ORIGINAL ARTICLE |
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Year : 2019 | Volume
: 8
| Issue : 1 | Page : 106 |
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Developing a community-based breast cancer risk prediction tool for resource-poor settings
Divya Pillai1, Shaikh Shah Hossain2, Vijay Kumar Chattu3
1 Department of Clinical Portfolio Management, Clinical Development Services Agency, Translational Health Science and Technology Institute, Faridabad, Haryana, India 2 Department of Public Health, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India 3 Department of Paraclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobag; Department of Public Health Research, Global Institute of Public Halth, Thiruvananthapuram, Kerala, India
Correspondence Address:
Dr. Vijay Kumar Chattu Faculty of Medical Sciences, University of the West Indies, St. Augustine, Trinidad and Tobago
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jehp.jehp_384_18
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BACKGROUND: With an estimation of every two women newly diagnosed with breast cancer, one dies. It is accounted that 1 in 28 women is likely to develop breast cancer during her lifetime. Developing a risk prediction tool by assessing the prevalence of known risk factors in the community will help public health intervention.
METHODOLOGY: A cross-sectional study was conducted among 18–64-year-old women to gather the prevalence of known breast cancer risk factors, through a community survey (sample survey). In this multistage random number-based cluster sampling study, the results were compiled, collated, and analyzed in rates and proportions. Statistical conclusions were made using spreadsheets (Microsoft) and the values were converted into ordinal values using modified Likert scale and median was used to estimate central values. The estimated prevalence of these known risk factors was re-assorted for analysis and these re-assorted data were categorized into range of values across the communities. The internal validity of the survey questionnaire was measured using Cronbach's alpha (α).
RESULTS: The analysis of 558 participants was performed for the known risk factors for breast cancer including participant's age, age at menarche, marriage, first childbirth, menopause, family history of breast cancer and benign breast disease, history of abortion, and body mass index. Based on the estimated prevalence of these risk factors, a community-based risk prediction tool was developed with Cronbach's α score of medium internal validity.
CONCLUSIONS: The risk assessment tool has collated most of the risk factors of breast cancer that are capable of being measured at community level. The survey findings concluded that the community under survey was bearing moderate risk for breast cancer for women. |
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