Evidence map›Paper›PMID 35525995›Full record

ArticleReproductive health2022

Patterns of contraceptive use among young Australian women with chronic disease: findings from a prospective cohort study.

Melissa L Harris, Nicholas Egan, Peta M Forder, Deborah Bateson, Aaron L Sverdlov, Vanessa E Murphy, Deborah Loxton

Open access · goldAbstract read
In one paragraph

Article in Reproductive health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Kidney disease and reproductive health.Nature reviews. Nephrology · 2025
    Review
  8. Article
  9. 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

7 authors at 3 institutions in 1 country.

Melissa L HarrisCentre for Women's Health Research, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, Australia. Melissa.Harris@newcastle.edu.au.ORCID http://orcid.org/0000-0002-5733-9684
Nicholas EganCentre for Women's Health Research, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, Australia.
Peta M ForderCentre for Women's Health Research, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, Australia.
Deborah BatesonFamily Planning NSW, Ashfield, NSW, Australia.
Aaron L SverdlovHunter Medical Research Institute, Newcastle, NSW, Australia.
Vanessa E MurphyHunter Medical Research Institute, Newcastle, NSW, Australia.
Deborah LoxtonCentre for Women's Health Research, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, NSW, Australia.
Hunter Medical Research Institute · AUJohn Hunter Hospital · AUThe University of Sydney · AU

Funding

Australian Research Council DE190101134
6 · The paper itself

Abstract

backgroundGiven chronic disease is increasing among young women and unintended pregnancies among these women are associated with poor maternal and fetal outcomes, these women would benefit from effective preconception care. However, there is a lack of understanding of how these women use or don't use contraception to inform such interventions. This study examined patterns of contraceptive use among an Australian cohort of young women and investigated the influence of chronic disease on contraceptive use over time.

methodsUsing data from 15,244 young women from the Australian Longitudinal Study on Women's Health (born 1989-1995), latent transition analysis was performed to identify distinct contraceptive patterns among women who were at risk of an unintended pregnancy. Multinomial mixed-effect models were used to evaluate the relationship between contraceptive combinations and chronic disease.

resultsContraceptive use for women with cardiac and autoinflammatory diseases differed to women without chronic disease over the observation period. Compared to women without chronic disease using the pill, women with cardiac disease had double the odds of using 'other' contraception and condoms (OR = 2.20, 95% CI 1.34, 3.59) and a modest increase in the odds of using the combined oral contraceptive pill and condoms (OR = 1.39, 95% CI 1.03, 1.89). Compared to women without chronic disease who used the pill, women with autoinflammatory disease had increased odds of using LARC and condoms (OR = 1.58, 95% CI 1.04, 2.41), using 'other' contraception and condoms (OR = 1.69, 95% CI 1.11, 2.57), and using the combined oral contraceptive pill and condoms (OR = 1.38, 95% CI 1.09, 1.75). No differences in contraceptive patterns over the observation period were found for women with asthma or diabetes when compared to women without chronic disease.

conclusionThe findings identified a need for effective contraceptive counselling as part of routine chronic disease care and improved communication between health care providers and women with chronic disease to improve young women's contraceptive knowledge and agency in contraceptive choice, particularly for those with cardiac or autoinflammatory conditions. This may be the key to reducing high-risk unintended pregnancies among this vulnerable population.

Indexed as

ContraceptionContraceptives, Oral, CombinedAustraliaChronic DiseaseContraception BehaviorFemaleHumansLongitudinal StudiesPregnancyProspective StudiesContraceptives, Oral, CombinedChronic diseaseCohort studyContraceptive methodsLong-acting reversible contraceptionLongitudinalPillWithdrawalYoung women

Identifiers

PMID35525995
PMCPMC9078003
OpenAlexW4229075183

What OpenQuestion holds

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LicenceCC BY
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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.