ABSTRACT:

Objective:

To analyze the spatial distribution of the four-year cancer mortality rates in the state of Mato Grosso, Brazil, from 2000 to 2015.

Methodology:

Ecological design study, in which mortality from neoplasia was analyzed, from 2000 to 2015, for the municipalities of Mato Grosso State. Mortality rates due to cancer were calculated by the ratio of the sum of deaths by cancer in each quadrennium, divided by the average of the population in the two central years of the period, multiplied by 10,000 inhabitants. Annual percentage change was calculated by the ratio of the linear regression coefficient to the cancer mortality rates in Mato Grosso State at the beginning of the analyzed period (2000 to 2003). Thematic maps were constructed for each quadrennium using intervals of equal classes.

Results:

Cancer caused 31,097 deaths in the state of Mato Grosso in the period, 13,058 in women and 18,039 in men, with a male to female ratio of 1.38. The top five causes of cancer death in the period were lung (12.2%), prostate (8.7%), stomach (7.7%), breast (6.0%), and liver (4.7%). There was an increase in the number of municipalities with rates greater than 23.67 deaths per 100,000 inhabitants in the period.

Conclusion:

There was an increase in cancer mortality and an increase in the proportion of municipalities with higher mortality rates. Higher density of cancer mortality occurred in the municipalities located in the West, Center-South, Southeast, and Center-North regions of the state.

Keywords:
Neoplasms; Information systems; Mortality; Spatial analysis; Temporal distribution

RESUMO:

Objetivo:

Analisar a distribuição espacial das taxas quadrimestrais de mortalidade por câncer no estado de Mato Grosso, Brasil, no período de 2000 a 2015.

Métodos:

Estudo de desenho ecológico, no qual foi analisada a mortalidade por neoplasia, de 2000 a 2015, para os municípios do estado de Mato Grosso. As taxas de mortalidade por câncer foram calculadas pela razão da soma das mortes por câncer em cada quadrênio, dividida pela média da população nos dois anos centrais do período, multiplicada por 10.000 habitantes. Uma variação percentual anual foi calculada pela razão do coeficiente de regressão linear para as taxas de mortalidade por câncer no estado de Mato Grosso no início do período analisado (2000 a 2003). Mapas temáticos foram construídos para cada quadriênio usando intervalos de classes iguais.

Resultados:

O câncer causou 31.097 óbitos no estado de Mato Grosso no período, 13.058 em mulheres e 18.039 em homens, com uma proporção de homens e mulheres de 1,38. As cinco principais causas de morte por câncer no período foram pulmão (12,2%), próstata (8,7%), estômago (7,7%), mama (6,0%) e fígado (4,7%). Houve um aumento no número de municípios com taxas superiores a 23,67 óbitos por 100.000 habitantes no período.

Conclusão:

Houve aumento da mortalidade por câncer e aumento na proporção de municípios com maiores taxas de mortalidade. Maiores densidades de mortalidade por câncer ocorreram nos municípios localizados nas regiões Oeste, Centro-Sul, Sudeste e Centro-Norte do estado.

Palavras-chave:
Neoplasias; Sistemas de informação; Mortalidade; Análise espacial; Distribuição temporal

INTRODUCTION

Chronic noncommunicable diseases are responsible for most deaths worldwide. It is estimated that cancer is at the top of the basic causes of death and is the most important barrier to increasing life expectancy in the world¹1. World Health Organization. Global Health Observatory [Internet]. Geneva: World Health Organization; 2018 [accessed on Jul. 10, 2018]. Available at: who.int/gho/database/en/
who.int/gho/database/en/... .

In 2016, about 41 million deaths were due to chronic noncommunicable diseases and, of these, 9 million (22%) had cancer as a basic cause¹1. World Health Organization. Global Health Observatory [Internet]. Geneva: World Health Organization; 2018 [accessed on Jul. 10, 2018]. Available at: who.int/gho/database/en/
who.int/gho/database/en/... . Worldwide, projections for the year 2030 indicate the occurrence of 26 million new cases and 17 million deaths from the disease²2. Thun MJ, DeLancey JO, Center MM, Jemal A, Ward EM. The global burden of cancer: priorities for prevention. Carcinogenesis 2010; 31(1): 100-10. https://doi.org/10.1093/carcin/bgp263
https://doi.org/10.1093/carcin/bgp263... . These numbers express the importance of cancer as a leading cause of death worldwide³3. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68(6): 394-424. https://doi.org/10.3322/caac.21492
https://doi.org/10.3322/caac.21492... .

In Brazil, between 1996 and 2010, there were 2,023,038 deaths from cancer, with 53.9% affecting men and 46.1% women⁴4. Barbosa IR, Souza DLB, Bernal MM, Costa ICC. Cancer mortality in Brazil: Temporal Trends and Predictions for the Year 2030. Medicine (Baltimore) 2015; 94(16): e746. https://doi.org/10.1097/md.0000000000000746
https://doi.org/10.1097/md.0000000000000... . In 2017, the five primary locations with the highest death rates in the male population in the country were: bronchi and lung with 15.60 per 100,000 inhabitants, followed by prostate with 14.24 per 100,000, thirdly the stomach with 8.82 per 100,000, in fourth position, the esophagus with 6.41 per 100.000, and in fifth place, liver and biliary tract with 5.71 per 100.000 inhabitants. In the female population, for the same year, the primary location that showed the highest rate was the breast with 13.22 per 100,000 inhabitants, secondly that of the bronchi and lung with 9.20 per 100,000, followed by cervical cancer with 5.14 per 100,000, colon in the fourth place with 4.62 per 100,000 and in the fifth place, pancreas cancer with 4.06 per 100,000 inhabitants⁵5. Instituto Nacional de Câncer José Alencar Gomes da Silva. Atlas da Mortalidade [Internet]. Brazil: Instituto Nacional de Câncer José Alencar Gomes da Silva; 1996-2014 [accessed on Feb. 15, 2020]. Available at: http://mortalidade.inca.gov.br/Mortalidade/
http://mortalidade.inca.gov.br/Mortalida... .

The estimate of new cases of cancer in Brazil for the period from 2020 to 2022 is 625 thousand and for the state of Mato Grosso, there were crude rates of 252.04 per 100,000 inhabitants for men and 217.31 per 100,000 for women⁶6. Instituto Nacional de Câncer José Alencar Gomes da Silva. Estimativa 2020: incidência de câncer no Brasil. Rio de Janeiro: INCA; 2019. 120 p..

Spatial analysis of data allows the analysis of cases according to the distribution in a specific geographical area. However, it is worth mentioning that the spaces are not homogeneous, since spatial differentiation implies several other singularities, such as culture, education, income, genetic, and housing characteristics⁷7. Barcellos C, Bastos FI. Geoprocessamento, ambiente e saúde: uma união possível? Cad Saúde Pública 1996; 12(3): 389-97. https://doi.org/10.1590/S0102-311X1996000300012
https://doi.org/10.1590/S0102-311X199600... .

Thus, the relevance of this study is unique, since the environment has characteristics that can act as risk factors for the occurrence of cancer. In addition, scientific production on the theme of cancer, using geoprocessing as an analysis tool, is still little explored, which further highlights the importance of this study, aiming to analyze the spatial distribution of the four-year rates of mortality from neoplasia, in the period from 2000 to 2015 in the state of Mato Grosso, Brazil.

METHODS

Ecological design study, in which mortality from neoplasia (by municipality of residence) was analyzed, from 2000 to 2015, for the state of Mato Grosso.

The Brazilian Legal Amazon corresponds to the area of operation of the Superintendence of Development of the Amazon (SUDAM), being formed by the states of Rondônia, Acre, Amazonas, Roraima, Pará, Amapá, Tocantins, Mato Grosso, and the western part of Maranhão. It has an area of approximately 5,015,067.749 km², corresponding to approximately 58.9% of the Brazilian territory⁸8. Instituto Brasileiro de Geografia e Estatística. Portal [Internet]. Brazil: Instituto Brasileiro de Geografia e Estatística [accessed on Jul. 10, 2018]. Available at: http://www.ibge.gov.br
http://www.ibge.gov.br... .

Data on the estimated population of the state were acquired from the Brazilian Institute of Geography and Statistics (IBGE)⁸8. Instituto Brasileiro de Geografia e Estatística. Portal [Internet]. Brazil: Instituto Brasileiro de Geografia e Estatística [accessed on Jul. 10, 2018]. Available at: http://www.ibge.gov.br
http://www.ibge.gov.br... for the year 2018 (3,441,998 inhabitants, with a population density of 3.36 inhabitants per km² and a territorial area of 903,206,997 km²). The state of Mato Grosso is divided into 7 geographic regions and 141 municipalities (Figure 1).

Mortality data were obtained from the databases of the Mortality Information System (Sistema de Informações sobre Mortalidade – SIM)⁹9. Brasil. Ministério da Saúde. Sistema de Informação sobre Mortalidade (SIM) [Internet]. Brazil: Ministério da Saúde [accessed on Jul. 10, 2018]. Available at: http://www2.datasus.gov.br/
http://www2.datasus.gov.br/... provided by the Mato Grosso State Department of Health. Cancer deaths were analyzed under codes C00 to C97, according to the 10^th ICD-10 (International Classification of Diseases). These deaths refer to individuals of all ages. Population estimates by age group were collected from the website of the Department of Informatics of the Unified Health System, of the Brazilian public health system¹⁰10. Brasil. Ministério da Saúde. Estimativas populacionais. Brazil: Ministério da Saúde [accessed on Jul. 10, 2018]. Available at: http://datasus.saude.gov.br/populacao-residente
http://datasus.saude.gov.br/populacao-re... .

Mortality rates due to cancer were calculated by the ratio of the sum of deaths by cancer in each quadrennium, divided by the average of the population in the two central years of the period, multiplied by 10,000 inhabitants. The rates were adjusted by the direct method by age groups, with intervals of four years, considering as a standard population the distribution of the world population¹¹11. Doll R. Comparison between registries and age-standardized rates. In: Waterhouse JA, Muir CS, Correa P, Powell J, editors. Cancer incidence in five continents. Lyon: IARC; 1976. v. 3. p. 453-9.. In order to reduce instability in the analysis of mortality data by municipality, we sought to smooth out random fluctuations by grouping rates in four-year periods: 2000 to 2003; 2004 to 2007; 2008 to 2011; and 2012 to 2015.

An annual percentage change was calculated by the ratio of the linear regression coefficient to the cancer mortality rates in Mato Grosso State at the beginning of the analyzed period (2000 to 2003). Significance level of 5%.

To explore the spatial distribution of cancer mortality rates, thematic maps were constructed for each quadrennium using intervals of equal classes (0.00; between 0.01 and 12.52; between 12.53 and 23.67; between 23.68 and 36.21; between 36.22 and 48.00; above 48.00). The intervals were defined based on the distribution of rates in the first quadrennium (2000–2003). The geographical unit of analysis were the 141 municipalities of Mato Grosso. The municipalities of Itanhangá and Ipiranga do Norte were created in 2005, which made it impossible to calculate the mortality rate for the quadrennium from 2000 to 2003 and were declared as missing. The cartographic bases were obtained from IBGE¹²12. Instituto Brasileiro de Geografia e Estatística. Encontre mapas [Internet]. Brazil: Instituto Brasileiro de Geografia e Estatística [accessed on Jul. 10, 2018]. Available at: https://mapas.ibge.gov.br/bases-e-referencial/bases-cartograficas/malhas-digitais
https://mapas.ibge.gov.br/bases-e-refere... . Kernel maps were built with an adaptive radius. Nine strata were used, divided into equal intervals.

For data analysis, the software STATA version 12.0 and the ArcMap Program version 10.3 were used. The study was approved by the Ethics and Research Committee of Hospital Universitário Júlio Muller.

RESULTS

In the period from 2000 to 2015, cancer caused 31,097 deaths in Mato Grosso State, 13,058 in women and 18,039 in men, with a male to female ratio of 1.38. The top five causes of cancer death in the period were lung (12.2%), prostate (8.7%), stomach (7.7%), breast (6.0%), and liver (4.7%). The mortality rates in the state in the quadrenniums from 2000 to 2003, 2004 to 2007, 2008 to 2011, and 2012 to 2015 were 30.0, 32.4, 32.8, and 33.2 per 100,000 inhabitants, respectively, indicating an average annual increase of 8.3% (p = 0.030) (data not shown).

Figure 2 shows the proportion of municipalities according to the intervals of equal classes defined in the maps. There is an increase in the proportion of municipalities with mortality rates between 23.68 to 36.21, between 36.22 to 48.00, and above 48.00. For the remaining intervals (0.00; between 0.01 and 12.52; between 12.53 to 23.67), there was a downward trend.

Figure 3 shows the four-year trends in cancer mortality rates according to municipality. There is an increase in the number of municipalities with rates greater than 23.67 deaths per 100,000 inhabitants in the period. The regions with the highest rate in the quadrenniums were West, Center-South, Southeast, Center-North, and North, while the Northeast and Northwest regions had the lowest rates.

The kernel intensity map (Figure 4) confirms that the highest density of cancer mortality occurred in the West, Center-South, Southeast, and Center-North regions of the state and the lowest in the Northeast and Northwest regions. This pattern tends to be maintained throughout the quadrenniums. For the North and Northwest regions there is a decrease in mortality densities over the four-year period. The Northeast region had the lowest densities in the entire period studied.

DISCUSSION

There was an average annual increase of 8.3% in cancer mortality rates and an increase in the proportion of municipalities with higher mortality rates. The municipalities located in the West, Center-South, Southeast, and Center-North regions of the state presented higher density of cancer mortality.

The results of this study identified space and time patterns that point to an increase in standardized rates of cancer mortality in the state of Mato Grosso from 2000 to 2015.

According to IBGE data on the age distribution of the population, at least 80% of the state's population is concentrated below 50 years of age. However, according to the Mato Grosso Oncology Care Action Plan, even though the state has a predominantly younger population, cancer has appeared as the second cause of death in mortality statistics (excluding external causes). In addition, there was also an increase in proportional cancer mortality, from 10.8% in 2001 to 14.3% in 2013¹³13. Mato Grosso. Governo de Mato Grosso. Secretaria de Estado de Saúde (SES-MT). Plano de Ação da Atenção Oncológica no Estado de Mato Grosso 2017 a 2019 [Internet]. Cuiabá: SES-MT; 2017 [accessed on Jul. 10, 2018]. Available at: www.saude.mt.gov.br/arquivo/7317
www.saude.mt.gov.br/arquivo/7317... .

The pattern shown in the state was different from the national pattern, where general rates for the disease have been showing some stability⁴4. Barbosa IR, Souza DLB, Bernal MM, Costa ICC. Cancer mortality in Brazil: Temporal Trends and Predictions for the Year 2030. Medicine (Baltimore) 2015; 94(16): e746. https://doi.org/10.1097/md.0000000000000746
https://doi.org/10.1097/md.0000000000000... . A study that described the main groups of causes of death from chronic non-communicable diseases between 1990 and 2015 according to estimates from the Global Burden of Disease (GBD) 2015 study, showed that, for Brazil, the standardized mortality rates for cancer went from 142.7 per 100,000 inhabitants (1990) to 133.5 per 100,000 inhabitants (2015), considered stable for the analyzed period¹⁴14. Malta DC, França E, Abreu DMX, Perillo RD, Salmen MC, Teixeira RA, et al. Mortality due to noncommunicable diseases in Brazil, 1990 to 2015, according to estimates from the Global Burden of Disease study. Sao Paulo Med J 2017; 135(3): 213-21. https://doi.org/10.1590/1516-3180.2016.0330050117
https://doi.org/10.1590/1516-3180.2016.0... .

The five main causes of death from cancer in the period for the state, considering the anatomical location, were lung, prostate, stomach, breast, and liver. With the exception of liver cancer, which appears only in Mato Grosso, the others are also among the five main types of cancer that kill the most in Brazil, although not in the same order¹⁵15. Brasil. Ministério da Saúde. Instituto Nacional de Câncer. Coordenação de Prevenção e Vigilância. Divisão de Vigilância e Análise de Situação. Sistema de Informação sobre Mortalidade [Internet]. Brasil: Ministério da Saúde; 2019 [accessed on Jul. 20, 2019]. Available at: https://www.inca.gov.br/numeros-de-cancer
https://www.inca.gov.br/numeros-de-cance... .

Estimates from Global Cancer Observatory show that, worldwide, lung cancer remains the leading cause of cancer mortality, with 1.8 million deaths predicted in 2018, representing about 1 out of 5 cancer deaths. Prostate cancer is considered the fifth leading cause of cancer death in men, and breast cancer the first in women, accounting for about 1 out of 4 cancer cases in this group. Stomach cancer remains an important cancer worldwide, accounting for about 783,000 deaths, equivalent to 1 out of 12 deaths from cancer, while liver cancer is considered the fourth leading cause of cancer death worldwide³3. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68(6): 394-424. https://doi.org/10.3322/caac.21492
https://doi.org/10.3322/caac.21492... .

The profile of deaths presented in the state has been associated with more urbanized, industrialized regions with an aging population, in line with developed countries in the West. On the other hand, the state continues to live with deaths due to types of cancer associated with infections, such as stomach cancer, which have a high potential for prevention and tend to be more prevalent in countries of low and medium development¹⁶16. Balakrishnan M, George R, Sharma A, Graham DY. Changing trends in stomach cancer throughout the world. Curr Gastroenterol Rep 2017; 19: 36. https://doi.org/10.1007/s11894-017-0575-8
https://doi.org/10.1007/s11894-017-0575-... .

Cancer is a multifactorial disease, however, according to the World Health Organization (WHO), some risk factors are related to most deaths from chronic noncommunicable diseases, including cancer, having an important contribution to the burden of diseases. Among these factors, smoking, excessive alcohol consumption, inadequate diet, and physical inactivity stand out¹⁷17. World Health Organization (WHO). Global status report on noncommunicable diseases 2010. Geneva: WHO; 2011..

Data from the Mato Grosso National Health Survey¹⁸18. Brasil. Ministério da Saúde. Pesquisa Nacional de Saúde 2013. Percepção do estado de saúde, estilos de vida e doenças crônicas. Brasil, Grandes Regiões e Unidades da Federação. Rio de Janeiro: Ministério da Saúde; 2014. showed that only 37.0% of the state's population aged 18 years old or older reported complying with the recommended consumption of fruits and vegetables, while 52.9% were classified as insufficiently active (behind Rondônia State only), 24.3% reported weekly alcohol consumption and 12.8% as current users of tobacco products.

There was also a higher proportion of deaths among men. This can be explained by the fact that the three main types of cancer were more present in this group. A study that aimed to analyze the temporal trend of cancer mortality in Brazil in the period from 1996 to 2010, in addition to calculating the projection of mortality for the period from 2011 to 2030, showed that 53.9% of deaths affected men and 46.1%, women. In addition, there was stability in female mortality and a significant increase in the trend for males between 1996 and 2008⁴4. Barbosa IR, Souza DLB, Bernal MM, Costa ICC. Cancer mortality in Brazil: Temporal Trends and Predictions for the Year 2030. Medicine (Baltimore) 2015; 94(16): e746. https://doi.org/10.1097/md.0000000000000746
https://doi.org/10.1097/md.0000000000000... .

Literature data have pointed out that men and women have different life expectancies and habits, with greater female demand for health services and, consequently, with women adopting greater preventive health care than men¹⁹19. Vieira KLD, Gomes VLO, Borba MR, Costa CFS. Atendimento da população masculina em unidade básica saúde da família: motivos para a (não) procura. Esc Anna Nery 2013; 17(1): 120-7. https://doi.org/10.1590/S1414-81452013000100017
https://doi.org/10.1590/S1414-8145201300... .

Spatial analysis of cancer mortality, through the use of maps, is an important tool to evaluate health risks, especially when this type of analysis considers environmental aspects, as the visualization of information allows a better understanding of how relationships occur, contributing to the identification of priority territories, as well as a better understanding of the health-disease process and health planning actions²⁰20. Carvalho MS, Souza-Santos R. Análise de dados espaciais em saúde pública: métodos, problemas, perspectivas. Cad Saúde Pública 2005; 21(2): 361-78. https://doi.org/10.1590/S0102-311X2005000200003
https://doi.org/10.1590/S0102-311X200500... .

The use of geoprocessing also allows for a historical analysis of the demand for care in health services, helping to optimize care in health units and producing important changes in epidemiological and operational indicators²¹21. Nardi SMT, Paschoal JAA, Pedro HSP, Paschoal VD, Sichieri EP. Geoprocessamento em Saúde Pública: fundamentos e aplicações. Rev Inst Adolfo Lutz 2013; 72(3): 185-91. https://doi.org/10.18241/0073-98552013721562
https://doi.org/10.18241/0073-9855201372... .

This analysis allowed to identify that the regions of the state with the highest mortality rates were the West, Center-South, Southeast, Center-North, and North regions. These regions showed differences that can be expressed through socioeconomic indicators of the municipalities that integrate them, as well as an inequality in installed capacity and in public and private investments, especially in those with less economic dynamism²²22. Mato Grosso. Secretaria de Estado de Saúde do Estado de Mato Grosso (SES-MT). Escola de Saúde Pública do Estado de Mato Grosso. Plano Estadual de Educação Permanente do Mato Grosso. Cuiabá: SES-MT; 2019.. Despite this diversity, what can be observed is that, in general, these regions have less availability of primary care services, and some also have low health care expenditures (West Region), low availability of specialized assistance establishments (West and North Regions), and low outpatient care per inhabitant in medium and high complexity (West, North and Center-North Regions)²³23. Scatena JHG, Oliveira LR, Galvão ND, das Neves MAB. Caracterização das regiões de saúde de Mato Grosso. In: Scatena JHG, Kehrig RT, Spinelli MAS, editors. Regiões de Saúde: diversidade e processo de regionalização em Mato Grosso. São Paulo: Hucitec; 2014.^,2424. Scatena JHG, Oliveira LR, Galvão ND, das Neves MAB. O uso de indicadores compostos para classificação das regiões de saúde de Mato Grosso. In: Scatena JHG, Kehrig RT, Spinelli MAS, editors. Regiões de Saúde: diversidade e processo de regionalização em Mato Grosso. São Paulo: Hucitec; 2014..

Specifically with regard to primary health care services, they serve as a gateway to the health care network. The low availability of these services may impair the identification, in the initial phase, of the first lesions suggestive of cancer and, consequently, determine the specialized services as the predominant places for the diagnosis of the disease, since the confirmation of the lesions requires procedures and supplies available only in medium and high complexity services²⁵25. Aquino RCA, Lima MLLT, Silva VL, Alencar FL, Rodrigues M. Acesso e itinerário terapêutico aos serviços de saúde nos casos de óbitos por câncer de boca. Rev CEFAC 2018; 20(5): 595-603. https://doi.org/10.1590/1982-0216201820515017
https://doi.org/10.1590/1982-02162018205... .

Another characteristic of the state is that, with the exception of some municipalities in the Center-South region, agriculture and services are the economic basis of practically all regions therein²³23. Scatena JHG, Oliveira LR, Galvão ND, das Neves MAB. Caracterização das regiões de saúde de Mato Grosso. In: Scatena JHG, Kehrig RT, Spinelli MAS, editors. Regiões de Saúde: diversidade e processo de regionalização em Mato Grosso. São Paulo: Hucitec; 2014..

Currently, Mato Grosso is the state that produces the most soy, corn, cotton, and cattle in Brazil, having become, for several years, a strategic territory for the expansion of agribusiness²⁶26. Instituto Brasileiro de Geografia e Estatística (IBGE). Produção Agrícola Municipal 2015 [Internet]. Brasília: IBGE; 2015 [accessed on Jul. 20, 2019]. Available at: https://sidra.ibge.gov.br/pesquisa/pam/tabelas
https://sidra.ibge.gov.br/pesquisa/pam/t... , whose model consists predominantly of large monoculture properties, intensive use of chemical and pesticide fertilizers to control unwanted species and use of biotechnology (transgenics)²⁷27. Albergoni L, Pelaez V. Da Revolução Verde à agrobiotecnologia: ruptura ou continuidade de paradigmas? Rev Economia 2007; 33(1): 31-5. https://doi.org/10.5380/re.v33i1.8546
https://doi.org/10.5380/re.v33i1.8546... . This issue was evidenced by the higher cancer mortality rates in cities close to BR-163 (a federal highway) (Figure 3), which can probably be explained by the relationship between soy production (with transgenics and use of pesticides, which have highly carcinogenic potentials) and the presence of the highway to transport production to other countries²⁸28. Brasil. Ministério da Infraestrutura. Departamento Nacional de Infraestrutura de Transportes. Portal [Internet]. Brazil: Ministério da Infraestrutura [accessed on Apr. 20, 2020]. Available at: http://www.dnit.gov.br/noticias/governo-federal-conclui-asfaltamento-da-br-163-pa
http://www.dnit.gov.br/noticias/governo-... .

The state has some municipalities that concentrate a large part of the national agricultural production, such as some municipalities located in the central and southeast regions. Consequently, due to the chemical-dependent production method, these municipalities have high rates of pesticide consumption²⁹29. Beserra L. Agrotóxicos, vulnerabilidade socioambientais e saúde: uma avaliação participativa em municípios da bacia do rio Juruena, Mato Grosso [dissertation]. Cuiabá: UFMT; 2017..

The relationship between exposure to pesticides and cancer development has been established in several studies³⁰30. Barry KH, Koutros S, Lubin JH, Coble JB, Barone-Adesi F, Beane Freeman LE, et al. Methyl bromide exposure and cancer risk in the Agricultural Health Study. Cancer Causes Control 2012; 23: 807-18. https://doi.org/10.1007/s10552-012-9949-2
https://doi.org/10.1007/s10552-012-9949-... ^–3333. Parada H Jr., Wolff MS, Engel LS, White AJ, Eng SM, Cleveland RJ, et al. Organochlorine insecticides DDT and chlordane in relation to survival following breast cancer. Int J Cancer 2016; 138(3): 565-75. https://doi.org/10.1002/ijc.29806
https://doi.org/10.1002/ijc.29806... , being modulated by type of product used, time of exposure, and amount absorbed by the body³⁴34. Alavanja MCR, Hoppin JA, Kamel F. Health effects of chronic pesticide exposure: cancer and neurotoxity. Annu Rev Public Health 2004; 25: 155-97. https://doi.org/10.1146/annurev.publhealth.25.101802.123020
https://doi.org/10.1146/annurev.publheal... . It is important to highlight that the entire population is susceptible to multiple exposures to pesticides, through the consumption of contaminated water and food, and not only farmers and workers in the pesticide production chain³⁵35. Dutra LS, Ferreira AP. Associação entre malformações congênitas e a utilização de agrotóxicos em monoculturas no Paraná, Brasil. Saúde Debate 2017; 41(2): 241-53. https://doi.org/10.1590/0103-11042017s220
https://doi.org/10.1590/0103-11042017s22... .

A possible limitation of the study concerns the incorrect or incomplete filling of information in death certificates in relation to the causes. There was no correction of rates for deaths due to ill-defined causes. However, deaths from these causes have decreased in recent decades in all Brazilian regions, especially in cities outside the capitals³⁶36. Silva GA, Gamarra CJ, Girianelli VR, Valente JG. Tendência da mortalidade por câncer nas capitais e interior do Brasil entre 1980 e 2006. Rev Saúde Pública 2011; 45(6): 1009-18. https://doi.org/10.1590/S0034-89102011005000076
https://doi.org/10.1590/S0034-8910201100... ^,3737. Frias PG, Szwarcwald CL, Lira PIC. Avaliação dos sistemas de informações sobre nascidos vivos e óbitos no Brasil na década de 2000. Cad Saúde Pública 2014; 30(10): 2068-280. https://doi.org/10.1590/0102-311X00196113
https://doi.org/10.1590/0102-311X0019611... . This has indicated an improvement in the quality of the information recorded in the SIM, especially for the group of malignant neoplasms, where the quality of information about the basic cause registered in the system can be considered better than that of other groups of causes³⁸38. Mello Jorge MH, Gotlieb SLD, Laurenti R. O sistema de informações sobre mortalidade: problemas e propostas para o seu enfrentamento I-mortes por causas naturais. Rev Bras Epidemiol 2002; 5(2): 197-211. https://doi.org/10.1590/S1415-790X2002000200007
https://doi.org/10.1590/S1415-790X200200... .

In 2015, the United Nations (UN) adopted a set of 17 goals as part of a sustainable development agenda. One of the goals is related to the reduction of premature mortality due to noncommunicable diseases through prevention and treatment. It has therefore become a global priority to monitor trends in mortality from these diseases, provided by quality information systems, in order to verify whether national and global commitments are being achieved³⁹39. United Nations (UN). Economic and Social Council [Internet]. New York: United Nations; 2019 [accessed on Jan. 28, 2020]. Available at: https://undocs.org/E/2019/68. Accessed 28 Jan 2020.
https://undocs.org/E/2019/68... .

Thus, the description of cancer mortality can bring important contributions to epidemiological studies based on the person-space-time triad. Studies of this magnitude are necessary, especially in Mato Grosso, since studies on this topic are scarce, and knowing this reality can potentially contribute to the identification of priority regions for intervention aiming to reduce mortality rates.

ACKNOWLEDGMENTS

To the Institute of Collective Health of Universidade Federal de Mato Grosso, for the opportunity to work and learn.

REFERENCES

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