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      Geografische Ansätze in der Gesundheitsberichterstattung Translated title: Geographic methods for health monitoring

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          Abstract

          Das Interesse an geografischen Darstellungen in der Gesundheitsberichterstattung (GBE) ist in den letzten beiden Jahrzehnten stark gewachsen. Gesundheitsdaten können mit diesen Methoden anschaulich und zielgruppenorientiert visualisiert werden. Neue technische Möglichkeiten und die breitere Verfügbarkeit von Daten tragen zur verstärkten Anwendung in der GBE bei. In diesem Artikel soll gezeigt werden, welche geografischen Ansätze in der GBE auf Bundes‑, Länder- und Kommunalebene jeweils aktuell verfolgt werden. Insbesondere soll dabei auf die verwendeten Methoden fokussiert werden.

          Es wird gezeigt, dass auf Bundesebene geografische Methoden z. B. in der Surveillance angewendet werden; auf Länderebene gibt es z. B. Gesundheitsatlanten und auf der Kommunalebene verschiedene geografische Analysen. Die methodische Spannweite reicht von einfacheren Kartendarstellungen auf unterschiedlichen Aggregationsebenen bis hin zu komplexeren Verfahren wie raum-zeitlichen Darstellungen und räumlichen Glättungsverfahren.

          Fehlender Datenzugang oder datenschutzrechtliche Aspekte behindern noch häufig die Verbindung mit weiteren Datenquellen oder kleinräumigere Darstellungen. Vor allem ein besserer Zugang zu Daten auf kleinräumiger Ebene könnte die GBE aber erheblich erleichtern. Die Bevölkerung und Entscheidungsträger könnten dadurch noch umfassender informiert und folglich die Gesundheit und die gesundheitliche Versorgung der Bevölkerung verbessert werden.

          Translated abstract

          The interest in using geographic methods for health monitoring has grown strongly over the last two decades. Through these methods, analysis and visualization of health data can be more focused and target-group specific. The application in health monitoring is possible mostly due to broader technical possibilities and more available datasets. In this article, we show which geographic aspects are adapted in health monitoring at different levels (federal, state, municipality).

          For example, at the federal level, surveillance methods are used; at the state level health atlases are created; and on the municipality level geographic analyses are performed for possible public health interventions.

          Methods range from simple maps on different levels of aggregation to more complex methods like space-temporal visualization or spatial-smoothing methods. While the technical possibilities are in place, a broader implementation of geographic methods is mostly hindered by missing data access to small-area information and data protection policies. Better access to data could especially improve the possibility for geographic methods in health monitoring and could inform the population and decision makers to inform and improve population health or healthcare.

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          International variation in neighborhood walkability, transit, and recreation environments using geographic information systems: the IPEN adult study

          Background The World Health Organization recommends strategies to improve urban design, public transportation, and recreation facilities to facilitate physical activity for non-communicable disease prevention for an increasingly urbanized global population. Most evidence supporting environmental associations with physical activity comes from single countries or regions with limited variation in urban form. This paper documents variation in comparable built environment features across countries from diverse regions. Methods The International Physical Activity and the Environment Network (IPEN) study of adults aimed to measure the full range of variation in the built environment using geographic information systems (GIS) across 12 countries on 5 continents. Investigators in Australia, Belgium, Brazil, Colombia, the Czech Republic, Denmark, China, Mexico, New Zealand, Spain, the United Kingdom, and the United States followed a common research protocol to develop internationally comparable measures. Using detailed instructions, GIS-based measures included features such as walkability (i.e., residential density, street connectivity, mix of land uses), and access to public transit, parks, and private recreation facilities around each participant’s residential address using 1-km and 500-m street network buffers. Results Eleven of 12 countries and 15 cities had objective GIS data on built environment features. We observed a 38-fold difference in median residential densities, a 5-fold difference in median intersection densities and an 18-fold difference in median park densities. Hong Kong had the highest and North Shore, New Zealand had the lowest median walkability index values, representing a difference of 9 standard deviations in GIS-measured walkability. Conclusions Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity. These measures allow cities to be ranked more precisely than previously possible. The highly variable measures of urban form will be used to explain individuals’ physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis. Present measures provide the ability to estimate dose–response relationships from projected changes to the built environment that would otherwise be impossible. Electronic supplementary material The online version of this article (doi:10.1186/1476-072X-13-43) contains supplementary material, which is available to authorized users.
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            [The KiGGS study. Nationwide representative longitudinal and cross-sectional study on the health of children and adolescents within the framework of health monitoring at the Robert Koch Institute].

            From 2003 to 2006 the KiGGS Baseline Study was conducted, including a clustered random sample of 167 sample points and 17,641 children and adolescents from 0 to 17 years, as well as their parents in 167 sample points. The children and adolescents were medically and physically examined, and their parents answered questions about physical, psychological and social aspects of their children's health, as did, from 11 years on, the children and adolescents themselves. Within the framework of the nationwide health monitoring at the Robert Koch Institute, the KiGGS study is being continued as a prospective cohort study with an interval of approximately 5 years between follow-ups. The study sample will be cross-sectionally refilled with younger age groups at each time of measurement. The assessment of the KiGGS core study follows a core indicator concept, which is modularly complemented by external scientific cooperation partners. The field work of the first wave (KiGGS Wave 1), a telephone survey, will continue until June 2012. The second follow-up (KiGGS Wave 2) will again combine examinations and interviews, starting in 2013. On the basis of the nationally representative KiGGS data, important questions about health policy can be answered, such as trends and trajectories of health. Important results are expected, among others concerning trends in overweight and obesity, the incidence of atopic diseases, and the persistency or remission of psychopathological symptoms and disorders.
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              Area Level Deprivation Is an Independent Determinant of Prevalent Type 2 Diabetes and Obesity at the National Level in Germany. Results from the National Telephone Health Interview Surveys ‘German Health Update’ GEDA 2009 and 2010

              Objective There is increasing evidence that prevention programmes for type 2 diabetes mellitus (T2DM) and obesity need to consider individual and regional risk factors. Our objective is to assess the independent association of area level deprivation with T2DM and obesity controlling for individual risk factors in a large study covering the whole of Germany. Methods We combined data from two consecutive waves of the national health interview survey ‘GEDA’ conducted by the Robert Koch Institute in 2009 and 2010. Data collection was based on computer-assisted telephone interviews. After exclusion of participants <30 years of age and those with missing responses, we included n = 33,690 participants in our analyses. The outcome variables were the 12-month prevalence of known T2DM and the prevalence of obesity (BMI ≥30 kg/m2). We also controlled for age, sex, BMI, smoking, sport, living with a partner and education. Area level deprivation of the districts was defined by the German Index of Multiple Deprivation. Logistic multilevel regression models were performed using the software SAS 9.2. Results Of all men and women living in the most deprived areas, 8.6% had T2DM and 16.9% were obese (least deprived areas: 5.8% for T2DM and 13.7% for obesity). For women, higher area level deprivation and lower educational level were both independently associated with higher T2DM and obesity prevalence [highest area level deprivation: OR 1.28 (95% CI: 1.05–1.55) for T2DM and OR 1.28 (95% CI: 1.10–1.49) for obesity]. For men, a similar association was only found for obesity [OR 1.20 (95% CI: 1.02–1.41)], but not for T2DM. Conclusion Area level deprivation is an independent, important determinant of T2DM and obesity prevalence in Germany. Identifying and targeting specific area-based risk factors should be considered an essential public health issue relevant to increasing the effectiveness of diabetes and obesity prevention.
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                Author and article information

                Contributors
                Daniela.koller@med.lmu.de
                Journal
                Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
                Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
                Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1436-9990
                1437-1588
                28 August 2020
                28 August 2020
                : 1-10
                Affiliations
                [1 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie – IBE, , LMU München, ; München, Deutschland
                [2 ]Referat für Gesundheit und Umwelt, Landeshauptstadt München, Bayerstr. 28a, 80335 München, Deutschland
                [3 ]GRID grid.13648.38, ISNI 0000 0001 2180 3484, Institut für Versorgungsforschung in der Dermatologie und bei Pflegeberufen (IVDP), FG Gesundheitsgeografie, , Universitätsklinikum Hamburg-Eppendorf, ; Hamburg, Deutschland
                Article
                3208
                10.1007/s00103-020-03208-6
                7453702
                32857174
                e948e4c2-5b23-475d-8591-260acd5df360
                © The Author(s) 2020

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                History
                Funding
                Funded by: Ludwig-Maximilians-Universität München (1024)
                Categories
                Leitthema

                gesundheitsberichterstattung,geografische methoden,gis,regionale variation,gesundheitsatlas,health monitoring,geographic methods,regional variation

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