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Background: Socioeconomic conditions are strongly associated with breast and cervical cancer incidence and mortality patterns; therefore, social protection programmes (SPPs) might impact these cancers. This study aimed to evaluate the effect of SPPs on breast and cervical cancer outcomes and their risk/protective factors. Methods: Five databases were searched for articles that assessed participation in PPS and the incidence, survival, mortality (primary outcomes), screening, staging at diagnosis and risk/protective factors (secondary outcomes) for these cancers. Only peer-reviewed quantitative studies of women receiving SPPs compared to eligible women not receiving benefits were included. Independent reviewers selected articles, assessed eligibility, extracted data, and assessed the risk of bias. A harvest plot represents the included studies and shows the direction of effect, sample size and risk of bias. Findings: Of 17,080 documents retrieved, 43 studies were included in the review. No studies evaluated the primary outcomes. They all examined the relationship between SPPs and screening, as well as risk and protective factors. The harvest plot showed that in lower risk of bias studies, participants of SPPs had lower weight and fertility, were older at sexual debut, and breastfed their infants for longer. Interpretation: No studies have yet assessed the effect of SPPs on breast and cervical cancer incidence, survival, or mortality; nevertheless, the existing evidence suggests positive impacts on risk and protective factors.
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BACKGROUND: Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030. METHODS: We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030. RESULTS: The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil's municipalities was observed, with a persistent sex differential. CONCLUSION: Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning.
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Teorema de Bayes , Cidades , Expectativa de Vida , Mortalidade , Humanos , Brasil/epidemiologia , Masculino , Feminino , Mortalidade/tendências , Lactente , Pré-Escolar , Idoso , Pessoa de Meia-Idade , Adolescente , Adulto , Criança , Adulto Jovem , Recém-Nascido , Idoso de 80 Anos ou mais , Fatores Sexuais , Distribuição por Idade , Fatores Etários , Distribuição por Sexo , PrevisõesRESUMO
OBJECTIVES: There is limited evidence regarding the impact of race/racism and its intersection with socioeconomic status (SES) on breast and cervical cancer, the two most common female cancers globally. We investigated racial inequalities in breast and cervical cancer mortality and whether SES (education and household conditions) interacted with race/ethnicity. DESIGN: The 100 Million Brazilian Cohort data were linked to the Brazilian Mortality Database, 2004-2015 (n = 20,665,005 adult women). We analysed the association between self-reported race/ethnicity (White/'Parda'(Brown)/Black/Asian/Indigenous) and cancer mortality using Poisson regression, adjusting for age, calendar year, education, household conditions and area of residence. Additive and multiplicative interactions were assessed. RESULTS: Cervical cancer mortality rates were higher among Indigenous (adjusted Mortality rate ratio = 1.80, 95%CI 1.39-2.33), Asian (1.63, 1.20-2.22), 'Parda'(Brown) (1.27, 1.21-1.33) and Black (1.18, 1.09-1.28) women vs White women. Breast cancer mortality rates were higher among Black (1.10, 1.04-1.17) vs White women. Racial inequalities in cervical cancer mortality were larger among women of poor household conditions, and low education (P for multiplicative interaction <0.001, and 0.02, respectively). Compared to White women living in completely adequate (3-4) household conditions, the risk of cervical cancer mortality in Black women with 3-4, 1-2, and none adequate conditions was 1.10 (1.01-1.21), 1.48 (1.28-1.71), and 2.03 (1.56-2.63), respectively (Relative excess risk due to interaction-RERI = 0.78, 0.18-1.38). Among 'Parda'(Brown) women the risk was 1.18 (1.11-1.25), 1.68 (1.56-1.81), and 1.84 (1.63-2.08), respectively (RERI = 0.52, 0.16-0.87). Compared to high-educated White women, the risk in high-, middle- and low-educated Black women was 1.14 (0.83-1.55), 1.93 (1.57-2.38) and 2.75 (2.33-3.25), respectively (RERI = 0.36, -0.05-0.77). Among 'Parda'(Brown) women the risk was 1.09 (0.91-1.31), 1.99 (1.70-2.33) and 3.03 (2.61-3.52), respectively (RERI = 0.68, 0.48-0.88). No interactions were found for breast cancer. CONCLUSION: Low SES magnified racial inequalities in cervical cancer mortality. The intersection between race/ethnicity, SES and gender needs to be addressed to reduce racial health inequalities.
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Neoplasias da Mama , Desigualdades de Saúde , Neoplasias do Colo do Útero , Adulto , Feminino , Humanos , Brasil/epidemiologia , Neoplasias da Mama/mortalidade , Etnicidade , Classe Social , Fatores Socioeconômicos , Neoplasias do Colo do Útero/mortalidade , Grupos RaciaisRESUMO
OBJECTIVE: To estimate the prevalence of adult smokers in the 26 capitals and the Federal District according to the Brazilian Deprivation Index (Índice Brasileiro de Privação - IBP). METHODS: Dataset on smoking were obtained from the Surveillance of Risk and Protective Factors for Noncommunicable Diseases by Survey (Vigitel) system for the 26 capitals and the Federal District, in the period from 2010 to 2013. The IBP classifies the census sectors according to indicators such as: income less than ½ minimum wage, illiterate population and without sanitary sewage. In the North and Northeast regions, the census sectors were grouped into four categories (low, medium, high and very high deprivation) and in the South, Southeast and Midwest regions into three (low, medium and high deprivation). Prevalence estimates of adult smokers were obtained using the indirect estimation method in small areas. To calculate the prevalence ratios, Poisson models are used. RESULTS: The positive association between prevalence and deprivation of census sector categories was found in 16 (59.3%) of the 27 cities. In nine (33.3%) cities, the sectors with the greatest deprivation had a higher prevalence of smokers when compared to those with the least deprivation, and in two (7.4%) there were no differences. In Aracaju, Belém, Fortaleza, João Pessoa, Macapá and Salvador, the prevalence of adult smokers was three times higher in the group of sectors with greater deprivation compared to those with less deprivation. CONCLUSION: Sectors with greater social deprivation had a higher prevalence of smoking, compared with less deprivation, pointing to social inequalities.
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Fumantes , Fumar , Humanos , Adulto , Brasil/epidemiologia , Prevalência , Fumar/epidemiologia , Fatores SocioeconômicosRESUMO
INTRODUCTION: There is a limited understanding of the early nutrition and pregnancy determinants of short-term and long-term maternal and child health in ethnically diverse and socioeconomically vulnerable populations within low-income and middle-income countries. This investigation programme aims to: (1) describe maternal weight trajectories throughout the life course; (2) describe child weight, height and body mass index (BMI) trajectories; (3) create and validate models to predict childhood obesity at 5 years of age; (4) estimate the effects of prepregnancy BMI, gestational weight gain (GWG) and maternal weight trajectories on adverse maternal and neonatal outcomes and child growth trajectories; (5) estimate the effects of prepregnancy BMI, GWG, maternal weight and interpregnancy BMI changes on maternal and child outcomes in the subsequent pregnancy; and (6) estimate the effects of maternal food consumption and infant feeding practices on child nutritional status and growth trajectories. METHODS AND ANALYSIS: Linked data from four different Brazilian databases will be used: the 100 Million Brazilian Cohort, the Live Births Information System, the Mortality Information System and the Food and Nutrition Surveillance System. To analyse trajectories, latent-growth, superimposition by translation and rotation and broken stick models will be used. To create prediction models for childhood obesity, machine learning techniques will be applied. For the association between the selected exposure and outcomes variables, generalised linear models will be considered. Directed acyclic graphs will be constructed to identify potential confounders for each analysis investigating potential causal relationships. ETHICS AND DISSEMINATION: This protocol was approved by the Research Ethics Committees of the authors' institutions. The linkage will be carried out in a secure environment. After the linkage, the data will be de-identified, and pre-authorised researchers will access the data set via a virtual private network connection. Results will be reported in open-access journals and disseminated to policymakers and the broader public.
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Trajetória do Peso do Corpo , Obesidade Infantil , Criança , Lactente , Recém-Nascido , Feminino , Gravidez , Humanos , Obesidade Infantil/epidemiologia , Brasil/epidemiologia , Fenômenos Fisiológicos da Nutrição Infantil , FamíliaRESUMO
INTRODUCTION: Housing-related factors can be predictors of health, including of diabetes outcomes. We analysed the association between subsidised housing residency and diabetes mortality among a large cohort of low-income adults in Brazil. RESEARCH DESIGN AND METHODS: A cohort of 9 961 271 low-income adults, observed from January 2010 to December 2015, was created from Brazilian administrative records of social programmes and death certificates. We analysed the association between subsidised housing residency and time to diabetes mortality using a Cox model with inverse probability of treatment weighting and regression adjustment. We assessed inequalities in this association by groups of municipality Human Development Index. Diabetes mortality included diabetes both as the underlying or a contributory cause of death. RESULTS: At baseline, the mean age of the cohort was 40.3 years (SD 15.6 years), with a majority of women (58.4%). During 29 238 920 person-years of follow-up, there were 18 775 deaths with diabetes as the underlying or a contributory cause. 340 683 participants (3.4% of the cohort) received subsidised housing. Subsidised housing residents had a higher hazard of diabetes mortality compared with non-residents (HR 1.17; 95% CI 1.05 to 1.31). The magnitude of this association was more pronounced among participants living in municipalities with lower Human Development Index (HR 1.30; 95% CI 1.04 to 1.62). CONCLUSIONS: Subsidised housing residents had a greater risk of diabetes mortality, particularly those living in low socioeconomic status municipalities. This finding suggests the need to intensify diabetes prevention and control actions and prompt treatment of the diabetes complications among subsidised housing residents, particularly among those living in low socioeconomic status municipalities.
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Diabetes Mellitus , Habitação , Humanos , Adulto , Feminino , Brasil/epidemiologia , Estudos Retrospectivos , Diabetes Mellitus/epidemiologiaRESUMO
ABSTRACT Objective: To analyze premature mortality due to noncommunicable chronic diseases (NCDs) in Brazilian capitals and the Federal District (DF) after redistribution of garbage causes and the temporal evolution according to social deprivation strata in the 2010 to 2012 and 2017 to 2019 triennia. Methods: Corrections were applied to the Mortality Information System (Sistema de Informação sobre Mortalidade - SIM) data such as the redistribution of garbage codes (GC). Premature mortality rates due to NCDs were calculated and standardized by age. The differences among NCDs mortality rates were analyzed according to the Brazilian Deprivation Index (Índice Brasileiro de Privação - IBP) categories and between the three-year periods. Results: In the capitals as a whole, rates increased between 8 and 12% after GC redistribution and the greatest increases occurred in areas of high deprivation: 11.9 and 11.4%, triennia 1 and 2, respectively. There was variability between the capitals. There was a reduction in rates in all strata of deprivation between the three-year periods, with the greatest decrease in the stratum of low deprivation (-18.2%) and the lowest in the stratum of high deprivation (-7.5%). Conclusion: The redistribution of GC represented an increase in mortality rates, being higher in the strata of greater social deprivation. As a rule, a positive gradient of mortality was observed with increasing social deprivation. The analysis of the temporal evolution showed a decrease in mortality from NCDs between the triennia, especially in areas of lower social deprivation.
RESUMO Objetivo: Analisar a mortalidade prematura por doenças crônicas não transmissíveis (DCNT) nas capitais brasileiras e Distrito Federal (DF) após redistribuição das causas garbage, e a evolução temporal segundo estratos de privação social nos triênios 2010 a 2012 e 2017 a 2019. Métodos: Foram aplicadas correções ao Sistema de Informação sobre Mortalidade (SIM), sendo empregada metodologia para redistribuição das causas garbage (CG). As taxas de mortalidade prematura por DCNT padronizadas por idade foram estimadas. Foram analisadas as diferenças entre as taxas de mortalidade por DCNT segundo categorias do Índice Brasileiro de Privação (IBP) e entre os triênios. Resultados: No conjunto das capitais, as taxas aumentaram entre 8 e 12% após a redistribuição de CG, e os maiores acréscimos ocorreram em áreas de alta privação: 11,9 e 11,4%, triênios 1 e 2, respectivamente. Houve variabilidade entre as capitais. Observou-se redução das taxas em todos os estratos de privação entre os triênios, sendo maior decréscimo no estrato de baixa privação (-18,2%), e menor no estrato de alta privação (-7,5%). Conclusão: A redistribuição de CG representou aumento das taxas de mortalidade, sendo maior nos estratos de maior privação social. Via de regra, observou-se gradiente positivo de mortalidade com o aumento da privação social. A análise da evolução temporal evidenciou decréscimo da mortalidade por DCNT entre os triênios, sobretudo em áreas de menor privação social.
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ABSTRACT Objective: To estimate the prevalence of adult smokers in the 26 capitals and the Federal District according to the Brazilian Deprivation Index (Índice Brasileiro de Privação - IBP). Methods: Dataset on smoking were obtained from the Surveillance of Risk and Protective Factors for Noncommunicable Diseases by Survey (Vigitel) system for the 26 capitals and the Federal District, in the period from 2010 to 2013. The IBP classifies the census sectors according to indicators such as: income less than ½ minimum wage, illiterate population and without sanitary sewage. In the North and Northeast regions, the census sectors were grouped into four categories (low, medium, high and very high deprivation) and in the South, Southeast and Midwest regions into three (low, medium and high deprivation). Prevalence estimates of adult smokers were obtained using the indirect estimation method in small areas. To calculate the prevalence ratios, Poisson models are used. Results: The positive association between prevalence and deprivation of census sector categories was found in 16 (59.3%) of the 27 cities. In nine (33.3%) cities, the sectors with the greatest deprivation had a higher prevalence of smokers when compared to those with the least deprivation, and in two (7.4%) there were no differences. In Aracaju, Belém, Fortaleza, João Pessoa, Macapá and Salvador, the prevalence of adult smokers was three times higher in the group of sectors with greater deprivation compared to those with less deprivation. Conclusion: Sectors with greater social deprivation had a higher prevalence of smoking, compared with less deprivation, pointing to social inequalities.
RESUMO Objetivo: Estimar as prevalências de adultos fumante nas 26 capitais e no Distrito Federal segundo o Índice Brasileiro de Privação. Métodos: Os dados sobre tabagismo foram obtidos junto ao sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito (Vigitel) para as 26 capitais e o Distrito Federal, no período de 2010 a 2013. O Índice Brasileiro de Privação classifica os setores censitários segundo indicadores como: renda menor que meio salário mínimo, população não alfabetizada e sem esgotamento sanitário. Nas regiões Norte e Nordeste, os setores censitários foram agrupados em quatro categorias (baixa, média, alta e muito alta privação) e, nas regiões Sul, Sudeste e Centro-Oeste, em três (baixa, média e alta privação). As estimativas de prevalências de adultos fumantes foram obtidas pelo método indireto de estimação em pequenas áreas. Para o cálculo das razões de prevalências, empregram-se modelos de Poisson. Resultados: A associação positiva entre a prevalência e a privação das categorias de setores censitários foi encontrada em 16 (59,3%) das 27 cidades. Em nove (33,3%) cidades, os setores de maior privação apresentaram maior prevalência de fumantes quando comparados aos de menor privação e, em duas (7,4%), não apresentaram diferenças. Em Aracaju, Belém, Fortaleza, João Pessoa, Macapá e Salvador, as prevalências de adultos fumantes foram três vezes maiores no grupo de setores com maior privação em relação aos de menor privação. Conclusão: Setores de maior privação social apresentaram maiores prevalências de tabagismo, comparados com menor privação, apontando desigualdades sociais.
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Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.
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Registro Médico Coordenado , Humanos , Viés , Estudos Epidemiológicos , Bases de Dados Factuais , Brasil/epidemiologiaRESUMO
OBJECTIVE: Summarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil. METHODS: This scoping review included articles published between January 1, 2000, and August 31, 2020, retrieved by means of a bibliographic search carried out in the Medline, Scopus, Web of Science, and Lilacs databases. Studies reporting on the association between composite socioeconomic indicators and all-cause, or specific cause of death in any age group in different geographical areas were selected. The review summarized the measures constructed, their associations with the outcomes, and potential study limitations. RESULTS: Of the 77 full texts that met the inclusion criteria, the study reviewed 24. The area level of composite socioeconomic indicators analyzed comprised municipalities (n = 6), districts (n = 5), census tracts (n = 4), state (n = 2), country (n = 2), and other areas (n = 5). Six studies used composite socioeconomic indicators such as the Human Development Index, Gross Domestic Product, and the Gini Index; the remaining 18 papers created their own socioeconomic measures based on sociodemographic and health indicators. Socioeconomic status was inversely associated with higher rates of all-cause mortality, external cause mortality, suicide, homicide, fetal and infant mortality, respiratory and circulatory diseases, stroke, infectious and parasitic diseases, malnutrition, gastroenteritis, and oropharyngeal cancer. Higher mortality rates due to colorectal cancer, leukemia, a general group of neoplasms, traffic accident, and suicide, in turn, were observed in less deprived areas and/or those with more significant socioeconomic development. Underreporting of death and differences in mortality coverage in Brazilian areas were cited as the main limitation. CONCLUSIONS: Studies analyzed mortality inequalities in different geographical areas by means of composite socioeconomic indicators, showing that the association directions vary according to the mortality outcome. But studies on all-cause mortality and at the census tract level remain scarce. The results may guide the development of new composite socioeconomic indicators for use in mortality inequality analysis.