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ONLINE DATA SUPPLEMENT
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ASSOCIATION BETWEEN HABITUAL PHYSICAL ACTIVITY AND BROWN ADIPOSE
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TISSUE ACTIVITY IN INDIVIDUALS UNDERGOING PET-CT SCAN
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Petros C. Dinas,1 Alexandra Nikaki,2 Athanasios Z. Jamurtas,3 Vassilios Prassopoulos,2 Roxani
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Efthymiadou,2 Yiannis Koutedakis,3,4 Panagiotis Georgoulias,5 and Andreas D. Flouris1
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Department, “DTCA HYGEIA” Hospital, Athens, Greece.
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Thessaly, Larissa, Greece.
FAME Laboratory, Department of Exercise Science, University of Thessaly, Trikala, Greece.
Nuclear Medicine Department and Positron Emission Tomography/Computed Tomography
School of Physical Education and Exercise Science, University of Thessaly, Greece.
Faculty of Education, Health, and Wellbeing, University of Wolverhampton, UK.
Nuclear Medicine Laboratory, Faculty of Medicine, School of Health Sciences, University of
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ADDRESS FOR CORRESPONDENCE:
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Andreas D. Flouris
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FAME Laboratory
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School of Physical Education and Exercise Science
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University of Thessaly
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Karies, Trikala, 42100, Greece.
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email: andreasflouris@gmail.com
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Tel: +302431500601, Fax: +302431063191
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PURPOSE
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Our aim in this prospective study was to investigate whether habitual (i.e., usual weekly
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participation) physical activity is linked with BAT activity and mass in humans, in a group of
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patients undergoing
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tomography (PET/CT) scanning. Our statistical analysis used non-parametric tests throughout.
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We investigated the associations between physical activity (total METs-minute/week), BMI, BAT
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mass, BAT activity, and age using Kendall’s tau-b correlation coefficient. We used Kruskal-
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Wallis analysis of variance with post hoc Mann-Whitney U tests to assess differences in BAT
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mass and activity due to variation in: (i) physical activity levels (i.e., low/moderate/high) and (ii)
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BMI categories (i.e., normal/overweight/obese). We also used Mann-Whitney U tests to assess
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sex differences. To confirm the validity of our results, all the data analyses were repeated after
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removal of all observations that are at a distance of more than two standard deviations from the
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mean of the distribution, as suggested previously (1, 2). The variables used to detect outliers
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were physical activity (in METs-minute/week) and BAT activity (normalized by LBM). Based on
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the adopted criteria, two outliers were identified and were removed from subsequent analyses
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(Supplementary Figure 1). The results of this analysis appear below confirming that the outliers
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did not influence our findings. We also present scatterplots illustrating the lack of association
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between environmental temperature, BAT activity, and BAT mass (Supplementary Figure 5).
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The results of this analysis are described in the main part of the paper. All analyses were
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conducted with PASW Statistics (version 18; SPSS Inc., Chicago, IL, USA) and a p≤0.05 level
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of significance.
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F-fluorodeoxyglucose positron emission tomography / computed
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RESULTS
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We detected a significant association between total energy expenditure in METs-minute/week
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and BAT activity normalized by lean body mass (LBM) [(τ=0.33, p=0.01) (Supplementary Figure
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2)]. We also found significant inverse correlations between body mass index (BMI) and brown
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adipose tissue (BAT) activity normalized by body weight (BW) [(τ=-0.30, p=0.007)
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(Supplementary Figure 3A)], body surface area (BSA) [(τ=-0.31, p=0.005) (Supplementary
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Figure 3B)], and LBM [(τ=-0.45, p=0.001) (Supplementary Figure 3C)]. No significant
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associations were observed for BAT mass (p>0.05). Interestingly, age was also inversely
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correlated with BAT activity normalized by LBM (τ=-0.26, p=0.02).
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Results from the Kruskal-Wallis analysis of variance and post hoc Mann-Whitney U tests
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appear in Supplementary Figure 4. BAT activity (BW normalization: p=0.04; BSA normalization:
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p=0.03; LBM normalization: p=0.04) varied between low/moderate/high levels of habitual
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physical activity participation. Post hoc tests showed that BAT activity was higher in participants
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with high levels of habitual physical activity compared to those with moderate (when normalized
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by BSA) and low levels (when normalized by BW, BSA, and LBM) [(p<0.05) (Supplementary
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Figure 4A)]. In contrast, we did not observe any statistically significant effects for BAT mass
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(p>0.05). The BAT activity normalized by BW (p=0.02), BSA (p=0.05), and LBM (p=0.006) was
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different across the BMI categories in both sexes, with normal BMI participants showing higher
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BAT activity than their overweight and obese counterparts [(p<0.05) (Supplementary Figure
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4B)]. Interestingly, we also found that BAT activity normalized by BW (p=0.04), BSA (p=0.05),
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and LBM (p=0.01) was greater in women than in men (Supplementary Figure 4C).
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REFERENCES
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1.
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65.
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2.
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Nov;114(3):510-32. PubMed PMID: 8272468. Epub 1993/11/01. eng.
Van Zandt T. How to fit a response time distribution. Psychon Bull Rev. 2000;7(3):424-
Ratcliff R. Methods for dealing with reaction time outliers. Psychological bulletin. 1993
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LIST OF SUPPLEMENTARY FIGURES
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Supplementary Figure 1. A scatter diagram of the physical activity (in METs-
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minute/week) and BAT activity (normalized by LBM) that were used to detect outliers.
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Based on the adopted criteria, two outliers were identified and were removed from
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subsequent analyses.
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Supplementary Figure 2. Correlation between habitual physical activity (METs-
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minute/week) and brown adipose tissue activity normalized by lean body mass. Note:
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BAT = brown adipose tissue; LBM = lean body mass.
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Supplementary Figure 3. Correlations between body mass index and brown adipose
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tissue activity normalized by body weight (A), body surface area (B) and lean body mass
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(C). Note: BAT = brown adipose tissue; BW = body weight; BMI = body mass index; BSA
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= body surface area; LBM = lean body mass.
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Supplementary Figure 4. Results from post hoc Mann-Whitney U tests for brown
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adipose tissue activity normalized by body weight, body surface area and lean body
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mass with respect to habitual physical activity (A), body mass index categories (B) and
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sex (C). Note: BMI = body mass index; BAT = brown adipose tissue; BW = body weight;
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BSA = body surface area; LBM = lean body mass.
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* Significant differences between low and high levels of habitual physical activity with
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respect to BAT activity normalized by BW (P=0.005), BSA (P=0.007) and LBM (P=0.01).
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† Significant differences between moderate and high levels of habitual physical activity
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with respect to BAT activity normalized by BSA (P=0.05).
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ǂ Significant differences between normal and overweight individuals with respect to BAT
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activity normalized by BW (P=0.03) and LBM (P=0.01).
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§ Significant differences between normal and obese individuals with respect to BAT
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activity normalized by BW (P=0.02), BSA (P=0.02) and LBM (P=0.02).
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¶ Significant differences between men and women with respect to BAT activity
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normalized by BW (P=0.04), BSA (P=0.05) and LBM (P=0.01).
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Supplementary Figure 5. Scatterplots illustrating the lack of association between
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environmental temperature and either BAT activity (top graph), and BAT mass (bottom
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graph). Kendall’s tau-b correlation coefficient did not detect any statistically meaningful
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associations between environmental temperature and BAT activity [normalized by BW
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(squares; τ=-0.14, p=0.212), BSA (rhombs; τ=-0.11, p=0.338), and LBM (triangles; τ=-
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0.06, p=0.599). Similar tests demonstrated no statistically significant correlations
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between environmental temperature and BAT mass [normalized by BW (squares; τ=-
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0.12, p=0.277), BSA (rhombs; τ=-0.10, p=0.350), and LBM (triangles; τ=-0.11, p=0.344).
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