Estimating the effect of socio-economic factors on infant mortality rates in Latin America between 2000 and 2019: a panel data analysis

OBJECTIVES

Infant mortality is a crucial indicator of socio-economic development, reflecting the conditions in which children are born and raised. Despite notable reductions in Latin America, infant mortality rates remain relatively high compared to other regions worldwide. By understanding the socio-economic factors that influence infant mortality, we not only uncover immediate causes of infant deaths but also shed light on broader socio-economic and healthcare disparities contributing to the burden of disease. This study analyzes the impact of socio-economic factors on infant mortality rates in Latin America from 2000 to 2019, estimating the speed and magnitude of the response of infant mortality rates to changes in specific socio-economic factors.

STUDY DESIGN

Longitudinal panel study.

METHODS

Panel data regression models were used to examine the influence of specific socio-economic factors on infant mortality rates in Latin America. Additionally, impulse response functions estimated by local projections were used to estimate the speed and magnitude of the impact of socio-economic factors on infant mortality rates.

RESULTS

The results highlight the importance of factors such as healthcare expenditure, female literacy, public expenditures on education, maternal mortality, physician density, total fertility rate, and tuberculosis incidence as significant determinants of infant mortality rates in the region.

CONCLUSION

This study adds to the existing literature by offering empirical evidence on the association between these socio-economic factors and infant mortality in Latin America. It also provides a foundation for future research that investigates specific cases within Latin America and examines the variations of these socio-economic factors within those countries.

The association between social support and self-rated health in midlife: are men more affected than women?

Social support from family and friends is recognized as an important social determinant of health, given its protective effects on individuals' physical and mental well-being. While most studies have focused on older adults, investigating midlife health is equally crucial since middle-aged individuals are also susceptible to the harmful health outcomes of inadequate social support from friends and family. This study contributes to the debate by examining whether social support is associated with self-rated health among middle-aged Brazilian adults and how this relationship varies between men and women. Using data from the nationwide Brazilian National Health Survey conducted in 2019, logistic regression models were employed to assess differences in self-rated health, accounting for confounding factors. The sample comprised 31,926 middle-aged adults, of which 52.5% were women. The overall prevalence of poor self-rated health was 40.7%, with a significant difference between men and women. Results from this study suggest that having no friends or family members to rely on, both during good and challenging times, was associated with poorer self-rated health. However, the strength of this association differs by gender, with social support from friends playing a more critical role in women's self-rated health. On the other hand, family support was associated with male self-rated health, particularly for men with three or more family members they can rely on. Future studies should consider cultural and contextual factors to better understand other dimensions of social support and its association with midlife health.

Urban-rural health disparities in Brazil: Do sociodemographic attributes play a role?

The debate over urban-rural health disparities in Latin American countries is disputed, and this relationship may not be as straightforward as initially thought. In this study, we investigate whether individual-level self-rated health (SRH) varies across urban and rural populations in the country and how sociodemographic attributes are associated with such differences. We relied on data from the Brazilian National Health Survey (n = 78,806), a nationwide household-based survey conducted in 2019 that is representative of Brazil, geopolitical macro-regions, states, and 27 state capitals. Logistic regression models were used to test for differences in SRH between urban and rural inhabitants. The findings suggest that Brazilian adults living in rural areas are at a higher risk of perceiving their health as poor than their urban counterparts. The urban-rural health disparities are significant and influenced by sociodemographic attributes, highlighting the importance of developing public health interventions to improve health outcomes in these populations.

Probabilistic survival modeling in health research: an assessment using cohort data from hospitalized patients with COVID-19 in a Latin American city

Probabilistic survival methods have been used in health research to analyze risk factors and adverse health outcomes associated with COVID-19. The aim of this study was to employ a probabilistic model selected among three distributions (exponential, Weibull, and lognormal) to investigate the time from hospitalization to death and determine the mortality risks among hospitalized patients with COVID-19. A retrospective cohort study was conducted for patients hospitalized due to COVID-19 within 30 days in Londrina, Brazil, between January 2021 and February 2022, registered in the database for severe acute respiratory infections (SIVEP-Gripe). Graphical and Akaike Information Criterion (AIC) methods were used to compare the efficiency of the three probabilistic models. The results from the final model were presented as hazard and event time ratios. Our study comprised of 7,684 individuals, with an overall case fatality rate of 32.78%. Data suggested that older age, male sex, severe comorbidity score, intensive care unit admission, and invasive ventilation significantly increased risks for in-hospital mortality. Our study highlights the conditions that confer higher risks for adverse clinical outcomes attributed to COVID-19. The step-by-step process for selecting appropriate probabilistic models may be extended to other investigations in health research to provide more reliable evidence on this topic.

COVID-19 vaccination and case fatality rates: a case report in a Brazilian municipality

Vaccination campaigns played a crucial role in reducing the incidence of COVID-19. However, a scant number of studies evaluated the impact of vaccination on case fatality rates (CFRs), including in Brazil. Our study aimed to compare CFRs according to vaccination status among subjects living in Arapongas (Paraná State, Brazil), considering the age composition of the population. Several strategies adopted by the Arapongas City Hall to minimize the spread of the virus were also elaborated upon. We accessed the 2021 database of the Arapongas Municipal Health Department, in which a total of 16,437 confirmed cases and 425 deaths were reported. The CFR was calculated as the ratio between COVID-19 deaths and the number of confirmed cases. Differences in age composition between unvaccinated and fully vaccinated individuals were observed in our study. Considering that CFR is a crude indicator and is highly sensitive to the age composition of the population, we adopted the average age distribution of confirmed cases among the three vaccination statuses (unvaccinated, partially, and fully) as a standard age distribution. The age-standardized CFR for unvaccinated and fully vaccinated groups were 4.55% and 2.42%, respectively. Fully vaccinated individuals showed lower age-specific CFRs in all age groups above 60 years than unvaccinated populations. Our findings strengthen the role of vaccination as a critical measure for preventing deaths among infected people and is particularly important to the ongoing reassessment of public health interventions and policies.

The impact of COVID-19 vaccination on case fatality rates in a city in Southern Brazil

BACKGROUND

Recent studies have established that vaccination plays a significant role in reducing COVID-19-related deaths. Here, we investigated differences in COVID-19 case fatality rates (CFRs) among vaccinated and unvaccinated populations, and analyzed whether the age composition of confirmed cases has a significant effect on the variations in the observed CFRs across these groups.

METHODS

The study considered 59,853 confirmed cases and 1,687 deaths from COVID-19, reported between January 1 to October 20, 2021, by the Health Department of Londrina, a city in Southern Brazil. We used Negative Binomial regression models to estimate CFRs according to vaccination status and age range.

RESULTS

There are significant differences between the CFR for fully vaccinated and unvaccinated populations (IRR = 0.596, 95% CI [0.460 - 0.772], P < .001). Vaccinated populations experience fatality rates 40.4% lower than non-vaccinated. In addition, the age composition of confirmed cases explains more than two-thirds of the variation in the CFR between these 2 groups.

CONCLUSIONS

Our novel findings reinforce the importance of vaccination as an essential public health measure for reducing COVID-19 fatality rates in all age groups. The results also provide means for accurately assessing differences in CFRs across vaccinated and unvaccinated populations. Such assessment is essential to inform and determine appropriate containment and mitigation interventions in Brazil and elsewhere.

Movimentos pendulares e integração regional no leste fluminense

A pendularidade é uma importante medida para avaliar os processos de integração das cidades e a dinâmica populacional regional. Em 2015, o IBGE identificou a intensificação dos movimentos pendulares entre os municípios do leste fluminense, de Arraial do Cabo a São João da Barra, considerando-os aspectos relevantes da urbanização brasileira. Contudo, pouco se sabe sobre o peso da pendularidade entre esses municípios e o nível de interação que eles estabelecem com Macaé, principal destino dos pendulares na região. Esse trabalho analisa o grau de integração regional do vetor leste fluminense, a partir dos dados censitários de 2000 e 2010. A pendularidade por trabalho e/ou estudo observada em Macaé o coloca em posição de destaque entre os municípios selecionados. Afirmamos, portanto, que Macaé não é apenas uma cidade em movimento, mas também um município potencialmente integrador do mercado de trabalho das demais municipalidades da região. É em torno desse município que o tecido urbano regional tem se reorganizado. Esse estudo pode iluminar novas discussões sobre os processos recentes de urbanização no estado do Rio de Janeiro, sobretudo por se tratar de uma região demograficamente integrada, mas politicamente fragmentada.