| Title: |
Prevalence of High-Risk HPV Infection in Community Women at Ho Chi Minh City in 2024: A Cross-Sectional Study with Self-Collect Sampling. |
| Authors: |
Pham, Ai HT; Ha, Thao H; Le, Thanh Q; Nguyen, Dat Q; Vo, Tuan M |
| Source: |
International Journal of Women's Health; Jun2025, Vol. 17, p1673-1679, 7p |
| Subject Terms: |
HUMAN papillomavirus; PROPORTIONAL representation; CERVICAL cancer; CROSS-sectional method; GENOTYPES |
| Abstract: |
Objectives of this study were to determine the prevalence and distribution of HPV types among female residents in Ho Chi Minh City. Methods: This cross-sectional study employed a self-collection method, involving 775 participants selected using a Probability Proportional to Size technique (PPS) between January and December 2024. Results: The study found that 7.5% [95% CI: 5.6– 9.3] of the 775 specimens tested positive for high-risk HPV infection, with HPV-16 accounting for 9.7%, HPV-18 for 3.2%, and other high-risk types for 87.1% (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66 và 68). Compared to similar studies many years ago in Vietnam, the prevalence of high-risk HPV infection has not changed much. However, among high-risk HPV infections, the ratio of types 16 and 18 has decreased dramatically. Conclusion: Findings from this investigation reveal that the high-risk HPV infection prevalence in Ho Chi Minh City communities is consistent with earlier research. Nevertheless, a significant change has been observed in the distribution of high-risk HPV genotypes. Specifically, the proportional representation of HPV types 16 and 18 within the high-risk HPV infection group has substantially diminished, now representing only approximately 30% of their prevalence a decade prior. [ABSTRACT FROM AUTHOR] |
| : |
Copyright of International Journal of Women's Health is the property of Dove Medical Press Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |