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Gender gap in life expectancy: the impact of mortality from external causes in Minas Gerais (1980-2018)

Hisrael Passarelli-Araujo – Passarelli-Araujo, Hisrael
Universidade Federal de Minas Gerais (UFMG)
Email: hisraelpassarelli@gmail.com
ORCID: https://orcid.org/0000-0003-3534-8392


Larissa Gonçalves Souza – Souza, Larissa Gonçalves
Universidade Federal de Alfenas (Unifal-MG)
Email: larissa.souza@unifal-mg.edu.br
ORCID: https://orcid.org/0000-0003-3536-3912


Pamila Cristina Lima Siviero – Siviero, Pamila Cristina Lima
Universidade Federal de São Paulo (Unifesp)
Email: pamila.siviero@unifesp.br
ORCID: https://orcid.org/0000-0003-2042-812X

Abstract: The gender gap in life expectancy reflects broader social inequalities. Despite advances in longevity, gender disparities persist, especially in mortality from external causes. These often-preventable causes raise the male mortality rate. In Minas Gerais, the extent and nature of these disparities and the impact of external causes have not been adequately explored. This study examines the impact of mortality from external causes on the gender gap in life expectancy in Minas Gerais from 1980 to 2018. Using scenarios of mortality reduction from external causes (25%, 50%, 75%, and total elimination), the study calculates the change generated by different scenarios in life expectancy at birth. Death data were combined with population data to calculate multiple decrement life tables. The results suggest that reducing external causes significantly decreases the gender gap in life expectancy. Eliminating 25% of external causes would already reduce the male disadvantage, with more pronounced gains as the proportion of eliminated causes increases. In a scenario of total elimination, the male disadvantage would drop drastically, also reflecting changes in the social and cultural norms that perpetuate these practices.
Keywords: Mortality Differentials; Gender; External Causes; Minas Gerais

Introduction
The gender gap in life expectancy is a key indicator of broader social inequalities, including economic disparities, healthcare access, and social status 1–3. Despite overall improvements in life expectancy, this gap persists, particularly due to mortality from external causes such as accidents, homicides, and suicides 4. These preventable causes heavily contribute to higher male mortality worldwide 5,6.
Studying the gender gap requires clarifying some fundamental concepts, such as the distinction between "sex" and "gender". While "sex" refers to the biological and physiological characteristics that differentiate men and women, "gender" relates to the socially constructed roles, behaviors, and expectations attributed to each sex 7–9. This distinction is crucial because social and cultural norms strongly influence the risk behaviors leading to mortality 10, especially from external causes. For instance, norms of masculinity that value courage and competitiveness drive men to engage in riskier behaviors, which are more closely tied to social expectations than biological factors 11. Therefore, the term "gender gap" is more appropriate to describe the difference in life expectancy between men and women, capturing the complexity of these influences on mortality.
Mortality from external causes remains a significant concern in Brazil. Since 1980, these causes have shifted age-specific mortality rates, cutting years from life expectancy 12. In São Paulo, for example, a study revealed that preventable deaths, particularly those caused by external factors, significantly contributed to the gender gap in life expectancy between men and women from 2014 to 2016 13. These findings highlight the persistence of gender disparities in preventable mortality, posing challenges for health policies and initiatives aimed at reducing inequalities among specific population groups 13,14.
In Minas Gerais, one of Brazil\'s most populous and diverse states 15, the impact of external causes on the gender gap in life expectancy at birth has not been extensively studied. Between 1999 and 2008, male mortality from external causes rose from 82.7 to 95.7 deaths per 100,000 inhabitants, a 15.7% increase 16. Studies have also shown that the leading causes of death were traffic accidents, suicides, and homicides, with most victims being young adult men aged 20–39 16. More recently, external cause mortality in Minas Gerais was about 68 deaths per 100,000 in 2022 17.
Moreover, previous research has analyzed the profile of deaths from external causes among specific population subgroups, such as the older adults in Minas Gerais18, while others have examined the quality of mortality data related to these causes in the state 19. However, the effect of external causes on the gender gap in life expectancy at birth remains unclear. This gap limits understanding of how external deaths shape mortality differences and how trends evolved over decades. Addressing this issue is essential for designing public health strategies to reduce gender disparities.
This article examines the impact of mortality from external causes on the gender gap in life expectancy in Minas Gerais from 1980 to 2018. Simulating distinct scenarios of mortality reduction has been an effective strategy employed in various studies 20–22, proving to be a valuable tool for assessing health policies, resource planning, comparing interventions, and understanding the complex interactions between health determinants. Moreover, working with different scenarios is crucial, as it is practically impossible to completely eliminate mortality from these causes. Simulating such scenarios provides concrete data that can assist public health policies.

Data and methods
This study relied on population data from 1980 and 2000, disaggregated by age and gender, obtained from Brazilian demographic censuses. The 2018 data resulted from population projections conducted by the Instituto Brasileiro de Geografia e Estatística (IBGE). Mortality data for all causes and external causes, disaggregated by age group and gender, were sourced from the Mortality Information System (SIM) through the Department of Informatics of the Unified Health System (DATASUS).
Mortality data were collected for the three-year periods 1979–1981, 1999–2001, and 2017–2019. The average number of deaths for each period was used to represent age-specific mortality for 1980, 2000, and 2018, reducing random fluctuations in the data. The final period was chosen to avoid the effects of the COVID-19 pandemic, which began in 2020 and caused a temporary rise in mortality. In Minas Gerais, mortality registration was nearly complete from 1980 to 2010, so no correction for underreporting was necessary.
From 1979 to 1995, death certificates were coded using the 9th Revision of the International Classification of Diseases (ICD-9), with external causes classified under Chapter XVII (E800–E999). Since 1996, the 10th Revision (ICD-10) has been used, with external causes classified under Chapter XX (V01–Y98). The transition from ICD-9 to ICD-10 in 1996 showed no abnormal fluctuations in external cause mortality, so the original data were used without adjustment for classification differences.
To analyze the age-specific gender gap in mortality, age-specific mortality rates for men and women were calculated for all causes and external causes. The sex ratio of age-specific mortality rates for external causes was then determined. This ratio compares men’s and women’s risk of death; higher values indicate a greater disadvantage for men.
The next step involved constructing life tables for men and women to examine the gender gap in life expectancy at birth. Two measures were used to analyze this gap: the absolute and relative differentials. The absolute differential is the difference between female and male life expectancy, while the relative differential indicates, in percentage terms, how much the gender gap would reduce compared to real data without eliminating external causes.
Finally, single-decrement associated life tables were calculated to assess the impact of external cause deaths on the gender gap in mortality. These tables estimate changes in life expectancy at birth if a specific cause of death were eliminated 23,24.
Single-decrement life tables describe a hypothetical scenario where a specific cause of death is eliminated, setting its death probability to 0 and its survival probability to 1. Eliminating a cause of death does not simply involve removing related deaths from the dataset. When a cause is removed, individuals who would have died from it are exposed to the risk of death from other causes, altering overall death probabilities.
This scenario requires addressing the violation of the independence assumption in competing risks. While mortality rates remain unchanged, more survivors at a given age increase exposure to other causes, modifying death probabilities 23.
To adjust for this, the decrement proportionality constant, R_x^(-i), is calculated as follows:
R_x^(-i)=(D_x-D_x^(-i))/D_x
where -i represents the eliminated cause (external causes), and D_x is the total observed deaths from all causes at age x. This constant assigns relative importance to each cause in relation to total deaths within each age group.
The method for calculating this constant follows the steps outlined in Grupo Foz 23. This study highlights its importance, as it is the basis for simulating scenarios with varying degrees of mortality reduction. While complete elimination (100%) of causes is standard, this approach allows adjustments for partial reductions (e.g., 25%, 50%, 75%), creating different scenarios.
The difference between total life expectancy and life expectancy after eliminating a cause quantifies the potential gain in life expectancy. In this study, we analyzed four hypothetical scenarios of external cause mortality reduction—25%, 50%, 75%, and 100%—to estimate potential life expectancy gains at various reduction levels.
Detailed methods for single-decrement life tables are available in Preston et al. 24 and Grupo Foz 23. Data were analyzed using Microsoft Excel 2019 and R 25.
Since this study used only aggregated, publicly available data without personal identifiers, it did not require ethical approval from the Research Ethics Committee/National Research Ethics Commission (CEP/CONEP). This ensured compliance with ethical principles, maintaining confidentiality and privacy while preventing individual identification.

Results
In Minas Gerais, 94,447 deaths occurred in 1980, of which 7,645 (8.1%) were caused by external causes. By 2000, this number rose to 96,093, with external causes accounting for 8.5% of deaths. In 2018, external causes represented 9.8% of the 130,603 total deaths. However, when disaggregating deaths by gender, a clear pattern emerged: in all analyzed years, the proportion of deaths from external causes was consistently higher for men than for women (Table 1).
Figure 1 displays age- and sex-specific mortality rates for all causes and external causes separately. A general decline in mortality over the study period was evident for all cause mortality (upper quadrant). However, this decline was more consistent for women, with reductions observed across all ages during all three years. For men, there was an increase in mortality among young individuals in 2018, reaching levels similar to those recorded in 1980 (Figure 1).

The lower quadrant of Figure 1, which focuses on external cause mortality, helps explain these differences. While the shapes of the curves for men and women are similar, men consistently experienced much higher rates, especially in younger and middle-aged groups.
For men, the age-specific mortality rates from external causes in younger age groups were nearly identical to overall mortality rates, indicating that external causes were the primary contributors to mortality among young men. As men aged, overall mortality rates increased, while external cause mortality remained relatively stable, except among those over 70. Notably, in 2018, the mortality risk among 15–25-year-olds exceeded that of earlier years (Figure 1, lower quadrant).
For women, external cause mortality rates decreased across all ages between 1980 and 2000. However, by 2018, these improvements were observed only among children. Women consistently exhibited lower external cause mortality rates than men, reaching comparable levels only after age 75 (Figure 1, lower quadrant).
Figure 2 highlights the sex ratios of external cause mortality rates, underscoring a persistent male disadvantage. In every year and age group analyzed, the sex ratio exceeded 1, indicating higher risks for men. In 1980, the pattern resembled an inverted U, with a peak at ages 35–39. During this period, men aged 35–39 were nearly six times more likely to die from external causes than women of the same age. By 2000, two trends emerged: an increase in the sex ratio across almost all ages, suggesting that men’s relative risk compared to women had risen over time; and a shift in the peak toward younger ages. In 2000, men aged 20–24 were seven times more likely to die from external causes than women of the same age. In 2018, this risk had increased to nearly eight times.
Table 2 provides life expectancy at birth for men and women and the gender gap for 1980, 2000, and 2018. It also includes results for four scenarios of external cause reduction, illustrating their impact on life expectancy and the gender gap in mortality.
In 1980, women in Minas Gerais could expect to live 69.0 years, 6.0 years longer than men. By 2000, this gap widened to 7.0 years, with men achieving a life expectancy of 70.9 years. In 2018, the gender gap began to narrow, with men facing a disadvantage of 6.6 years compared to women. However, while the gap narrowed to 6.6 years in 2018, it remained wider than the 6.0 years observed in 1980 (Table 2).
In all four external cause reduction scenarios, the gender gap narrowed primarily due to significant gains in male life expectancy. For instance, in the first scenario (25% reduction in external causes), the male disadvantage would shrink to 5.6 years in 1980 (a 6% reduction), 6.6 years in 2000 (a 5% reduction), and 6.1 years in 2018 (a 7% reduction). As the proportion of external cause reduction increased, the gender gap diminished further. Notably, in Scenario 3 (75% reduction), the gap in 2018 reached levels similar to 1980. In this scenario, the male disadvantage would be 5.0 years in 1980 (17% lower) and 5.1 years in 2018 (14% lower). Under complete elimination of external causes (Scenario 4), the male disadvantage would decrease substantially: 4.6 years in 1980 (23% reduction), 5.5 years in 2000 (21% reduction), and 4.6 years in 2018 (29% reduction).
Figure 3 complements this analysis, illustrating the gender gap in life expectancy gains under the four reduction scenarios. As expected, the largest gains occurred with complete elimination of external causes. However, even in moderate reduction scenarios, the male disadvantage decreased significantly, particularly in 2018.

Discussion and Conclusion
This study examined the impact of external cause mortality on the gender gap in mortality in Minas Gerais from 1980 to 2018. Simulating different scenarios of external cause reduction showed a significant decrease in the gender gap in life expectancy at birth. Eliminating just 25% of external causes would reduce the male mortality disadvantage across all analyzed periods, with the gap shrinking further as the proportion of eliminated causes increased. Under a total elimination scenario, the male disadvantage would decrease dramatically, highlighting the significant role external causes play in the gender gap. Reducing these deaths would have a substantial impact on male life expectancy, narrowing the mortality gap between men and women.
The literature provides several explanations that help contextualize the findings of this study. Demographically, external causes of mortality—such as accidents, homicides, and suicides—are significantly higher among men, particularly in younger and middle-aged groups 4,13. This pattern results in a disproportionately higher male mortality rate compared to women, negatively impacting male life expectancy – a trend observed across Brazil 20,26, in Latin American cities 27 and globally 28. Eliminating external causes would lead to a substantial increase in male life expectancy, thereby reducing the gender gap.
Previous studies support the finding that external cause mortality rates are higher among men due to risk-taking behaviors and greater exposure to dangerous environments 4,29. For example, in Minas Gerais, both in 2000 and 2018, men had a higher proportion of deaths from transport accidents compared to women, although this difference slightly decreased in 2018 30. Additionally, publicly available data revealed a significant increase in the percentage of deaths from assaults among men, who remain disproportionately affected by this cause in both periods 30.
Findings from Minas Gerais align with evidence from other regions. A study analyzing adult mortality profiles in ten Latin American countries found that external causes, particularly homicides and traffic accidents, are major contributors to higher male mortality rates 31. Despite differences in overall adult mortality across these countries, the elevated external cause mortality among men is consistent, suggesting a widespread regional issue 31.
The age-specific analysis of male mortality disadvantage in Minas Gerais between 1980 and 2018 highlights two main trends: rising mortality levels across most age groups and the "rejuvenation" of the external cause mortality curve. These patterns are consistent with findings from studies conducted in other locations, including São Paulo 32,33 and some developed countries 34.
The rejuvenation of external cause mortality suggests that younger men are increasingly affected, likely due to urbanization and migration to cities in the late 20th century in search of better opportunities35, increasing the exposure to risks associated with external causes, such as urban violence and traffic accidents, which disproportionately affect young men 4. Other factors, such as changes in social norms and increased occupational hazards (e.g., high-risk jobs in construction and transportation), may also explain the shifting patterns but require further investigation.
The gender gap in mortality also reflects broader social inequalities, shaped by social norms, economic conditions, and cultural practices 10. Higher male mortality from external causes often stems from gender roles that encourage risky and aggressive behaviors among men11,36,37. Traditional masculinity promotes bravery, competitiveness, and risk-taking, which heightens risky behaviors 36,38. Gender norms often push men to be assertive and competitive, leading to aggressive behaviors like fighting or extreme sports to assert their position 39.
Reducing external causes of death, such as traffic accidents and homicides, would significantly decrease deaths associated with these behaviors and, consequently, the gender gap in mortality 40,41. However, such a reduction would not occur in isolation; it would reflect broader social and cultural changes that perpetuate these practices 42. Reducing these deaths would signal not only an improvement in public health but also a shift in cultural norms around traditional masculinity 43. Norms that once valued bravery, competitiveness, and risk-taking would be gradually replaced by a greater emphasis on health and safety, both personally and socially. Addressing external cause mortality would thus promote cultural change toward gender equity and healthier lifestyles 41.
While reducing the gender gap in mortality from external causes is often seen as primarily benefiting men, it is also important to consider the impact on women. Reducing these deaths reflects a change in norms that perpetuate male risk behaviors, but it also involves a shift in gender dynamics that can affect women\'s health 44,45. As men gain in life expectancy through reduced risk behaviors, women may experience changes in their own mortality and longevity. Increased female participation in traditionally male-dominated sectors, like emergency services and technical industries, brings new occupational challenges, including physical and biomechanical risks 46. This female advantage in longevity could be threatened if changing social norms lead women into riskier environments traditionally dominated by men.
Thus, a balanced view requires recognizing that reducing the gender gap in mortality is not solely about male gains but also about how changing social and cultural norms reshape mortality and longevity experiences for both genders 47. As these norms evolve to encourage less risky behavior, external cause mortality should decline, supporting the idea that social changes can directly impact public health 48,49.
This study contributes to the literature by providing evidence of how external cause deaths influence the gender gap in mortality in Minas Gerais and how this trend has evolved over decades. However, it also acknowledges some limitations. First, the analysis relies on aggregated mortality data, which may mask significant intra-regional and socioeconomic differences within Minas Gerais. Additionally, the quality of mortality data may vary over time and across regions, potentially affecting the accuracy of external cause mortality estimates.
Future research should include more detailed analyses in sub-regions of Minas Gerais to identify areas needing intervention. Qualitative data, such as interviews and focus groups, could help explore cultural and social factors influencing risky behaviors among men. Further, it is important to examine how different age groups and causes of death contribute to variations in external cause mortality rates using decomposition methods. Other measures of inequality, such as variability in age at death across municipalities, should also be investigated using survival tables for both men and women.

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