Since the beginning of the pandemic of the new coronavirus, Brazil is a country that has been heavily affected by this new disease, and from March 2020 this country saw its death records increased as the number of Covid-19 infected got out of control. Consequently, many studies tried to explain the influence of this illness in the number of deaths and possible reductions in life expectancy. Until now, there were few empirical attempts to comprehend the effects of pandemic on birth reductions. In this work, we sought to analyze the influence of the pandemic Covid-19 on birth numbers of six major cities of Brazil. Using data from the Ministry of Health, we compared the number of monthly births from October-December 2020 and January-March 2021 with the amount of newborns in similar months and in years previous to the pandemic. Our results show a strong decline in the number of births in all cities analyzed, and most of the reductions occurred at mothers' age of 30 years old. Because of the uncertain scenario that the pandemic brought us, women are postponing their fertility intentions, causing a perhaps temporary baby bust in major cities of Brazil.
In this work, we analyzed the spatial distribution of fertility levels in 558 microregions of Brazil and correlated it with vote outcomes from the last presidential election of 2018, controlling for important confounding variables. Applying spatial regression models, to the contrary of expected, we see that votes in Bolsonaro did not associate positively with fertility levels. In fact, in regions where its political adversary won, the Brazilian Labour Party (PT), the fertility levels are on average higher than the ones where Bolsonaro had electoral success. However, we would expect that these results will be different, due to the fact that Bolsonaro represents conservatism and traditional family values, which in turn resumes in desires for more children. In line with McDonald’s gender equity theory, we argue that votes in Bolsonaro may actually indicate other facets of reproduction, like an electorate with defending lesser gender equity in family institutions and that also configures in smaller TFR as consequence.
Background: Small area age- and sex-specific mortality rates are useful measures for population projections, health, economic, and social planning. Mortality rate estimation in small areas can be difficult due the low number of events/exposure. If a country’s mortality registration has problems, such as incomplete information, then estimating mortality rates can be even more difficult. Previous studies in Brazil have combined demographic and statistical methods to overcome these issues. These approaches depend on a gold standard for age-specific mortality rates and do not estimate uncertainties. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010, and forecasted mortality rates between 2010 and 2030. Methods: We used the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS) and a Bayesian model to estimate age- and sex-specific mortality rates in all Brazilian municipalities in 2010 while incorporating two types of uncertainties: low exposure and incomplete coverage of death counts. We adapted the Lee-Carter model to forecast age- and sex-specific mortality rates between 2010 and 2030 for all municipalities. Results: The proposed methodology was robust in adjusting for the mortality age profile and in estimating mortality rate uncertainties at the municipal level. The forecasted mortality rates indicated a convergence in life expectancy at birth, and variability of age at death across Brazil’s municipalities, with a persistent sex differential. Conclusion: We estimated and forecasted mortality rates in small areas with limited and incomplete death counts, and high mortality heterogeneity. The methodological approach applied could be useful for countries with death data quality problems similar to Brazil. Our results incorporated the main sources of uncertainty in estimating age- and sex-specific mortality rates and could be used as an important input for policy planning at the municipal level.
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