Decreasing Birth Rate Determining Worldwide Incidence and Regional Variation of Female Breast Cancer

Purpose: Urbanization, obesity and ageing associated with lifestyle changes (Westernized diet patterns, pollution, physical inactivity) have been proposed as the major contributing factors for the global rise in breast cancer (BCa) and have been the variables used to predict the future breast cancer rate. At the same time, socio-economic level, instead of birth rate, has been proposed for explanation of dramatic regional variations of breast cancer incidence. We sought to determine which factor plays the determining role in predicting worldwide breast cancer incidence rates and regional variations. Methods: Bivariate correlation was conducted to examine the relationships between country-specific estimates of birth rate, BCa incidence, urbanization, overweight, ageing and GDP. Partial correlation was performed to identify the correlation between BCa incidence with each independent variable while we controlled the other four variables. Multiple linear regression was used to identify the most significant predictors of BCa incidence. Post hoc Scheff and independent T-Test analysis were performed to compare mean differences in BCa incidence rates and residuals of BCa standardised on birth rate in the WHO regions, and UN developed and developing regions respectively. Results: Worldwide, BCa incidence rate tends to increase while birth rate decreases and urbanization, overweight, ageing and GDP increase. However, birth rate was the only variable that had a significant correlation with BCa incidence when controlled for the other four variables. Birth rate was the only significant predictor of BCa incidence in regression analysis. Multiple mean differences of BCa incidence between regions were significant, but all disappeared when the contributing effect of birth rate on BCa incidence rate was removed. Conclusions: Birth rate plays a determining role in worldwide BCa incidence rate and regional variations. Current BCa projection methods may estimate future rates of BCa poorly if they fail to incorporate the impact of birth rate.