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Abstract

Background
Multiples of resting metabolic rate (RMR) are often used to classify physical activity intensity, a concept known as the Metabolic Equivalent of Task (MET). However, the METs metrics may misclassify physical activity intensity in older adults because of age related changes in RMR and maximal aerobic capacity (V̇O2max). This study aimed to 1) compare classifications of activity intensity by estimated (METsestimated) and measured (METsmeasured) METs and 2) compare physical activity classified by absolute (METsmeasured) versus relative intensity (%V̇O2Reserve) in older adults.


Methods
Ninety-eight adults aged 75-90 years participated in the study. RMR and V̇O2 during sitting, standing, daily activities and 6-minute-walking-test were measured. V̇O2Reserve was defined as the difference between V̇O2max and RMR. Moderate and vigorous intensity was classified as 3 and 6 METs and 40% and 60% of V̇O2Reserve, respectively. Paired t-tests and a confusion matrix were used to investigate aim 1 and 2, respectively.


Results
METsmeasured was 24% lower than the standard 1 MET of 3.5 ml O2·min-1·kg-1. METsestimated underestimated the intensity during daily and walking activities when compared to METsmeasured. Nevertheless, when comparing METsmeasured to percentages of V̇O2Reserve, a mismatch was shown for moderate intensity in 47-67% of the participants during daily activities, and 21% of the participants during self-selected gait speed.


Conclusion
Applying METsestimated for older adults leads to potential underestimation of physical activity intensity, suggesting that current classification metrics should be revised for older adults. V̇O2Reserve is a candidate metric for establishing precise physical activity intensity cut-points for older adults.

Article in press ; Dynamic sitting, such as fidgeting and desk work, might be associated with health, but remains difficult toidentify out of accelerometry data. We examined, in a laboratory study, whether dynamic sitting can beidentified out of triaxial activity counts. Among 18 participants (56% men, 27.3 ± 6.5 years), up to 236 countsper minute were recorded in the anteroposterior and mediolateral axes during dynamic sitting using a hip-worn accelerometer. Subsequently, we examined in 621 participants (38% men, 80.0 ± 4.7 years) from theAGES-Reykjavik Study whether dynamic sitting was associated with cardio-metabolic health. Compared toparticipants who recorded the fewest dynamic sitting minutes (Q1), those with more dynamic sittingminutes had a lower BMI (Q2=−1.39 (95%CI =−2.33;–0.46); Q3=−1.87 (−2.82;–0.92); Q4=−3.38 (−4.32;–2.45)), a smaller waist circumference (Q2=−2.95 (−5.44;–0.46); Q3=−3.47 (−6.01;–0.93); Q4=−8.21 (−10.72;–5.71)), and a lower odds for the metabolic syndrome (Q2= 0.74 [0.45;1.20] Q3= 0.58 [0.36;0.95]; Q4=0.36[0.22;0.59]). Our findings suggest that dynamic sitting might be identified using accelerometry and that thisbehaviour was associated with health. This might be important given the large amounts of time peoplespend sitting. Future studies with a focus on validation, causation and physiological pathways are needed tofurther examine the possible relevance of dynamic sitting. ; This work was supported by the National Institute on Aging;National Institutes of Health [N01-AG-12100];FP7 People: Marie-Curie Actions (FP7- PEOPLE-2011-CIG) [PCIG09-GA-2011-293621];Icelandic Heart Association; Icelandic Parliament. ; Peer reviewed

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Download ; Dynamic sitting, such as fidgeting and desk work, might be associated with health, but remains difficult to identify out of accelerometry data. We examined, in a laboratory study, whether dynamic sitting can be identified out of triaxial activity counts. Among 18 participants (56% men, 27.3 ± 6.5 years), up to 236 counts per minute were recorded in the anteroposterior and mediolateral axes during dynamic sitting using a hip-worn accelerometer. Subsequently, we examined in 621 participants (38% men, 80.0 ± 4.7 years) from the AGES-Reykjavik Study whether dynamic sitting was associated with cardio-metabolic health. Compared to participants who recorded the fewest dynamic sitting minutes (Q1), those with more dynamic sitting minutes had a lower BMI (Q2 = -1.39 (95%CI = -2.33;-0.46); Q3 = -1.87 (-2.82;-0.92); Q4 = -3.38 (-4.32;-2.45)), a smaller waist circumference (Q2 = -2.95 (-5.44;-0.46); Q3 = -3.47 (-6.01;-0.93); Q4 = -8.21 (-10.72;-5.71)), and a lower odds for the metabolic syndrome (Q2 = 0.74 [0.45;1.20] Q3 = 0.58 [0.36;0.95]; Q4 = 0.36 [0.22;0.59]). Our findings suggest that dynamic sitting might be identified using accelerometry and that this behaviour was associated with health. This might be important given the large amounts of time people spend sitting. Future studies with a focus on validation, causation and physiological pathways are needed to further examine the possible relevance of dynamic sitting. ; National Institute on Aging National Institutes of Health FP7 People: Marie-Curie Actions (FP7-PEOPLE-2011-CIG) Icelandic Heart Association Icelandic Parliament

Introduction: Sedentary time has been associated with detrimental health effects, so in some countries, guidelines to reduce sedentary time have been developed. As reducing sedentary time inevitably results in more nonsedentary time, effects of this reduction may depend on the activity with which it is replaced. Purpose: This study aimed to examine associations of theoretical reallocations of sedentary time to standing or stepping with cardiometabolic outcomes and type 2 diabetes. Methods: We included 2213 participants (51% men, mean +/- SD age = 60.0 +/- 8.1 yr) of the Maastricht Study who were asked to wear an accelerometer 24 h.d(-1) for a week. We calculated daily sedentary, standing, and stepping time. An isotemporal substitution modeling approach was applied to examine effects on waist circumference; body mass index; cholesterol, triacylglycerol, glucose, and insulin levels; metabolic syndrome; and type 2 diabetes. Results: Replacement of sedentary time (30 min.d(-1)) with stepping was associated with lower odds for metabolic syndrome (odds ratio [OR] = 0.72, 95% confidence interval [CI] = 0.66-0.78) and type 2 diabetes (OR = 0.79, 95% CI = 0.72-0.87), more favorable waist circumference (B = -1.42, 95% CI = -1.78 to -1.06), and body mass index (B = -0.48, 95% CI = -0.62 to -0.35) and improved cholesterol, triacylglycerol, glucose, and insulin levels. Replacing sedentary time with standing was associated with lower odds for metabolic syndrome and type 2 diabetes and favorable outcomes in waist circumference, cholesterol, triacylglycerol, and insulin levels. Conclusion: Theoretical replacements of sedentary time with nonsedentary time (both standing and stepping) were associated with lower odds for metabolic syndrome, type 2 diabetes, and beneficial metabolic outcomes. These results could be important for the general population, including those who cannot meet physical activity guidelines. Consideration should be given to developing recommendations for daily reallocating sedentary time. ; This study was supported by the European Regional Development Fund via OP-Zuid, the Province of Limburg, the Dutch Ministry of Economic Affairs (grant no. 31O.041), Stichting De Weijerhorst (Maastricht, the Netherlands), the Pearl String Initiative Diabetes (Amsterdam, the Netherlands), the Cardiovascular Center (CVC, Maastricht, the Netherlands), CARIM School for Cardiovascular Diseases (Maastricht, the Netherlands), CAPHRI School for Public Health and Primary Care (Maastricht, the Netherlands), NUTRIM School for Nutrition and Translational Research in Metabolism (Maastricht, the Netherlands), Stichting Annadal (Maastricht, the Netherlands), and Health Foundation Limburg (Maastricht, the Netherlands) and by unrestricted grants from Janssen-Cilag B.V. (Tilburg, the Netherlands), Novo Nordisk Farma B.V. (Alphen aan den Rijn, the Netherlands), and Sanofi-Aventis Netherlands B.V. (Gouda, the Netherlands). A Koster has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2011-CIG) under grant agreement PCIG09-GA-2011-293621.