Determinants of infant mortality trends in developing countries—some evidence from São Paulo city

1989 ◽  
Vol 83 (1) ◽  
pp. 5-9 ◽  
Author(s):  
Carlos Augusto Monteiro ◽  
Maria Helena D'Aquino Benicio
Keyword(s):  
Developing Countries ◽  
Infant Mortality ◽  
Sao Paulo ◽  
São Paulo ◽  
Mortality Trends

scholarly journals Determinants of neonatal, postneonatal and maternal mortality on models of primary health

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A B Guerra ◽  
L M Guerra ◽  
L F Probst ◽  
B V Castro Gondinho ◽  
G M Bovi Ambrosano ◽  
...  
Keyword(s):  
Health Care ◽  
Infant Mortality ◽  
Maternal Mortality ◽  
Public Policies ◽  
Family Health ◽  
Mortality Rates ◽  
Sao Paulo ◽  
The State ◽  
Care Organization ◽  
São Paulo

Abstract Background The state of São Paulo recorded a significant reduction in infant mortality, but the desired reduction in maternal mortality was not achieved. Knowledge of the factors with impact on these indicators would be of help in formulating public policies. The aims of this study were to evaluate the relations between socioeconomic and demographic factors, health care model and both infant mortality and maternal mortality in the state of São Paulo, Brazil. Methods In this ecological study, data from national official open sources were used. Analyzed were 645 municipalities in the state of São Paulo, Brazil. For each municipality, the infant mortality and maternal mortality rates were calculated for every 1000 live births, 2013. The association between these rates, socioeconomic variables, demographic models and the primary care organization model in the municipality were verified. We used the zero-inflated negative binomial model. Gross analysis was performed and then multiple regression models were estimated. For associations, we adopted “p” at 5%. Results The increase in the HDI of the city and proportion of Family Health Care Strategy implemented were significantly associated with the reduction in both infant mortality (neonatal + post-neonatal) and maternal mortality rates. In turn, the increase in birth and caesarean delivery rates were associated with the increase in infant and maternal mortality rates. Conclusions It was concluded that the Family Health Care Strategy model that contributed to the reduction in infant (neonatal + post-neonatal) and maternal mortality rates, and so did actors such as HDI and cesarean section. Thus, public health managers should prefer this model. Key messages Implementation of public policies with specific focus on attenuating these factors and making it possible to optimize resources, and not interrupting the FHS. Knowledge of the factors with impact on these indicators would be of help in formulating public policies.

Educating and Training Undergraduate Applied Statisticians

1985 ◽  
Vol 10 (3) ◽  
pp. 283-292
Author(s):  
Clovis A. Peres ◽  
Pedro A. Morettin ◽  
Subhash C. Narula
Keyword(s):  
Developing Countries ◽  
Sao Paulo ◽  
Applied Statistics ◽  
São Paulo ◽  
Statistical Work ◽  
And Training

A course on Applied Statistics, offered since 1978 at the Instituto de Matemática e Estatística, Universidade de São Paulo, Brasil, is designed to educate statisticians at the bachelor’s level for jobs in government statistical offices, industry, and business. Because most of the statistical work at these places is carried out by bachelor’s level individuals, such a course is almost mandatory for developing countries and may be useful for other countries. Our objective is to share our experience with the course.

The Political Economy of Infant Mortality in São Paulo, Brazil

1982 ◽  
Vol 12 (2) ◽  
pp. 215-229 ◽  
Author(s):  
Charles H. Wood
Keyword(s):  
Infant Mortality ◽  
Urban Poor ◽  
Death Rate ◽  
Vital Statistics ◽  
Sao Paulo ◽  
Purchasing Power ◽  
São Paulo ◽  
Mortality Trend ◽  
Wide Range ◽  
The Government

After the military took power in Brazil in 1964, the government adopted a wide range of policies designed to stimulate economic growth. A central aspect of the Brazilian model of development was the control of wages. From 1964 to 1975 this strategy caused the purchasing power of the minimum wage in the city of São Paulo to fall. The decline in the real wage index was associated with a rise in infant mortality during the period. When real wages rose after 1974, the death rate dropped off. The infant mortality trend cannot be explained by other factors that affect the actual or the reported death rate, such as changes in cityward migration, shifts in the distribution of income, and improvements in the quality of vital statistics. The findings of this study indicate a causal relationship between the infant mortality trend and changes in the purchasing power of the urban poor. Additional data on nutrition, changes in household behavior, and shifts in the cause structure of mortality support this conclusion.

scholarly journals Infant mortality in the Metropolitan Region of São Paulo: an ecological study

2021 ◽  
Vol 19 ◽  
Author(s):  
Michele Ribeiro Alexandre Nunes ◽  
Luiz Vinicius de Alcantara Sousa ◽  
Vânia Barbosa do Nascimento
Keyword(s):  
Infant Mortality ◽  
Ecological Study ◽  
Sao Paulo ◽  
Metropolitan Region ◽  
São Paulo

Income inequalities and stroke mortality trends in Sao Paulo, Brazil, 1996-2011

2015 ◽  
Vol 10 (SA100) ◽  
pp. 34-37 ◽  
Author(s):  
Tiótrefis G. Fernandes ◽  
Daniel H. Bando ◽  
Airlane P. Alencar ◽  
Isabela M. Benseñor ◽  
Paulo A. Lotufo
Keyword(s):  
Sao Paulo ◽  
São Paulo ◽  
Stroke Mortality ◽  
Mortality Trends ◽  
Income Inequalities

Developing Gerontology in a Developing Country: The Case of Sao Paulo, Brazil

1978 ◽  
Vol 8 (4) ◽  
pp. 325-337 ◽  
Author(s):  
Patricia L. Kasschau
Keyword(s):  
Developing Countries ◽  
Labor Market ◽  
Knowledge Base ◽  
Developing Country ◽  
Financial Support ◽  
Sao Paulo ◽  
São Paulo ◽  
European Context

This paper details the efforts of a team of professionals to establish a gerontology center in Sao Paulo, Brazil. The focus is on some of the problems of the emergent profession in Brazil: the uncertain labor market; the problems of recruiting; the problems of generating a knowledge base on aging drawn from Brazil rather than borrowed from the American or European context; the problems of visibility, legitimacy, and financial support for the new gerontology center; the competition of aging programs with other government priorities. The article concludes by citing some benefits that might accrue to the field of gerontology by underwriting the development of such centers on aging in the developing countries.

scholarly journals Alcohol use among fatally injured victims in São Paulo, Brazil: bridging the gap between research and health services in developing countries

Addiction ◽  
2017 ◽  
Vol 112 (4) ◽  
pp. 596-603 ◽  
Author(s):  
Gabriel Andreuccetti ◽  
Vilma Leyton ◽  
Nikolas P. Lemos ◽  
Ivan Dieb Miziara ◽  
Yu Ye ◽  
...  
Keyword(s):  
Developing Countries ◽  
Alcohol Use ◽  
Health Services ◽  
Sao Paulo ◽  
São Paulo

scholarly journals Machine Learning to Predict Neonatal Mortality Using Public Health Data from São Paulo - Brazil

2020 ◽  
Author(s):  
Carlos Eduardo Beluzo ◽  
Luciana Correia Alves ◽  
Everton Silva ◽  
Rodrigo Bresan ◽  
Natália Arruda ◽  
...  
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Infant Mortality ◽  
Neonatal Mortality ◽  
Sao Paulo ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
São Paulo ◽  
Health Quality ◽  
Health Features

AbstractInfant mortality is one of the most important socioeconomic and health quality indicators in the world. In Brazil, neonatal mortality accounts to 70% of the infant mortality. Despite its importance, neonatal mortality shows increasing signals, which causes concerns about the necessity of efficient and effective methods able to help reducing it. In this paper a new approach is proposed to classify newborns that may be susceptible to neonatal mortality by applying supervised machine learning methods on public health features. The approach is evaluated in a sample of 15,858 records extracted from SPNeoDeath dataset, which were created on this paper, from SINASC and SIM databases from São Paulo city (Brazil) for this paper intent. As a results an average AUC of 0.96 was achieved in classifying samples as susceptible to death or not with SVM, XGBoost, Logistic Regression and Random Forests machine learning algorithms. Furthermore the SHAP method was used to understand the features that mostly influenced the algorithms output.

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