I am a social scientist with a Masters and PhD in demography. I am interested in determinants and differentials in mortality, longevity, formal demography, trans-humanism, inequality, math and philosophy. I currently work as a post-doc in the Vienna Institute of Demography in the Determinants of Longevity and Ageing in Good Health group.
ObjectivesThis study investigates the relationship between socioeconomic environment (SEE) and su... more ObjectivesThis study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria.DesignHospital-based observational data of STEMI patients are linked with district-level information on SEE and the mortality register, enabling survival analyses with a 19-year follow-up (2000–2018).SettingThe analysis is set at the main tertiary care hospital of the City of Vienna. On weekends, it is the only hospital in charge of treating STEMIs and thus provides representative data for the Viennese population.ParticipantsThe study comprises a total of 1481 patients with STEMI, including women and men aged 24–94 years.Primary and secondary outcome measuresPrimary outcome measures are age at STEMI and age at death. We further distinguish between deaths from coronary artery disease (CAD), deaths from acute coronary syndrome (ACS), and other causes of death. SEE is ...
Background Health expectancy indicators aim at capturing the quality dimension of total life expe... more Background Health expectancy indicators aim at capturing the quality dimension of total life expectancy.; however, the underlying approach, definition of health, and information source differ considerably among the indicators available. Objective (1) Review the main concepts and approaches used to estimate health expectancy focusing on two widely used European health indicators: Health-Adjusted Life Expectancy (HALE) and Healthy Life Years (HLY); (2) identify underlying differences between the results yielded by these two indicators. Method Statistical differences between the HALE and HLY indicators by sex at ages 50, 60, and 70 were tested using pairwise and global Student´s t-tests and z-scores based on standard deviation. Data for 29 European countries were collected from the European Health Expectancy Monitoring Unit (EHEMU) information system and the World Health Organization (WHO) Global Burden of Disease Study 2016 (GBD 2016). Results The HALE indicator estimates were smoothe...
The COVID-19 pandemic caused an increase in mortality in 2020 with a resultant decrease in life e... more The COVID-19 pandemic caused an increase in mortality in 2020 with a resultant decrease in life expectancy in most countries around the world. In Germany, the reduction in life expectancy at birth between 2019 and 2020 was comparatively small, at -0.20 years. The decrease was stronger among men than among women (-0.24 vs. -0.13 years) and in eastern rather than in western Germany (-0.36 vs. -0.16 years). Men in eastern Germany experienced the biggest decline in life expectancy at birth (-0.41 years). For western German men, the decline was less pronounced (-0.19 years). Among women, the decline in life expectancy at birth was also greater in eastern (-0.25 years) than in western Germany (-0.10 years). As a result of these developments, the differences in life expectancy between the two parts of Germany, and between women and men, increased compared with the previous year. Life expectancy at age 65 decreased more strongly than life expectancy at birth for both sexes and in all region...
In this work, we assess the global impact of COVID-19 showing how demographic factors, testing po... more In this work, we assess the global impact of COVID-19 showing how demographic factors, testing policies and herd immunity are key for saving lives. We extend a standard epidemiological SEIR model in order to: (a) identify the role of demographics (population size and population age distribution) on COVID-19 fatality rates; (b) quantify the maximum number of lives that can be saved according to different testing strategies, different levels of herd immunity, and specific population characteristics; and (d) infer from the observed case fatality rates (CFR) what the true fatality rate might be. Different from previous SEIR model extensions, we implement a Bayesian Melding method in our calibration strategy which enables us to account for data limitation on the total number of deaths. We derive a distribution of the set of parameters that best replicate the observed evolution of deaths by using information from both the model and the data.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Li... more This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Health expectancy indicators: what do they measure? Indicadores de expectativa de vida saudável: o que medem?
Women live longer but can expect to spend more years in poorer health compared to men. In the con... more 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 affect 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 morta...
Data for ten European countries which provide detailed distribution of COVID-19 cases by sex and ... more Data for ten European countries which provide detailed distribution of COVID-19 cases by sex and age show that among people of working age, women diagnosed with COVID-19 substantially outnumber infected men. This pattern reverses around retirement: infection rates among women fall at age 60-69, resulting in a cross-over with infection rates among men. The relative disadvantage of women peaks at ages 20-29, whereas the male disadvantage in infection rates peaks at ages 70-79. The elevated infection rates among women of working age are likely tied to their higher share in health- and care-related occupations. Our examination also suggests a link between women's employment profiles and infection rates in prime working ages. The same factors that determine women's higher life expectancy account for their lower fatality and higher male disadvantage at older ages.
There is consistent evidence that women live longer than men at all ages, but spend a higher prop... more There is consistent evidence that women live longer than men at all ages, but spend a higher proportion of their total life expectancy in poorer health, a phenomenon described as the “male-female health-survival paradox” or the “gender paradox in health and mortality”. However, it is difficult to explain the process because morbidity by sex differs considerably across domains of health, age groups, social contexts and severity level. In addition, women and men report differently their health in surveys, making it cumbersome to understand whether what drives the paradox is a higher female morbidity or male mortality, a different reporting behaviour, or all of those aspects together. The aim of this chapter is to demonstrate the magnitude of those differences in Europe using different health domain indicators (activity limitation, chronic morbidity and self-perceived health) from the EHEMU Information System and the reporting behaviour by sex from the SHARE survey vignettes.
Despite ongoing substantial decline in total fertility since the 1960’s, age-specific fertility r... more Despite ongoing substantial decline in total fertility since the 1960’s, age-specific fertility rates for the age groups 15-19 and 20-24 rose from 1991 to 2000 (Berquó and Cavenaghi 2005). In this sense, Brazil is a very particular case of a rejuvenated fertility pattern. By 2010, the total fertility rate had already reached below replacement level at 1.9 children per woman and the age-specific fertility rates for younger women also started to fall, albeit still a high one when compared to other countries that underwent similar demographic transitions or have proximate fertility levels (Alves 2012). With an increasing unmet demand for contraception and a continuously lowering of fertility for the remaining age groups, it all indicates that this age group is the one with the most potential of contributing for the future of fertility trends in Brazil. This study provides simulations that show the short and long-term pure demographic effects of changes in fertility for these specific a...
This introduction to the 2021 special issue of the Vienna Yearbook of Population Research explore... more This introduction to the 2021 special issue of the Vienna Yearbook of Population Research explores demographic perspectives on human wellbeing across time and space. While the idea of relating demographic parameters to wellbeing has been around for a while, a more concrete research agenda on this topic has only recently gained momentum. Reviewing the research presented in this volume, we show how existing theoretical concepts and methodological tools in demography can be used to make substantial advances in the study of wellbeing. We also touch upon the many challenges researchers face in defining and measuring wellbeing, with the most important debate being about whether the focus should be on objective or subjective measures. The studies discussed here define wellbeing as health and mortality; as income, education or other resources; as happiness or life satisfaction; or as a combination thereof. They cover wellbeing in historical and contemporary populations in high- and low-inco...
The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to... more The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive, limiting their use to specific population subgroups. In this paper, we propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) in order to indirectly estimate the fraction of people ever infected (from the total population) and detected (from the ever infected). We apply the technique to the U.S. due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25% (0.39–2.16%, 90% CI) in F...
Period life expectancy is one of the most used summary indicators for the overall health of a pop... more Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Eu-rope-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.
ObjectivesThis study investigates the relationship between socioeconomic environment (SEE) and su... more ObjectivesThis study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria.DesignHospital-based observational data of STEMI patients are linked with district-level information on SEE and the mortality register, enabling survival analyses with a 19-year follow-up (2000–2018).SettingThe analysis is set at the main tertiary care hospital of the City of Vienna. On weekends, it is the only hospital in charge of treating STEMIs and thus provides representative data for the Viennese population.ParticipantsThe study comprises a total of 1481 patients with STEMI, including women and men aged 24–94 years.Primary and secondary outcome measuresPrimary outcome measures are age at STEMI and age at death. We further distinguish between deaths from coronary artery disease (CAD), deaths from acute coronary syndrome (ACS), and other causes of death. SEE is ...
Background Health expectancy indicators aim at capturing the quality dimension of total life expe... more Background Health expectancy indicators aim at capturing the quality dimension of total life expectancy.; however, the underlying approach, definition of health, and information source differ considerably among the indicators available. Objective (1) Review the main concepts and approaches used to estimate health expectancy focusing on two widely used European health indicators: Health-Adjusted Life Expectancy (HALE) and Healthy Life Years (HLY); (2) identify underlying differences between the results yielded by these two indicators. Method Statistical differences between the HALE and HLY indicators by sex at ages 50, 60, and 70 were tested using pairwise and global Student´s t-tests and z-scores based on standard deviation. Data for 29 European countries were collected from the European Health Expectancy Monitoring Unit (EHEMU) information system and the World Health Organization (WHO) Global Burden of Disease Study 2016 (GBD 2016). Results The HALE indicator estimates were smoothe...
The COVID-19 pandemic caused an increase in mortality in 2020 with a resultant decrease in life e... more The COVID-19 pandemic caused an increase in mortality in 2020 with a resultant decrease in life expectancy in most countries around the world. In Germany, the reduction in life expectancy at birth between 2019 and 2020 was comparatively small, at -0.20 years. The decrease was stronger among men than among women (-0.24 vs. -0.13 years) and in eastern rather than in western Germany (-0.36 vs. -0.16 years). Men in eastern Germany experienced the biggest decline in life expectancy at birth (-0.41 years). For western German men, the decline was less pronounced (-0.19 years). Among women, the decline in life expectancy at birth was also greater in eastern (-0.25 years) than in western Germany (-0.10 years). As a result of these developments, the differences in life expectancy between the two parts of Germany, and between women and men, increased compared with the previous year. Life expectancy at age 65 decreased more strongly than life expectancy at birth for both sexes and in all region...
In this work, we assess the global impact of COVID-19 showing how demographic factors, testing po... more In this work, we assess the global impact of COVID-19 showing how demographic factors, testing policies and herd immunity are key for saving lives. We extend a standard epidemiological SEIR model in order to: (a) identify the role of demographics (population size and population age distribution) on COVID-19 fatality rates; (b) quantify the maximum number of lives that can be saved according to different testing strategies, different levels of herd immunity, and specific population characteristics; and (d) infer from the observed case fatality rates (CFR) what the true fatality rate might be. Different from previous SEIR model extensions, we implement a Bayesian Melding method in our calibration strategy which enables us to account for data limitation on the total number of deaths. We derive a distribution of the set of parameters that best replicate the observed evolution of deaths by using information from both the model and the data.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Li... more This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Health expectancy indicators: what do they measure? Indicadores de expectativa de vida saudável: o que medem?
Women live longer but can expect to spend more years in poorer health compared to men. In the con... more 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 affect 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 morta...
Data for ten European countries which provide detailed distribution of COVID-19 cases by sex and ... more Data for ten European countries which provide detailed distribution of COVID-19 cases by sex and age show that among people of working age, women diagnosed with COVID-19 substantially outnumber infected men. This pattern reverses around retirement: infection rates among women fall at age 60-69, resulting in a cross-over with infection rates among men. The relative disadvantage of women peaks at ages 20-29, whereas the male disadvantage in infection rates peaks at ages 70-79. The elevated infection rates among women of working age are likely tied to their higher share in health- and care-related occupations. Our examination also suggests a link between women's employment profiles and infection rates in prime working ages. The same factors that determine women's higher life expectancy account for their lower fatality and higher male disadvantage at older ages.
There is consistent evidence that women live longer than men at all ages, but spend a higher prop... more There is consistent evidence that women live longer than men at all ages, but spend a higher proportion of their total life expectancy in poorer health, a phenomenon described as the “male-female health-survival paradox” or the “gender paradox in health and mortality”. However, it is difficult to explain the process because morbidity by sex differs considerably across domains of health, age groups, social contexts and severity level. In addition, women and men report differently their health in surveys, making it cumbersome to understand whether what drives the paradox is a higher female morbidity or male mortality, a different reporting behaviour, or all of those aspects together. The aim of this chapter is to demonstrate the magnitude of those differences in Europe using different health domain indicators (activity limitation, chronic morbidity and self-perceived health) from the EHEMU Information System and the reporting behaviour by sex from the SHARE survey vignettes.
Despite ongoing substantial decline in total fertility since the 1960’s, age-specific fertility r... more Despite ongoing substantial decline in total fertility since the 1960’s, age-specific fertility rates for the age groups 15-19 and 20-24 rose from 1991 to 2000 (Berquó and Cavenaghi 2005). In this sense, Brazil is a very particular case of a rejuvenated fertility pattern. By 2010, the total fertility rate had already reached below replacement level at 1.9 children per woman and the age-specific fertility rates for younger women also started to fall, albeit still a high one when compared to other countries that underwent similar demographic transitions or have proximate fertility levels (Alves 2012). With an increasing unmet demand for contraception and a continuously lowering of fertility for the remaining age groups, it all indicates that this age group is the one with the most potential of contributing for the future of fertility trends in Brazil. This study provides simulations that show the short and long-term pure demographic effects of changes in fertility for these specific a...
This introduction to the 2021 special issue of the Vienna Yearbook of Population Research explore... more This introduction to the 2021 special issue of the Vienna Yearbook of Population Research explores demographic perspectives on human wellbeing across time and space. While the idea of relating demographic parameters to wellbeing has been around for a while, a more concrete research agenda on this topic has only recently gained momentum. Reviewing the research presented in this volume, we show how existing theoretical concepts and methodological tools in demography can be used to make substantial advances in the study of wellbeing. We also touch upon the many challenges researchers face in defining and measuring wellbeing, with the most important debate being about whether the focus should be on objective or subjective measures. The studies discussed here define wellbeing as health and mortality; as income, education or other resources; as happiness or life satisfaction; or as a combination thereof. They cover wellbeing in historical and contemporary populations in high- and low-inco...
The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to... more The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive, limiting their use to specific population subgroups. In this paper, we propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) in order to indirectly estimate the fraction of people ever infected (from the total population) and detected (from the ever infected). We apply the technique to the U.S. due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25% (0.39–2.16%, 90% CI) in F...
Period life expectancy is one of the most used summary indicators for the overall health of a pop... more Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Eu-rope-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.
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