Behavioural and structural prevention to promote the health of socially disadvantaged children and adolescents: an overview of European and German health promotion strategies

This study aims to determine the predictive factors of technical efficiency of Organization for Economic Co-operation and Development (OECD) countries according to Health Care Quality Indicators (HCQI) and health status measures. The technical efficiency of OECD countries was analyzed by using data envelopment analysis and different model specifications from 1 to 13. Data was obtained from HCQI project statistics and OECD reports for the years between 2008 and 2011. The technical efficiency of OECD countries according to acute care, primary care, cancer care, cardiovascular diseases, and diabetes and health status measures was determined. The different model specification results indicate that the first model, which includes HCQI, such as primary care, acute care, cancer care, and cardiovascular diseases, as input variables and life expectancy and maternal mortality as output variables have the highest technical efficiency score (79%). The most influential variable that predicts the technical efficiency of OECD countries according to HCQI and health status measures is case fatality in adults within 30 days after admission for acute myocardial infarction (AMI). This study highlights the need to improve diagnostic and treatment technologies of acute care to reduce hospital mortality following AMI to develop quality of health care in developed countries.

This scientific article is devoted to the analysis of challenges, trends, and opportunities for rural development of the OECD (Organization for Economic Cooperation and Development) member countries. Agriculture plays a crucial role in global food security but faces significant challenges such as climate change, demographic change, and economic hardship. The importance of the member countries of the Organization for Economic Cooperation and Development (OECD) in the global development of the agro-industrial complex cannot be underestimated. OECD countries occupy an important place in the world production and export of agricultural products, which is pivotal in ensuring global food supply. They attract significant investments in the agro-industrial sector, contributing to the modernization of production technologies, the introduction of innovations, and increased productivity. OECD countries have a developed scientific base that helps improve agricultural practices, implement environmentally friendly production methods, and create sustainable rural development. In addition, OECD countries influence the formation of international standards and policies related to the agro-industrial complex. They cooperate in trade in agricultural products, develop strategies to ensure food security, and support the development of rural communities. Thus, the OECD countries play an essential role in the global expansion of the agro-industrial complex, attracting investments, introducing the latest technologies, defining standards, and cooperating with other countries. Their efforts aim to achieve sustainable, innovative, and socially responsible development of the agro-industrial sector, which is essential for ensuring food security and improving the population's quality of life. The article analyzes the current state of production and consumption of critical products of the OECD agro-industrial complex. It considers opportunities for the development of agriculture, particularly in the context of sustainable development, technological progress, and innovative approaches. Within the framework of this article, both opportunities and challenges and trends of systemic development of agriculture in OECD countries are analyzed in the medium term. Conclusions on the research topic are formed. Keywords: agriculture, OECD, agro-industrial complex, agro-industrial complex, development of agriculture.

Social Exclusion of the Elderly: A Comparative Study of EU Member States

Background Gender plays a well-recognized role in many health inequalities. However, the population-level health consequences of gender inequalities have not been measured comprehensively. The goal of this study, therefore, was to evaluate associations between gender inequality and health indicators in OECD countries. Methods Ecological study based on 1990-2017 panel data for Organisation for Economic Co-operation and Development (OECD) member countries. Gender inequality was measured using the Gender Inequality Index (GII). The population health parameters evaluated were: life expectancy (LE), healthy life expectancy (HALE), years of life lost (YLL), years lived with disability (YLD), disability-adjusted life years (DALYs), and specific-cause mortality. Two way fixed-effects linear models were developed to assess the relationship between gender inequality and health outcomes. Models included potential mediating and confounding factors such as health spending, political model, and economic inequities. Results Greater gender inequality was associated with lower LE (-0·49%; CI95 -0·63%- -0·31%; p-value <0·0001) and HALE (-0·47%; CI95 -0·63%- -0·31%; p-value <0·0001) as well as less-favorable figures for YLL (6·82%; CI95 3·63%-10·75%; p-value <0·0001), DALYs (1·50%; CI95 0·48%-2·46%; p-value=0·0028), and YLD (2·59%; CI95 0·67%-4·77%; p-value=0·0063). The sensitivity analysis indicated that the results were robust to the various specifications of the causal models. Conclusions Our results suggest that gender inequality has a negative impact on the health of the population. Promoting gender equality as part of policy-making is vital for optimizing health on a population scale Key messages Reduce gender inequality can advance health outcomes on a population scale, resulting in increased LE and HALE and decreasing YLL, YLD, and DALY, in the general population, and in men as well as women. This information supports the need to develop gender-sensitive public policies, for the benefit of society as a whole.

This study empirically explores international and intersectoral R&D spillover effects on the total factor productivity growth of manufacturing and nonmanufacturing sectors based on a pooled time‐series data set of 14 OECD economies and 3 East Asian economies—Korea, Singapore, and Taiwan. The study finds that foreign manufacturing R&D has strong influence on domestic productivity growths of both sectors and that domestic manufacturing R&D has a substantial intersectoral R&D spillover effect on domestic nonmanufacturing productivity growth. The social rates of return to manufacturing R&D are estimated to be two to six times greater than the private rates of return.

1. Introduction Improvements in health and welfare have increased life expectancy in the world. Increasing life expectancy together with low fertility rates (in other words population ageing) is one of the greatest challenges that countries are facing now and in the future. Public pension spending increased 6.4% in the OECD (Organisation for Economic Co-operation and Development) between 1980-2007 in parallel with growing retired population (Adema, et al., 2011, p.3). Public spending on pensions and other retirement benefits in OECD countries grew on average 17.5% faster than national income between 1990 and 2005 (OECD, 2009, p.2). It will become harder for the governments to sustain fiscal sustainability of public pension systems in the long term. Life expectancy at birth for males is projected to increase by about 8 years over the projection period, from 76.7 in 2010 to 84.6 in 2060. Life expectancy at birth is projected to increase by 6.5 years for females, from 82.5 in 2010 to 89.1 in 2060 in the EU (European Union). On the other hand the total fertility rate is projected to rise from 1.59 in 2010 to 1.64 by 2030 and further to 1.71 by 2060. The EU population is projected to increase (from 502 million in 2010) up to 2040 by almost 5%, when it will peak (at 526 million). Thereafter, a steady decline occurs and the population shrinks by nearly 2% by 2060. Nonetheless, according to the projections, the population in 2060 will be slightly higher than in 2010, at 517 million. The age structure of the EU population is projected to change dramatically during projection period. It is projected that the population aged 15-64 will drop by 14%, and the population aged 65 and above will almost double, rising from 87.5 million in 2010 to 152.6 million in 2060 in the EU. Consequently the demographic old-age dependency ratio (people aged 65 or above relative to those aged 15-64) is projected to increase from 26% to 52.5% in the EU as a whole over the projection period (European Commission, 2012a, pp.24-27). The purpose of this study is firstly to present the public pension systems briefly and then evaluate the financial sustainability of public pension systems in consideration of pension expenditures, ageing and the Eurozone sovereign debt crisis. 2. Structures of Pension Systems in the EU Member Countries Pension systems in EU-27 differ from each other in a lot of ways such as general and financial structures, pension schemes, eligibility requirements, and conditions of normal and early retirements, historical past, income sources, economic development levels and demographic structures of member countries. However pension systems of many EU member countries rests on three pillars which are called as public pensions, funded occupational pensions and personal pension plans. The share of these pillars within the overall architecture varies from country to country. Classifications of mandatory parts of the pension systems of EU member countries in accordance with OECD are given in Table 1. EU countries generally use multiple programs which are designed to ensure pensioners achieve some absolute, minimum standard of living. Similarly the mandatory second-tier, savings components of pension systems are different across EU countries. Defined benefit (DB) plans are provided by the public sector in 12 EU countries and by the private sector in the Netherlands. Defined-contribution (DC) plans are compulsory in 6 EU countries. In Denmark and Sweden, there are quasi-mandatory, occupational DC schemes in addition to smaller compulsory plans. The notional-accounts schemes (sometimes call defined-contribution plans (NDC)) used by 3 countries (Italy, Poland and Sweden) and points schemes used by 4 countries (Estonia, France, Germany and Slovak Republic). When the pension schemes in EU member countries are analyzed, it is seen that public pensions dominate the pension system mostly, occupational pension schemes are mandatory only in Austria, Netherlands; mandatory for public sector employees in Ireland, Malta, Spain; mandatory for only for selected professions in Portugal, Slovenia and quasi mandatory in Denmark, Sweden and it does not exist in 8 countries. …

ABSTRACTObjectivesTo examine the associations of health and social spending with health outcomes, including Disability‐Adjusted Life Years (DALY), Years of Life Lost (YLL), Years Lived with Disability (YLD), death, and life expectancy at birth among Organization for Economic Cooperation and Development (OECD) member countries from 2000 to 2019.Study Setting and DesignWe conducted a retrospective longitudinal study.Data Sources and Analytical SampleOur sample included 36 OECD member countries as of 2019 using data from the Global Burden of Disease Study 2021, the OECD, and the World Bank.Principal FindingsFixed‐effect analysis revealed significant associations of health and social spending with health outcomes, but the patterns varied. Specifically, a one‐percentage‐point increase in health spending was associated with a 1.43% (95% CI: −1.86, −1.01) decrease in the death rate per 100,000 population and a 0.68% (0.56, 0.79) increase in YLD per 100,000 population. In contrast, a one‐percentage‐point increase in social spending was associated with a 0.29% (−0.45, −0.12) reduction in DALYs, primarily driven by a 0.30% (−0.37, −0.23) decrease in YLDs and a 0.07% (0.03, 0.12) increase in life expectancy. No significant associations were found for the remaining outcomes. These associations remained robust when incorporating one‐ and two‐year lagged effects.ConclusionsThese findings highlight the distinct mechanisms through which health and social spending impact health outcomes. Health spending predominantly influenced mortality, while social spending was more closely associated with improvements in quality‐of‐life measures. Policymakers should consider these complementary effects when designing interventions to optimize health outcomes.

(ProQuest: ... denotes formulae omitted.)1.IntroductionSuicide - intentional death resulting from a victim's own action - is the product of a complex interplay between individuals and society (Durkheim 1952). Since the mid1990s, South Korea (hereafter Korea) has experienced an unprecedented increase in suicide, and currently has the third highest suicide rate in the world, after Guyana (44.2 per 100,000) and North Korea (38.5 per 100,000) (World Health Organization 2014). In 2010, Korea had both the highest suicide rate and the highest rate of increase in suicide among the Organization for Economic Co-operation and Development (OECD) countries (Figure 1). At 33.5 per 100,000, Korea's suicide rate was nearly 2.5 times higher than the average rate for OECD countries (13.3 per 100,000) (World Health Organization Statistical Information System 2014). For Korea, this rate translates into about 40 suicides every day, or about one suicide every 37 minutes. Indeed, the suicide epidemic has become one of the most important and urgent public health concerns in Korea (Kim and Yoon 2013).The alarming rise in Korea's suicide rate has occurred alongside a rapid increase in life expectancy. In 1960, life expectancy in Korea was only 53.0 years, which was well below the OECD average; by 2012 it had risen to 81.4 years, surpassing the OECD average (World Bank Group 2013; Yang et al. 2010) (see Figure 2). This equates to an increase of nearly 28.4 years over the last five decades, or more than one-half year each year, a remarkable gain. With the rapid rise in the suicide rate that began in the mid-1990s, understanding the contribution of suicide to life expectancy has become more critical because it is important for designing effective public policies to promote better population health.The effect of suicide on life expectancy depends on two factors, the proportion of people who commit suicide (that is, the lifetime risk of dying from suicide), and the average age of suicide victims. Hence the effect of change in suicide on change in life expectancy is a function of change in the proportion of people who commit suicide (the suicide rate) and change in the average age of suicide victims compared to their life expectancy. We subsequently describe a method for estimating the separate contributions of change in the suicide rate (the 'incidence component') from change in the average age of suicide victims (the 'age component'). The important point to note here is that change in the suicide rate is not the entire story. Because suicide victims tend to be disproportionately young or middle-aged, the effect of rising suicide rates on life expectancy can be substantially diminished if the age of the suicide victims also rises. Likewise, the effect of falling suicide rates can be diminished if the age of suicide victims declines.To understand the contributions of suicide to life expectancy in Korea, this study examines how much the rise in suicide rate has reduced life expectancy in Korea and why, using the age-incidence decomposition method to separate the age component from the incidence component (Firebaugh et al. 2014). Specifically, this study addresses the following questions. Has the reduction been a) entirely a function of the change in suicide rate (i.e., no age component), or b) a function of change in suicide rates and an age component? If the reduction has been a function of change in suicide rates and an age component, is the age component positive (indicating that the adverse effect of the rising suicide rate has been attenuated), or negative (indicating that the adverse effect of the rising suicide rate has been amplified)?2.Suicide in the Korean contextGiven the unprecedented increase in suicide rates in Korea in the past two decades, its contribution to total mortality is worthy of study. The importance of considering the role of suicide in life expectancy is apparent: Suicide is the leading cause of death for all individuals in their teens, twenties, and thirties. …

Purpose The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018. Design/methodology/approach We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure. Findings Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input. Practical implications These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation. Originality/value Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

Countries of the Organization for Economic Cooperation and Development (OECD) exhibit substantial increases in both income inequality and obesity prevalence since the 1970s. Income inequality may affect obesity through increased psychosocial distress, concentrated poverty, erosion of social cohesion, and inadequate policy interventions. Substantial variations appear in estimated obesity prevalence across OECD countries in 2010. Particularly important are the United States and Mexico, which lead OECD countries in current obesity rates, income inequality, and the pace of increases in obesity prevalence over time. When both countries are included in the analysis, differences in obesity prevalence are more related to differences in income inequality than to differences in absolute income across these countries. This association between income inequality and obesity prevalence virtually disappears when both countries are excluded from analysis. So far, limited research exploring the association between income inequality and obesity has not yielded conclusive, unequivocal findings.

Background: Height is considered an indicator of health and well-being of an individual and population. Height variation results from a complex interaction of genetic, environmental, socioeconomic, and cultural influences. In order to understand the contribution of environmental stress associated with the child's growth, we correlated indicators of a stressful environment with adult height.Methods: We utilized seven equally weighted indicators of a stressful environment: homicide rates, GDP per capita, income inequality (GINI index), corruption perception index (CPI), unemployment rate, urban air pollution, and life expectancy (LE). Data on male and female height by country from 1992 to 1996 were obtained from the NCD Risk Factor Collaboration dataset. We assessed separately data from the 31 member countries of the Organization for Economic Co-operation and Development (OECD). In order to establish whether the indicators reflected a single conceptual dimension, we conducted an exploratory analysis and principal component analysis (PCA) with orthogonal transformation of the original variables. The relationships between male and female heights and the z-transformed principal components: Quality of life (QoL) and the Social factor (SF) that were derived after the PCA was assessed.Results: Male and female heights strongly correlated (p < 0.0001) with each of the seven indicators. In the PCA, the indicators clustered into “Quality of Life” factors (QoL), which comprised the CPI, GDP, air pollution, LE, and “Social factors” (SF), which comprised homicide rate and GINI index. For males and females, the average height by country strongly correlated with QoL (p < 0.0001) and SF (p < 0.0001). Within OECD countries, male and female height strongly and negatively correlated with the SF, but not with QoL.Conclusion: Growth attenuation is a tradeoff adaptive response: a calorie used for growth cannot be used for fighting stress. Here we show that: (1) Adult height, when used as a measure of child's growth, is an indicator of a stressful environment in context with the genetic background and spatial factors; (2) Stressful QoL factors and the SF exert a greater effect on men's height than women's height; and (3) The ranking of the indicators of short stature are income inequality > air pollution > GDP > CPI > homicide rate > LE > unemployment.

Aims: This study examines the impact of the number of health personnel and health expenditures on life expectancy and infant mortality rates in Turkiye. The study's primary purpose is to determine the effect of increased health personnel and health expenditures on quality of life and infant mortality rates. Therefore, the impact of health personnel and expenses on life expectancy and infant mortality rates was investigated. It was analyzed how these variables shape the effectiveness of health services and how they affect public health. Methods: This study used multiple regression analysis to assess the effects of healthcare workforce and expenditures on health outcomes in Turkiye between 2001 and 2021. Life expectancy and infant mortality rate were dependent variables, while per capita healthcare expenditure, the number of doctors, and the number of nurses were used as independent variables. Data were obtained from the World Health Organization (WHO) and the Organization for Economic Cooperation and Development (OECD) databases and analyzed using the SPSS software. Results: The findings indicate that per capita healthcare expenditures positively and significantly affect life expectancy (B=0.015, p=0.016), suggesting that increases in healthcare spending contribute to longer life expectancy. Conversely, the effects of the number of doctors (B=-1.580, p=0.138) and nurses (B=0.232, p=0.400) were not statistically significant, indicating that workforce numbers alone may not directly impact life expectancy. Regarding infant mortality rate, healthcare expenditure (B=0.016, p=0.166) and doctor availability (B=-1.503, p=0.467) showed negative associations, while the number of nurses had a positive but non-significant association (B=0.407, p=0.457). Although these variables theoretically demonstrated the potential to reduce infant mortality rates, none of these effects reached statistical significance. The model explained 82.5% (R²=0.825) of the variance in life expectancy and 88.7% (R²=0.887) in infant mortality rate, underscoring the model's robustness in explaining variations in these health outcomes. Conclusion: The study findings suggest that while healthcare expenditures positively affect life expectancy, the number of healthcare workers alone is insufficient, and factors such as service quality and efficiency also play a role. In developing health policies, strategies should focus on systematically improving the quality of services rather than merely increasing the number of personnel. Particularly in rural and low-income areas, the scope and quality of healthcare services should be enhanced to reduce disparities in health indicators.

economics of education in 1963, and the proceedings (Robinson and Vaizey, 1966) contain several very interesting items on the contribution of education to economic growth, the measurement of educational costs and expenditures, the balance between different types and levels of education, and problems of finance and planning. The American Economic Association devoted its 1965 meeting to the related topics of innovation, knowledge, and education, and several of the papers presented at that meeting will be cited later in the chapter. The Organization for Economic Cooperation and Development (OECD) formed a study group in the economics of education which has published studies of the relationship between education and growth, the finance of education, organizational problems in educational planning, and the economics of higher education (OECD, 1964a, b; 1966). The OECD (1965b) also launched the Mediterranean Regional Project, which represents a new era in educational planning: six countries have cooperated in drawing up detailed educational plans geared to specific social and economic objectives, and this cooperative exercise has produced useful research and experience on the techniques of planning. UNESCO continued its work in the field and established an International Institute of Educational

BackgroundThere is a lack of cross-national research to examine the role of new graduate nurses in improving the quality of nursing care and patient outcomes.PurposeTo measure the role and clinical effectiveness of new graduate nurses in improving the quality of acute hospital care in the members of Organisation for Economic Co-operation and Development (OECD).MethodsThe total number of nursing graduates per 100,000 population and three OECD’s Health Care Quality Indicators (HCQI) in acute care including 30-day in-hospital and out-of-hospital mortality rates per 100 patients based on acute myocardial infarction (MORTAMIO), hemorrhagic stroke (MORTHSTO) and ischemic stroke (MORTISTO) were collected in 33 OECD countries. Four control variables including the number of medical graduates, practicing nurses and doctors densities per 1000 population (proxies for other health professions) and the total number of Computed Tomography scanners per one million population (proxy of medical technology level) were added in investigations. The statistical technique of Generalized Linear Models (GLM) and Data Envelopment Analysis (DEA) were used in data analysis.ResultsResults of GLM confirm the existence of meaningful association between the density of nursing graduates and improving the quality of acute care i.e. a 1% rise in the number of nursing graduates in year 2015 reduced MORTAMIO, MORTHSTO and MORTISTO by 1.11%, 0.08% and 0.46%, respectively. According to the result of DEA, clinical effectiveness of new graduate nurses – i.e. reaching the higher clinical outcomes with the same staffing level – in reducing mortality rates in patients with life-threatening conditions were at highest level in Luxembourg, Finland, Japan, Italy, Norway, Sweden and Switzerland.ConclusionsHigher staffing level of new graduate nurses associates with better patient outcomes in acute care, although the clinical effectiveness of nursing graduates – associated with the level of education and practice – is the determinant factor of improving the quality of acute hospital care and patient survival rates in OECD.

We are entering into a new phase in EU corporate governance. More than ever, our action plan must be focused and based on a solid assessment of actual needs of market players and investors. 1 As Ch...