Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO).

Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.

Childhood Trauma and Somatic and Mental Illness in Adulthood.

BACKGROUND: Childhood trauma is associated with somatic and mental illness in adulthood. The strength of the association varies as a function of age, sex, and type of trauma. Pertinent studies to date have mainly focused on individual diseases. In this study, we investigate the association between childhood trauma and a multiplicity of somatic and mental illnesses in adulthood. METHODS: Data from 156 807 NAKO Health Study participants were analyzed by means of logistic regressions, with adjustment for age, sex, years of education, and study site. The Childhood Trauma Screener differentiated between no/minor (n = 115 891) and moderate/severe childhood trauma (n = 40 916). The outcome variables were medical diagnoses of five somatic and two mental health conditions as stated in the clinical history. RESULTS: Persons with childhood trauma were more likely to bear a diagnosis of all of the studied conditions: cancer (odds ratio [OR] = 1.10; 95% confidence interval: [1.05; 1.15]), myocardial infarction (OR = 1.13 [1.03; 1.24]), diabetes (OR = 1.16, [1.10; 1.23]), stroke (OR = 1.35 [1.23; 1.48]), chronic obstructive pulmonary disease (OR = 1.45 [1.38; 1.52]), depression (OR = 2.36 [2.29; 2.43]), and anxiety disorders (OR = 2.08 [2.00; 2.17]). All of these associations were stronger in younger persons, regardless of the nature of childhood trauma. Differences between the sexes were observed only for some of these associations. CONCLUSION: Childhood trauma was associated with a higher probability of developing mental as well as somatic illness in adulthood. As childhood trauma is an element of individual history that the victim has little to no control over, and because the illnesses that can arise in adulthood in association with it are a heavy burden on the affected persons and on society, there is a need for research on these associations and for the development of preventive measures.

Better Together: Data Harmonization and Cross-Study Analysis of Abdominal MRI Data From UK Biobank and the German National Cohort.

OBJECTIVES: The UK Biobank (UKBB) and German National Cohort (NAKO) are among the largest cohort studies, capturing a wide range of health-related data from the general population, including comprehensive magnetic resonance imaging (MRI) examinations. The purpose of this study was to demonstrate how MRI data from these large-scale studies can be jointly analyzed and to derive comprehensive quantitative image-based phenotypes across the general adult population. MATERIALS AND METHODS: Image-derived features of abdominal organs (volumes of liver, spleen, kidneys, and pancreas; volumes of kidney hilum adipose tissue; and fat fractions of liver and pancreas) were extracted from T1-weighted Dixon MRI data of 17,996 participants of UKBB and NAKO based on quality-controlled deep learning generated organ segmentations. To enable valid cross-study analysis, we first analyzed the data generating process using methods of causal discovery. We subsequently harmonized data from UKBB and NAKO using the ComBat approach for batch effect correction. We finally performed quantile regression on harmonized data across studies providing quantitative models for the variation of image-derived features stratified for sex and dependent on age, height, and weight. RESULTS: Data from 8791 UKBB participants (49.9% female; age, 63 ± 7.5 years) and 9205 NAKO participants (49.1% female, age: 51.8 ± 11.4 years) were analyzed. Analysis of the data generating process revealed direct effects of age, sex, height, weight, and the data source (UKBB vs NAKO) on image-derived features. Correction of data source-related effects resulted in markedly improved alignment of image-derived features between UKBB and NAKO. Cross-study analysis on harmonized data revealed comprehensive quantitative models for the phenotypic variation of abdominal organs across the general adult population. CONCLUSIONS: Cross-study analysis of MRI data from UKBB and NAKO as proposed in this work can be helpful for future joint data analyses across cohorts linking genetic, environmental, and behavioral risk factors to MRI-derived phenotypes and provide reference values for clinical diagnostics.

Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies.

Large epidemiological studies such as the UK Biobank (UKBB) or German National Cohort (NAKO) provide unprecedented health-related data of the general population aiming to better understand determinants of health and disease. As part of these studies, Magnetic Resonance Imaging (MRI) is performed in a subset of participants allowing for phenotypical and functional characterization of different organ systems. Due to the large amount of imaging data, automated image analysis is required, which can be performed using deep learning methods, e. g. for automated organ segmentation. In this paper we describe a computational pipeline for automated segmentation of abdominal organs on MRI data from 20,000 participants of UKBB and NAKO and provide results of the quality control process. We found that approx. 90% of data sets showed no relevant segmentation errors while relevant errors occurred in a varying proportion of data sets depending on the organ of interest. Image-derived features based on automated organ segmentations showed relevant deviations of varying degree in the presence of segmentation errors. These results show that large-scale, deep learning-based abdominal organ segmentation on MRI data is feasible with overall high accuracy, but visual quality control remains an important step ensuring the validity of down-stream analyses in large epidemiological imaging studies.

Framework and baseline examination of the German National Cohort (NAKO).

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19-74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2-3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4-5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years.

Association between socioeconomic position and cystatin C in the Heinz Nixdorf Recall Study.

Social inequalities in health and disease are well studied. Less information is available on inequalities in biomarker levels indicating subclinical stages of disease such as cystatin C, an early diagnostic marker of renal dysfunction and predictor for cardiovascular disease. We evaluated the relationship between cystatin C, socioeconomic position (SEP) and established cardiovascular risk factors in a population-based study. In 4475 men and women aged 45-75 years participating in the baseline examination of the Heinz Nixdorf Recall Study cystatin C was measured from serum samples with a nephelometric assay. SEP was assessed by education and household income. Linear regression models were used to analyse the association between SEP and cystatin C as well as the impact of cardiovascular risk factors (i.e., body mass index, blood pressure, blood glucose, diabetes mellitus, blood lipids, C-reactive protein, smoking) on this association. After adjustment for age and sex cystatin C decreased by 0.019 mg/l (95% confidence interval (CI) - 0.030 to - 0.008) per five years of education. While using a categorical education variable cystatin C presented 0.039 mg/l (95% CI 0.017-0.061) higher in men and women in the lowest educational category (≤ 10 years of education) compared to the highest category (≥ 18 years). Concerning income, cystatin C decreased by 0.014 mg/l (95% CI - 0.021 to - 0.006) per 1000 € after adjustment for age and sex. For men and women in the lowest income quartile cystatin C was 0.024 mg/l (95% CI 0.009-0.038) higher compared to the highest income quartile. After adjusting for established cardiovascular risk factors the observed associations were substantially diminished. Social inequalities seem to play a role in subclinical stages of renal dysfunction, which are also related to development of cardiovascular disease. Adjustment for traditional cardiovascular risk factors showed that these risk factors largely explain the association between SEP and cystatin C.

A genetic sum score of effect alleles associated with serum lipid concentrations interacts with educational attainment.

High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC) levels are influenced by both genes and the environment. The aim was to investigate whether education and income as indicators of socioeconomic position (SEP) interact with lipid-increasing genetic effect allele scores (GES) in a population-based cohort. Using baseline data of 4516 study participants, age- and sex-adjusted linear regression models were fitted to investigate associations between GES and lipids stratified by SEP as well as including GES×SEP interaction terms. In the highest education group compared to the lowest stronger effects per GES standard deviation were observed for HDL-C (2.96 mg/dl [95%-CI: 2.19, 3.83] vs. 2.45 mg/dl [95%-CI: 1.12, 3.72]), LDL-C (6.57 mg/dl [95%-CI: 4.73, 8.37] vs. 2.66 mg/dl [95%-CI: -0.50, 5.76]) and TC (8.06 mg/dl [95%-CI: 6.14, 9.98] vs. 4.37 mg/dl [95%-CI: 0.94, 7.80]). Using the highest education group as reference, interaction terms showed indication of GES by low education interaction for LDL-C (ßGES×Education: -3.87; 95%-CI: -7.47, -0.32), which was slightly attenuated after controlling for GESLDL-C×Diabetes interaction (ßGES×Education: -3.42; 95%-CI: -6.98, 0.18). The present study showed stronger genetic effects on LDL-C in higher SEP groups and gave indication for a GESLDL-C×Education interaction, demonstrating the relevance of SEP for the expression of genetic health risks.

Socioeconomic position is associated with N-terminal pro-brain natriuretic peptide (NT-proBNP)-Results of the population-based Heinz Nixdorf Recall study.

OBJECTIVES: N-Terminal pro Brain Natriuretic Peptide (NT-proBNP) is a diagnostic marker for heart failure and a prognostic factor for cardiovascular disease (CVD). The aim of this study was to examine the association of socioeconomic position (SEP) with NT-proBNP while assessing sex-differences and the impact of CVD risk factors and prevalent CVD on the association. METHODS: Baseline data of 4598 participants aged 45-75 years of the Heinz Nixdorf Recall Study were used. Income and education were used as SEP indicators. Age- and sex-adjusted linear regression models were fitted to calculate effect size estimates and 95% confidence intervals (95%-CIs) for the total effect of SEP indicators on NT-proBNP, while potential mediation was assessed by additionally accounting for traditional CVD risk factors (i.e., systolic blood pressure, HDL cholesterol, LDL cholesterol, diabetes, anti-hypertensive medication, lipid-lowering medication, BMI, current smoking). Education and income were included separately in the models. RESULTS: With an age- and sex-adjusted average change in NT-proBNP of -6.47% (95%-CI: -9.91; -2.91) per 1000€, the association between income and NT-proBNP was more pronounced compared to using education as a SEP indicator (-0.80% [95%-CI: -1.92; 0.32] per year of education). Sex-stratified results indicated stronger associations in men (-8.43% [95%-CI: -13.21; -3.38] per 1000€; -1.63% [95%-CI: -3.23; -0.001] per year of education) compared to women (-5.10% [95%-CI: -9.82; -0.01] per 1000€; -1.04% [95%-CI: -2.59; 0.50] per year of education). After adjusting for CVD risk factors some of the observed effect size estimates were attenuated, while the overall association between SEP indicators and NT-proBNP was still indicated. The exclusion of participants with prevalent coronary heart disease or stroke did not lead to a substantial change in the observed associations. CONCLUSIONS: In the present study associations of education and income with NT-proBNP were observed in a population-based study sample. Only parts of the association were explained by traditional CVD risk factors, while there were substantial sex-differences in the strength of the observed association. Overt coronary heart disease or stroke did not seem to trigger the associations.

Self-reported medication intake vs information from other data sources such as pharmacy records or medical records: Identification and description of existing publications, and comparison of agreement results for publications focusing on patients with cancer - a systematic review.

PURPOSE: To identify and describe publications addressing the agreement between self-reported medication and other data sources among adults and, in a subgroup of studies dealing with cancer patients, seek to identify parameters which are associated with agreement. METHODS: A systematic review including a systematic search within five biomedical databases up to February 28, 2019 was conducted as per the PRISMA Statement. Studies and agreement results were described. For a subgroup of studies dealing with cancer, we searched for associations between agreement and patients' characteristics, study design, comparison data source, and self-report modality. RESULTS: The literature search retrieved 3392 publications. Included articles (n = 120) show heterogeneous agreement. Eighteen publications focused on cancer populations, with relatively good agreement identified in those which analyzed hormone therapy, estrogen, and chemotherapy (n = 11). Agreement was especially good for chemotherapy (proportion correct ≥93.6%, kappa ≥0.88). No distinct associations between agreement and age, education or marital status were identified in the results. There was little evaluation of associations between agreement and study design, self-report modality and comparison data source, thus not allowing for any conclusions to be drawn. CONCLUSION: An overview of the evidence available from validation studies with a description of several characteristics is provided. Studies with experimental design which evaluate factors that might affect agreement between self-report and other data sources are lacking.

[Lung function in the German National Cohort: methods and initial results]. / Lungenfunktion in der NAKO Gesundheitsstudie: Methoden und erste Ergebnisse.

BACKGROUND: A nationwide assessment of the respiratory status on the basis of standardized lung function measurements has so far not been available in Germany. The present work describes the lung function tests in the German National Cohort (GNC) and presents initial results based on the GNC Midterm Baseline Dataset. MATERIAL AND METHODS: The assessment of lung function in the GNC comprised spirometry (level 1) and the determination of exhaled nitric oxide (FeNO, level 2). Our quality assurance concept included regular training of lung function test procedures at various GNC sites, interim evaluations of test quality, as well as regular calibration/measurement checks of test equipment. For spirometry, we established a stepwise procedure for offline quality control based on raw flow volume curves. RESULTS: In the present dataset (n = 101,734), spirometry was available for 86,893 study participants and FeNO was available for 15,228 participants. The average (±SD) FEV1 Z score (according to GLI 2012) was -0.321 ± 1.047, the FVC Z score was -0.153 ± 0.941, and the FEV1/FVC Z score was -0.337 ± 0.901. The difference in FEV1/FVC between current smokers and never-smokers increased with age. The average FeNO was 14.2 ÷ 2.0 ppb. Current smoking reduced FeNO levels by 43%, whereas respiratory allergy increased FeNO levels by 16% in nonsmokers. DISCUSSION: The results of spirometry and the FeNO measurements are in the expected range with regard to their distributions and correlates. The GNC provides a valuable basis for future investigations of respiratory health and its determinants as well as research into the prevention of respiratory diseases in Germany.

[Socio-demographic and employment-related factors in the German National Cohort (GNC; NAKO Gesundheitsstudie)]. / Soziodemografische und erwerbsbezogene Merkmale in der NAKO Gesundheitsstudie.

BACKGROUND: In epidemiologic studies, standardised measurement of socio-demographic and employment-related factors is becoming increasingly important, as variables such as gender, age, education or employment status are factors influencing health and disease risks. AIMS: The article gives an overview of the scientific background and assessment of socio-demographic factors in the German National Cohort Study. In addition, the distribution of individual characteristics in the cohort as well as relationships with health-related measures are presented by way of example. MATERIAL AND METHODS: The analysis is based on the data of the first half of the baseline survey (n = 101,724). On this basis, we present the distribution of key socio-demographic characteristics and analyse relationships with exemplary selected health indicators (body mass index, self-reported health) to assess the validity of socio-demographic data measurements. RESULTS: On average, study participants were 52.0 years old (SD = 12.4). Of the participants, 53.6% were women, 54.3% had high education, 60.1% were married and 72% were employed while 3.4% were unemployed. Well-established correlations between socio-demographic factors and health could be reproduced with the German National Cohort data. For example, low education, old age and unemployment were associated with an increased prevalence of obesity and poor self-reported health. DISCUSSION: The German National Cohort provides a comprehensive measurement of socio-demographic characteristics. Combined with a wide range of health data and the longitudinal measurements available in the future, this opens up new opportunities for health science and social epidemiological research in Germany.