Körperliche Aktivität und das Risiko für chronische Erkrankungen : Entwicklung und Evaluierung eines Indexes zur Messung körperlicher Aktivität und Baseline-datenkalibrierung in EPIC-Deutschland

Körperliche Aktivität (KA) ist ein Lifestyle Faktor, der vor chronischen Erkrankungen zu schützen scheint. In der European Prospective Investigation into Cancer and Nutrition (EPIC)-Studie wurden zwei Fragebögen verwendet, mit denen anhand des Cambridge Indexes und des Total Physical Activity Indexes die KA der Teilnehmer kategorisiert werden kann. Die präzise Messung der PA ist essentiell, um die wahre Assoziationsstärke zwischen KA und chronischen Erkrankungen zu schätzen. Objektive Messmethoden, die heutzutage zum Einsatz kommen, vereinfachen die schwierige Aufgabe der präzisen Messung der KA. Basierend darauf, wurden die folgenden Ziele in dieser Doktorarbeit verfolgt: die Entwicklung und Evaluierung eines validen KA Indexes– den Improved Physical Activity Index (IPAI), welcher in der Lage sein soll, die KA der Personen zu kategorisieren aber auch eine kontinuierliche Messung der KA zu liefern. Diese soll das Bewegungsausmaß widerspiegeln. Des Weiteren wurde eine Kalibrierung der Basis Fragebogen-Daten zur PA und die Schätzung des Zusammenhangs zwischen nicht-kalibrierter und kalibrierter KA und chronischen Erkrankungen, Typ 2 Diabetes, Myokardinfarkt, Schlaganfall und Krebs, angestrebt. Diese Ziele wurden in den deutschen EPIC-Zentren Potsdam und Heidelberg verfolgt. In einer Substudie wurden 1615 Teilnehmer rekrutiert. Diese Substudie beinhaltete ein breites Fragenspektrum zur üblichen KA, sowie eine objektive 7-Tage Messung der KA mittels eines Herzfrequenz und Bewegungsmessers - Actiheart. Die Baseline Fragebogenangaben zur KA wurden, mittels der aus der Substudie gewonnenen Daten, kalibriert. Das Risiko für chronische Erkrankungen wurde in der Gesamtkohorte mit Hilfe von proportionaler Hazards-Regression nach Cox berechnet. Der IPAI besteht aus den folgenden Aktivitätsvariablen: Art der Berufstätigkeit, Fahrrad fahren (Stunden/Woche), dem Sporthäufigkeitsscore, sowie Fernsehscore und Computernutzung (Stunden/Wochenende ab 18Uhr). Korrelationen zwischen dem IPAI und objektiv gemessener KA betrugen r=0.39-0.44 für Aktivitätscounts und r=0.32-0.40 für Aktivitätsenergieausgabe (PAEE). Der Cambridge Index und der Total Physical Activity Index waren schwächer mit objektiv gemessener KA korreliert als der IPAI. In nicht-berufstätigen Teilnehmern war der IPAI auch stärker mit objektiv gemessener KA korreliert, als die bisher genutzten Indizes. Stückweise Regression wurde zur Kalibrierung der Baseleine KA Daten angewandt. In den kalibrierten Daten waren die Hazardraten (HR (95% Konfidenzeinterval)) zwischen der höchsten KA Kategorie, im Vergleich zur niedrigsten KA Kategorie, niedriger als in den nicht kalibrierten Daten für die meisten chronischen Erkrankungen HR=0.40(0.35-0.46), Typ 2 Diabetes HR=0.08(0.06-0.10), Myokardinfarkt HR=0.40(0.24-0.67) und Schlaganfall HR=0.54(0.33-0.87). Die nicht-kalibrierten HRs betragen, in der gleichen Reihenfolge: HR=0.72(0.66-0.80), HR=0.57(0.48-0.67), HR=0.62(0.44-0.88), und HR=0.86(0.62-1.19), Es wurden keine Zusammenhänge zwischen KA und Krebs gefunden, auch nicht nach Ausschluss von Erkrankungen, die in den ersten 3 Jahren der Nachbeobachtung aufgetreten sind. Zusammenfassend zeigen die vorliegenden Ergebnisse, dass der IPAI ein valides Instrument zur populationsbezogenen subjektiven Messung der üblichen KA/Bewegung (sowohl kontinuierlich als auch in Kategorien) ist und in Studien zu diesem Zweck angewandt werden kann. Die Datenkalibrierung liefert eine präzisere Schätzung des Zusammenhangs zwischen KA und chronischen Erkrankungen. Die präventiven Effekte von KA auf chronische Erkrankungen, Typ 2 Diabetes, Myokardinfarkt und Schlaganfall werden in Studien mit Fragebogenmessung der KA unterschätzt. Interventionen im Bereich Public Health, vor allem in der Gruppe von Typ 2 Diabetes Gefährdeten, sollten einen stärkeren Fokus auf KA legen.Physical activity (PA) is a lifestyle factor that has been shown to prevent chronic diseases. The accurate PA measurement is essential to estimate the true magnitude of the relationship between PA and disease risk. Nowadays, objective measurement methods for PA have been developed and improve the challenging task of measuring the individuals’ PA level. Therefore, the aims of this thesis were firstly, the development and evaluation of a valid physical activity index – the Improved Physical Activity Index (IPAI), which will be able to categorize people into activity categories but may also be used as a continuous measure that reflects one’s activity amount (movement). Secondly, the calibration of the available baseline PA questionnaire measurement and finally, the estimation of the associations between calibrated and non-calibrated baseline PA data and risk of overall chronic diseases, type 2 diabetes, myocardial infarction, stroke and overall cancer. These objectives were accomplished by applying an extensive physical activity questionnaire and a 7-day heart rate and acceleration sensor PA measurement to a sub-sample (n=1,615) of older adults from the European Prospective Investigation into Cancer and Nutrition (EPIC-Germany) study. Baseline self-reported PA was calibrated using statistical models based on the objective PA measurement in the sub-sample. The risk of chronic diseases was estimated using Cox proportional hazards regression in the whole EPIC-Germany cohort. The IPAI consists of items covering five areas including PA at work, sport, cycling, television viewing, and computer use. The correlations between the IPAI and accelerometer counts in the training and validation sample ranged from r=0.39 to 0.44 and with physical activity energy expenditure from r=0.32 to 0.40 and were higher than between the Cambridge Index or the Total Physical Activity Index with the objective measures. In non-working participants the IPAI also showed higher correlations than the established indices. For the baseline PA data calibration segmented regression analysis has been chosen. The hazard rates (HR (95% confidence intervals)) for the risk reduction in the highest calibrated PA category compared to the lowest for overall chronic diseases HR=0.40(0.35-0.46), type 2 diabetes HR=0.08(0.06-0.10), myocardial infarction HR=0.40(0.24-0.67) and stroke HR=0.54(0.33-0.87) were lower than the non-calibrated results HR=0.72(0.66-0.80), HR=0.57(0.48-0.67), HR=0.62(0.44-0.88), and HR=0.86(0.62-1.19), respectively. There were no associations between the calibrated PA and risk of cancer, even after excluding the first 3 years of follow up. In conclusion, a valid PA index which is able to express PA on a continuous scale as well as to categorize participants was developed. In populations with increasing rates of non-working people the performance of the IPAI is better than the established indices used in EPIC. The PA data calibration provides more precise risk estimates. The preventive effects of PA on overall chronic disease risk, type 2 diabetes, myocardial infarction and stroke, has been shown to be underestimated. Public health interventions should persistently focus on PA, especially in type 2 diabetes jeopardized individuals

Physical Activity, Bone Health, and Obesity in Peri-/Pre- and Postmenopausal Women: Results from the EPIC-Potsdam Study

Physical activity (PA) is suggested to increase the peak bone mass and to minimize age-related bone loss, and thereby to reduce the risk of osteoporosis. However, the relation between PA and bone health considering the obesity status is unclear so far. The present study examines the association between PA levels and calcaneal broadband ultrasound attenuation (BUA), particularly under consideration of obesity. Data from a population-based sample of 6776 German women from the EPIC-Potsdam cohort were analyzed. Calibrated PA data were used. Statistical analyses were stratified by menopausal and obesity status. Multiple linear regression was used to model the relationship between PA and BUA levels after adjustment for age, body mass index (BMI), smoking status, education, alcohol and calcium intake, and hormone use. Peri-/premenopausal had higher BUA levels (112.39 ± 10.05 dB/MHz) compared to postmenopausal women (106.44 ± 9.95 dB/MHz). In both groups, BUA levels were higher in the fourth compared to the lowest quartile of PA (p for trend < 0.05). In women with BMI < 30, but not BMI ≥ 30 kg/m(2), PA remained positively associated with BUA levels (p for interaction = 0.03). However, when waist circumference higher than 88 cm or body fat percentage (BF%) measures above the median were used to define obesity, a significant positive relationship was also observed in women with BMI < 30 kg/m(2) but with higher waist circumference or BF%. In conclusion, our results strengthen the hypothesis that PA has a positive influence on BUA levels, though dependent on weight

The improved physical activity index for measuring physical activity in EPIC Germany.

In the European Investigation into Cancer and Nutrition study (EPIC), physical activity (PA) has been indexed as a cross-tabulation between PA at work and recreational activity. As the proportion of non-working participants increases, other categorization strategies are needed. Therefore, our aim was to develop a valid PA index for this population, which will also be able to express PA continuously. In the German EPIC centers Potsdam and Heidelberg, a clustered sample of 3,766 participants was re-invited to the study center. 1,615 participants agreed to participate and 1,344 participants were finally included in this study. PA was measured by questionnaires on defined activities and a 7-day combined heart rate and acceleration sensor. In a training sample of 433 participants, the Improved Physical Activity Index (IPAI) was developed. Its performance was evaluated in a validation sample of 911 participants and compared with the Cambridge Index and the Total PA Index. The IPAI consists of items covering five areas including PA at work, sport, cycling, television viewing, and computer use. The correlations of the IPAI with accelerometer counts in the training and validation sample ranged r = 0.40-0.43 and with physical activity energy expenditure (PAEE) r = 0.33-0.40 and were higher than for the Cambridge Index and the Total PA Index previously applied in EPIC. In non-working participants the IPAI showed higher correlations than the Cambridge Index and the Total PA Index, with r = 0.34 for accelerometer counts and r = 0.29 for PAEE. In conclusion, we developed a valid physical activity index which is able to express PA continuously as well as to categorize participants according to their PA level. In populations with increasing rates of non-working people the performance of the IPAI is better than the established indices used in EPIC

Studies on the effects of public policy on formation of large-scale landscapes : Focusing on Sapporo and Obihiro regions in Hokkaido [an abstract of dissertation and a summary of dissertation review]

<p>Spearman correlation coefficients and 95% confidence intervals (95% CI) between accelerometer counts, Physical Activity Energy Expenditure (PAEE), Physical Activity Level (PAL), Moderate and Vigorous Physical Activity (MVPA), sedentary time, the Improved Physical Activity Index (IPAI) (continuous and in categories), the Cambridge Index, and the Total Physical Activity Index in 911 participants of the EPIC Germany study validation sample.</p

Spearman correlation coefficients and 95% confidence intervals (95% CI) between accelerometer counts, Physical Activity Energy Expenditure (PAEE), Physical Activity Level (PAL), Moderate and Vigorous Physical Activity (MVPA), sedentary time, the Improved Physical Activity Index (IPAI) (continuous and in categories), the Cambridge Index, and the Total Physical Activity Index in 699 non-working participants of the EPIC Germany sub-study.

<p>Spearman correlation coefficients and 95% confidence intervals (95% CI) between accelerometer counts, Physical Activity Energy Expenditure (PAEE), Physical Activity Level (PAL), Moderate and Vigorous Physical Activity (MVPA), sedentary time, the Improved Physical Activity Index (IPAI) (continuous and in categories), the Cambridge Index, and the Total Physical Activity Index in 699 non-working participants of the EPIC Germany sub-study.</p

Characteristics for the Improved Physical Activity Index (IPAI) variables sport score, cycling (h/week), type of work, television viewing score, and weekend evening computer use in 433 participants of the EPIC Germany study training sample.

<p>Characteristics for the Improved Physical Activity Index (IPAI) variables sport score, cycling (h/week), type of work, television viewing score, and weekend evening computer use in 433 participants of the EPIC Germany study training sample.</p

Study population characteristics.

<p>Study population characteristics.</p

Cross-Sectional Associations of Objectively Measured Physical Activity, Cardiorespiratory Fitness and Anthropometry in European Adults

Objective: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. Methods: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s(2)/d), moderate and vigorous physical activity (MVPA) (% time/d), sedentary time (% time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. Results: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. Conclusion: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity

Cross-Sectional Associations of Objectively Measured Physical Activity, Cardiorespiratory Fitness and Anthropometry in European Adults

Objective: To quantify the independent associations between objectively measured physical activity (PA), cardiorespiratory fitness (CRF), and anthropometry in European men and women. Methods: 2,056 volunteers from 12 centers across Europe were fitted with a heart rate and movement sensor at 2 visits 4 months apart for a total of 8 days. CRF (ml/kg/min) was estimated from an 8 minute ramped step test. A cross-sectional analysis of the independent associations between objectively measured PA (m/s(2)/d), moderate and vigorous physical activity (MVPA) (% time/d), sedentary time (% time/d), CRF, and anthropometry using sex stratified multiple linear regression was performed. Results: In mutually adjusted models, CRF, PA, and MVPA were inversely associated with all anthropometric markers in women. In men, CRF, PA, and MVPA were inversely associated with BMI, whereas only CRF was significantly associated with the other anthropometric markers. Sedentary time was positively associated with all anthropometric markers, however, after adjustment for CRF significant in women only. Conclusion: CRF, PA, MVPA, and sedentary time are differently associated with anthropometric markers in men and women. CRF appears to attenuate associations between PA, MVPA, and sedentary time. These observations may have implications for prevention of obesity