Identifying and Visualizing risk factors of Breast Cancer data
Location
Hager-Lubbers Exhibition Hall
Description
PURPOSE: This study aims to identify and visualize various risk factors for breast cancer using data from The Breast Cancer Surveillance Consortium (BCSC) to inform new measures and preventive care for potential breast cancer patients. SUBJECTS: The study utilized data from 26,173 Americans, focusing on age, race, menopausal status, BMI, and family history as factors associated with an increased risk of developing breast cancer. METHODS AND MATERIALS: Using R studio for analysis, the BCSC dataset covering a range of demographic and health-related attributes was employed to investigate the impact of identified risk factors on breast cancer incidence. ANALYSES: Statistical tests, including Chi-square and logistic regression analyses, were conducted to determine the significance of each risk factor in predicting breast cancer risk. RESULTS: Findings indicate that 39.58% of participants used digital platforms for health information, with a significant correlation found between digital platform use and factors such as age, education level, geographical location, and chronic illness prevalence. Notably, predictors of increased use included multiple chronic conditions, higher education levels, and certain racial demographics. CONCLUSIONS: The study concludes that individuals with more education and chronic conditions, particularly within specific racial demographics, are more likely to utilize digital resources for medication information. These insights emphasize the importance of tailoring digital health literacy programs to enhance the accessibility and effectiveness of online health resources.
Identifying and Visualizing risk factors of Breast Cancer data
Hager-Lubbers Exhibition Hall
PURPOSE: This study aims to identify and visualize various risk factors for breast cancer using data from The Breast Cancer Surveillance Consortium (BCSC) to inform new measures and preventive care for potential breast cancer patients. SUBJECTS: The study utilized data from 26,173 Americans, focusing on age, race, menopausal status, BMI, and family history as factors associated with an increased risk of developing breast cancer. METHODS AND MATERIALS: Using R studio for analysis, the BCSC dataset covering a range of demographic and health-related attributes was employed to investigate the impact of identified risk factors on breast cancer incidence. ANALYSES: Statistical tests, including Chi-square and logistic regression analyses, were conducted to determine the significance of each risk factor in predicting breast cancer risk. RESULTS: Findings indicate that 39.58% of participants used digital platforms for health information, with a significant correlation found between digital platform use and factors such as age, education level, geographical location, and chronic illness prevalence. Notably, predictors of increased use included multiple chronic conditions, higher education levels, and certain racial demographics. CONCLUSIONS: The study concludes that individuals with more education and chronic conditions, particularly within specific racial demographics, are more likely to utilize digital resources for medication information. These insights emphasize the importance of tailoring digital health literacy programs to enhance the accessibility and effectiveness of online health resources.