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Latent class analysis of symptoms for sexually transmitted infections among Iranian women

Results from a population-based survey

Bibliographic Data

ID15218756
AuthorsMohammad Javad Tarrahi (0000-0001-7875-4572, Isfahan University of Medical Sciences), Sina Kianersi (0000-0003-0950-2675, Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA), Maryam Nasirian (0000-0002-8365-3845, Isfahan University of Medical Sciences, corresponding author)
Year2019
Volume41
Issue4
Pages461-475
Publication date2019-01-28
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueHealth Care For Women International (JOURNAL)
Journal identifiersISSN: 0739-9332 • E-ISSN: 1096-4665
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/07399332.2019.1566335
PMID30689520
OpenAlexW2911409829
LanguageEN
Citations received1
References cited23

A preliminary symptom-based screening test would lower the financial burden of sexually transmitted infections (STIs) caused by clinical testing. To develop such a screening method, we should first identify the most specific STI symptoms. We aim to distinguish the specific STI symptom(s) that are most likely to be found in the truly infected individuals. We used data from a population-based survey that was conducted in Iran, in 2014. Using Latent Class Analysis (LCA) in R software, we classified 3049 Iranian women, 18-60 years old, with reference to seven self-reported STI-associated symptoms. Using LCA, we categorized nearly 1% of women as "probably STI-infected". Above 70% of participants reported the "seven symptoms" that are associated with STIs, except for genital ulcer. These symptoms could be used to distinguish healthy participants from infected ones. The "probably healthy" class incorporated about 77% of the participants. Lower abdominal pain and abnormal vaginal discharge were the most frequently reported symptoms of this class. The LCA determined classes along with the WHO syndromic guidelines for STI diagnosis can help physicians to make a more accurate diagnosis. Hence, cost-effectively, only patients who are classified as probably infected need to be referred to medical laboratories for further investigations

Class (philosophy · Environmental health · Latent class model · Population · Social class · Sociology · Statistics · Adolescent Sexual and Reproductive Health · Computer Science · Demography · Mathematics · Medicine · Psychology · Reproductive Health and Contraception · Reproductive tract infections research

  • Cluster analysis for symptomatic management of Neisseria gonorrhoea and Chlamydia trachomatis in sexually transmitted infections related clinics in China

    Open Access•Ning Ning, Rongxing Weng et al.•Frontiers in Public Health•2022

  • Latent structure analysis

    Paul Felix Lazarsfeld•Latent structure analysis•1968

  • Sexual Dysfunction in the United States

    Edward O Laumann, A Paik et al.•JAMA•1999

  • Latent Class Analysis

    Open Access•Stephanie T Lanza, Brittany L Rhoades•Prevention Science•2013

Unique citing works1
Citations per year0,25
Citation span2022 - 2022 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1

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