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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. Longitudinal panel study. 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. 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. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. • Rural Brazilian adults have a higher risk of perceiving their health as poor compared to urban counterparts. • Sociodemographic factors significantly shape the urban-rural health gap. • Chronic illnesses are associated with higher risk of poor SRH in rural residents than in urban residents. • The study calls for public health interventions to improve health outcomes in rural populations. [ABSTRACT FROM AUTHOR]