CCATClinical Analysis Tool
‹ Knowledge base

Browse the corpus

Walk the evidence base by book and chapter — the raw source passages that ground Ask, Differential, and the rest.

1 passage

abstractpubmed· Abstract 2016· item PMID:24575733

Predictors in breast cancer screening behaviors of South Asian women. AIM: Screening is important in minimizing breast cancer-related morbidity. It is prudent to identify the factors that affect women's choice in participation in mammographic screening. Our objective was to identify the factors that influence the breast screening behaviors in Sri Lankan women. METHODS: Data on referral, sociodemographic factors and relevant personal history of all the women visiting a single mammography center were prospectively collected during a 4-year period. RESULTS: Of the 2695 participants, 1580 had sought mammographic services for screening purposes while 1115 were due to symptoms. A majority had Advanced Level (AL) or higher education (n = 1570, 58.3%) and were parous. Only a minority had past history (n = 221, 8.2%) or family history (n = 357, 13.3%) of breast cancer. Majority has normal mammographic findings with detection of 289 (10.7%) benign lesions. The mean age was 50.2 years in screening participants, 45.9 years in symptomatic women. Use of hormone replacement therapy, age >50 years, AL or higher education, having had undergone hysterectomy, past history of breast cancer, family history of breast cancer, family history of other cancer and self-referral were statistically significant contributors to mammography participation. In the logistic regression analysis age >50 years, AL or higher education, premenopausal status, having undergone hysterectomy and self-referral were significantly associated with screening participation and the model predicted 72.1% of the cases accurately. CONCLUSION: Five statistically significant predictors of mammographic screening among Sri Lankan women were identified. These suggest that higher health awareness and exposure to health care providers are important predictors.