The economic impact of cancer mortality among working-age individuals in Brazil from 2001 to 2030.

BACKGROUND: About half of cancer deaths in Brazil occur among individuals of working-age (under 65 years for men, under 60 for women), resulting in a substantial economic impact for the country. We aimed to estimate the years of potential productive life lost (YPPLL) and value the productivity lost due to premature deaths from cancer between 2001 and 2015 and the projected to 2030. METHODS: We used the Human Capital Approach to estimate the productivity losses corresponding to YPPLL for cancer deaths in working age people (15-64 years). Mortality data were obtained from the Mortality Information System from 2001 to 2015 and projected between 2016 and 2030. Economic data were obtained from the Continuous National Household Sample Survey and forecasted to 2030. Productivity lost was calculated as the monetary value arising from YPPLL in Int$(2016). RESULTS: Between 2001 and 2030, a total of 2.3 million premature deaths from all cancers combined were observed and forecasted in Brazil (57% men, 43% women), corresponding to 32 million YPPLL and Int$141.3 billion in productivity losses (men: Int$102.5 billion, women: Int$38.8 billion). Between 2001 and 2030, among men, lung (Int$ 12.6 billion), stomach (Int$ 10.6 billion) and colorectal (Int$ 9.4 billion) cancers were expected to contribute to the greatest productivity losses; and among women, it will be for breast (Int$ 10.0 billion), cervical (Int$ 6.4 billion) and colorectal (Int$ 3.2 billion) cancers. CONCLUSIONS: Many preventable cancers result in high lost productivity, suggesting measure to reduce smoking prevalence, alcohol consumption, physical inactivity and inadequate diet, improving screening programs and increasing vaccination coverage for human papillomavirus and hepatitis B would have a positive impact on the economy, as well as reducing morbidity and mortality from cancer.

Health, lifestyle and sociodemographic characteristics are associated with Brazilian dietary patterns: Brazilian National Health Survey.

This study aimed to identify Brazilian dietary patterns and their associations with health, lifestyle and sociodemographic characteristics. Data from the Brazilian National Health Survey conducted in 2013 were used. A questionnaire was applied containing 22 items related to dietary consumption. Dietary patterns were determined through factor analysis (FA). Poisson regression models, with robust variance, were used to identify associations between dietary patterns and independents variables. Statistical significance was defined as p-value<0.05. Data were analysed for 60,202 adults (estimated population size: 146,308,458). FA identified three dietary patterns: healthy, protein, and western. The younger age group (18-24 years) had a lower adherence to the healthy pattern (PR:0.53; 95%CI:0.49-0.58) and greater adherence to the protein (PR:1.52; 95%CI:1.42-1.62) and western (PR:1.80; 95%CI:1.68-1.93) patterns compared to the elderly (≥60 years). Women had a greater association with the healthy pattern (PR:1.32; 95%CI:1.28-1.38) and lower association with the protein pattern (PR:0.80; 95%CI:0.77-0.82) compared to men. Illiterate participants showed lower adherence to the healthy (PR:0.58; 95%CI:0.53-0.63) and western (PR:0.54; 95%CI:0.48-0.62) patterns compared to those with higher educational levels. Smokers had lower adherence to the healthy (PR:0.76; 95%CI:0.71-0.81) and higher adherence to the protein (PR:1.14; 95%CI:1.11-1.19) patterns compared to non-smokers. Participants with poor/very poor self-rated health status had a lower adherence to the healthy (PR:0.79; 95%CI:0.73-0.86) and western (PR:0.81; 95%CI:0.73-0.89) patterns compared to those in a very good/good self-rated health status. Multimorbidity was positively associated with the healthy pattern (PR:1.18; 95%CI:1.11-1.26) and inversely associated with the protein pattern (PR:0.88; 95%CI:0.80-0.96) compared to participants without comorbidities. We suggest that strategies to promote healthy eating should consider health, lifestyle and sociodemographic characteristics in the Brazilian population.