A History of Population Health

In A history of Population Health Johan P. Mackenbach offers a comparative study of trends in 40 specific diseases in Europe and their explanation, focusing on the causes of the spectacular improvements in people’s health since the early 18th century. ; Readership: Health care professionals with an interest in medical history, students and scientists in public health, economics, sociology, and related disciplines, and anyone interested in the history of health and disease

A History of Population Health

In A history of Population Health Johan P. Mackenbach offers a comparative study of trends in 40 specific diseases in Europe and their explanation, focusing on the causes of the spectacular improvements in people’s health since the early 18th century. ; Readership: Health care professionals with an interest in medical history, students and scientists in public health, economics, sociology, and related disciplines, and anyone interested in the history of health and disease

Can inequalities in political participation explain health inequalities?

Inequalities in health are pervasive and durable, but they are not uniform. To date, however, the drivers of these between-country patters in health inequalities remain largely unknown. In this analysis, we draw on data from 17 European countries to explore whether inequalities in political participation, that is, inequalities in voting by educational attainment, are correlated with health inequalities. Over and above a range of relevant confounders, such as GDP, income inequality, health spending, social protection spending, poverty rates, and smoking, greater inequalities in political participation remain correlated with higher health inequalities. If ‘politicians and officials are under no compulsion to pay much heed to classes and groups of citizens that do not vote’ then political inequalities could indirectly affect health through its impact on policy choices that determine who has access to the resources necessary for a healthy life. Inequalities in political participation, then, may well be one of the ‘causes of the causes’ of ill-health

How comparable are different measures of self-rated health? Evidence from five European countries

Self-rated health (SRH) is a common health measurement in international research. Yet different versions of this item are often applied. This study compares the US (United States) version (from excellent to poor) and the EU (European) version (from very good to very bad) of SRH, and examines differences in their associations with demographic and objective health variables. Data were drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE), comprising information from 11,622 respondents aged 50 years and over in five countries. Respondents were presented with both the EU and US versions. Information was collected on basic demographics and health variables including chronic diseases, symptoms, functional limitations and depression. Firstly, the distribution of each version of the SRH item was assessed, and both relative and literal concordance was examined. Subsequently, multivariate regression analysis was used to assess differences in the associations of both items with demographic and health indicators. The US version has a more symmetric distribution and smaller variance than the EU version. Although the EU version discriminates better at the negative end, the US version shows better discrimination at the negative end of the scale. 69% of respondents provided literally concordant answers, while only about one third provided relatively concordant answers. Overall, however, less than 10% of respondents were discordant in either sense. Furthermore, the two versions were strongly correlated (polychoric correlatio

Trends in inequalities in disability in Europe between 2002 and 2017

Monitoring socioeconomic inequalities in population health is important in order to reduce them. We aim to determine if educational inequalities in Global Activity Limitation Indicator (GALI) disability have changed between 2002 and 2017 in Europe (26 countries). We used logistic regression to quantify the annual change in disability prevalence by education, as well as the annual change in prevalence difference and ratio, both for the pooled sample and each country, as reported in the European Union Statistics on Income and Living Conditions (EU-SILC) and the European Social Survey (ESS) for individuals aged 30–79 years. In EU-SILC, disability prevalence tended to decrease among the high educated. As a result, both the prevalence difference and the prevalence ratio between the low and high educated increased over time. There were no discernible trends in the ESS. However, there was substantial heterogeneity between countries in the magnitude and direction of these changes, but without clear geographical patterns and without consistency between surveys. Socioeconomic inequalities in disability appear to have increased over time in Europe between 2002 and 2017 as per EU-SILC, and have persisted as measured by the ESS. Efforts to further harmonise disability instruments in international surveys are important, and so are studies to better understand international differences in disability trends and inequalities.</p

Екслібриси Станіслава Шодуара на книжках родового бібліотечного зібрання Шодуарів у фондах НБУВ

Проаналізовано екслібриси з рукописно-книжкового зібрання найвідомішого представника роду баронів Шодуарів – Станіслава Шодуара, зокрема, здійснений їх книгознавчий та мистецтвознавчий аналіз, визначено кількість та різновиди екслібрисів Станіслава Шодуара у різні періоди, атрибутовано авторство, встановлено роль екслібрисів у контексті формування та розвитку зібрання першої половини ХІХ ст.The author performs the analysis of the bookplates from the manuscript and book collection of the most famous member of the Chaudoir family – Stanislav Chaudoir. In particular, their bibliological and art analysis is carried out, the number and kinds of Chaudoir’s bookplates are defined, the authorship is attributed, the role of bookplates in the context of formation and growth of the collection if the 1st half of the 19th century is ascertained

Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter?

Background Currently, poor-rich inequalities in health in developing countries receive a lot of attention from both researchers and policy makers. Since measuring economic status in developing countries is often problematic, different indicators of wealth are used in different studies. Until now, there is a lack of evidence on the extent to which the use of different measures of economic status affects the observed magnitude of health inequalities. Methods This paper provides this empirical evidence for 10 developing countries, using the Demographic and Health Surveys data-set. We compared the World Bank asset index to three alternative wealth indices, all based on household assets. Under-5 mortality and measles immunisation coverage were the health outcomes studied. Poor-rich inequalities in under-5 mortality and measles immunisation coverage were measured using the Relative Index of Inequality. Results Comparing the World Bank index to the alternative indices, we found that (1) the relative position of households in the national wealth hierarchy varied to an important extent with the asset index used, (2) observed poor-rich inequalities in under-5 mortality and immunisation coverage often changed, in some cases to an important extent, and that (3) the size and direction of this change varied per country, index, and health indicator. Conclusion Researchers and policy makers should be aware that the choice of the measure of economic status influences the observed magnitude of health inequalities, and that differences in health inequalities between countries or time periods, may be an artefact of different wealth measures used

Sports participation, perceived neighborhood safety, and individual cognitions: how do they interact?

After publication of this work [Beenackers et al: Int J Behav Nutr Phys Act 2011, 8:76] it was realized that formula 3 and formula 4 in the Statistical Analysis section of the Methods were incorrectly listed. Since the formulas were correctly used in the analysis, this correction does not affect the results or conclusions of the paper