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Since the nineteenth century, the census has provided the number of 100-year-olds in Brazil one of the most populous countries worldwide. In 1900, 4,438 individuals reported themselves to be centenarians, a figure that increased about fivefold by the 2000 census. However, due to data quality issues, we are skeptical about the real size of the recorded population in the Brazilian census. We offer alternative estimates of the most likely number of centenarians during the twentieth century by combining variable-r relations with different mortality models. Our results indicate there was virtually no centenarian at the beginning of the twentieth century. The population has become larger than 1,000 individuals only in the 1990s, suggesting there has been an extensive, although diminishing, overenumeration of centenarians in the census records. Our results can help policymakers to plan the demands of a growing old age population in places that face stricter family and public budget constraints.

Background The COVID-19 pandemic has significantly increased mortality rates, disrupting historical trends and making it challenging to forecast future life expectancy levels. São Paulo, the first city in Brazil to report a COVID-19 case and death, saw a decrease of over four years in life expectancy at birth for males and over three years for females between 2019 and 2021. São Paulo has been at the forefront of the demographic transition in the country and experienced a nonlinear mortality decline over the twentieth century. The city's historical mortality trajectory and the disruptive effects of COVID-19 have introduced challenges to mortality forecasting. Methods In this study, we used a unique dataset dating 1920–2022 to forecast life expectancy in São Paulo until 2050 using the Lee-Carter and Lee-Miller methods. Mortality rates were obtained from a combination of deaths gathered by the SEADE Foundation (SEADE) and population collected by the Brazilian Institute of Geography and Statistics. To mitigate the dependency on the fitting period's choice and better incorporate the effects of the recent mortality shock, we used different baseline periods, using all years from 1920 to 1995 as the starting year of the analysis and six scenarios for post-pandemic mortality levels. Prediction intervals were derived from simulated trajectories of the models' time indices. Based on 73,200 simulations for each year between 2023 and 2050, we synthesized the resulting life expectancy forecasts into median values and 95% prediction intervals (PI). Results By 2050, we predict that life expectancy at birth in São Paulo will reach approximately 81.4 years for men and 88.3 years for women. Also, within the 95% PI, we estimated that by 2045, male life expectancy could reach the levels of best-performing countries. Conclusions Our approach is among the first attempts to forecast mortality in the presence of shocks. Additionally, by evaluating different baseline periods, we advocate for the adoption of more accurate forecasting strategies, particularly in contexts of recent mortality decline. These findings provide valuable resources for policymakers and researchers working to address public health challenges arising from the pandemic and plan for the future well-being of many populations.

ObjectiveGender gaps in healthy life expectancy are frequently used as indicators of health inequality between women and men. However, total gaps can be misleading—masking critical disparities such as women living longer yet spending more years with disability or illness, or men experiencing premature mortality. We therefore critically evaluate whether these gaps accurately capture gender-based health.DesignWe estimate gender gaps in disability- and chronic disease-free life expectancy using the Sullivan method and decompose those gaps via the continuous-change approach to distinguish mortality from morbidity contributions. Data are drawn from the harmonised Gateway to Global Aging Data and the UN life tables from the 2022 Revision of World Population Prospects for all countries, except England, where the life tables are from the UK Office for National Statistics.SettingThe analysis is performed on 24 countries and regions, including the USA, England, South Korea, China, India, Mexico and 19 European Union countries for the years 2014–2015 and 2017–2019 (N=201 723).Main outcome measuresThe main outcomes are gender gaps in disability- and chronic disease-free life expectancy and the contribution of mortality and health in explaining the gender gap.ResultsGender gaps in disability-free life expectancy ranged from −0.37 years (Portugal) to almost 5 years (South Korea), with most European countries showing female advantages of 3.0–3.5 years, while minimal gaps were observed in China, Mexico and India (0.4–0.9 years). Decomposition revealed striking inconsistencies between total gaps and underlying components—South Korea’s 4.9-year gap reflected a survival advantage outweighing disability disadvantage by 13-fold, while Portugal’s −0.37-year gap masked opposing contributions (mortality: +2.3; disability: −2.7). Chronic disease-free life expectancy showed female disadvantage in most countries, especially Portugal (−2.3), Korea (−1.6) and Mexico (−1.9).ConclusionsUsing gender gaps in healthy life expectancy as a metric for gender inequality in health is misleading. Countries with very different levels of development, healthcare systems and gender roles can have similar gender gaps, but substantial differences in the levels of mortality and health. Because these gaps mask important underlying differences in health and mortality between women and men, caution is warranted when using them.

Age misreporting affects population estimates at older ages. In Brazil, every citizen must be registered and show an identity document to vaccinate against COVID-19. This requirement to present proof of age provides a unique opportunity for measuring the oldest-old population using novel administrative data. To offer critically assessed estimates of the Brazilian population aged 80 and older based on data from the vaccination registration system (VRS). To uncover discrepancies between the number of vaccinated oldest-old people and the projections used to estimate target populations for COVID-19 vaccination. We calculate data quality indicators based on data from the VRS - namely, 100+/80+ and 90+/80+ population proportions, sex ratios, and the Myers blended index - and compare them to those based on data on target populations from Brazilian censuses and demographic projections, and from Sweden - a country with high-quality data. We also estimate vaccination coverage ratios using population projections adjusted to excess deaths as the denominators. Requiring documentation reduces age heaping, age exaggeration, and sex ratios marginally. However, it cannot solve the problem of the misreporting of birth dates due to the absence of long-standing birth registration systems in Brazil, particularly in the northern and central regions. In addition, we find a mismatch between the projected populations and numbers of vaccinated people across regions. Despite improvements in data quality in Brazil, we are still not confident about the accuracy of age reporting among the oldest old in the less advantaged Brazilian regions. The postponement of the 2020 census reduced the ability of authorities to define the target populations for vaccinations against COVID-19 and other diseases.

BACKGROUND Population aging is a fundamental element of the demographic transition. In the absence of births, deaths, and migration, the mean age of any population will increase one year per calendar year. The intensity of period birth, death, and migration conditions (i.e., their crude rates and the difference between their mean age and the mean age of the population) either lessen or strengthen this natural tendency of populations to age. OBJECTIVE We investigate the contribution of births, deaths, and migration to population aging across the globe from 1950 to 2100. We examine whether a concerted pattern of population aging is associated with changes in period demographic conditions. METHODS We apply a mathematical expression proposed by Preston, Himes, and Eggers (1989) that decomposes the rate of change in the mean age of a population according to period demographic conditions. We use the 2022 revision of the United Nations population estimates and projections covering 236 countries or areas. RESULTS During the demographic transition, population aging follows a general concerted pattern characterized by five distinct stages. Populations age because of declining inflows (births) at age zero and insufficient outflows (deaths) at older ages. Overall, migration does not play a pivotal role but can be more relevant in specific countries or regions. CONTRIBUTION Our study combines long-time series data for most countries in the world with an elegant mathematical solution proposed by Preston, Himes, and Eggers (1989) to empirically measure the dynamics of population aging according to period demographic conditions.

Brazil has been heavily affected by coronavirus disease 2019 (COVID-19). In this study, we used data on reported total deaths in 2020 and in January–April 2021 to measure and compare the death toll across states. We estimate a decline in 2020 life expectancy at birth ( e 0 ) of 1.3 years, a mortality level not seen since 2014. The reduction in life expectancy at age 65 ( e 65 ) in 2020 was 0.9 years, setting Brazil back to 2012 levels. The decline was larger for males, widening by 9.1% the female–male gap in e 0 . Among states, Amazonas lost 60.4% of the improvements in e 0 since 2000. In the first 4 months of 2021, COVID-19 deaths represented 107% of the total 2020 figures. Assuming that death rates would have been equal to 2019 all-cause rates in the absence of COVID-19, COVID-19 deaths in 2021 have already reduced e 0 in 2021 by 1.8 years, which is slightly larger than the reduction estimated for 2020 under similar assumptions. New estimates of life expectancy at birth and at age 65 years in Brazil reveal substantial declines as a result of COVID-19, bringing mortality back to levels observed 20 or more years ago.

In developing countries, improving access to schooling has been and remains a priority. At the same time, a growing body of research relates education to demographic variables. It is therefore essential to measure the educational variable accurately. In Brazil, although the high degree of inaccuracy in age reporting is known, previous research has neglected that problems of misreporting may affect other variables such as education. To fill this gap, we calculate mortality levels by education as implied by intercensal survivorship ratios to investigate the quality of self-reported education among adults in Brazil between the 1991 and 2000 censuses. Our findings show evidence of inaccurate educational data in the censuses. Analysis by single year of schooling weakly reflects the known educational gradient in mortality. After categorization of age and years of schooling into groups, a positive relationship between education and survival does appear, although some implausible patterns remain.

The impact of extreme conditions on survival has been the focus of mortality studies using military data. However, in countries at peace, the military live in favorable conditions, being positively selected with respect to health. In this type of context, military data may help to improve our understanding of mortality differentials, particularly in countries where defective vital systems are still cumbersome for mortality studies. We estimate death rates for Brazilian Air Force (BAF) officers through Poisson regression models, compute life expectancies, and compare them with those of average Brazilians and people in low-mortality countries. We also examine causes of death and mortality differentials through a competing risks framework and Fine and Gray regression models. BAF life expectancy is higher than that of the average Brazilian and comparable to Sweden, France, and Japan in 2000. Younger pilots have a higher risk of dying on duty when compared with other officers but experience lower mortality rates from other causes at advanced ages. BAF officers are a population subgroup in Brazil with a life expectancy comparable to the one in advanced societies. There is no association between mortality and place of birth, which indicates that different childhood backgrounds did not affect BAF mortality differentials later in life.

Women live longer but can expect to spend more years in poorer health compared to men. In the context of population aging and declining gender ratios at older ages, there are increasing concerns about how this disadvantage in female health will a effct well-being and sustainability, particularly in developing regions that are rapidly aging. Our study compares differences in health expectancies at older ages for men and women in order to assess gender disparities in health. We use data from the Survey on Health, Well-Being, and Aging in Latin America and the Caribbean to decompose the gender gap into total and age-specific mortality and disability effects in seven cities in the region. Our results show that at older ages, higher disability rates among women reduced the gender gap in healthy life expectancy by offsetting women’s mortality advantage. In addition, we find that women’s mortality advantage decreased almost systematically with age, which reduced the contribution of the mortality effect to the gender gap at older ages. Although the gender gap in health followed a similar pattern across the region, its decomposition into mortality and disability effects reveals that there was substantial variation among cities. Thus, across the region, the implications of the gender gap in health for well-being vary, and the policies aimed at reducing this gap should also differ.