English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Urinary bladder cancer is the most common genitourinary system malignancy in humans. Objectives: Due to the high prevalence of urinary bladder cancer, having enough knowledge about urinary bladder cancer risk factors can assist in prevention and early recognition of this malignancy. Patients and Methods: In this study case-control, 109 individuals with urinary bladder tumor (as a case group) and 200 individuals without any neoplastic history aged u003e40 years (as a control group) were included (2016-2017). The data were collected using patients’ files, their pathology reports and also a checklist. The data were analyzed using SPSS version 20, and logistic regression test was applied to investigate the binary outcome. A P value less than 0.05 was considered significant. Results: The results showed, a significant relationship between smoking (Pu003c0.001), having high risk occupation (Pu003c0.001), low water intake (Pu003c0.001) and pickle consumption (Pu003c0.001) with urinary bladder cancer. Conclusion: Smoking is a strong risk factor for urinary bladder cancer. Our study showed smoking and other occupational carcinogens are the main causes of urinary bladder cancers. Thus preventing and controlling these risk factors are important for health schedules.

Study of risk factors for development of urinary bladder cancer in patients in Urmia; a single-center study by logit regression approach