Abstract

The study identified the risk factors associated with breast cancer development and determined its prevalence. A cross sectional design using mixed method was adopted for the study. It was conducted in 22 Primary Health Care centres (PHCs) in Osogbo and Olorunda Local government areas of Osun State. A purposive sampling technique was used to select four hundred child bearing age women (19 - 44 years) who brought their babies for immunization at the 22 PHCs in the two selected local government areas in Osogbo. Respondents from each PHC were selected by proportionate sampling. Two instruments were used for data collection. The Short Form Breast Cancer Risk Questionnaire was used to collect data on the Socio-demographic profile and other relevant data related to breast cancer risk factors. In depth interview was also used to collect data on risk factors associated with breast cancer from 10 women selected from 3 PHCs out of the 22 PHCs which were randomly selected through balloting method. The Gail model which is a mathematical model was used to estimate individual five year absolute breast cancer risk. Women with score of 1.67% and above were categorized as high risk, 1.49 to 1.66% as average risk and a score < 1.49% as low risk. The rationale for using Gail model in the study is to classify the distribution of risk factors in the study according to the level of risks, (high, average and low) as explained above i.e. Women with score of 1.67% and above were categorized as high risk, 1.49 to 1.66% as average risk and a score < 1.49% as low risk. The logistic regression further revealed that family history of breast cancer increased significantly the odds of having higher risk of breast cancer development (OR = 1.12, 95% CI = 0.06–11.46, p-value = 0.002). However, increase in average duration of breastfeeding reduced significantly the odds of having higher risk of breast cancer (OR = 0.98, 95% CI = 0.97 - 1.00, p-value-0.013). The Gail model calculation revealed that 2.3% were at high risk, 2% were at average risk while 95.7% were at low risk. The researcher used the statistical modelling method (logistic regression) to examine the relative importance of each risk factor in predicting the outcome. This study concluded that the key risk factors for breast cancer development were presence of family history and short duration of breastfeeding. Key words: Assessment, breast cancer, reproductive age, risk factors, Gail model.

Highlights

  • In 2017, an estimated 252,710 new cases of invasive breast cancer will be diagnosed among women and 2,470 cases will be diagnosed in men

  • The study provided information on the risk factors that were detected in women of child bearing age, the prevalence and the distribution of the risk factors according to level of risks factors were noted

  • Over a quarter (26.7%) of the respondents‟ mothers were dead, 52.3% of these deaths being traceable to breast cancer. 10.5% of the respondents have never breastfed a child

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Summary

Introduction

In 2017, an estimated 252,710 new cases of invasive breast cancer will be diagnosed among women and 2,470 cases will be diagnosed in men.

Results
Discussion
Conclusion

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