Exploring Environmental Health Inequalities: A Scientometric Analysis of Global Research Trends (1970–2020)

Environmental health inequalities (EHI), understood as differences in environmental health factors and in health outcomes caused by environmental conditions, are studied by a wide range of disciplines. This results in challenges to both synthesizing key knowledge domains of the field. This study aims to uncover the global research status and trends in EHI research, and to derive a conceptual framework for the underlying mechanisms of EHI. In total, 12,320 EHI publications were compiled from the Web of Science core collection from 1970 to 2020. Scientometric analysis was adopted to characterize the research activity, distribution, focus, and trends. Content analysis was conducted for the highlight work identified from network analysis. Keyword co-occurrence and cluster analysis were applied to identify the knowledge domain and develop the EHI framework. The results show that there has been a steady increase in numbers of EHI publications, active journals, and involved disciplines, countries, and institutions since the 2000s, with marked differences between countries in the number of published articles and active institutions. In the recent decade, environment-related disciplines have gained importance in addition to social and health sciences. This study proposes a framework to conceptualize the multi-facetted issues in EHI research referring to existing key concepts.China Scholarship CouncilPeer Reviewe

Epidemiologische Methoden und Erkenntnisse als eine Grundlage für Stadtplanung und gesundheitsfördernde Stadtentwicklung

Die Zusammenarbeit von Stadtplanung und Public Health ist grundlegend für eine gesundheitsfördernde Stadtentwicklung und zur Bewältigung von ungerechten gesundheitlichen Ungleichheiten. Die Epidemiologie als eine Kerndisziplin von Public Health befasst sich mit der Häufigkeit von gesundheitsbezogenen Zuständen und Ereignissen sowie mit deren Determinanten in Bevölkerungen und der Anwendung der Erkenntnisse in Maßnahmen der Gesundheitsförderung und des Gesundheitsschutzes. Moderne epidemiologische Ansätze betrachten komplexe Zusammenhänge durch Berücksichtigung individueller und kontextueller Einflussfaktoren für Gesundheit sowie deren Interaktionen auf Bevölkerungsebene. Epidemiologische Daten, Methoden und Ergebnisse sind für Stadtplanung wesentlich hinsichtlich integrierter Berichterstattung, Strategieentwicklung, prospektiver Abschätzung von Gesundheitseffekten von Maßnahmen sowie Evaluation durchgeführter Interventionen.The collaboration of urban planning and public health is fundamental for healthy urban development and to tackle health inequities. Epidemiology, as a core discipline of public health, analyses the frequency of health-related conditions and outcomes, investigates their determinants at population level, and applies the findings to measures of health promotion and health protection. Modern epidemiologic approaches examine complex relationships by considering individual and contextual drivers for health as well as their interactions at population level. Epidemiologic data, methods, and results are essential for urban planning with regard to integrated monitoring, development of strategies, prospective health impact assessment of measures, and evaluation of realised interventions

Geschlecht in der Public-Health-Forschung zu gesundheitlichen Ungleichheiten: Potenziale und Begrenzungen des Intersektionalitätsansatzes

"Soziale und geschlechtsbezogene Ungleichheiten bei Gesundheit stellen eine Herausforderung für die Public-Health-Forschung hinsichtlich der Identifikation ihrer Ursachen und der Entwicklung wirksamer Interventionsmaßnahmen dar. Aktuelle konzeptionelle Arbeiten zu Geschlecht in der epidemiologischen Gesundheitsforschung betonen die Komplexität, Verwobenheit und wechselseitige Beeinflussung der Dimensionen Sex und Gender. Intersektionalität als Forschungsperspektive berücksichtigt Machtverhältnisse sowie die kulturellen, historischen und politischen Kontexte von Geschlechter- und sozialen Ungleichheiten. Der Beitrag hat zum Ziel, konzeptionelle und methodische Anknüpfungsmöglichkeiten einer Intersektionalitätsperspektive an die epidemiologische, quantitative Forschung zur Erfassung und Erklärung von geschlechtsbezogenen gesundheitlichen Ungleichheiten aufzuzeigen. Es werden einerseits Potenziale zur Verbesserung der Aussagekraft von Forschung zu gesundheitlichen Ungleichheiten dargestellt. Andererseits werden Begrenzungen und aktuelle Herausforderungen für die Verwendung und Interpretation von Begriffen und Konzepten, die Kategorisierung sozialer Merkmale und die Umsetzung in multivariablen statistischen Analysen diskutiert." (Autorenreferat)"Social and gender inequalities in health are a challenge for public health research when it comes to identifying the causes and development of effective interventions. Current conceptual work on gender in epidemiological health research emphasizes the complexity, interrelatedness and mutual influence of the dimensions 'sex' and 'gender'. Intersectionality as a research perspective considers power relations as well as cultural, historical and political contexts of gender and social inequalities. The aim of this article is to illustrate conceptual and methodical starting points for an intersectionality approach within epidemiological, quantitative research on measuring and explaining gender inequalities in health. On the one hand, potentials for improving the validity of research on health inequalities are presented. On the other hand, limitations and current challenges concerning the use and interpretation of terminology and concepts, the categorization of social characteristics and the implementation into multivariate statistical analyses are discussed." (author's abstract

Modelle und Indikatoren sozialer Ungleichheit bei umweltbezogener Gesundheit: Erklärungsansätze aus der Umweltepidemiologie

"Umweltgerechtigkeit beruht auf einem multidimensionalen Konzept. Politische, soziale, ökonomische und physische Aspekte greifen auf gesellschaftlicher, kommunaler und individueller Ebene ineinander. Die Umweltepidemiologie muss dieser Komplexität durch Anwendung geeigneter Methoden gerecht werden. Verschiedene Modelle wurden bereits entwickelt, um die Komplexität des Themas zu beschreiben. Gerade im Themenfeld soziale Lage, Wohnen und Gesundheit werden neue Ansätze zu Mehrebenenmodellen entwickelt. Dabei werden aggregierte Daten auf lokaler oder regionaler Ebene mit individuellen Daten verknüpft und analysiert. In der Sozialepidemiologie sind klassische Indikatoren des sozioökonomischen Status Bildung, Einkommen und der berufliche Status. Bisher wurde der Sozialstatus in umweltepidemiologischen Studien noch unzureichend erfasst. In Studien zu Gesundheit und Umweltbelastungen wird oftmals nur Bildung als Confounder erfasst. Neuere Studien weisen darauf hin, dass Einkommen für die Erklärung von sozialer Ungleichheit bei umweltbezogener Gesundheit eine bedeutsamere Rolle spielt als z.B. Bildung. Darüber hinaus wird immer häufiger darauf hingewiesen, dass ein einzelner Indikator den sozioökonomischen Status nicht ausreichend abbilden kann. Daher werden zunehmend auch alternative Beschreibungen der sozialen Lage verwendet wie zum Beispiel soziales Kapital und soziale Netzwerke. Diese Konzepte sind insofern für umweltepidemiologische Fragestellungen interessant, da sie die soziale Lage des Wohnumfelds und der Nachbarschaft miteinbeziehen, die Einfluss sowohl auf die subjektive Einschätzung des Sozialstatus als auch auf Gesundheit und subjektiv wahrgenommene Umweltbelastungen hat. Ziel der Umweltgerechtigkeitsforschung muss sein, das Ausmaß der sozialen Ungleichheit bei Umweltexpositionen und umweltbezogener Gesundheit zu quantifizieren und deren Ursachen zu identifizieren, Indikatoren für Umweltgerechtigkeit zu entwickeln und letztlich Gesundheitsförderungsprogramme im Bereich umweltbezogener Gesundheit so zu gestalten, dass gesundheitliche Ungleichheit verringert wird." (Autorenreferat

Neighbourhood socio-economic status and positive affectivity among older residents in Germany: a cross-sectional analysis with data from the Heinz Nixdorf Recall Study

Background: Physical and social neighbourhood characteristics can vary according to the neighbourhood socio-economic status (SES) and influence residents’ perceptions, behaviours and health outcomes both positively and negatively. Neighbourhood SES has been shown to be predictive of mental health, which is relevant for healthy ageing and prevention of dementia or depression. Positive affectivity (PA) is an established indicator of mental health and might indicate a positive emotional response to neighbourhood characteristics. In this study, we focussed on the association of neighbourhood SES with PA among older residents in Germany and considered social integration and environmental perceptions in this association. Methods: We used questionnaire-based data of the ongoing population-based Heinz Nixdorf Recall Study for our cross-sectional analysis, complemented by secondary data on social welfare rates in the neighbourhood of residents’ address. PA was assessed using the Positive and Negative Affect Schedule (PANAS) in 2016. Linear regression models were performed to estimate the associations and adjusted for socio-demographic variables. Results: Higher social welfare rates were associated with lower PA scores. The strongest negative association from the crude model (b = -1.916, 95%-CI [-2.997, -0.835]) was reduced after controlling for socio-demographic variables (b = -1.429, 95%-CI [-2.511, -0.346]). Social integration factors (b = -1.199, 95%-CI [-2.276, -0.121]) and perceived environmental factors (b = -0.875, 95%-CI [-1.971, 0.221]) additionally diminished the association of social welfare rates with PA in the full model (b = -0.945, 95%-CI [-2.037, 0.147]). Conclusion: Our results suggest that neighbourhoods have an influence on the occurrence and the extent of PA. Public health interventions that address socio-economic disadvantage in the neighbourhood environment could be an effective and far-reaching way to reduce the risk of depression and depressive symptoms due to low PA in older residents

The Operationalisation of Sex and Gender in Quantitative Health–Related Research: A Scoping Review

Current trends in quantitative health research have highlighted the inadequacy of the usual operationalisation of sex and gender, resulting in a growing demand for more nuanced options. This scoping review provides an overview of recent instruments for the operationalisation of sex and gender in health-related research beyond a concept of mutually exclusive binary categories as male or masculine vs. female or feminine. Our search in three databases (Medline, Scopus and Web of Science) returned 9935 matches, of which 170 were included. From these, we identified 77 different instruments. The number and variety of instruments measuring sex and/or gender in quantitative health-related research increased over time. Most of these instruments were developed with a US-American student population. The majority of instruments focused on the assessment of gender based on a binary understanding, while sex or combinations of sex and gender were less frequently measured. Different populations may require the application of different instruments, and various research questions may ask for different dimensions of sex and gender to be studied. Despite the clear interest in the development of novel sex and/or gender instruments, future research needs to focus on new ways of operationalisation that account for their variability and multiple dimensions.German Federal Ministry of Health (BMG)Peer Reviewe

Gender equality and smoking among 15 to 25 year olds—a time-based ecological analysis of developments in Germany from 1960 to 2005

IntroductionSmoking is a major risk factor for premature death and health problems in which there are significant gender differences in the prevalence of smoking. This ecological study examines the correlation between changes in gender equality and prevalence of smoking among young adults (15–25 years old) in Germany over a period of 45 years (1960–2005).MethodsGender inequality was measured using the United Nations Gender Inequality Index (GII), which is composed of three dimensions; health, empowerment and labour market. It was calculated for the entire registered German population in five-year intervals with values between 0 and 1 (1 = highest inequality). The smoking prevalence of young women and men in Germany was established using a reconstruction method. A gender smoking ratio (GSR) with values between 0 and 1 was determined (1 = identical smoking prevalence among men and women). The smoking behaviour was illustrated and stratified by education. The correlation between the GII and the GSR was analysed.ResultsThe GII decreased from 0.98 to 0.56 between 1960 and 2005. The GSR increased from 0.34 to 0.93. There was a strong negative correlation between the GII and the GSR (r = −0.71). The strength of the correlation fell slightly as the level of education decreased. An increase in gender equality as measured by the GII came along with similarities of smoking prevalence between young women and young men.ConclusionSuccessful tobacco prevention among young women and men may benefit from involving experts in gender-specific public health research to develop counter-advertising and gender-specific information as needed

Environmental Health Inequalities Resource Package

Environmental conditions are a major determinant of health and well-being but are not distributed equally across the WHO European Region. Higher levels of environmental risk are often found in disadvantaged population subgroups, leading to a need for targeted environmental and intersectoral action to protect these groups and achieve environmental justice. This resource package aims to generate awareness of the concept of environmental health inequalities and to support action against disparities in exposure to environmental risks at the national and subnational levels. It sets out the various dimensions of environmental health inequality; presents relevant methods and approaches for monitoring and assessment; and suggests ways to use this evidence for action. It also provides information on a range of tools and guidance documents that may be helpful for national and local actors tackling environmental inequalities and striving to improve health and health equity. The publication is also available on this website in English and Russian http://www.euro.who.int/en/health-topics/environment-and-health/health-impact-assessment/publications/2019/environmental-health-inequalities-resource-packag

Early environmental quality and life-course mental health effects : The Equal-Life project

Background: There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children's suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitive development and mental health over time. Methods: Equal-Life develops and tests combined exposures and their effects on children's mental health and cognitive development. Data from eight birth-cohorts and three school studies (N = 240.000) linked to exposure data, will provide insights and policy guidance into aspects of physical and social exposures hitherto untapped, at different scale levels and timeframes, while accounting for social inequities. Reasoning from the outcome point of view, relevant stakeholders participate in the formulation and validation of research questions, and in the formulation of environmental hazards. Exposure assessment combines GIS-based environmental indicators with omics approaches and new data sources, forming the early-life exposome. Statistical tools integrate data at different spatial and temporal granularity and combine exploratory machine learning models with hypothesis-driven causal modeling. Conclusions: Equal-Life contributes to the development and utilization of the exposome concept by (1) integrating the internal, physical and social exposomes, (2) studying a distinct set of life-course effects on a child's development and mental health (3) characterizing the child's environment at different developmental stages and in different activity spaces, (4) looking at supportive environments for child development, rather than merely pollutants, and (5) combining physical, social indicators with novel effect markers and using new data sources describing child activity patterns and environments.Peer reviewe