2000 WHRG Grant Program

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Is Obesity a Barrier to Cancer Screening?

Kevin Fontaine, Ph.D.
School of Medicine, University of Maryland, Baltimore

Background: Twenty five percent of American women are obese (i.e., body mass index [BMI: kg/m²]>=30), and the prevalence of obesity among women from minority groups is much higher. Compared to non-obese women, obese women are at increased risk of breast, cervical, endometrial, and colorectal cancer. Thus, it is important that obese women obtain cancer screenings regularly to detect abnormalities since early detection and intervenion can greatly reduce mortality.

Objective: To examine the relationship between obesity (i.e., BMI>=30) and the use of cancer screening services among a large nationally representative sample of women. I will also examine whether minority women that are obese are at greater risk of delaying screenings than white women that are obese.

Design: Secondary data analysis of cross-sectional survey data.

Data Source: Data from the 1998 Behavioral Risk Factor Surveillance Survey (BRFSS). The BRFSS is the world's largest ongoing telephone health surveillance survey. Using a multistage cluster design based on random digit dialing methods, it annually collects uniform, state-based data on preventive health practices and risk behaviors that are linked to chronic diseases, injuries, and preventable infectious diseases in the US adult population. The 1998 BRFSS contains responses from over 80,000 women, nearly 70% of which are >= 35 years of age.

Main Outcome Variables: Interval, based on the recommendations of the American Cancer Society, since the most recent screening: a)clinical breast examination, b)mammography, c)Papanicolaou [Pap] smear, d)fecal occult blood test, and e)sigmoidoscopy/proctoscopy.

Data Analysis: Multiple logistic regression will be used to estimate the independent influence of obesity on the interval since most recent use of the cancer screenings. Variables in the models will include potential confounders of the obesity-screening relationship such as age, insurance status, marital status, educational attainment, annual income, and smoking status. To investigate whether race moderates the obesity-screening relationship, I will run a logistic regression model that includes a BMI by race interaction term for each of the cancer screenings.

Relevance to Women's Health: The proposed secondary data analysis will increase our understanding of the influence obesity has on cancer screening. This is important because: 1) obese women are at increased cancer risk, and 2) the prevalence of obesity and severe obesity among US women continues to increase rapidly implying that cancer incidence will rise accordingly. Thus, it is in the interest of the public health to establish whether obesity, and/or obesity in conjunction with race, decreases the likelihood of obtaining cancer screenings. Such information will inform the development of interventions targeted to increase the use of screening among this high-risk group.