Social Inequalities in Child Development: Analysis of Low-Birth-Weight Trends in Brazil, 2010-2020.

INTRODUCTION: Low birth weight (LBW) is a global issue prevalent in low-income countries. Economic assessments of interventions to reduce this burden are crucial to guide health policies. However, there is a relative scarcity of research that illustrates the magnitude of LBW by country and region to support the design of public policies. OBJECTIVE: This study aimed to analyze the temporal trend of fetal growth in newborns in Brazil between 2010 and 2020. METHODS: A time series study was conducted using data from the Live Births Information System (SINASC), which is managed by the Department of Information and Informatics of the Unified Health System (DATASUS) of the Brazilian Ministry of Health. The Prais-Winsten linear model was applied to analyze the annual proportions of LBW. The annual percentage changes (APC) and their respective 95% confidence intervals (95%CI) were calculated. Prevalence rate averages of LBW were calculated and displayed on thematic maps to visualize the evolution dynamics in each Federation Unit (FU). RESULTS: A total of 31,887,329 women from all Federative Units of Brazil were included in the study from 2010 to 2020. The Southeast region had the largest proportion of participants, with records from 2015 accounting for 9.5% of the total. Among the women in the study, 49.6% were between the ages of 20 and 29, and the majority (75.5%) had between 8 and 12 years of schooling. The newborns of these women were predominantly male (58.8%) and non-white (59.5%). The study found that there was a trend towards stabilization of increasing proportions of LBW in the North, Northeast, and Centre-West regions between 2010 and 2020. In Brazil and other regions, these tendencies remained stable. CONCLUSION: To improve living conditions and reduce social inequalities and health inequities, public policies and actions are necessary. Strengthening the Unified Health System (SUS), income transfer programs, quota policies for vulnerable groups, and gender equality measures such as improving access to education for women and the labor sector are among the suggested approaches.

Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review.

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.

Differentials in death count records by databases in Brazil in 2010.

OBJECTIVE: To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM - Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC - Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count. METHODS: This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators - the Índice de Privação Brasileiro (IBP - Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM - Municipal Human Development Index) - was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps. RESULTS: Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country. CONCLUSION: The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire.

Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review

ABSTRACT 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.

Differentials in death count records by databases in Brazil in 2010

ABSTRACT OBJECTIVE To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM - Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC - Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count. METHODS This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators - the Índice de Privação Brasileiro (IBP - Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM - Municipal Human Development Index) - was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps. RESULTS Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country. CONCLUSION The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire.