Principal investigator: Silvio da Rosa Paula
Article title: REDUCING SOCIOECONOMIC INEQUALITIES IN LIFE EXPECTANCY
AMONG MUNICIPALITIES: THE BRAZILIAN EXPERIENCE
Article authors: Antonio Fernando Boing, SV Subramanian and Alexandra Crispim Boing
Location of the intervention: Brazil
Sample size: Brazilian population in the censuses of 1991, 2000 and 2010
Main theme: Health Insurance
Type of Intervention: Assessment of the impact of socioeconomic and regional inequalities.
Primary variable of interest: Life expectancy at birth
Evaluation method: Poisson regression
Evaluation Context
Between the 1990s and 2000s, Brazil underwent significant economic and social changes. In the context of health, the 1988 Constitution universalized access to healthcare with the creation of the Unified Health System (SUS), guaranteeing that all Brazilians had access to health services. Currently, the SUS is the largest public and universal health system in the world, covering even the most complex levels of healthcare, providing services ranging from immunizations to organ transplants (PAIM). et al(2011). The decentralization of health service provision to the municipal level has impacted primary care coverage and generated effects on local health. Studies find evidence that the expansion of primary care promoted by the SUS (Brazilian Unified Health System) is associated with a reduction in deaths from preventable causes, fewer hospitalizations, a reduction in racial inequalities in mortality, and a reduction in infant mortality (MACINKO). et al2010; Guanais 2015; HONE et al. 2017a, 2017b).
In 1994, with the creation of the Real Plan, Brazil managed to contain hyperinflation and stabilize the economy, factors that were later important for the increase in the minimum wage, reduction of unemployment, and the creation and expansion of social programs. In this context, the 2000s saw an expansion of social programs. The main program is Bolsa Família (BF), which, broadly speaking, aims to break the intergenerational cycle of poverty through direct income transfers to families living in poverty or extreme poverty, who in return fulfill certain health and education requirements. Studies indicate that BF contributed to the reduction of diseases such as tuberculosis and leprosy (Nery). et al. 2014, 2017), increased visits by children to health centers for preventive services (Shei et al. 2014), and also contributed to the reduction of infant mortality (Rasella et al. 2013).
In the field of education, progress was also observed, such as an increase in the educational level of the poorest population, as well as greater access to basic sanitation services, important factors that have a strong impact on health indicators, especially on children's health. However, between 1985 and 1990 there was an increase of 4.1 percentage points (pp) in the Gini index, which measures income concentration. The same occurred for the period between 1998 and 2009, with an increase of 5.4 pp, indicating that there was an increase in income inequality for these periods.
Exclusive
Data from the 1991, 2000, and 2010 demographic censuses at the municipal level were used. Municipalities were divided into percentiles according to average per capita income, calculated in each of the three years analyzed. The method used to assess the impact of inequalities on life expectancy was Poisson regression. In short, Poisson regression is a probabilistic method that plays an important role in the analysis of count data that assume non-negative integer values. An example of its application is the modeling of the number of deaths from traffic accidents. With this technique, it is possible to estimate the probability or the expected number of deaths if the accident involves, for example, a motorcycle or a pedestrian.
Intervention Details
During the 20th century, there was a significant increase in life expectancy worldwide. According to the OECD, it is estimated that in 1900 the average life expectancy was 30 years, reaching 71,4 years in 2015. In Brazil, life expectancy increased by almost 20 years between 1967 and 2015. However, significant inequalities in life expectancy are still observed between countries and also within each country. Studies conducted in the United States, the European Union, Japan, and New Zealand find evidence of inequalities in life expectancy among their counties.
In the context of Brazil, the profound economic and social changes that occurred during the 1990s and 2000s allowed not only the expansion of social programs but also unequal economic growth among different regions, being stronger in developed regions than in the poorer areas of the country. It is within this perspective of accentuated inequalities that this study proposes to evaluate how regional inequality evolved in life expectancy, as well as in the probability of living to 40 and 60 years of age, in Brazilian municipalities for the period from 1991 to 2010.
According to the Brazilian Institute of Geography and Statistics (IBGE), in 1940 the average life expectancy was 45,5 years, with 42,9 years for men and 48,3 years for women. Furthermore, in 1940, for every thousand people who reached 65 years of age, 259 would reach 80 years or more. In 2017, for every thousand elderly people aged 65, 632 would reach 80 years of age. Also in 2017, life expectancy at birth showed significant differences between the federative units, as indicated in the graph provided by IBGE.[1].
It can be observed that, among the federative units, Santa Catarina had the highest life expectancy at 79,4 years, followed by Espírito Santo (78,5 years), the Federal District and São Paulo (78,4 years), and Rio Grande do Sul (78 years). On the other hand, the lowest life expectancy was observed in the state of Maranhão (70,6 years), followed by Piauí (71,2 years), Rondônia (71,5 years), and Roraima (71,8 years).
Finally, the most recent statistics from IBGE.[2]The data indicates that a person born in Brazil in 2018 had an increase of three months and four days in life expectancy compared to 2017. Furthermore, the life expectancy for men increased from 72,5 years in 2017 to 72,8 years in 2018, while that for women increased from 79,6 to 79,9 years.
Results
The results indicate that the average life expectancy in Brazilian municipalities increased by 8.8 years between 1991 and 2010. An increase of 6.7 percentage points (pp) was also observed in the probability of surviving to age 40, and 12.2 pp in the probability of surviving to age 60.
The increase in life expectancy, as well as the probability of survival, has generated a substantial decrease in the differences between regions and socioeconomic groups. For example, in 1991, the inhabitants of the municipalities that were among the richest 1% lived on average 11,6 years longer than the inhabitants of the municipalities that were among the poorest 1%. In 2010, this difference fell to 7,1 years. In the context of the probability of survival to age 40, the difference fell from 11,7 percentage points in 1991 to 1,2 percentage points in 2010. As for the probability of survival to age 60, this decrease was from 1.3 percentage points in 1991 to 1.04 percentage points in 2010.
It is worth highlighting that, during the analyzed period, no municipality showed a reduction in life expectancy or probability of survival. However, while the poorest municipalities gained approximately 12 years of life expectancy, the richest municipalities saw a gain of approximately 7 years. Looking at the different periods, between 1991 and 2000, the richest municipalities benefited the most; however, in the decade from 2000 to 2010, the poorest municipalities observed the greatest gains in life expectancy.
Lessons in Public Policy
Between 1991 and 2010, Brazil managed to significantly reduce municipal differences in life expectancy and the probability of living to 40 and 60 years of age. The reduction in inequalities was more pronounced in the 2000s and 2010s. Despite all the progress, Brazil remains one of the most unequal countries in the world. It is clear that there are no magic solutions or simple answers to the problem of inequality; however, there are areas where we can improve. For example, many of our public policies lack clear objectives and were not designed to be evaluated. This implies a lot of wasted money, ineffective programs, and often overlapping, hindering or even preventing the evaluation of a program's effectiveness.
References
BOING, Antonio Fernando; SUBRAMANIAN, SV; BOING, Alexandra Crispim. Reducing socioeconomic inequalities in life expectancy among municipalities: the Brazilian experience. International journal of public health, vol. 64, no. 5, p. 713-720, 2019.
[1] See more at: https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/23200-em-2017-expectativa-de-vida-era-de-76-anos
[2] See more at: https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/26104-em-2018-expectativa-de-vida-era-de-76-3-anos
