Wambui Gathirua-Mwangi1, Andrea Cohee2, Will L Tarver3, Andrew Marley4, Erika Biederman4, Timothy Stump5, Patrick Monahan5, Susan Rawl6, Celette Sugg Skinner7, Victoria L Champion8. 1. School of Nursing and Richard M Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana. Electronic address: ggathiru@iu.edu. 2. Department of Community and Health Systems, Indiana University School of Nursing, Indianapolis, Indiana. 3. Center for Health Information & Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana. 4. T32 Behavioral Oncology Training Program, School of Nursing and Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana. 5. Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana. 6. Training in Behavioral Nursing Research, Indiana University School of Nursing, Indianapolis, Indiana; Cancer Control and Population Sciences, Indiana University Simon Cancer Center (IUSCC), Indianapolis, Indiana. 7. Division of Behavioral & Communications Sciences, Department of Clinical Sciences, Harold C. Simmons Cancer Center, UT Southwestern Medical Center, Dallas, Texas. 8. Cancer Control and Population Sciences, Indiana University Simon Cancer Center (IUSCC), Indianapolis, Indiana.
Abstract
BACKGROUND: Breast cancer is the second leading cause of cancer mortality, yet mammography screening rates remain less than optimal and differ by income levels. The purpose of this study was to compare factors predicting mammography adherence across income groups. METHODS: Women 41 to 75 years of age (N = 1,681) with health insurance and with no mammogram in the last 15 months were enrolled to participate in an interventional study. Binary logistic regression was used to estimate multivariable-adjusted odds ratios (ORs) for demographic and health belief factors predicting mammography adherence for each income group: 1) low, less than $30,000, 2) middle, $30,000 to 75,000, and 3) high, greater than $75,000 per year. RESULTS: Being in the contemplation stage (vs. precontemplation) of obtaining a mammogram predicted mammography adherence across all income groups and was the only predictor in the middle-income group (OR, 3.9; 95% CI, 2.61-5.89). Increase in age was associated with 5% increase (per year increase in age) in mammography adherence for low-income (OR, 1.05; 95% CI, 1.01-1.09) and high-income (OR, 1.05; 95% CI, 1.02-1.08) women. Having a doctor recommendation predicted mammography adherence only in low-income women (OR, 10.6; 95% CI, 2.33-48.26), whereas an increase in perceived barriers predicted mammography adherence only among high-income women (OR, 0.96; 95% CI, 0.94-0.99). In a post hoc analysis, high-income women reported difficulty in remembering appointments (53%) and lack of time to get a mammogram (24%) as key barriers. CONCLUSIONS: For all income groups, being in contemplation of obtaining a mammogram predicted mammography adherence; however, age predicted mammography adherence for low- and high-income groups, whereas doctor recommendation and perceived barriers were unique predictors for low- and high-income women, respectively. Health care providers should be aware of differences in factors and emphasize strategies that increase mammography adherence for each income group.
BACKGROUND:Breast cancer is the second leading cause of cancer mortality, yet mammography screening rates remain less than optimal and differ by income levels. The purpose of this study was to compare factors predicting mammography adherence across income groups. METHODS:Women 41 to 75 years of age (N = 1,681) with health insurance and with no mammogram in the last 15 months were enrolled to participate in an interventional study. Binary logistic regression was used to estimate multivariable-adjusted odds ratios (ORs) for demographic and health belief factors predicting mammography adherence for each income group: 1) low, less than $30,000, 2) middle, $30,000 to 75,000, and 3) high, greater than $75,000 per year. RESULTS: Being in the contemplation stage (vs. precontemplation) of obtaining a mammogram predicted mammography adherence across all income groups and was the only predictor in the middle-income group (OR, 3.9; 95% CI, 2.61-5.89). Increase in age was associated with 5% increase (per year increase in age) in mammography adherence for low-income (OR, 1.05; 95% CI, 1.01-1.09) and high-income (OR, 1.05; 95% CI, 1.02-1.08) women. Having a doctor recommendation predicted mammography adherence only in low-income women (OR, 10.6; 95% CI, 2.33-48.26), whereas an increase in perceived barriers predicted mammography adherence only among high-income women (OR, 0.96; 95% CI, 0.94-0.99). In a post hoc analysis, high-income women reported difficulty in remembering appointments (53%) and lack of time to get a mammogram (24%) as key barriers. CONCLUSIONS: For all income groups, being in contemplation of obtaining a mammogram predicted mammography adherence; however, age predicted mammography adherence for low- and high-income groups, whereas doctor recommendation and perceived barriers were unique predictors for low- and high-income women, respectively. Health care providers should be aware of differences in factors and emphasize strategies that increase mammography adherence for each income group.
Authors: Victoria L Champion; Patrick O Monahan; Timothy E Stump; Erika B Biederman; Eric Vachon; Mira L Katz; Susan M Rawl; Ryan D Baltic; Carla D Kettler; Natalie L Zaborski; Electra D Paskett Journal: Cancers (Basel) Date: 2022-09-07 Impact factor: 6.575