In 2005, the Working Group for the Survey and Utilisation of Secondary Data (AGENS) of the German Society for Social Medicine and Prevention (DGSMP) and the German Society for Epidemiology (DGEpi) first published "Good Practice in Secondary Data Analysis (GPS)" formulating a standard for conducting secondary data analyses. GPS is intended as a guide for planning and conducting analyses and can provide a basis for contracts between data owners. The domain of these guidelines does not only include data routinely gathered by statutory health insurance funds and further statutory social insurance funds, but all forms of secondary data. The 11 guidelines range from ethical principles and study planning through quality assurance measures and data preparation to data privacy, contractual conditions and responsible communication of analytical results. They are complemented by explanations and practical assistance in the form of recommendations. GPS targets all persons directing their attention to secondary data, their analysis and interpretation from a scientific point of view and by employing scientific methods. This includes data owners. Furthermore, GPS is suitable to assess scientific publications regarding their quality by authors, referees and readers. In 2008, the first version of GPS was evaluated and revised by members of AGENS and the Epidemiological Methods Working Group of DGEpi, DGSMP and GMDS including other epidemiological experts and had then been accredited as implementation regulations of Good Epidemiological Practice (GEP). Since 2012, this third version of GPS is on hand and available for downloading from the DGEpi website at no charge. Especially linguistic specifications have been integrated into the current revision; its internal consistency was increased. With regards to contents, further recommendations concerning the guideline on data privacy have been added. On the basis of future developments in science and data privacy, further revisions will follow.

This study indicates that traffic noise exposure might lead to depression. As a potential explanation for the decreasing risks at high traffic noise levels, vulnerable people might actively cope with noise (e.g. insulate or move away).

The lidA Cohort Study (German Cohort Study on Work, Age, Health and Work Participation) was set up to investigate and follow the effects of work and work context on the physical and psychological health of the ageing workforce in Germany and subsequently on work participation. Cohort participants are initially employed people subject to social security contributions and born in either 1959 (n = 2909) or 1965 (n = 3676). They were personally interviewed in their homes in 2011 and will be visited every 3 years. Data collection comprises socio-demographic data, work and private exposures, work ability, work and work participation attitudes, health, health-related behaviour, personality and attitudinal indicators. Employment biographies are assessed using register data. Subjective health reports and physical strength measures are complemented by health insurance claims data, where permission was given. A conceptual framework has been developed for the lidA Cohort Study within which three confirmatory sub-models assess the interdependencies of work and health considering age, gender and socioeconomic status. The first set of the data will be available to the scientific community by 2015. Access will be given by the Research Data Centre of the German Federal Employment Agency at the Institute for Employment Research (http://fdz.iab.de/en.aspx).

Objective To revise the German guidelines and recommendations for ensuring Good Epidemiological Practice (GEP) that were developed in 1999 by the German Society for Epidemiology (DGEpi), evaluated and revised in 2004, supplemented in 2008, and updated in 2014. Methods The executive board of the DGEpi tasked the third revision of the GEP. The revision was arrived as a result of a consensus-building process by a working group of the DGEpi in collaboration with other working groups of the DGEpi and with the German Association for Medical Informatics, Biometry and Epidemiology , the German Society of Social Medicine and Prevention (DGSMP), the German Region of the International Biometric Society (IBS-DR), the German Technology, Methods and Infrastructure for Networked Medical Research (TMF), and the German Network for Health Services Research (DNVF). The GEP also refers to related German Good Practice documents (e.g. Health Reporting, Cartographical Practice in the Healthcare System, Secondary Data Analysis). Results The working group modified the 11 guidelines (after revision: 1 ethics, 2 research question, 3 study protocol and manual of operations, 4 data protection, 5 sample banks, 6 quality assurance, 7 data storage and documentation, 8 analysis of epidemiological data, 9 contractual framework, 10 interpretation and scientific publication, 11 communication and public health) and modified and supplemented the related recommendations. All participating scientific professional associations adopted the revised GEP. Conclusions The revised GEP are addressed to everyone involved in the planning, preparation, execution, analysis, and evaluation of epidemiological research, as well as research institutes and funding bodies.

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In this study, a substantial proportion of the population was exposed to traffic noise levels that were associated with an albeit small increase in the risk of myocardial infarction. These findings underscore the importance of effective traffic noise prevention.

In the German health service research there exists, unlike in labour market research, no experience with the combination of personal primary and secondary data. One of the reasons for this is, among other things, data protection. The lidA cohort study analyses persons in employment (excluding civil servants and self-employed), born in 1959 and 1965. It is intended to give answers to questions from the health services research as well as from the labour market research. It relies on different primary and secondary data sources: survey data, process data from the Federal Employment Agency, aggregated and individual health insurance data. The experiences made in the lidA study, in addition to the data protection needs and the expenditures for the implementation, are summarised as "best practice". The procedure for the application process according to § 75 SGB X, the directive to develop data security concepts, the informed consent for the linkage of personal information are described and the importance of a transparent approach is explained. So far it has been shown that the preparation and approval process for the release of the actual data, both within the project consortium, but also with external parties such as health insurance companies or the responsible data protection officer, requires a major effort. In view of all the identified legal and organisational challenges, our findings should be extremely useful for answering different research questions in the fields of labour market and health services research. In combination with primary data, they may even represent a "gold standard" for epidemiology and health services research.