Soil-app: a tool for soil analysis interpretation

New apps have changed the traditional way of learning and teaching; they are also applied as a quickly executed and effective method in agriculture. Soil-app is a web application with a friendly click-point interface built through packages lodged in R software. The app is an advanced model of an open-source platform to support teaching and learning activities in soil analyses and fertilizer recommendations. Soil-app includes soil test interpretation, soil amendment calculations (lime and gypsum), the fertilizer rate for the most important crops in Brazil, an NPK blend calculator, and NPK blend evaluation. It also includes experimental statistical analysis as applied to soil science. Soil-app is a user-friendly and high-performance tool, garnering fast adoption by both students and professionals. It is available for network use through the following link: http://www.genetica.esalq.usp.br/alogamas/R.htm

Diferenciais de mortalidade, beneficiários do Instituto Nacional do Seguro Social do Brasil em 2015

Este trabalho tem por objetivo estimar a mortalidade e analisar seus diferenciais por sexo, idade e grupos de beneficiários do Instituto Nacional de Seguro Social (INSS) brasileiro em 2015 e fazer comparações com estimativas oficiais para a população geral, avaliando a distribuição dos óbitos por idade e da sobrevida a partir dos 65 anos. Os resultados reforçam a necessidade de mais estudos sobre diferenciais de mortalidade entre grupos de beneficiários e do contínuo investimento para a melhoria da qualidade dos dados. O envelhecimento populacional, entre outros aspectos, pressiona o sistema de previdência social brasileiro, com preocupação real sobre sua sustentabilidade. As tábuas de vida por subgrupos populacionais são fundamentais como ferramenta para análise do equilíbrio financeiro e atuarial do sistema. Os resultados contribuem para o debate sobre os diferenciais de mortalidade entre grupos de beneficiários do regimente geral de previdência e da seguridade social no Brasil. Os dados de óbitos e população são dos registros administrativos do INSS. Utilizaram-se os modelos Gompertz e Van der Maen e regressão Topals para estimar as taxas de mortalidade acima de 65 anos, segundo os seguintes grupos de beneficiários: aposentados por idade do Regime Geral de Previdência Social (RGPS) – desagregados por clientelas urbana e rural; aposentados por tempo de contribuição; e beneficiários de amparos assistenciais para idosos de baixa renda. Entre os principais resultados, foi possível minimizar o crossover nas taxas de mortalidade das idades avançadas, quando a mortalidade da população menos favorecida se torna menor do que a mortalidade de populações com melhores indicadores sociais. Cotejando os resultados com as estimativas oficiais de mortalidade, observou-se que as esperanças de vida para as idades de 65 e 75 anos para a população-alvo desse estudo são maiores do que na população geral.This paper aims to estimate mortality and analyze its differentials by sex, age, and groups of beneficiaries of the Brazilian National Institute of Social Security (INSS) in 2015 and make comparisons with official estimates for the general population, assessing the distribution of deaths by age and of survival after 65 years old. The results reinforce the need for more studies on mortality differentials between beneficiary groups and for continuous investment to improve the quality of the data. Population aging, among other aspects, puts pressure on the Brazilian social security system, and there is real concern about its sustainability. Life tables by population subgroups are fundamental as a tool for analyzing the financial and actuarial equilibrium of the system. The results contribute to the debate on the mortality differentials between groups of beneficiaries of the general pension and social security system in Brazil. The death and population data derive from the administrative records of the INSS. We used Gompertz and Van de Maen models and Topals regression to estimate the mortality rates above the age of 65, according to the following beneficiary groups: retirees through age of the General Social Security Regime (Regime Geral de Previdência Social – RGPS) – disaggregated by urban and rural clienteles; retirees through period of contribution; and beneficiaries of welfare support for low income seniors. Among the main results, it was possible to minimize the crossover in the mortality rates of older ages, when the mortality of the less advantaged population becomes lower than the mortality of populations with better social indicators. Cross-checking the results with the official mortality estimates, it was observed that life expectancies for the 65 and 75 year old age groups of the target population of this study are higher than in the general population

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

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