[Developments in the digitalization of public health since 2020 : Examples from the Leibniz ScienceCampus Digital Public Health Bremen]. / Entwicklungen in der Digitalisierung von Public Health seit 2020 : Beispiele aus dem Leibniz-WissenschaftsCampus Digital Public Health Bremen.

Digital public health has received a significant boost in recent years, especially due to the demands associated with the COVID-19 pandemic. In this report, we provide an overview of the developments in digitalization in the field of public health in Germany since 2020 and illustrate these with examples from the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH).The following topics are central: How do digital survey methods as well as digital biomarkers and artificial intelligence methods shape modern epidemiology and prevention research? What is the status of digitalization in public health offices? Which approaches to health economics evaluation of digital public health interventions have been utilized so far? What is the status of training and further education in digital public health?The first years of the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH) were also strongly influenced by the COVID-19 pandemic. Repeated population-based digital surveys of the LSC indicated an increase in use of health apps in the population, for example, in applications to support physical activity. The COVID-19-pandemic has also shown that the digitalization of public health enhances the risk of misinformation and disinformation.

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort.

AIMS/HYPOTHESIS: There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution. METHODS: Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin. RESULTS: A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin. CONCLUSIONS/INTERPRETATION: The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

In atrial fibrillation epilepsy risk differs between oral anticoagulants: active comparator, nested case-control study.

AIMS: Atrial fibrillation (AF) is a risk factor for brain infarction, which can lead to epilepsy. We aimed to investigate whether treatment of AF with direct oral anticoagulants (DOACs) affects the risk of epilepsy in comparison to treatment with the vitamin K antagonist phenprocoumon (PPC). METHODS AND RESULTS: We performed an active comparator, nested case-control study based on the German Pharmacoepidemiological Research Database that includes claims data from statutory health insurance providers of about 25 million persons since 2004. In 2011-17, 227 707 AF patients initiated treatment with a DOAC or PPC, of which 1828 cases developed epilepsy on current treatment with an oral anticoagulant. They were matched to 19 084 controls without epilepsy. Patients with DOAC treatment for AF had an overall higher risk of epilepsy with an odds ratio of 1.39, 95% CI (1.24; 1.55) compared to current PPC treatment. Cases had higher baseline CHA2DS2-VASc scores and more frequently a history of stroke than controls. After excluding patients with ischaemic stroke prior to the diagnosis of epilepsy, the risk of epilepsy was still higher on DOACs than on PPC. In contrast, within a cohort of patients with venous thromboembolism, the risk of epilepsy on treatment with DOACs was less elevated [adjusted odds ratio 1.15, 95% CI (0.98; 1.34)]. CONCLUSION: In patients with AF initiating oral anticoagulation, treatment with a DOAC was associated with an increased risk of epilepsy compared to the vitamin K antagonist PPC. Covert brain infarction may explain the observed elevated risk of epilepsy.

Record linkage of claims and cancer registries data-Evaluation of a deterministic linkage approach based on indirect personal identifiers.

PURPOSE: In Germany, record linkage of claims and cancer registry data is cost- and time-consuming, since up until recently no unique personal identifier was available in both data sources. The aim of this study was to evaluate the feasibility and performance of a deterministic linkage procedure based on indirect personal identifiers included in the data sources. METHODS: We identified users of glucose-lowering drugs with residence in four federal states in Northern and Southern Germany (Bavaria, Bremen, Hamburg, Lower Saxony) in the German Pharmacoepidemiological Research Database (GePaRD) and assessed colorectal and thyroid cancer cases. Cancer registries of the federal states selected all colorectal and thyroid cancer cases between 2004 and 2015. A deterministic linkage approach was performed based on indirect personal identifiers such as year of birth, sex, area of residence, type of cancer and an absolute difference between the dates of cancer diagnosis in both data sources of at most 90 days. Results were compared to a probabilistic linkage using "direct" personal identifiers (gold standard). RESULTS: The deterministic linkage procedure yielded a sensitivity of 71.8% for colorectal cancer and 66.6% for thyroid cancer. For thyroid cancer, the sensitivity improved when using only inpatient diagnosis to define cancer in GePaRD (71.4%). Specificity was always above 99%. Using the probabilistic linkage to define cancer cases, the risk for colorectal cancer was estimated 10 percentage points lower than when using the deterministic approach. CONCLUSIONS: Sensitivity of the deterministic linkage approach appears to be too low to be considered as reasonable alternative to the probabilistic linkage procedure.

[Linkage of claims data with data from epidemiological cancer registries: possibilities and limitations in the German federal states]. / Verknüpfung von Abrechnungsdaten gesetzlicher Krankenkassen mit Daten epidemiologischer Krebsregister: länderspezifische Möglichkeiten und Limitationen.

BACKGROUND: In recent years, there has been an increasing demand for the reuse of research data in accordance with the so-called FAIR principles. This would allow researchers to conduct projects on a broader data basis and to investigate new research questions by linking different data sources. OBJECTIVES: We explored if nationwide linking of claims data from statutory health insurances (SHI) with data from population-based cancer registries can be used to obtain additional information on cancer that is missing in claims data and to assess the validity of SHI tumour diagnoses. This paper focuses on describing the specific requirements of German federal states for such data linkage. MATERIALS AND METHODS: The Pharmacoepidemiological Research Database GePaRD at the Leibniz Institute for Prevention Research and Epidemiology - BIPS and six cancer registries were used as data sources. The logistically complex direct linkage was compared with a less complex indirect linkage. For this purpose, permission had to be obtained for GePaRD and for each cancer registry from the respective responsible authority. RESULTS: Regarding the linkage of cancer registry data with GePaRD, the cancer registries showed profound differences in the modalities for data provision, ranging from a complete rejection to an uncomplicated implementation of linkage procedures. DISCUSSION: In Germany, a consistent legal framework is needed to adequately enable the reuse and record linkage of personal health data for research purposes according to the FAIR principles. The new law on the consolidation of cancer registry data could provide a remedy regarding the linkage of cancer registry data with other data sources.

Polygenic risk for obesity and its interaction with lifestyle and sociodemographic factors in European children and adolescents.

BACKGROUND: 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. METHODS: 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. RESULTS: The PRS was associated with BMI (beta estimate [95% confidence interval (95%-CI)] = 0.33 [0.30, 0.37], r2 = 0.11, p value = 7.9 × 10-81) and WC (beta [95%-CI] = 0.36 [0.32, 0.40], r2 = 0.09, p value = 1.8 × 10-71). 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]). CONCLUSIONS: Our results highlight that a healthy childhood environment might partly offset a genetic predisposition to obesity during childhood and adolescence.

The temporal relationship between parental concern of overeating and childhood obesity considering genetic susceptibility: longitudinal results from the IDEFICS/I.Family study.

BACKGROUND: Many genes and molecular pathways are associated with obesity, but the mechanisms from genes to obesity are less well known. Eating behaviors represent a plausible pathway, but because the relationships of eating behaviors and obesity may be bi-directional, it remains challenging to resolve the underlying pathways. A longitudinal approach is needed to assess the contribution of genetic risk during the development of obesity in childhood. In this study we aim to examine the relationships between the polygenic risk score for body mass index (PRS-BMI), parental concern of overeating and obesity indices during childhood. METHODS: The IDEFICS/I.Family study is a school-based multicenter pan-European cohort of children observed for 6 years (mean ± SD follow-up 5.8 ± 0.4). Children examined in 2007/2008 (wave 1) (mean ± SD age: 4.4 ± 1.1, range: 2-9 years), in 2009/2010 (wave 2) and in 2013/2014 (wave 3) were included. A total of 5112 children (49% girls) participated at waves 1, 2 and 3. For 2656 children with genome-wide data we constructed a PRS based on 2.1 million single nucleotide polymorphisms. Z-score BMI and z-score waist circumference (WC) were assessed and eating behaviors and relevant confounders were reported by parents via questionnaires. Parental concern of overeating was derived from principal component analyses from an eating behavior questionnaire. RESULTS: In cross-lagged models, the prospective associations between z-score obesity indices and parental concern of overeating were bi-directional. In mediation models, the association between the PRS-BMI and parental concern of overeating at wave 3 was mediated by baseline z-BMI (ß = 0.16, 95% CI: 0.10, 0.21) and baseline z-WC (ß = 0.17, 95% CI: 0.11, 0.23). To a lesser extent, baseline parental concern of overeating also mediated the association between the PRS-BMI and z-BMI at wave 3 (ß = 0.10, 95% CI: 0.07, 0.13) and z-WC at wave 3 (ß = 0.09, 95% CI: 0.07, 0.12). CONCLUSIONS: The findings suggest that the prospective associations between obesity indices and parental concern of overeating are likely bi-directional, but obesity indices have a stronger association with future parental concern of overeating than vice versa. The findings suggest parental concern of overeating as a possible mediator in the genetic susceptibility to obesity and further highlight that other pathways are also involved. A better understanding of the genetic pathways that lead to childhood obesity can help to prevent weight gain. TRIAL REGISTRATION: Registry number: ISRCTN62310987 Retrospectively registered 17 September 2018.

[Secondary Data for Pharmacoepidemiological Research - Making the Best of It!] / Nutzung von Sekundärdaten für die pharmakoepidemiologische Forschung ­ machen wir das Beste draus!

Studies using secondary data such as health care claims data are often faced with methodological challenges due to the time-dependence of key quantities or unmeasured confounding. In the present paper, we discuss approaches to avoid or suitably address various sources of potential bias. In particular, we illustrate the target trial principle, marginal structural models, and instrumental variables with examples from the "GePaRD" database. Finally, we discuss the strengths and limitations of record linkage which can sometimes be used to supply missing information.

[Epidemiological approaches to address key research questions on COVID-19-an overview]. / Epidemiologische Ansätze zur Klärung wichtiger Forschungsfragen zu COVID-19 ­ eine Übersicht.

Epidemiology as a scientific discipline is predestined to address key problems in the COVID-19 pandemic. In order to do so, classic and new methods are used, and new challenges are emerging.This paper addresses the various phases of the population-based progression of SARS-CoV­2 infection and COVID-19. Based on a selective literature search, sample questions from studies conducted in Germany and internationally are presented, their respective epidemiological approaches discussed, and research gaps described.Scientific questions to be answered with epidemiological data and research approaches arise in every phase of infection and disease. Descriptive data are often generated via (repeated) cross-sectional studies. For analytical questions, such as the identification of risk groups, case-control studies could have provided valuable results, especially in the early phase of the pandemic, but were rarely conducted. Data from health insurance companies have an important function in the analysis of the course of disease; however, the potential of this data source with regard to questions on vaccination can probably hardly be used. Improved coordination of the various studies and a more "open data" oriented research infrastructure can further strengthen the contribution of epidemiology to the control of the current and future pandemics.

[The contribution of epidemiological models to the description of the outbreak of the COVID-19 pandemic]. / Der Beitrag von epidemiologischen Modellen zur Beschreibung des Ausbruchsgeschehens der COVID-19-Pandemie.

After the global outbreak of the COVID-19 pandemic, an infection dynamic of immense extent developed. Since then, numerous measures have been taken to bring the infection under control. This was very successful in the spring of 2020, while the number of infections rose sharply the following autumn. To predict the occurrence of infections, epidemiological models are used. These are in principle a very valuable tool in pandemic management. However, they still partly need to be based on assumptions regarding the transmission routes and possible drivers of the infection dynamics. Despite numerous individual approaches, systematic epidemiological data are still lacking with which, for example, the effectiveness of individual measures could be quantified. Such information generated in studies is needed to enable reliable predictions regarding the further course of the pandemic. Thereby, the complexity of the models could develop hand in hand with the complexity of the available data. In this article, after delineating two basic classes of models, the contribution of epidemiological models to the assessment of various central aspects of the pandemic, such as the reproduction rate, the number of unreported cases, infection fatality rate, and the consideration of regionality, is shown. Subsequently, the use of the models to quantify the impact of measures and the effects of the "test-trace-isolate" strategy is described. In the concluding discussion, the limitations of such modelling approaches are juxtaposed with their advantages.

[Making COVID-19 research data more accessible-building a nationwide information infrastructure]. / COVID-19-Forschungsdaten leichter zugänglich machen ­ Aufbau einer bundesweiten Informationsinfrastruktur.

Public health research and epidemiological and clinical studies are necessary to understand the COVID-19 pandemic and to take appropriate action. Therefore, since early 2020, numerous research projects have also been initiated in Germany. However, due to the large amount of information, it is currently difficult to get an overview of the diverse research activities and their results. Based on the "Federated research data infrastructure for personal health data" (NFDI4Health) initiative, the "COVID-19 task force" is able to create easier access to SARS-CoV-2- and COVID-19-related clinical, epidemiological, and public health research data. Therefore, the so-called FAIR data principles (findable, accessible, interoperable, reusable) are taken into account and should allow an expedited communication of results. The most essential work of the task force includes the generation of a study portal with metadata, selected instruments, other study documents, and study results as well as a search engine for preprint publications. Additional contents include a concept for the linkage between research and routine data, a service for an enhanced practice of image data, and the application of a standardized analysis routine for harmonized quality assessment. This infrastructure, currently being established, will facilitate the findability and handling of German COVID-19 research. The developments initiated in the context of the NFDI4Health COVID-19 task force are reusable for further research topics, as the challenges addressed are generic for the findability of and the handling with research data.

Like me, like you - relative importance of peers and siblings on children's fast food consumption and screen time but not sports club participation depends on age.

BACKGROUND: Lifestyle interventions to prevent paediatric obesity often target family and peer settings; their success is likely to depend on the influence that peers and families exert on children's lifestyle behaviors at different developmental stages. OBJECTIVE: First, to determine whether children's lifestyle behavior more closely resembles their peers' or siblings' behaviors. Secondly, to investigate longitudinally whether children's behavioral change is predicted by that of their peers or their siblings as they grow older. METHODS: The European prospective IDEFICS/I.Family cohort (baseline survey: 2007/2008, first follow-up: 2009/2010, and second follow-up: 2013/2014) aims at investigating risk factors for overweight and related behaviors during childhood and adolescence. The present investigation includes 2694 observations of children and their siblings aged 2 to 18 years. Peers were defined as same-sex, same-age children in the same community and identified from the full cohort. The longitudinal analysis (mean follow-up time: 3.7 years) includes 525 sibling pairs. Children's lifestyle behaviors including fast food consumption (frequency/week), screen time (hours/week) and sports club participation (hours/week) were assessed by questionnaire. Data were analyzed using multilevel linear models. RESULTS: Children's lifestyle behavior was associated with the respective behavior of their peers and sibling for all 3 behaviors. For fast food consumption, the peer resemblance was more than 6-fold higher than the sibling resemblance and the peer resemblance surpassed the sibling resemblance by the age of 9-10 years. The similarities with peers for fast food consumption and screen time steadily increased, while the similarities with siblings steadily decreased with increasing age of the children (Pinteraction < 0.001). In contrast, the relative importance of peers and siblings on sports club duration did not vary by the age of the children. Longitudinal results showed that children's changes in fast food consumption were more strongly associated with those in their peer group than their sibling, in particular if the age gap between siblings was large. CONCLUSION: In conclusion, our results support the implementation of multi-setting interventions for improving lifestyle behaviors in children. Our findings might also guide future intervention studies in the choice of timing and setting in which interventions are likely to be most effective. From the ages of 9-10 years onwards, family- or home-based interventions targeting children's fast food intake and screen time behavior may become less effective than school- or community-based interventions aimed at peer groups.

Adverse drug reaction or innocent bystander? A systematic comparison of statistical discovery methods for spontaneous reporting systems.

PURPOSE: Spontaneous reporting systems (SRSs) are used to discover previously unknown relationships between drugs and adverse drug reactions (ADRs). A plethora of statistical methods have been proposed over the years to identify these drug-ADR pairs. The objective of this study is to compare a wide variety of methods in their ability to detect these signals, especially when their detection is complicated by the presence of innocent bystanders (drugs that are mistaken to be associated with the ADR, since they are prescribed together with the drug that is the ADR's actual cause). METHODS: Twelve methods, 24 measures in total, ranging from simple disproportionality measures (eg, the reporting odds ratio), hypothesis tests (eg, test of the Poisson mean), Bayesian shrinkage estimates (eg, the Bayesian confidence propagation neural network, BCPNN) to sparse regression (LASSO), are compared in their ability to detect drug-ADR pairs in a large number of simulated SRSs with varying numbers of innocent bystanders and effect sizes. The area under the precision-recall curve is used to assess the measures' performance. RESULTS: Hypothesis tests (especially the test of the Poisson mean) perform best when the associations are weak and there is little to no confounding by other drugs. When the level of confounding increases and/or the effect sizes become larger, Bayesian shrinkage methods should be preferred. The LASSO proves to be the most robust against the innocent bystander effect. CONCLUSIONS: There is no absolute "winner". Which method to use for a particular SRS depends on the effect sizes and the level of confounding present in the data.

SIMEX for correction of dietary exposure effects with Box-Cox transformed data.

Modelling dietary data, and especially 24-hr dietary recall (24HDR) data, is a challenge. Ignoring the inherent measurement error (ME) leads to biased effect estimates when the association between an exposure and an outcome is investigated. We propose an adapted simulation extrapolation (SIMEX) algorithm for modelling dietary exposures. For this purpose, we exploit the ME model of the NCI method where we assume the assumption of normally distributed errors of the reported intake on the Box-Cox transformed scale and of unbiased recalls on the original scale. According to the SIMEX algorithm, remeasurements of the observed data with additional ME are generated in order to estimate the association between the level of ME and the resulting effect estimate. Subsequently, this association is extrapolated to the case of zero ME to obtain the corrected estimate. We show that the proposed method fulfils the key property of the SIMEX approach, that is, that the MSE of the generated data will converge to zero if the ME variance converges to zero. Furthermore, the method is applied to real 24HDR data of the I.Family study to correct the effects of salt and alcohol intake on blood pressure. In a simulation study, the method is compared with the NCI method resulting in effect estimates with either smaller MSE or smaller bias in certain situations. In addition, we found our method to be more informative and easier to implement. Therefore, we conclude that the proposed method is useful to promote the dissemination of ME correction methods in nutritional epidemiology.

[Digital public health-an overview]. / Digital Public Health ­ ein Überblick.

The rapid development and proliferation of digital health technologies have not only changed the medical professions, but offer great potential for public health, particularly in health promotion and disease prevention.At the same time, this emerging field is also characterized by conceptual and terminological fuzziness, a marked lack of high-quality evidence, and an absence of an honest discussion of unintended consequences and side effects. Further challenges for digital public health lie in the fact that the development of new health technologies is mainly driven by technological progress and less by evidence-based needs and research in public health.In this overview paper, we aim at conceptually denoting the field of digital public health, using principal public health functions as guiding principles. We discuss some current applications of digital health technologies in fulfilling public health functions and propose a needs-based development of digital health technologies.We will further address specific challenges to digital public health, in particular socio-economic differences in the usage of and profiting from digital health technologies, data protection and privacy issues, as well as ethical issues.

[The investigation of health outcomes in the German National Cohort: the most relevant endpoints and their assessment]. / Erforschung von Erkrankungen in der NAKO Gesundheitsstudie. Die wichtigsten gesundheitlichen Endpunkte und ihre Erfassung.

The focus of the German National Cohort, the largest population-based cohort study in Germany to date, is the investigation of the most important widespread diseases, such as cardiovascular diseases, diabetes, cancer, neurological and psychiatric disorders, and frequent respiratory and infectious diseases. This cohort will answer questions on the development of these diseases and on the impact of genetic, environmental and lifestyle-related risk factors. Another focus is on the identification of early, subclinical markers of emerging diseases. To answer these questions, a comprehensive assessment of these health outcomes as well as of all potential determinants and precursors is mandatory.This paper describes the various health outcomes that are assessed in the German National Cohort, as well as the examination modules that are applied for deep phenotyping of study participants. Repeated collection of biosamples as well as functional measurements and application of modern imaging techniques at various time points allow for assessing the dynamics of physiological changes related to the individuals' health status. The prognostic value of these changes for disease development will be explored and translated to novel approaches for prevention and personalised medicine. Incident diseases are being assessed through self-reports by study participants and through record linkage with data from health insurances and cancer registries. Additional information about clinical diagnoses is obtained from the treating physicians to ensure the highest possible validity.

[The baseline assessment of the German National Cohort (NAKO Gesundheitsstudie): participation in the examination modules, quality assurance, and the use of secondary data]. / Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten.

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20-69 years derived from random samples of the German general population were recruited in 18 study centers (2014-2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.

Urban Moveability and physical activity in children: longitudinal results from the IDEFICS and I.Family cohort.

BACKGROUND: Physical activity (PA) is one of the major protective behaviours to prevent non-communicable diseases. Positive effects of the built environment on PA are well investigated, although evidence of this association is mostly based on cross-sectional studies. The present study aims to investigate the longitudinal effects of built environment characteristics in terms of a moveability index on PA of children in their transition phase to adolescence using data of the IDEFICS/I.Family cohort. METHODS: We used data on 3394 accelerometer measurements of 2488 children and adolescents aged 3 to 15 years old from survey centres of three countries, Germany, Italy, and Sweden, who participated in up to three surveys over 6 years. In network-dependent home neighbourhoods, a moveability index was calculated based on residential density, land use mix, street connectivity, availability of public transport and public open spaces such as green spaces and public playgrounds in order to quantify opportunities for PA of children and adolescents. Linear trajectories of light PA (LPA) and moderate-to-vigorous PA (MVPA) were estimated using linear mixed models accounting for repeated measurements nested within individuals. Least squares means were estimated to quantify differences in trajectories over age. RESULTS: LPA and MVPA declined annually with age by approximately 20 min/day and 2 min/day respectively. In girls, the moveability index showed a consistent significantly positive effect on MVPA ([Formula: see text] = 2.14, 95% CI: (0.11; 4.16)) for all ages, while in boys the index significantly lessened the decline in LPA with age for each year. ([Formula: see text] = 2.68, 95% CI: (0.46; 4.90)). Availability of public open spaces was more relevant for MVPA in girls and LPA in boys during childhood, whereas in adolescence, residential density and intersection density became more important. CONCLUSION: Built environment characteristics are important determinants of PA and were found to have a supportive effect that ameliorates the decline in PA during the transition phase from childhood to adolescence. In childhood environmental support for leisure time PA through public open spaces was found to be the most protective factor whereas in adolescence the positive influence of street connectivity and residential density was most supportive of physical activity.

Urinary sucrose and fructose to validate self-reported sugar intake in children and adolescents: results from the I.Family study.

PURPOSE: Excessive consumption of free sugar increases the risk for non-communicable diseases where a proper assessment of this intake is necessary to correctly estimate its association with certain diseases. Urinary sugars have been suggested as objective biomarkers for total and free sugar intake in adults but less is known about this marker in children and adolescents. Therefore, the aim of this exploratory study is to evaluate the relative validity of self-reported intake using urinary sugars in children and adolescents. METHODS: The study was conducted in a convenience subsample of 228 participants aged 5-18 years of the I.Family study that investigates the determinants of food choices, lifestyle and health in European families. Total, free and intrinsic sugar intake (g/day) and sugar density (g/1000 kcal) were assessed using 24-h dietary recalls (24HDRs). Urinary sucrose (USUC) and urinary fructose (UFRU) were measured in morning urine samples and corrected for creatinine excretion (USUC/Cr, UFRU/Cr). Correlation coefficients, the method of triads and linear regression models were used to investigate the relationship between intake of different types of sugar and urinary sugars. RESULTS: The correlation between usual sugar density calculated from multiple 24HDRs and the sum of USUC/Cr and UFRU/Cr (USUC/Cr + UFRU/Cr) was 0.38 (p < 0.001). The method of triads revealed validity coefficients for the 24HDR from 0.64 to 0.87. Linear regression models showed statistically significant positive associations between USUC/Cr + UFRU/Cr and the intake of total and free sugar. CONCLUSIONS: These findings support the relative validity of total and free sugar intake assessed by self-reported 24HDRs in children and adolescents.

Modeling physical activity data using L0 -penalized expectile regression.

In recent years accelerometers have become widely used to objectively assess physical activity. Usually intensity ranges are assigned to the measured accelerometer counts by simple cut points, disregarding the underlying activity pattern. Under the assumption that physical activity can be seen as distinct sequence of distinguishable activities, the use of hidden Markov models (HMM) has been proposed to improve the modeling of accelerometer data. As further improvement we propose to use expectile regression utilizing a Whittaker smoother with an L0 -penalty to better capture the intensity levels underlying the observed counts. Different expectile asymmetries beyond the mean allow the distinction of monotonous and more variable activities as expectiles effectively model the complete distribution of the counts. This new approach is investigated in a simulation study, where we simulated 1,000 days of accelerometer data with 1 and 5 s epochs, based on collected labeled data to resemble real-life data as closely as possible. The expectile regression is compared to HMMs and the commonly used cut point method with regard to misclassification rate, number of identified bouts and identified levels as well as the proportion of the estimate being in the range of ±10% of the true activity level. In summary, expectile regression utilizing a Whittaker smoother with an L0 -penalty outperforms HMMs and the cut point method and is hence a promising approach to model accelerometer data.