Pischon Lab

Diet and physical activity (PA) are among the main factors influencing metabolic dysfunction and chronic diseases, but their determinants are less clear. As part of the JPI HDHL Knowledge Hub Determinants of Diet and Physical Activity (DEDIPAC), we contributed to systematic reviews on determinants of PA (1-8). Surprisingly, although a number of potential determinants were identified, the evidence for a causal relationship was mostly low, warranting further research, particularly using objective measurements. One of the focusses of our research is, therefore, to examine determinants of physical activity and sedentary beheavior, particularly, by relying on 24-hour accelerometry data as more objective measurements of physical activity as compared to traditional assessments using questionnaires (9-13). As part of the Scientice on Stage project Teachers and Scientists and of the EU Open Science project SMOVE (“Science that makes me move”), we examined physcial activity, sedentary behavior, and potential determinants in school childeren in Berlin and Brandenburg (14).

Investigations into the role of diet, nutrition, and physical activity in metabolic dysfunction are particularly promising because results may point to opportunities for modification of adverse metabolic profiles by lifestyle changes. We are therefore interested to examine to what extent these factors may be related to metabolism and disease risk (15-19).

References

1) Aleksovska K, Puggina A, Giraldi L, et al. Biological determinants of physical activity across the life course: a "Determinants of Diet and Physical Activity" (DEDIPAC) umbrella systematic literature review. Sports medicine - open 2019;5:2.

2) Carlin A, Perchoux C, Puggina A, et al. A life course examination of the physical environmental determinants of physical activity behaviour: A "Determinants of Diet and Physical Activity" (DEDIPAC) umbrella systematic literature review. PLoS One 2017;12:e0182083.

3) Condello G, Ling FC, Bianco A, et al. Using concept mapping in the development of the EU-PAD framework (EUropean-Physical Activity Determinants across the life course): a DEDIPAC-study. BMC Public Health 2016;16:1145.

4) Condello G, Puggina A, Aleksovska K, et al. Behavioral determinants of physical activity across the life course: a "DEterminants of DIet and Physical ACtivity" (DEDIPAC) umbrella systematic literature review. Int J Behav Nutr Phys Act 2017;14:58.

5) Cortis C, Puggina A, Pesce C, et al. Psychological determinants of physical activity across the life course: A "DEterminants of DIet and Physical ACtivity" (DEDIPAC) umbrella systematic literature review. PLoS One 2017;12:e0182709.

6) Jaeschke L, Steinbrecher A, Luzak A, et al. Socio-cultural determinants of physical activity across the life course: a 'Determinants of Diet and Physical Activity' (DEDIPAC) umbrella systematic literature review. Int J Behav Nutr Phys Act 2017;14:173.

7) O'Donoghue G, Kennedy A, Puggina A, et al. Socio-economic determinants of physical activity across the life course: A "DEterminants of DIet and Physical ACtivity" (DEDIPAC) umbrella literature review. PLoS One 2018;13:e0190737.

8) Puggina A, Aleksovska K, Buck C, et al. Policy determinants of physical activity across the life course: a 'DEDIPAC' umbrella systematic literature review. European journal of public health 2018;28:105-18.

9) Jaeschke L, Luzak A, Steinbrecher A, et al. 24 h-accelerometry in epidemiological studies: automated detection of non-wear time in comparison to diary information. Sci Rep 2017;7:2227.

10) Jaeschke L, Steinbrecher A, Boeing H, et al. Factors associated with habitual time spent in different physical activity intensities using multiday accelerometry. Sci Rep 2020;10:774.

11) Jaeschke L, Steinbrecher A, Jeran S, Konigorski S, Pischon T. Variability and reliability study of overall physical activity and activity intensity levels using 24 h-accelerometry-assessed data. BMC Public Health 2018;18:530.

12) Jeran S, Steinbrecher A, Pischon T. Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review. Int J Obes (Lond) 2016;40:1187-97.

13) Jeran S, Steinbrecher A, Haas V, et al. Prediction of activity-related energy expenditure under free-living conditions using accelerometer-derived physical activity. Sci Rep 2022;12:16578.

14) Lubasch JS, Thumann B, Bucksch J, et al. School- and Leisure Time Factors Are Associated With Sitting Time of German and Irish Children and Adolescents During School: Results of a DEDIPAC Feasibility Study. Front Sports Act Living 2020;2:93.

15) Nimptsch K, Lee DH, Zhang X, et al. Dairy intake during adolescence and risk of colorectal adenoma later in life. Br J Cancer 2021;124:1160-8.

16) Joh HK, Lee DH, Hur J, et al. Simple sugar and sugar-sweetened beverage intake during adolescence and risk of colorectal cancer precursors: Adolescent sugar intake and colorectal polyp. Gastroenterology 2021.

17) Hur J, Otegbeye E, Joh HK, et al. Sugar-sweetened beverage intake in adulthood and adolescence and risk of early-onset colorectal cancer among women. Gut 2021;70:2330-6.

18) Pinart M, Jeran S, Boeing H, et al. Dietary Macronutrient Composition in Relation to Circulating HDL and Non-HDL Cholesterol: A Federated Individual-Level Analysis of Cross-Sectional Data from Adolescents and Adults in 8 European Studies. J Nutr 2021;151:2317-29.

19) Romo Ventura E, Konigorski S, Rohrmann S, et al. Association of dietary intake of milk and dairy products with blood concentrations of insulin-like growth factor 1 (IGF-1) in Bavarian adults. Eur J Nutr 2020;59:1413-20.