[Infant mortality and gender in Brazil: an investigation using updated statistics]

Taytiellen Fernandes Alves1, Alexandre Bragança Coelho1

  • 1Departamento de Economia Rural, Centro de Ciências Agrárias, Universidade Federal de Viçosa. Av. P. H. Rolfs s/n, Campus Universitário. 36571-000 Viçosa MG Brasil. taytiellen@hotmail.com.

Insights

Male infants in Brazil face higher mortality rates, but recent improvements are noted. Factors like income and prenatal care significantly reduce infant deaths, especially for males, highlighting their greater susceptibility.

Area of Science:

  • Public Health
  • Demography
  • Pediatrics

Background:

  • Male infant mortality in Brazil exceeds female mortality.
  • Recent trends show a reduction in excess male infant mortality.
  • Factors influencing this reduction require further investigation.

Purpose of the Study:

  • To analyze the impact of socioeconomic and healthcare factors on infant mortality in Brazil.
  • To investigate if these factors disproportionately affect male infant mortality.
  • To understand the drivers behind the declining excess male infant mortality.

Main Methods:

  • Utilized data from Brazilian states spanning 1996-2014.
  • Developed a model to assess the association between key variables and infant mortality.
  • Analyzed the influence of average income, low birth weight, prenatal visits, and fertility rate.

Main Results:

  • Average income, low birth weight, prenatal visits, and fertility rate are significant factors in Brazilian infant mortality.
  • These factors demonstrate a greater impact on reducing male infant mortality compared to female infant mortality.
  • Findings suggest male infants' higher susceptibility necessitates targeted health interventions.

Conclusions:

  • Socioeconomic status and healthcare access are crucial for reducing infant mortality in Brazil.
  • Male infants' vulnerability underscores the need for enhanced parental and health authority attention.
  • Further research on breastfeeding's role in mitigating gender-specific infant mortality is recommended.

Related Concept Videos

Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
157
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
919
Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
301
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
26.4K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
678
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
176