Age-Related and Gender-Related Increases in Colorectal Cancer Mortality Rates in Brazil Between 1979 and 2015: Projections for Continuing Rises in Disease

Abstract

Purpose: Brazil is the largest country in South America. Although a developing nation, birth rates have been decreasing in the last few decades, while its overall population is undergoing lifestyle changes and ageing significantly. Moreover, Brazil has had increasingly high mortality rates related to colorectal cancer (CRC). Herein, we investigated whether the Brazilian population is exhibiting increasing mortality rates related to colon cancer (CC) or rectal cancer (RC) in recent years.

Methods: We examined data from the Brazilian Federal Government from 1979 to 2015 to determine whether CRC mortality and the population ageing process may be associated.

Results: Our mathematical modelling suggests that mortality rates related to CC and RC events in the Brazilian population may increase by 79% and 66% in the next 24 years, respectively. This finding led us to explore the mortality rates for both diseases in the country, and we observed that the highest levels were in the south and southeast regions from the year 2000 onwards. CC events appear to decrease life expectancy among people during their second decade of life in recent years, whereas RC events induced decreases in life expectancy in those aged >30 years. Additionally, both CC and RC events seem to promote significant mortality rates in the male population aged > 60 years and living in the southern states.

Conclusion: Our dataset suggests that both CC and RC events may lead to a significantly increasing number of deaths in the Brazilian male population in coming years.

Keywords: Ageing; Cancer mortality; Epidemiology; Lifestyle.

Fig. 1

Mortality rates related to colon (CC) and rectal cancer (RC) in Brazil. While the recorded period (1979–2015) is shown as continuous lines for both diseases, dashed lines represent the data collected from perspective calculations between 2016 and 2040

Fig. 2

Mortality rates for colon cancer (CC) and rectal cancer (RC) in Brazil. a and b Heatmaps illustrate proportional mortality rates (PMR) for CC (a) and RC (b) according to a population of 100,000 people in different regions of Brazil (North [N]; Northeast [NE]; Midwest [MW]; Southeast [SE]; South [S]) from 1979 until 2015. Whether bright green colours represent the lowest mean values of proportional mortality rates (PMR) in each Brazilian region, bright red colours represent the highest values. c and d Scatter dot plots show P values that have been calculated by the two-way ANOVA model followed by correction of multiple comparisons through the control of false discovery rates according to the two-stage step-up method of Benjamini, Krieger, and Yekutieli

Fig. 3

Years of potential life lost (YPLL) due to colon cancer (CC) and rectal cancer (RC) events in Brazil. a and b Heatmaps illustrate YPLL values for CC (a) and RC (b) are shown in different populations with age ranging from 15 to 79 years old between 1979 and 2015 in Brazil. Whether bright green colours represent the lowest mean values of YPLL, bright red colours represent the highest values. c and d Scatter dot plots show P values that have been calculated by the two-way ANOVA model followed by correction of multiple comparisons through the control of false discovery rates according to the two-stage step-up method of Benjamini, Krieger, and Yekutieli

Fig. 4

Age-adjusted death rates (AADR) related to colon cancer events (CC) during the year of 2015 are shown for both male (M) and female populations (F) living in different Brazilian states according to their regional location in the country. a AADR values related to CC are shown in different populations with age ranging from 20 to 80 years old during the year of 2015 in Brazil. These values were determined based on data from regional health centres (RHCs) within each Brazilian state in the Midwest (MW; Federal capital region [DF; RHC = 1], Goias state [GO; RHC = 16], and Mato Grosso do Sul [MS; RHC = 12] and Mato Grosso [MT; RHC = 16] states), Southeast (SE; Espirito Santo [ES; RHC = 4], Minas Gerais [MG; RHC = 16], Rio de Janeiro [RJ; RHC = 9], and Sao Paulo [SP; RHC = 16] states), and South regions (S; Parana [PR; RHC = 16], Santa Catarina [SC; RHC = 16], and Rio Grande do Sul [RS; RHC = 16]). Values have been adjusted to the Brazilian population of 2010. Whether bright green colours represent the lowest mean values of AADR in each Brazilian region, bright red colours represent the highest values. b Scatter dot plots show P values that have been calculated by the two-way ANOVA model followed by correction of multiple comparisons through the control of false discovery rates according to the two-stage step-up method of Benjamini, Krieger, and Yekutieli

Fig. 5

Age-adjusted death rates (AADR) related to rectal cancer events (RC) during the year of 2015 are shown for both male (M) and female populations (F) living in different Brazilian states according to their regional location in the country. a AADR values related to RC are shown in different populations with age ranging from 20 to 80 years old during the year of 2015 in Brazil. These values were determined based on data from regional health centres (RHCs) within each Brazilian state in the Midwest (MW; Federal capital region [DF; RHC = 1], Goias state [GO; RHC = 16], and Mato Grosso do Sul [MS; RHC = 12] and Mato Grosso [MT; RHC = 16] states), Southeast (SE; Espirito Santo [ES; RHC = 4], Minas Gerais [MG; RHC = 16], Rio de Janeiro [RJ; RHC = 9], and Sao Paulo [SP; RHC = 16] states), and South regions (S; Parana [PR; RHC = 16], Santa Catarina [SC; RHC = 16], and Rio Grande do Sul [RS; RHC = 16]). Values have been adjusted to the Brazilian population of 2010. Whether bright green colours represent the lowest mean values of AADR in each Brazilian region, bright red colours represent the highest values. b Scatter dot plots show P values that have been calculated by the two-way ANOVA model followed by correction of multiple comparisons through the control of false discovery rates according to the two-stage step-up method of Benjamini, Krieger, and Yekutieli