Some German cohort studies have already linked secondary and registry data with primary data from interviews and medical examinations. This offers the opportunity to obtain more valid information by ...taking advantage of the strengths of these data synergistically and overcome their individual weaknesses at the same time. The potential and the requirements for linking secondary and registry data with primary data from cohort studies is described generally and illustrated by the example of the "German National Cohort" (GNC). The transfer and usage of secondary and registry data require that administrative and logistic efforts be made over the whole study period. In addition, rigid data protection regulations for using social data have to be observed. The particular strengths of secondary and registry data, namely their objectivity and independence from recall bias, add to the strengths of newly collected primary data and improve the assessment of morbidity endpoints, exposure history and need of patient care. Moreover, new insights on quality and on the added value of linking different data sources may be obtained.
What is the appropriate differentiation of digital public health versus digital health - or is there none? This is an essential question when pondering digitalisation and public health, especially ...with a view to the potential development of the field. Digital health seems to be a general term related to information and communication technology in health care. Putting a public health lens on this general descriptive term can be done by simply expanding it towards public health as a population science and practice field, rather than the narrow medical and health care arena. However, a more specific approach towards outlining similarities and differences will also focus on digital technologies and their challenges in the core areas of prevention and health promotion. Considering the leading public health functions, their relationship with digitalisation and their specific requirements towards digitalisation can be a valuable path to describe and discuss what digital public health is all about. We will also highlight where interfaces and interrelations with digital health need to be considered for research and practice. This contribution will aim to provide such a perspective.
What is the appropriate differentiation of digital public health versus digital health - or is there none? This is an essential question when pondering digitalisation and public health, especially ...with a view to the potential development of the field. Digital health seems to be a general term related to information and communication technology in health care. Putting a public health lens on this general descriptive term can be done by simply expanding it towards public health as a population science and practice field, rather than the narrow medical and health care arena. However, a more specific approach towards outlining similarities and differences will also focus on digital technologies and their challenges in the core areas of prevention and health promotion. Considering the leading public health functions, their relationship with digitalisation and their specific requirements towards digitalisation can be a valuable path to describe and discuss what digital public health is all about. We will also highlight where interfaces and interrelations with digital health need to be considered for research and practice. This contribution will aim to provide such a perspective.
There is a worldwide increase of overweight and obesity not only in adults, but also in children. Data used to estimate prevalence are, however, collected in differing age groups using ...nonstandardized measurements and instruments and refer to differing time periods. Moreover, various reference systems to classify overweight and obesity exist, thus, adding to the difficulty in comparing countries. In this paper, these problems are discussed in detail. The most common reference systems are introduced, and their impact on the estimation of the prevalence of overweight and obesity is demonstrated. Based on available data of the global situation, maps that depict the worldwide distribution of the prevalence of overweight and obesity in children and adolescents are presented. Finally, these maps will be discussed critically. Although it may be assumed that these data are collected according to the best quality standards available, the lack of a unified protocol to conduct studies on childhood obesity hampers the comparability of data between countries. Obvious limitations in that respect are the use of different reference systems, differing sampling schemes, and differing age groups. More subtle limitations result from, e.g., different measurement methods, including self-reported weight and height.
There continues to be a lack of evidence-based programs in the primary prevention of chronic diseases. This also applies to overweight and obesity, a health problem for which primary prevention in ...childhood is seen as key. Primary prevention is characterized by its focus on specific risk factors of a disease. For the development of effective prevention programs, a theoretical model of health and health behavior changes is an important prerequisite. With regard to such models, an epidemiologic life course approach may offer new perspectives for primary prevention. Major prevention concepts are those considering population versus selective, high-risk group strategies and prevention approaches targeting behavior or environmental and social conditions. All modern prevention programs require a systematic evaluation that should not only focus on processes, but also on health outcomes. Lack of resources or short program time spans are frequently cited as obstacles for stringent program evaluation. These barriers and others need to be tackled to further develop evidence-based primary prevention.
Abstract
Background
The collected primary data are enriched with secondary and registry data from different data owners to support morbidity follow-up and to obtain important exposure and progression ...data that could not be obtained otherwise.
Goal
A sophisticated data protection procedure had to be developed and agreed upon with hundreds of data owners. The outlines of this procedure and the various data bodies to be linked are presented, and consent behavior is described. Furthermore, it is discussed which hurdles still have to be overcome for a successful implementation of record linkage in Germany.
Methods
Study participants were asked for informed written consent to link their secondary and registry data. Confidentiality was ensured, among other things, by means of a complex pseudonymization procedure by an independent trust center. Legal and technical requirements for annual transmission and long-term use of their data were established with the data owners.
Results
At baseline, a total of 205,000 study participants were screened and interviewed in 18 study centers distributed across Germany starting in 2014. A second study wave followed from 2019, with a third starting in 2024. A high willingness to consent of 90.5% to use health insurance data was achieved. Willingness to consent is higher in the west than in the east of Germany, with 88.1% of consenters insured by one of the 113 statutory health insurance providers and 11.9% insured by one of the 46 private health insurance providers.
Conclusions
Large-scale record linkage of secondary data is a novelty in Germany. In addition to the identification of incident diseases, an almost complete medication history can be collected for the majority of study participants, independent of health insurance. However, linking is associated with a high administrative and technical effort, and some of the required data protection regulations will have a negative impact on data quality if improvements are not made here.
The ICD-coding quality for outpatients' diagnoses by German physicians was analysed in a sample of five million members of the German Statutary Health Insurance System. New federal legislation coming ...into effect in 2009 for the reimbursement of physicians is based on patients' morbidity risks and thus on the quality of a provider's ICD coding. A sample of physicians' billing data for 2001-2003 containing ICD codes for patients' morbidity and the billed services was linked with outpatients' prescription data for the time period 2002- 2003. As in 2001-2003 information on the certainty of diagnosis was not yet mandatory, only 7.4% of all diagnoses were labelled as either "suspected diagnosis", "excluded diagnosis" or "history of diagnosis", hampering coding validity measurements. Chronic disease persisted in the time window analysed showing only minor successive prevalence decreases after an initial dip of at least 6% in the calendar term following the index term. The immediate decrease following the initial term may be due to initially suspected disease not confirmed until the work up at subsequent visits is completed. The slight downward slope after six months may indicate minor undercoding of chronic diagnoses. Few acute diagnoses persisted for longer than two calendar terms making it unlikely that acute diagnoses were erroneously maintained for repetitive reimbursement. Undercoding of diagnosis was abundant in patients receiving insulin prescriptions, as a diagnosis of diabetes was often missing. Numerous drugs prescribed could not be associated with a corresponding diagnosis coded by physicians. We suggest that before reimbursements to physicians are based on ICD-coded morbidity, a re-analysis of the data should be performed containing information on diagnosis certainty (mandatory since 2004) and the recently updated catalogue on fees for medical procedures provided "Einheitlicher Bewertungsmassstab" (EBM).
Childhood obesity is a complex multifaceted condition, which is influenced by genetics, environmental factors, and their interaction. However, these interactions have mainly been studied in twin ...studies and evidence from population-based cohorts is limited. Here, we analyze the interaction of an obesity-related genome-wide polygenic risk score (PRS) with sociodemographic and lifestyle factors for BMI and waist circumference (WC) in European children and adolescents.
The analyses are based on 8609 repeated observations from 3098 participants aged 2-16 years from the IDEFICS/I.Family cohort. A genome-wide polygenic risk score (PRS) was calculated using summary statistics from independent genome-wide association studies of BMI. Associations were estimated using generalized linear mixed models adjusted for sex, age, region of residence, parental education, dietary intake, relatedness, and population stratification.
The PRS was associated with BMI (beta estimate 95% confidence interval (95%-CI) = 0.33 0.30, 0.37, r
= 0.11, p value = 7.9 × 10
) and WC (beta 95%-CI = 0.36 0.32, 0.40, r
= 0.09, p value = 1.8 × 10
). We observed significant interactions with demographic and lifestyle factors for BMI as well as WC. Children from Southern Europe showed increased genetic liability to obesity (BMI: beta 95%-CI = 0.40 0.34, 0.45) in comparison to children from central Europe (beta 95%-CI = 0.29 0.23, 0.34), p-interaction = 0.0066). Children of parents with a low level of education showed an increased genetic liability to obesity (BMI: beta 95%-CI = 0.48 0.38, 0.59) in comparison to children of parents with a high level of education (beta 95%-CI = 0.30 0.26, 0.34), p-interaction = 0.0012). Furthermore, the genetic liability to obesity was attenuated by a higher intake of fiber (BMI: beta 95%-CI interaction = -0.02 -0.04,-0.01) and shorter screen times (beta 95%-CI interaction = 0.02 0.00, 0.03).
Our results highlight that a healthy childhood environment might partly offset a genetic predisposition to obesity during childhood and adolescence.
The prevalence of overweight/obesity in childhood has also been rising at an alarming rate in Germany during recent years. Central components of successful intervention measures include the ...underpinning of the program with a theoretical model and the inclusion of several target groups as well as schools and kindergartens as whole units. Evaluation of the program is necessary for the development of evidence-based interventions. These central components are highlighted using the example of the development and implementation of the IDEFICS intervention. The IDEFICS intervention was developed using the intervention mapping protocol and aims for a healthy diet, more physical activity, and relaxation. For the implementation of the IDEFICS intervention, ten modules targeting different levels were developed. The implementation is illustrated using Germany as an example. Difficulties in the implementation arose due to unclear responsibilities and the necessary cultural adaptation of internationally developed modules. However, the strengths (e.g., inclusion of the socially disadvantaged, the implementation in a school/kindergarten setting, and a scientific evaluation) also need to be stressed.
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