REAL

Influencing factors on attendance in cervical cancer screening among women with diabetes in Hungary: a cross-sectional study using European Health Interview Surveys 2009-2019

Faludi Vargáné, Eszter and Ghanem, Amr Sayed and Nguyen, Minh Chau and Pataki, Jenifer and Szőllősi, Gergő József and Nagy, Attila Csaba (2025) Influencing factors on attendance in cervical cancer screening among women with diabetes in Hungary: a cross-sectional study using European Health Interview Surveys 2009-2019. FRONTIERS IN ONCOLOGY, 15. No. 1501654. ISSN 2234-943X

[img]
Preview
Text
bo_850_24_csatolmany_2_12.pdf - Published Version
Available under License Creative Commons Attribution.

Download (674kB) | Preview

Abstract

Introduction: With this study, we examined the participation in cervical cancer screening among women with diabetes and the influencing factors of attendance. Methods: Data from the European Health Interview Surveys in Hungary (2009, 2014, 2019) were analyzed with multivariate and multiple logistic regressions. Results: A higher level of education (OR=2.56, 95% CI: 1.03-6.33 in the case of secondary level in 2014; and OR=3.09, 95% CI: 1.17-8.13 in the case of tertiary level in 2019, OR= 2.24, 95% CI: 1.12-4.46 in the case of tertiary level in the pooled data), a perceived good economic situation (OR=2.31, 95% CI: 1.30-4.09 in the pooled data), participation in breast cancer screening (OR= 5.41, 95% CI: 3.49-8.38 in the pooled data), and social support (OR= 2.04 95% CI: 1.03-4.03 in 2019) have a positive effect on participation in screening. Taking prescription drugs (OR= 0.31 95% CI: 0.12-0.83, in the pooled data), lower economic status (OR=0.25 95% CI:0.07-0.88, in 2009) and worse perceived health (OR= 0.20, 95% CI: 0.06-0.64 in 2014) can be considered factors with a negative effect. Conclusion: This study identified groups with low participation rates and made it clear that those groups with unfavorable health factors (bad financial status, bad perceived health, taking prescription drugs) participate the least in screening.

Item Type: Article
Subjects: Q Science / természettudomány > QA Mathematics / matematika > QA76.9.D343 Data mining and searching techniques / adatbányászati és keresési módszerek
R Medicine / orvostudomány > R1 Medicine (General) / orvostudomány általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 25 Sep 2026 07:09
Last Modified: 25 Sep 2026 07:09
URI: https://real.mtak.hu/id/eprint/247623

Actions (login required)

View Item View Item