Mobile mammography in underserved populations: analysis of outcomes of 3,923 women

J Community Health. 2013 Oct;38(5):900-6. doi: 10.1007/s10900-013-9696-7.

Abstract

Mobile health units are increasingly utilized to address barriers to mammography screening. Despite the existence of mobile mammography outreach throughout the US, there is a paucity of data describing the populations served by mobile units and the ability of these programs to reach underserved populations, address disparities, and report on outcomes of screening performance. To evaluate the association of variables associated with outcomes for women undergoing breast cancer screening and clinical evaluation on a mobile unit. Retrospective analysis of women undergoing mammography screening during the period 2008-2010. Logistic regression was fitted using generalized estimating equations to account for potential repeat annual visits to the mobile unit. In total, 4,543 mammograms and/or clinical breast exams were conducted on 3,923 women with a mean age of 54.6, 29 % of whom had either never been screened or had not had a screening in 5 years. Age < 50 years, lack of insurance, Hispanic ethnicity, current smoking, or having a family relative (<50 years of age) with a diagnosis of cancer were associated with increased odds of a suspicious mammogram finding (BIRADS 4,5,6). Thirty-one breast cancers were detected. The mobile outreach initiative successfully engaged many women who had not had a recent mammogram. Lack of insurance and current smoking were modifiable variables associated with abnormal screens requiring follow up.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Age Factors
  • Breast Neoplasms / diagnosis*
  • Early Detection of Cancer / statistics & numerical data*
  • Female
  • Genetic Predisposition to Disease
  • Humans
  • Mammography / statistics & numerical data*
  • Middle Aged
  • Mobile Health Units / statistics & numerical data*
  • Racial Groups
  • Retrospective Studies
  • Smoking / epidemiology
  • Socioeconomic Factors
  • Vulnerable Populations / statistics & numerical data*