Prevalence of Cervical Cancer and Associated Factors Among Women Attended Cervical Cancer Screening Center at Gahandi Memorial Hospital, Ethiopia.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Cancer Informatics Pub Date : 2021-12-22 eCollection Date: 2021-01-01 DOI:10.1177/11769351211068431
Mulugeta Mekuria, Kebede Edosa, Mulualem Endashaw, Elias Teferi Bala, Eshetu E Chaka, Berhanu Senbeta Deriba, Bikila Tesfa
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引用次数: 17

Abstract

Background: Despite the fact that cervical cancer is preventable disease, it is the fourth most frequently diagnosed cancer and leading cause of cancer death in women. An estimated 604 000 women were diagnosed with cervical cancer worldwide and 342 000 women died from the disease. Therefore, the purpose of this study was to determine the prevalence and factors associated with cervical cancer among women attended cervical cancer screening center in Gahandi memorial Hospital.

Methods: An institutional-based cross-sectional study was conducted at Gahandi Memorial Hospital in which simple random sampling technique was used to select 422 registration books of women who visited the hospital between May 2015 and May 2019. Texts, tables, and graph were used to present results. Binary logistic regression with a P-value of <.25 and multivariate logistic regression with a P-value of <.05 were used to determine the association between independent variables and outcome variable.

Results: In this study, from the total of 422 women screened with visual inspection with acetic acid (VIA) screening test, 23.5% of them were found to be positive for VIA test. From those who were diagnosed positive with VIA screening test, about 10.1 % were identified with high grade lesions. Having multiple sexual partners (AOR = 1.83, 95% CI: 1.21-3.29), being HIV-positive (AOR = 2.22, 95% CI:1.10-4.69), having a history of Sexual Transmitted Infection (STI) (AOR = 6.76, 95% CI: 1.14-3.90), and beginning sexual intercourse at early age (AOR = 1.38, 95% CI: 1.20-5.13) were factors associated with cervical cancer.

Conclusion: The study concluded that the high prevalence of cervical cancer. Having multiple sexual partners, being Human Immune Deficiency Virus (HIV) positive, having STI history and early initiation of sexual intercourse were factors associated with cervical cancer. Therefore, avoiding multiple sexual partners, delaying of early sexual contact, and self-protection from STI infections might help to prevent cervical cancer.

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埃塞俄比亚Gahandi纪念医院宫颈癌筛查中心妇女宫颈癌患病率及相关因素
背景:尽管子宫颈癌是可以预防的疾病,但它是第四大最常诊断的癌症,也是妇女癌症死亡的主要原因。全世界估计有60.4万名妇女被诊断患有宫颈癌,34.2万名妇女死于该疾病。因此,本研究的目的是确定在Gahandi纪念医院宫颈癌筛查中心就诊的妇女宫颈癌的患病率及其相关因素。方法:在Gahandi纪念医院进行基于机构的横断面研究,采用简单随机抽样的方法,选取2015年5月至2019年5月期间就诊的妇女422本登记簿。采用文本、表格和图表来展示结果。二值logistic回归,p值为结果的p值:在本研究中,共有422名妇女进行了醋酸目视检查(VIA)筛查试验,其中23.5%的妇女VIA试验呈阳性。在VIA筛查试验中诊断为阳性的患者中,约有10.1%被确定为高级别病变。有多个性伴侣(AOR = 1.83, 95% CI: 1.21-3.29)、hiv阳性(AOR = 2.22, 95% CI:1.10-4.69)、有性传播感染(STI)史(AOR = 6.76, 95% CI: 1.14-3.90)和早期开始性行为(AOR = 1.38, 95% CI: 1.20-5.13)是宫颈癌的相关因素。结论:本研究得出宫颈癌高发的结论。有多个性伴侣、人类免疫缺陷病毒(HIV)阳性、有性传播感染史和过早开始性交是宫颈癌的相关因素。因此,避免多个性伴侣,推迟早期性接触,自我保护免受性传播感染可能有助于预防宫颈癌。
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来源期刊
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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