Contextual Factors, Health History, and Daily Living Activities for Ovarian Cancer Risks: A Case-Control Study in Indonesia

Background: Women are encouraged to aware for risk factors that may aid in the early detection of ovarian cancer before symptoms and sign appear. However, limited studies evaluated the broad aspects of the risk factors for ovarian cancer, particularly in Indonesia. For a more thorough analysis of ovarian cancer risk factors, more variables and a research approach that can make it easier to uncover risk factors of ovarian cancer are necessary. Detecting factors associated with ovarian cancer could serve as the foundation for developing an early warning model.Purpose: The aim of this study was to analyze contextual factors, reproductive health history, and Activity Daily Living (ADLs) associated with ovarian cancer risks.Methods: This retrospective case-control study included 408 women with a 1:1 balanced composition: 204 women diagnosed with ovarian cancer and 204 without. The study was conducted at the Cancer Referral Hospital in West Java Province, Indonesia, from April to November 2020. The instrument was developed based on previous studies and hospital medical/nursing records. The data were analyzed using the Chi-square test and the logistic regression test. The sensitivity and specificity were examined using the Receiver Operating Characteristic (ROC).Results: The variables significantly associated with an increased risk of developing ovarian cancer were advanced age (≥ 45 years) with an odds ratio (OR) of 19.76, low education (OR: 225.00), obesity (OR: 6.04), prior surgery (OR: 51.06), parity (OR: 110.38), and poor sleep quality (OR: 15.75). These factors were found to have the strongest associations with ovarian cancer development.Conclusion: The present study has identified risk factors that have a statistically significant association with the occurrence of ovarian cancer. Healthcare practitioners have the potential to employ this information as foundational data for future research in the development of a self-detection tool for assessing the risk of ovarian cancer.