Widening educational disparities in all-cause mortality: An analysis of Austrian data with international comparisons

Recent studies have demonstrated a widening in the relative mortality gap between the various socio-economic classes in several industrialised, Western countries. The present paper aims to determine whether or not education-related differentials in mortality have increased between 1981/82 and 1991/92 in Austria, and compares these findings with those gleaned from other European countries as well as the US and New Zealand. For the Austrian analysis, the data source consists of census records from 1981 and 1991 for the entire Austrian population that were linked with the respective death registry records for a follow-up period of one year. The disparities were measured by means of the regression-based Slope Index of Inequality and Relative Index of Inequality. The findings suggest that educational inequalities in mortality have widened in Austria, but more among men than among women. Austrian results are similar to patterns observed in other countries. International patterns pertaining to social disparities in mortality appeared mixed, when we distinguish between the various age groups and between men and women. However, widening educational mortality disparities are a worldwide phenomenon, a phenomenon that persists even when the educational expansion of the 1980s is taken into account.

Widening educational inequalities in mortality: An analysis for Austria with international comparisons

Recent studies have reported a widening in the relative mortality gap between the socioeconomic classes in several industrialized western countries. The present paper aims to determine whether or not education-related differentials in mortality have increased between 1981/82 and 1991/92 in Austria, and compares the findings with those from other European countries, the USA and New Zealand. For the Austrian analysis the source of the data is based on a one year mortality follow up of the entire Austrian census population, and contains for the examined population aged 30-74 in total 3,805,208 individual records for 1981/82 and 4,064,184 records for 1991/92 of which 34,218 and 29,443 were deceased. The study applies a sophisticated measure of inequality that takes into account the relative position of the educational groups, since changing educational compositions over time may reduce comparability. The findings suggest that educational inequalities in mortality have widened in Austria, but more among men than among women. The Austrian results are similar to patterns observed in the other countries. However, the international trends vary with regard to age groups and sex

Analysis of inequalities in waiting time at the visit to the physician using regression modeling for duration data

When we visit our physician, we usually have to wait for a more or less long duration until we are called into the doctors' office. This study reveals inequalities in the waiting time at the visit to the general practitioner by using multiplicative intensity regression analysis, which is frequently used for modeling time to event data. In general, people with higher education have a higher efficiency to reduce waiting time. Further, Austrians show a higher efficiency than foreigners. With regard to health-related factors, those with better health and less frequent consultations have also a higher efficiency to reduce waiting time. It also matters where people live. Those living in rural areas in general wait longer, and furthermore, the longer the journey from home to the doctors' practice takes, the longer is the waiting time

The contributions of diseases to increasing educational mortality differential in Austria

This paper examines how much changing educational disparity for specific causes of death contributed to the change in overall educational mortality disparity between 1981/82 and 1991/92 among Austrian adults aged 30-74 years. Besides specific causes of death, the study also examines educational differentials for both avoidable causes of death and mortality amenable to medical intervention. The data source is based on a one-year mortality follow-up of the total Austrian census population. The data for the examined population is made up of individual records for people aged 30-74, totaling 3,805,208 for 1981/82 and 4,064,184 for 1991/92, from which 34,218 and 29,443, respectively, were on deceased persons. The study uses a new approach for decomposing the change in overall mortality differentials into contributions of specific causes to the change. For this purpose, it extends the regression-based Slope Index of Inequality. The findings suggest that educational inequalities in overall mortality have widened significantly in Austria, but more among men than among women. However, without the increase in the disparity for ischemic heart disease, between 1981/82 and 1991/92, there would have been a decline in absolute educational disparity in overall mortality among Austrian men and women. Also striking are the rising absolute and relative disparities for diabetes among females as well as the increasing disparities for colorectal cancer and digestive diseases among men. Increasing differentials in avoidable mortality essentially contributed to increased educational disparities in overall mortality. With regard to mortality amenable to medical treatment, the differentials increased considerably for men but not for women

Behavioral explanation for educational health and mortality differentials in Austria

The present study examines the health behavior of more than 30,000 individuals aged 25-74 in Austria, using education as an indicator of socioeconomic status. Of particular interest is the magnitude of the educational disparities in health behavior between hypothetical most and least educated, measured by the Relative Index of Inequality. The findings show that education has a great positive impact on the extent to which a person lives a healthy lifestyle with regard to diet, physical activity, and smoking. Furthermore, the prevalence of overweight decreases significantly with any increase in education, and people with more education are also much more likely to get their periodical vaccinations

Sozioökonomische Ungleichheiten im Gesundheitsverhalten in Österreich

"Warum leben Menschen mit höherem sozioökonomischen Status im Durchschnitt länger als jene mit geringerem sozioökonomischen Status und warum sind diese im Allgemeinen gesünder? Unterschiede in Bezug auf Gesundheit und Mortalität können dabei auf Ungleichheiten im Gesundheitsverhalten und auf unterschiedliche Umwelteinflüsse zurückgeführt werden. Die vorliegende Studie zeigt derartige sozioökonomische Ungleichheiten im Gesundheitsverhalten der österreichischen Bevölkerung auf. Die sozioökonomischen Faktoren Bildungsabschluss, Gemeindetyp, Staatsbürgerschaft und Familienstand beeinflussen stark den Lebensstil, den Body Mass Index, das Auftreten von Stress sowie die Bereitschaft zur Gesundheitsvorsorge. Insbesondere das Bildungsniveau, welches hier den sozioökonomischen Status beschreibt, spielt im Gesundheitsverhalten eine wesentliche Rolle." (Autorenreferat)"Why do people of higher socioeconomic status, on average, live longer than those of lower socioeconomic status do, and why are they generally in a better state of health? In this context, differences with regard to health and mortality may be traced back to inequalities in health behavior, strains, and environment. This study reveals such socioeconomic inequalities in health behavior and strains among the Austrian population. The socioeconomic covariates educational attainment, municipality type, nationality and marital status affect the lifestyle, the body mass index, the occurrence of stresses and strains, and the taking of preventive health measures to a great extend. In particular, educational attainment, which serves as the most relevant proxy for socioeconomic status, plays a substantial role when it comes to health behavior." (author's abstract

Alcohol-related mortality among men in Austria 1981 - 2002 and the importance of qualification and employment

The aim of this paper is to explore the relationship between alcohol-related mortality and social status among men in Austria, and to examine changes during the 1980s and 1990s. We linked individual census records for the Austrian population from 1981, 1991, and 2001 with death register records for a follow-up period of one year. The final data set contains 5,038,654 records of men 35-74 years old, of whom 3824 died of causes explicitly related to alcohol abuse. Standardized mortality ratios by education, occupation and employment were calculated for alcohol- and non-alcohol-related causes of death. A regression-based inequality measure was used for analyses of trends. We find that low educated men were 2.77 (1981/82), 3.49 (1991/92), and 3.23 (2001/02) times more likely to die of alcohol-related causes of death than high educated, while it was just 1.59, 1.80, and 1.89 for other conditions. Among men 35-59 years old, unskilled blue-collar workers had on average a 5.6 and 5.0 times higher risk than upper white-collar employees in 1981/82 and 1991/92; for non-alcohol related causes it was 2.0 and 2.2. Unemployed or early retired men were particularly at risk. In 2001/02 low-skilled inactive were 18 times more likely to die on alcohol-related causes than high-skilled economically active men. Over time the social inequalities in alcohol-related mortality increased but only between 1981/82 and 1991/92; and among those 35-59 years old only for the economically inactive. A good education and sophisticated vocational skills are important protective factors for alcohol problems; however, what matters most is whether or not people are employed

University Education: An Analysis in the Context of the FAMSIM+ Microsimulation Model for Austria

Das ÖIF betreibt zum Thema Bildungsentscheidung aktuelle Forschungen, u.a. werden Mikroanalysen als Basis eines Simulationsmodells verwendet, welches die zukünftige Zusammensetzung der österreichischen Bevölkerung nach Bildungsschicht untersucht. Diese Modelle schließen zusätzlich das unterschiedliche Fertilitätsverhalten (Anzahl, Zeitpunkt von Geburten) und Partnerschaftsverhalten (etwa Bildungsunterschiede in Partnerschaften) unterschiedlicher Bildungsgruppen ein. Datenbasis für diese Mikrosimulationsmodelle ist das Sonderprogramm des Mikrozensus 2/1996.This working paper on university education analyzes the influencing factors on university enrollment rates, graduation vs. dropout rates as well as study durations in Austria. The analysis is based on the special program of the 1996 micro census that includes detailed educational histories. On the macro level, a considerable increase of enrollment rates can be observed that more than doubled in the second half of the last century. Female enrollment rates that were only one third of the male rates for the 1935-39 birth cohort, have already drawn level with the male rates. Changes on the macro level are the outcome of decisions taken by the individual agents on the micro level. Moving from the macro to a micro analysis of university enrollments and graduations, a very stable relation between parents’ educational attainments and the university graduation rates of their offspring can be found, besides the diminishing gender differences in educational behavior. For given educational levels of the parents, enrollment rates almost remained constant or even slightly decreased over time for the males, while female rates moderately increased and eventually met the male rates in the last decades. Given the marked differences in enrollment rates according to parents’ education - for the last birth cohort 1965-69 the rates range from around 4% to nearly 60% for the lowest and the highest (of the five) educational groups - a considerable part of the changes on the macro level can therefore be attributed to the changing educational composition of the parents’ generation. This result is consistent with the findings regarding prior educational transitions as studied in two previous papers. Being written in the framework of the FAMSIM+ microsimulation model currently under development at the Austrian Institute for Family Studies, various regression models regarding university education will be developed in this paper, besides providing a descriptive analysis. These models will serve as basis of the behavioral modules of the FAMSIM+ model that consists of three sub modules regarding university enrollments and graduations: First, it is determined whether a person enrolls at university. Second, it is decided if an enrolled person will graduate from university or drop out. Third, the individual enrollment duration is determined by means of a survival analysis

Gender, Regional and Social Differences at the Transition from Lower to Upper Secondary Education: An Analysis in the Context of FAMSIM+ Family Microsimulation Model for Austria

Die Entwicklung von Simulationsmodellen nimmt in der sozioökonomischen Abteilung einen zentralen Forschungsschwerpunkt ein, dies einerseits in der Form von Hochrechnungsmodellen zur Berechnung von Kosten und Verteilungswirkungen familienpolitischer Maßnahmen (Förderungen) - hierzu wurden insbesondere Modelle und Softwarepakete für die Bundesländer Niederösterreich und Wien entwickelt - und andererseits in der Form des dynamischen Mikrosimulationsmodells FAMSIM. Dynamische Mikrosimulation erlaubt es, die Individuen einer Bevölkerung über ihren ganzen Lebenslauf im Computer zu simulieren, was insbesondere zur Erforschung demographischer Prozesse dient bzw. die Erforschung der Auswirkungen dieser Prozesse auf andere Systeme - wie etwa Pensionssysteme. Statische "cell-based" Modelle zur Berechnung der Kosten von Familienförderungen in der Form frei parametrisierbarer Simulationsmodelle auf Basis von realen Antragsdaten zu Förderungen: Anwendungen in Wien und Niederösterreich. Modellierung, Programmierung und ökonometrische Schätzung des dynamischen FAMSIM Modells für 5 Europäische Länder; Internationale Vergleichsstudien zu typischen "Risikomustern" betreffend dem Beginn und Ende von Partnerschaften, Erwerbstätigkeit, Ausbildungen sowie Schwangerschaften/Geburten. Zusammenführung der statischen und dynamischen Modelle zu einem dynamischen Familien - Mikrosimulationsmodell FAMSIM+ zur Erforschung demographischer Prozesse (wie sich verändernder Familienstrukturen) sowie der Evaluierung der Kosten und Wirkung familienrelevanter Maßnahmen im Quer- und Längsschnitt. Dieser Ansatz erlaubt zum Beispiel die Erforschung der Auswirkungen von Erwerbsunterbrechungen zur Kinderbetreuung auf die gesamte weitere Erwerbskarriere einschließlich Pensionsansprüche. Nationale und internationale Kooperationen für verschiedene Anwendungsgebiete, wie derzeit für Bildungsprognosen (Kooperation mit dem Institut für Bildungsforschung der Wirtschaft) sowie im Bereich Altenpflege (Netzwerkpartner im International Network for the Research on Elderly Care INREC).The central aim of this paper is to reveal differences in educational placement at the transition from lower to upper secondary education, such as gender differences, differences caused by the education of parents, the place of living (rural vs. urban areas) as well as by the type of school attended in lower secondary education ('Hauptschule' vs. 'AHS'). Beside a descriptive analysis, this paper develops a model of the second educational choice in the form of a logistic regression model with multiple outcome that can be directly employed in the FAMSIM+ microsimulation project, currently developed at the Austrian Institute for Family Studies

Education and the importance of the first educational choice of the FAMSIM+ Family Microsimulation Model for Austria

Die Entwicklung von Simulationsmodellen nimmt in der sozioökonomischen Abteilung einen zentralen Forschungsschwerpunkt ein, dies einerseits in der Form von Hochrechnungsmodellen zur Berechnung von Kosten und Verteilungswirkungen familienpolitischer Maßnahmen (Förderungen) - hierzu wurden insbesondere Modelle und Softwarepakete für die Bundesländer Niederösterreich und Wien entwickelt - und andererseits in der Form des dynamischen Mikrosimulationsmodells FAMSIM. Dynamische Mikrosimulation erlaubt es, die Individuen einer Bevölkerung über ihren ganzen Lebenslauf im Computer zu simulieren, was insbesondere zur Erforschung demographischer Prozesse dient bzw. die Erforschung der Auswirkungen dieser Prozesse auf andere Systeme - wie etwa Pensionssysteme. Statische "cell-based" Modelle zur Berechnung der Kosten von Familienförderungen in der Form frei parametrisierbarer Simulationsmodelle auf Basis von realen Antragsdaten zu Förderungen: Anwendungen in Wien und Niederösterreich. Modellierung, Programmierung und ökonometrische Schätzung des dynamischen FAMSIM Modells für 5 Europäische Länder; Internationale Vergleichsstudien zu typischen "Risikomustern" betreffend dem Beginn und Ende von Partnerschaften, Erwerbstätigkeit, Ausbildungen sowie Schwangerschaften/Geburten. Zahlreiche Publikationen: ÖIF Schriftenreihe, ÖIF Working-Paper, IIASA Interim Report, Brasilian Electronic Journal of Economics. Zusammenführung der statischen und dynamischen Modelle zu einem dynamischen Familien - Mikrosimulationsmodell FAMSIM+ zur Erforschung demographischer Prozesse (wie sich verändernder Familienstrukturen) sowie der Evaluierung der Kosten und Wirkung familienrelevanter Maßnahmen im Quer- und Längsschnitt. Dieser Ansatz erlaubt zum Beispiel die Erforschung der Auswirkungen von Erwerbsunterbrechungen zur Kinderbetreuung auf die gesamte weitere Erwerbskarriere einschließlich Pensionsansprüche. Nationale und internationale Kooperationen für verschiedene Anwendungsgebiete, wie derzeit für Bildungsprognosen (Kooperation mit dem Institut für Bildungsforschung der Wirtschaft) sowie im Bereich Altenpflege (Netzwerkpartner im International Network for the Research on Elderly Care INREC)