting. In addition to questions on women's background characteristics, reproductive history, and contraceptive experiences, interviewers asked women whether they had ever done something to bring back their period at a time when they were worried they were pregnant, and if so, when it occurred and what methods and source they used. A total of 11,106 reproductive-aged women completed the survey in Nigeria, 2,738 in Cote d'Ivoire, and 5,832 in Rajasthan. We calculated one-year incidence of menstrual regulation overall and by women's background characteristics separately for each context using adjusted Wald tests to assess significant. We then examined the distribution of menstrual regulation methods and sources using univariate analyses. Method categories included surgery, medication abortion pills, other pills (including unknown pills), and traditional or "other" methods. Source categories included public facilities or public mobile outreach, private or non-governmental facilities or doctors, pharmacy or chemist shops, and traditional or "other" sources.

resultsResults indicate substantial levels of menstrual regulation in West Africa with a one-year incidence rate of 22.6 per 1,000 women age 15-49 in Nigeria and 20.6 per 1,000 in Cote d'Ivoire; women in Rajasthan reported only 3.3 per 1,000. Menstrual regulations primarily involved traditional or "other" methods in Nigeria (47.8%), Cote d'Ivoire (70.0%), and Rajasthan (37.6%) and traditional or "other" sources (49.4%, 77.2%, and 40.1%, respectively).

conclusionThese findings suggest menstrual regulation is not uncommon in these settings and may put women's health at risk given the reported methods and sources used. Results have implications for abortion research and our understanding of how women manage their fertility.

Indexed as

Abortion, SpontaneousAdultCote d'IvoireCross-Sectional StudiesFemaleHumansIncidenceIndiaPregnancySurveys and QuestionnairesAbortionFertilityMenstrual regulationSurvey methods

Identifiers

PMID36804033
PMCPMC9938613
OpenAlexW4321217319

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.