Study: Higher income linked to increased breast cancer incidence
Breast cancer incidence was highest among women residing in the highest neighborhood income quintile, while residence in the lowest quintile was associated with a 15 percent lower risk of breast cancer diagnosis, according to a study published online in Statistics Canada.
Lower socio-economic status is linked with increased incidence and mortality for most chronic diseases and several types of cancer. However, the relationship between income and breast cancer may be inverted even when risk factors such as parity, age at first birth and hormone use are taken into account, according to Marilyn J. Borugian, MD, of the British Columbia Cancer Agency in Vancouver, and colleagues.
Borugian and colleagues designed the study to test the hypothesis, using population data from the Canadian Cancer Registry to calculate age-specific and age-standardized incidence rates of breast cancer from 1992 through 2004 by neighborhood income quintile and region.
The researchers analyzed data for 226,169 cases of breast cancer, including age at diagnosis, year of diagnosis and postal code of residence at diagnosis. They factored in 1991 census data on the number of children born per 1,000 women age 15 or older (parity) by neighborhood income quintile to partially adjust for individual data on reproductive risk factors.
Borugian and colleagues calculated breast cancer incidence rates for each 10-year age group, year of diagnosis, region and neighborhood income quintile and determined age-standardized breast cancer incidence rates per 100,000 female person-years at risk.
“For women in all age groups, the risk of being diagnosed with breast cancer was greatest in the highest neighborhood income quintile. Compared with women in neighborhoods in the top quintile, the rate ratios for those in the lowest, second-lowest, middle and second-highest quintile were lower: 0.85, 0.89, 0.92 and 0.95, respectively,” reported Borugian and colleagues.
Although parity was inversely related to neighborhood income quintile, the researchers noted that the relationship between neighborhood income and breast cancer incidence persisted throughout the study. In addition, in British Columbia, previously compiled data indicated higher-income women, except those age 70 to 79, were more likely to have presented for their first mammogram than those in lower income neighborhoods.
The researchers acknowledged that risk factors that vary with socio-economic status such as parity may partially explain the association between breast cancer risk and neighborhood income. However, the largest difference in parity occurred between the lowest and second lowest income quintiles, while the largest difference in incidence occurred between the top two income quintiles.
“Lower parity and a higher prevalence of screening mammography may be related to the higher breast cancer incidence rates among women in the highest neighborhood income quintile, but these factors did not fully explain the difference across income categories,” wrote Borugian, who called for future research of prospective cohorts into individual and neighborhood risk factors, such as lifestyle, family history, occupational and residential history and biologic sample data collected prior to the diagnosis.
Lower socio-economic status is linked with increased incidence and mortality for most chronic diseases and several types of cancer. However, the relationship between income and breast cancer may be inverted even when risk factors such as parity, age at first birth and hormone use are taken into account, according to Marilyn J. Borugian, MD, of the British Columbia Cancer Agency in Vancouver, and colleagues.
Borugian and colleagues designed the study to test the hypothesis, using population data from the Canadian Cancer Registry to calculate age-specific and age-standardized incidence rates of breast cancer from 1992 through 2004 by neighborhood income quintile and region.
The researchers analyzed data for 226,169 cases of breast cancer, including age at diagnosis, year of diagnosis and postal code of residence at diagnosis. They factored in 1991 census data on the number of children born per 1,000 women age 15 or older (parity) by neighborhood income quintile to partially adjust for individual data on reproductive risk factors.
Borugian and colleagues calculated breast cancer incidence rates for each 10-year age group, year of diagnosis, region and neighborhood income quintile and determined age-standardized breast cancer incidence rates per 100,000 female person-years at risk.
“For women in all age groups, the risk of being diagnosed with breast cancer was greatest in the highest neighborhood income quintile. Compared with women in neighborhoods in the top quintile, the rate ratios for those in the lowest, second-lowest, middle and second-highest quintile were lower: 0.85, 0.89, 0.92 and 0.95, respectively,” reported Borugian and colleagues.
Although parity was inversely related to neighborhood income quintile, the researchers noted that the relationship between neighborhood income and breast cancer incidence persisted throughout the study. In addition, in British Columbia, previously compiled data indicated higher-income women, except those age 70 to 79, were more likely to have presented for their first mammogram than those in lower income neighborhoods.
The researchers acknowledged that risk factors that vary with socio-economic status such as parity may partially explain the association between breast cancer risk and neighborhood income. However, the largest difference in parity occurred between the lowest and second lowest income quintiles, while the largest difference in incidence occurred between the top two income quintiles.
“Lower parity and a higher prevalence of screening mammography may be related to the higher breast cancer incidence rates among women in the highest neighborhood income quintile, but these factors did not fully explain the difference across income categories,” wrote Borugian, who called for future research of prospective cohorts into individual and neighborhood risk factors, such as lifestyle, family history, occupational and residential history and biologic sample data collected prior to the diagnosis.