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. 2026 Aug 20;104(10):673–681. doi: 10.2471/BLT.25.295087

How a 10-minute bout requirement for physical activity affects guideline adherence estimates, Germany

Impact de l’exigence d’une séance d’activité physique de 10 minutes sur les estimations du suivi de recommandations, Allemagne

Cómo afecta a las estimaciones de la adherencia a las directrices de la OMS el requisito de realizar la actividad física en sesiones de al menos 10 minutos seguidos, Alemania

كيف يؤثر شرط ممارسة النشاط البدني لمدة 10 دقائق متواصلة على تقديرات الالتزام بالإرشادات، ألمانيا

德国：身体活动单次持续 10 分钟的要求对指南依从率的估计有何影响

Влияние требования минимальной 10-минутной физической активности на оценку показателя соблюдения рекомендаций, Германия

Julian Brummer a, Michael J Stein b, Hansjörg Baurecht b, Mirko Brandes c, Christoph Buck c, Antje Hebestreit c, Lilian Krist d, Michael Leitzmann b, Andrea Weber b, Volker Harth e, Jana-Kristin Heise f, Verena Katzke g, Thomas Keil d, Alexander Kluttig h, Claudia Meinke-Franze i, Rafael Mikolajczyk h, Ute Mons j, Katharina Nimptsch k, Nadia Obi e, Cara Övermöhle l, Annette Peters m, Tobias Pischon k, Börge Schmidt n, Matthias B Schulze o, Henry Völzke i, Stefan N Willich d, Florian Herbolsheimer a, Karen Steindorf a,✉
PMCID: PMC13626531  PMID: 42819644

Abstract

Objective

To examine how adherence to the World Health Organization’s (WHO) physical activity guidelines changes with and without the application of a 10-minute bout requirement.

Methods

We analysed accelerometry data from the baseline assessment of the German National Cohort, NAKO. Using predefined acceleration thresholds, we classified each participant’s volumes of moderate and vigorous intensity physical activity and compared these values with WHO guidelines. We analysed data with and without the 10-minute bout requirement. We used Welch’s analysis of variance and equal proportions tests to compare demographic and health characteristics between participants who met the activity guidelines and those who did not.

Findings

Of 63 134 participants, 22 226 (35.2%) met the guidelines with the bout requirement, while 62 532 (99.0%) met the guidelines without it. Participants who met the guidelines under each condition differed in demographic and health-related characteristics. For example, mean age was 48.6 years (SD: 13.0) among participants meeting the guidelines with the bout, 50.8 years (SD: 12.2) among those meeting only the guidelines without the bout and 60.8 years (SD: 10.4) among those meeting neither guidelines. Participants meeting the guidelines with the bout had a lower body mass index (25.2 kg/m2; SD: 4.0) than those meeting only the guidelines without the bout (27.0 kg/m2; SD: 5.1) and those meeting neither guidelines (30.6 kg/m2; SD: 7.1)

Conclusion

Removing the 10-minute bout requirement for accelerometry-measured activity volumes substantially increased estimated guideline adherence. The change has implications for interpreting time trends in guideline adherence and alters conclusions about which population subgroups meet the guidelines.

Introduction

Physical activity provides many health benefits.1,2 Consequently, health authorities worldwide have established physical activity guidelines1–6 which serve as a foundation for public health strategies.1 In 2020, the World Health Organization (WHO) published revised physical activity guidelines.1,4 The revised guidelines continue to recommend a minimum of 150 minutes moderate intensity aerobic physical activity, 75 minutes of vigorous intensity aerobic physical activity or an equivalent combination of both per week.1 An important change, however, was the removal of the requirement that only activity bouts of at least 10 minutes could count towards the weekly goal (henceforth referred to as the bout requirement).1 Within the broader evolution of physical activity guidelines in recent decades,7,8 the bout requirement became increasingly obsolete as device-based measurements of physical activity gained prominence. This shift coincided with evidence supporting the health benefits of physical activity of any duration, which could be assessed without relying solely on participants’ self-reports.9,10 The implications of the change to the bout requirement on guideline adherence remain unclear.

The broader definition of guideline-relevant physical activity means that, irrespective of actual changes in population physical activity, more individuals are now likely to be classified as adhering to the guidelines. Few studies address this issue and those that do use varying methodologies and report inconsistent findings. Several accelerometry-based studies observed that removing the 10-minute bout requirement substantially increased adherence to moderate and vigorous physical activity guidelines.11–13 For example, a nationally representative Canadian study reported that removing the 10-minute bout requirement increased guideline adherence from 18.5% to 45.3%,11 while a smaller-scale Japanese study found an even greater increase from 12.5% to 92.4%.12 In contrast, two self-report-based studies found only marginal changes when removing the bout requirement.14,15 These differences in adherence after removing the bout requirement may affect subgroups of the population differently,11,12 which could have important implications for targeted physical activity promotion.

This study aimed to determine how accelerometry-measured adherence to the WHO aerobic physical activity guidelines changes with and without the application of the 10-minute bout requirement. We also aimed to examine the demographic and health-related characteristics of participants meeting the guideline under both conditions.

Methods

The reporting of this study follows the STROBE guidelines.16

Study setting

We used data from the baseline examination of the German National Cohort (NAKO) study, conducted between 2014 and 2019.17 NAKO is an ongoing multidisciplinary, multicentre, population-based prospective cohort study, whose framework, design, and methods have previously been described in detail.17–19 The NAKO study used random age- and sex-stratified sampling from compulsory population registries in 16 study regions, comprising 18 study centres across Germany. At baseline, the study included 205 414 participants from 1 316 055 million randomly selected eligible residents, marking a response proportion of 15.6%.19 Participants were aged 19–74 years at baseline.17 All relevant ethics committees approved the study before onset. The NAKO study follows the Declaration of Helsinki and all participants provided written informed consent. All study data can be applied for and obtained via the NAKO electronic application portal.20

Physical activity assessment

A subsample from the NAKO baseline examination took part in seven-day, triaxial, hip-worn, 100Hz accelerometry using ActiGraph (Pensacola, United States of America) devices to measure physical movement.21 The NAKO study sampling strategy for this subsample of its multilevel data collection is described in detail elsewhere.17 In brief, accelerometry was assigned to 50% of participants undergoing only the basic examination programme (74 222 out of 148 444 participants).17 However, some study centres exceeded that proportion, resulting in 89 949 out of the 205 414 participants being offered accelerometry.17 As participation in the accelerometry module was voluntary, not all assigned participants took part, and the data set we received from the NAKO team contained accelerometry data from 72 713 participants.

The evolution of ActiGraph product line during the NAKO baseline examination necessitated the use of three ActiGraph models (GT3X+, wGT3X+, and wGT3X-BT).20 NAKO study personnel attached the ActiGraph devices to participants during the study centre visit, placing them above the right hip on the mid-axillary line using an elastic strap, wearable over or underneath clothing.21 The NAKO team asked participants to conduct their usual activities and remove the ActiGraph devices only during prolonged (more than 30 minutes) water exposure. Based on the methodological recommendations of the NAKO Expert Group on Physical Activity and Fitness, we considered days to be valid if the device recorded at least 16 valid hours per day. With the advice of the expert group, we evaluated the validity of any single measurement day before examining whether the required number of weekdays and weekend days was available, and excluded participants with less than one valid weekend day or fewer than two valid weekdays. Additionally, we excluded participants with an incomplete 24-hour cycle (participants with consistently invalid data for any given 15-minute interval across all recording days) to ensure full representation of the 24-hour cycle. The quality control measures and data processing of the raw accelerometry data have been described in detail elsewhere.21 Briefly, we primarily processed the data using GGIR (Version 2.10–3) an open-source R package;22 we excluded recordings with calibration errors exceeding 0.02 units of gravitational acceleration, detected and imputed non-wear time, and derived summary metrics for physical activity.21

We used the mean amplitude deviation to quantify time spent at different physical activity intensities.21 By applying established acceleration thresholds23 we calculated each participant’s weekly duration of moderate and vigorous intensity physical activity. In our primary analyses we applied thresholds at 90 milligravity for moderate and 410 milligravity for vigorous intensity activity (where 1 g ≈9.81 m/s2). For sensitivity analyses, we also applied lower and higher thresholds:21 80 milligravity and 100 milligravity for moderate, and 400 milligravity and 420 milligravity for vigorous intensity activity. We aggregated the raw data over a time interval of five seconds, equating to an epoch length of five seconds. To derive the weekly volumes of moderate and vigorous intensity activity, we multiplied the average daily values by seven. We winsorized outliers at the 99.9th percentile within each age and sex group to address possible calibration issues or sensor malfunctions,21 because some extreme values persisted despite rigorous exclusion criteria.

We dichotomized adherence to the WHO physical activity guidelines, categorizing participants as adherent or non-adherent based on the following criteria: (i) at least 150 minutes per week of moderate intensity activity; (ii) at least 75 minutes per week of vigorous intensity activity; or (iii) an equivalent combination of moderate and vigorous intensity activity, calculated as minutes per week of moderate intensity plus two times minutes per week of vigorous intensity totalling at least 150 minutes per week.

We assessed guideline adherence in two ways: (i) applying the 10-minute bout requirement11, following the previous WHO guidelines24 and requiring at least 80% of epochs to meet the threshold criteria; and (ii)  removing the 10-minute bout requirement, consistent with the current WHO guidelines.1

We extended previous work11 by categorizing participants into three mutually exclusive groups: (i) adherents, who met the previous guidelines with the bout and therefore also met the current guidelines without the bout; (ii) transitioners, who met only the guidelines without the bout; and (iii) non-adherents, who did not meet either set of guidelines.

Statistical analysis

We computed descriptive statistics, including means and standard deviations (SD). We used paired t-tests to compare volumes of moderate and vigorous intensity physical activity. To compare adherents, transitioners and non-adherents by age, body mass index (BMI), self-reported overall health (scale from one to five, from poor to excellent) and activity volumes, we applied Welch's analysis of variance followed by Games–Howell post hoc tests. We chose these procedures because Levene's tests indicated that the assumption of homogeneity of variance was violated for all variables of interest (P-values: < 0.001). To compare the three groups by sex and highest educational attainment, we used tests of equal proportions (prop.test function in R) and pairwise comparisons for proportions, with Bonferroni correction (pairwise.prop.test function in R). For educational level, we used the 2011 International Standard Classification of Education to classify participants as having low (primary and lower-secondary education), medium (upper-secondary and post-secondary non-tertiary education) or high (bachelor’s level or equivalent and above).25 Where indicated, we report P-values and 95% confidence intervals (CI) to evaluate statistical significance.

We used R version 4.4.1,26 in RStudio version 2024.04.2, (Posit Software, PBC, Boston, USA) to conduct all statistical analyses.

Results

The analysis included data from 63 134 participants (Fig. 1). The sample had a relatively balanced sex distribution. The mean age of participants was 50.1 years (SD: 12.6; range: 19.0–74.0), with a mean BMI of 26.4 kg/m2 (SD: 4.8; range: 14.4–62.2) and they reported relatively good overall health with a mean score of 3.3 points (SD: 0.7; range: 1–5; Table 1).

Fig. 1.

Participant flow in the study on the 10-minute bout requirement for physical activity guideline adherence, Germany, 2014–2019

NAKO: German National Cohort.

Fig. 1

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Table 1. Participant characteristics in the study on the 10-minute bout requirement for physical activity guideline adherence, Germany, 2014–2019.

Characteristic Total sample (n = 63 134) Adherents (n = 22 226) Transitioners (n = 40 306) Non-adherents (n = 602) P for group differencea
Sex, no. (%) < 0.001
Male 30 210 (47.9) 11 082 (49.9) 18 796 (46.6) 332 (55.1)  
Female 32 924 (52.1) 11 144 (50.1) 21 510 (53.4) 270 (44.9)  
Age in years, no. (%) NA
19–29 5 678 (9.0) 2 681 (12.1) 2 980 (7.4) 17 (2.8)  
30–39 6 535 (10.4) 2 439 (11.0) 4 080 (10.1) 16 (2.7)  
40–49 16 533 (26.2) 5 933 (26.7) 10 566 (26.2) 34 (5.6)  
50–59 17 184 (27.2) 5 897 (26.5) 11 165 (27.7) 122 (20.3)  
60–69 15 895 (25.2) 4 885 (22.0) 10 663 (26.5) 347 (57.6)  
≥ 70 1 309 (2.1) 391 (1.8) 852 (2.1) 66 (11.0)  
Age in years, mean (SD) 50.1 (12.6) 48.6 (13.0) 50.8 (12.2) 60.8 (10.4) < 0.001
Education level, no. (%)b < 0.001
Low 1 553 (2.5) 365 (1.7) 1 142 (2.9) 46 (7.7)  
Medium 25 096 (40.6) 7 402 (34.4) 17 376 (43.8) 318 (53.4)  
High 35 152 (56.9) 13 775 (63.9) 21 145 (53.3) 232 (38.9)  
BMI (kg/m2), no. (%) NA
< 18.5 674 (1.1) 268 (1.2) 399 (1.0) 7 (1.2)  
≥ 18.5 and < 25.0 26 567 (42.1) 11 484 (51.7) 14 953 (37.1) 130 (21.6)  
≥ 25.0 and < 30.0 23 454 (37.2) 7 971 (35.9) 15 310 (38.0) 173 (28.7)  
≥ 30.0 and < 35.0 8 816 (14.0) 2 021 (9.1) 6 651 (16.5) 144 (23.9)  
≥ 35.0 and < 40.0 2 611 (4.1) 388 (1.7) 2 135 (5.3) 88 (14.6)  
≥ 40.0 994 (1.6) 87 (0.4) 847 (2.1) 60 (10.0)  
BMI in kg/m2, mean (SD) 26.4 (4.8) 25.2 (4.0) 27.0 (5.1) 30.6 (7.1) < 0.001
Self-reported overall health, no. (%) NA
Poor 459 (0.7) 94 (0.4) 324 (0.8) 41 (7.3)  
Less good 5 765 (9.3) 1 346 (6.2) 4 221 (10.7) 198 (35.1)  
Good 34 065 (55.2) 10 700 (49.1) 23 083 (58.6) 282 (50.0)  
Very good 19 066 (30.9) 8 387 (38.5) 10 642 (27.0) 37 (6.6)  
Excellent 2 349 (3.8) 1 246 (5.7) 1 097 (2.8) 6 (1.1)  
Self-reported overall health score, mean (SD) 3.3 (0.7) 3.4 (0.7) 3.2 (0.7) 2.6 (0.8) < 0.001
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BMI: body mass index; NA: not applicable; SD: standard deviation.

a Refers to differences among the three groups: Adherents, transitioners and non-adherents 

b Classified using the International Standard Classification of Education 2011 level24 and categorized as low (primary and lower-secondary education), medium (upper-secondary and post-secondary, non-tertiary education) or high (bachelor’s or equivalent level and above).

Notes: adherents are those who met the physical activity guideline with the bout (participants in this group automatically also met the physical activity guideline without the bout); transitioners are those who did not meet the guideline with the bout, but met the guideline without the bout. Non-adherents are those who did not meet the guideline without the bout and therefore met neither guideline. Due to missing data, the number of participants in the variables education level, BMI and self-reported overall health does not equal the total sample size reported for each column.

Guideline adherence

Among participants, 35.2% (22 226) were adherents who met the guideline with the bout, an additional 63.8% (40 306) of participants qualified as transitioners, which together resulted in 99.0% (62 532) meeting the guideline without the bout. Only 1.0% (602) of participants were in the non-adherents category, not meeting either guideline.

The sensitivity analyses using ± 10 milligravity as the acceleration thresholds for classifying moderate and vigorous intensity activity showed that, for activity without the bout, 98.3% (62 065) met the guideline at the higher thresholds and 99.5% (62 835) at the lower thresholds. For the activity with the bout, 31.7% (20 045) met the guideline at the higher thresholds and 39.5% (24 934) at the lower thresholds.

Physical activity volumes

Weekly volumes of both moderate and vigorous activity were considerably higher when activity without the bout was included than when only the activity with the bout was considered (Table 2). Under both conditions, participants accumulated substantially more moderate activity than vigorous activity.

Table 2. Participant weekly activity levels in the study on the 10-minute bout requirement for physical activity guideline adherence, Germany, 2014–2019.

Intensity of physical activity Mean minutes per week (SD)
 P for group differencea
Total sample (n = 63 134) Adherents (n = 22 226) Transitioners (n = 40 306) Non-adherents (n = 602)
With bout 
Moderate 123.5 (133.3) 256.4 (140.3) 52.0 (43.9) 6.6 (15.1) < 0.001
Vigorous 9.4 (32.6) 24.6 (50.9) 1.1 (6.0) 0.1 (1.0) < 0.001
Moderate and vigorous 132.9 (141.3) 280.9 (138.9) 53.1 (44.1) 6.7 (15.2) NA
Without bout
Moderate 565.9 (216.4) 695.5 (205.4) 501.2 (183.0) 108.5 (34.3) < 0.001
Vigorous 18.5 (39.3) 40.0 (57.9) 6.9 (13.2) 0.3 (1.7) < 0.001
Moderate and vigorous 584.3 (226.6) 735.5 (209.0) 508.1 (185.9) 108.8 (34.2) NA
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NA: not applicable; SD: standard deviation.

a Refers to differences among the three groups: adherents, transitioners and non-adherents.

Notes: adherents are those who met the physical activity guideline with the bout (participants in this group automatically also met the physical activity guideline without the bout); transitioners are those who did not meet the guideline with the bout but met the guideline without the bout. Non-adherents are those who did not meet the guideline without the bout and therefore met neither guideline. Moderate and vigorous physical activity was calculated by summing moderate and physical activity. Note that means and standard deviations are reported to facilitate comparability and interpretability, despite right-skewness in several variables.

Activity volumes were highest among adherents, intermediate among transitioners and lowest among non-adherents under both definitions. Fig. 2 and Fig. 3 visualize the respective moderate and vigorous activity volumes, respectively.

Fig. 2.

Mean weekly volumes of moderate physical activity in the study on the 10-minute bout requirement for physical activity guideline adherence, Germany, 2014–2019

Note: acceleration thresholds used were 90 milligravity for moderate physical activity. All group differences and pairwise comparisons reached statistical significance (P-values: < 0.001).

Fig. 2

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Fig. 3.

Mean weekly volumes of vigorous physical activity in the study on the 10-minute bout requirement for physical activity guideline adherence, Germany, 2014–2019

Note: acceleration thresholds used were 410 milligravity for vigorous physical activity. All group differences and pairwise comparisons reached statistical significance (P-values: < 0.001).

Fig. 3

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Associated factors

The demographic and health-related characteristics differed across adherents, transitioners and non-adherents (Table 1). Analysis of variance with post-hoc pairwise comparisons yielded statistically significant results (all P-values: < 0.001) showing that adherents were younger, had the lowest BMI, and reported better overall health than the other two groups. The differences were most pronounced in the comparisons between adherents and non-adherents: On average, the adherents were 12.1 years (95% CI: 11.1–13.2) younger, their BMI was 5.5 kg/m2 (95% CI: 4.8–6.1) lower, and their self-reported overall health was 0.8 points (95% CI: 0.8–0.9) higher. Transitioners were located in between the adherents and the non-adherents for all three measures. Compared with adherents, transitioners were on average 2.1 years (95% CI: 1.9–2.4) older, had a BMI 1.9 kg/m2 (95% CI: 1.8–1.9) higher and reported overall health scores 0.2 points (95% CI: 0.2–0.2) lower. Compared with the non-adherents, transitioners were 10.0 years (95% CI: 9.0–11.0) younger, had a BMI that was 3.6 kg/m2 (95% CI: 2.9–4.3) lower, and their self-reported overall health was 0.6 points (95% CI: 0.5–0.7) higher.

The tests of equal proportions revealed statistically significant differences in the sex and education composition of the groups (Table 1). The post-hoc tests showed several statistically significant pairwise comparisons. There was a greater proportion of females among the transitioners than among the adherents and the non-adherents (all P-values: < 0.001). While, among the adherents and the transitioners, there was a higher proportion of participants with high versus medium education, among the non-adherents, there was a greater proportion of participants with medium versus high education (all P-values: < 0.001).

Discussion

Based on accelerometry data in a large population-based sample from Germany, our study found that removing the 10-minute bout requirement nearly tripled adherence to WHO aerobic physical activity guidelines. Further, there were systematic differences in demographic and health-related characteristics among participants meeting the guidelines when the 10-minute bout requirement was removed rather than applied.

The finding that guideline adherence was notably higher when using activity without the bout is consistent with previous studies examining the impact of the bout requirement on accelerometry-measured guideline adherence.11–13 The findings appear plausible, as the removal of the bout requirement considerably broadens the range of physical activity that counts towards guideline adherence. Physical activity that is now considered guideline-relevant includes brief forms of exercise and non-exercise activities. Brief forms of physical exercise, such as high-intensity interval training, have well documented health benefits, including reducing adiposity and increasing cardiorespiratory fitness.27,28 A growing body of evidence also indicates that short bursts of exercise and intermittent physical activity can promote health.29,30

It is important to acknowledge that removing the 10-minute bout requirement hampers the analysis of time trends in moderate and vigorous physical activity guideline adherence. Increases in adherence are partly due to changes in the guidelines rather than actual increases in physical activity. Therefore, accelerometry-based studies examining guideline adherence should report results with and without the bout to enable comparisons with previous studies.

Our study also identified clear differences in the demographic, health and physical activity characteristics among individuals meeting the moderate and vigorous physical activity guidelines. Overall, we observed a gradient: those meeting the guideline with the bout were the youngest, had the lowest BMI, reported the best health and accumulated the most moderate and vigorous physical activity. Differences by sex and education were also evident. Taken together, and contrary to a previous accelerometry study,11 we found that the revised guidelines activity without the bout seem to capture a different demographic than the guidelines with the bout, although it should be noted that almost all participants were classified as adhering to the guideline of activity without the bout. The small subset of the sample that still did not meet the broader guidelines may represent an important target for public health interventions. Interestingly, despite this small subset of participants not meeting the guideline without the bout, around 10% of the total sample (6224/61 704 with data on self-reported overall health) reported less-than-good or poor overall health. This finding suggests that the guideline without the bout targets might be so low that individuals with health impairments can still meet them.

Several lessons emerge from our study. First, the revisions to the 2020 WHO guidelines relied on self-reported physical activity data, which may not translate well to accelerometry-derived metrics due to discrepancies between measures.31 Future guidelines should incorporate more evidence from accelerometry-based assessments.10,32,33 Notably, almost all participants met the guideline when the 10-minute bout requirement was removed, raising questions about whether most individuals genuinely achieve sufficient moderate and vigorous physical activity levels or if the thresholds need to be reconsidered. Second, methodological choices in accelerometry research, such as epoch length, substantially influence activity estimates. Short epochs capture brief, sporadic movements prompting questions of whether higher activity thresholds may be necessary or the use of longer epochs for comparability with existing evidence. Harmonization efforts are needed to address processing differences while maintaining clarity and usability for the general population.

A strength of our study is the use of a large, population-based sample, aiding subgroup analysis and the use of accelerometry to overcome self-report bias. Accelerometry may be particularly valuable for assessing activity without the bout by helping to overcome individuals’ recall issues, such as forgetting brief and irregular bursts of activity. However, our approach also has limitations. The sampling strategy may have introduced bias due to differences between study centres and self-selection bias of participants willing to engage in the accelerometry module. Similarly, the baseline data of the NAKO study, collected between 2014 and 2019, may not fully reflect current activity patterns in Germany given the widespread use of device-based self-monitoring of activity. Further, accelerometry analysis involves certain limitations related to computational approaches. We required participants to have valid data for at least two weekdays and one weekend day to better represent weekly activity, considering the typical differences in activity patterns between weekdays and weekends.34,35 Our method averaged data across available days and extrapolated to a full week, implicitly assuming that the observed days are representative of the entire period. Further potential concerns pertain to differences in results due to analysis choices36,37 or the generalizability of thresholds derived from smaller studies.21 We have documented our analytical approach to facilitate future evaluations and replication. Our sensitivity analyses using several acceleration thresholds yielded consistent results, but limitations like reactivity bias, where participants may move more due to wearing the accelerometer, cannot be completely ruled out.

In conclusions, our study found that applying the revised guidelines to accelerometry data substantially changes estimates of population adherence and the characteristics of those classified as meeting the guidelines. The findings have important implications for the interpretation of time trends in physical activity guideline adherence, the identification of which population subgroups are meeting or are not meeting the guidelines, and methodological considerations for analysing accelerometry data for guideline development.

Acknowledgments

FH and KS contributed equally and share last authorship. JB is also affiliated with the Medical Faculty, Heidelberg University, Heidelberg, Germany. TK is also affiliated with the Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany, and the State Institute of Health, Bavarian Health and Food Safety Authority, Erlangen, Germany. UM is also affiliated with the Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. AP is also affiliated with the Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany. TP is also affiliated with the Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Biobank Technology Platform, Berlin, Germany, and the Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. MBS is also affiliated with the Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany. We thank all participants who took part in the NAKO study and the staff of this research initiative. We also thank Vincent T van Hees (Accelting, Almere, Kingdom of the Netherlands) and Hansjörg Baurecht (University of Regensburg, Regensburg, Germany).21

Funding:

This project was conducted with data (Application No. NAKO-899) from the German National Cohort (NAKO). The NAKO is funded by the Federal Ministry of Research, Technology and Space (BMFTR) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, 01ER1801A/B/C/D and 01ER2301A/B/C], Federal States of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association.

Competing interests:

None declared.

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