Breast and colorectal cancer screening and associated correlates among Chinese older women

Asian Pac J Cancer Prev. 2012;13(1):283-7. doi: 10.7314/apjcp.2012.13.1.283.


Objective: To explore the participation rates for breast and colorectal cancer screening and identify associated correlates among elderly women.

Methods: Logistic regressions were conducted using data collected in 2006 from 1,533 elderly women aged 60 years or above who had completed a screening instrument, the Minimum Data Set-Home Care, while applying for long-term care services at the first time in Hong Kong.

Results: The participation rates for breast and colorectal cancer screening among frail older Chinese women were 3.7% and 10.8% respectively. Cognitive status was inversely associated with the likelihood of participation in screening (breast: OR = 0.66, 95%CI = 0.47-0.94; colon: OR = 0.81, 95%CI = 0.66-0.99), as was educational level with the likelihood of participation in breast cancer screening (no formal education: OR = 0.20, 95%CI = 0.06-0.61, some primary education: OR = 0.31, 95%CI = 0.10-1.00).

Conclusion: The delivery of cancer preventive health services to frail older women is less than ideal. Cognitive status and educational level were important factors in cancer screening behaviour. Tailor-made strategic promotion programmes targeting older women with low cognitive status and educational levels are needed to enhance awareness and acceptance within this vulnerable group.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Asian Continental Ancestry Group
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / prevention & control*
  • Breast Neoplasms / psychology*
  • Cognition
  • Cohort Studies
  • Colorectal Neoplasms / diagnosis
  • Colorectal Neoplasms / prevention & control*
  • Colorectal Neoplasms / psychology*
  • Early Detection of Cancer / statistics & numerical data*
  • Educational Status
  • Female
  • Follow-Up Studies
  • Health Services Accessibility
  • Humans
  • Logistic Models
  • Mammography / statistics & numerical data*
  • Middle Aged
  • Patient Participation
  • Prognosis
  • Risk Factors
  • Socioeconomic Factors