Association assessment among risk factors and breast cancer in a low income country: Bangladesh

Kawsar Ahmed, Sayed Asaduzzaman, Mamun Ibn Bashar, Goljar Hossain, Touhid Bhuiyan

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

Background: In the low incoming country Bangladesh, breast cancer is second most common neoplasm and is increasing at an alarming rate among females. Lack of awareness and illiteracy are contributory factors for late presentation and therefore mortality. Purpose: To examine associations of different factors with breast cancer mortality and to raise awareness among the women of society in Bangladesh. Materials and Methods: This descriptive case-control study was conducted on 160 participants from April 2011 till July 2014. Through a valid questionnaire covering personal and family history, data were collected by face to face interview. For analyzing correlations among factors with breast cancer data, binary logistic regression, Pearson's χ2-value, odd ratios and p-value tests were conducted with SPSS version 20. Results: The mean age of the patients was 43.0 (SD=±11.12). In ascending order the leading significant factors were hormone therapy (p<0.0000, OR=4.897), abortion (p<0.0001, OR=3.452), early start menarche (p<0.0002, OR=3.500), family history (p<0.0022, OR=3.235), and late menopause (p<0.0093, OR=3.674) with both χ2 test and logistic regression analyses. Non-significant factors were cancer experience, fatty food habits, marital status and taking alcohol. Conclusions: Regarding the investigation of this study, significant and insignificant factor's correlation visualization with breast cancer will be helpful to increase awareness among Bangladeshi women as well as all over the world.
Original languageEnglish
Pages (from-to)7507-7512
Number of pages6
JournalAsian Pacific Journal of Cancer Prevention
Volume16
Issue number17
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Keywords

  • Bangladesh
  • Breast cancer
  • Correlation
  • Data mining
  • Regression
  • Risk factors

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