Metabolic Cost of Sitting, Standing, and Transitions

Introduction Regular physical activity (PA) positively influences most physiological processes in the human body. Inversely, sedentary behavior (SB)-too much sitting as distinct from too little physical activity-contributes adversely to cardio metabolic health outcomes and premature mortality [1-3]. Obesity results from a long-term excess of energy consumed vs. energy expended, a positive energy balance [4]. While overeating certainly contributes to a positive energy balance, the epidemic of obesity and related metabolic disorders is also driven by reductions in energy expended [5]. Modern human environments are vastly different from those of our ancestors. Technologic developments in transportation, communications, workplaces, and home entertainment confer a wealth of comfort, but increase the time spent in SB which represents costs to human health [6]. With increased use of computers, office workers may remain seated for long periods of time during which metabolic cost (MC) is minimal, making many worksites obesogenic environments [7]. Sitting time not only contributes to positive energy balance but is also an independent risk factor for excess adiposity [8,9] and obesity [10] even among people participating in high levels of moderate-to-vigorous physical activity (MVPA) [11,12]. Even without performing exercise people can have markedly variable low intensity physical activity (LIPA) levels, which in turn substantially varies PA energy expenditure (PAEE) by up to 2000 kcal/day [13]. Emerging evidence supports the feasibility of raising daily MC by replacing office work-related SB with LIPA via workstation alternatives to the traditional office chair and desktop computer-based combinations [14].

Regardless of total sitting time, evidence has been growing on the metabolic benefits of interrupting sitting time more often [15-17], with less focus on MC as a result from these breaks. There is some basic science on the differences of MC associated with "sitting" and "standing", however the results are contradictory [14,18]. Also, other alternatives have been investigated [14,19] and it seems that in terms of MC, sitting on a stability ball or using sit-stand/standing desks are comparable to the traditional seated condition EE (≅1.2 kcal min(-1)). The treadmill and pedal desks (active workstation alternatives) have been shown to offer the greatest promise in terms of EE (≅2-4 kcal min(-1)) [14]. Another strategy is to introduce walking breaks into prolonged sedentary time which according to a recent study [20] can yield an additional 24, 59 or 132 kcal per day, if they stood up and walked at a normal, self-selected pace for one, two or five minutes compared with sitting for the 8-hour working period. From this intervention, heart rate (HR) was also examined to assess differences between conditions with no significant between-condition differences for heart rate. Therefore, taking breaks from sitting is a potential outlet to prevent obesity and the rise of obesity but the real contribution of the simple action of standing up from a seated position and returning to the seated position (sit/stand transition) on MC and HR is yet to be investigated. To overcome these limitations, a randomized controlled trial will be conducted to examine the MC and HR associated with sitting, standing, and transitions between the previous behaviors in laboratory settings and using accurate methods (indirect calorimetry). By including this methodological approach we will be able to estimate the additional contribution of a "break" compared to just standing when accumulating sedentary time on MC and HR [18].

Hypothesis

1. The percent increase in MC and heart rate (HR) above resting associated with sitting, standing and sitting/stand transitions will be different, independently of gender, body composition, and age.
2. The MC, either per kg of body weight or per kg of fat-free mass, associated with sitting and standing will be similar but a higher cost is expected for the sitting-to-stand transitions, regardless of gender, age, and FFM.

Purposes

1. To determine the MC differences between sitting, standing and transitions conditions, adjusting for the effects of gender, body composition, and age.
2. To determine the HR differences between sitting, standing and transitions, adjusting for the effects of gender, body composition, and age.

Participants Sample power analysis For sample and power calculations we used the (GPower software, version 3.1.9.2) and consider MC as the continuous response variable. Based on a pilot study with a small sample size that aimed to test the differences in MC between the three conditions assessed by indirect calorimetry we have an effect size of approximately 0.385 by using repeated measures ANCOVA. Therefore we will need to study 50 participants to be able to reject the null hypothesis that the population means of the three experimental conditions are equal with probability (power) 0.8. The Type I error probability associated with this test of this null hypothesis is 0.05. Considering a 10% drop out rate may occur due to invalid data we will enroll 60 participants using a crossover design where participants will be randomly assigned to perform the 3 conditions in different orders.

Sample recruitment and selection A total of 60 healthy participants, both men and women will be selected. Participants will be recruited through advertisements placed nearby the institution and volunteer to participate in this study. If inclusion criteria are present participants will be randomly assigned to one of the conditions' orders and participate in the study.

Assessments Anthropometry Subjects will be weighed to the nearest 0.1kg wearing minimal clothes and without shoes and height will be measured to the nearest 0.1cm in a digital scale with integrated stadiometer (Seca, Hamburg, Germany) according to the standardized procedures described elsewhere [21]. BMI will be calculated using the formula [weight(Kg)/height2(m2)].

Body Composition To estimate total fat mass and FFM it will be used the dual energy X-ray absorptiometry (Hologic Explorer-W, Waltham, USA). A whole-body scan will be performed and the attenuation of X-rays pulsed between 70 and 140 kV synchronously with the line frequency for each pixel of the scanned image will be measured.

Resting Energy Expenditure (REE) The REE will be estimated using an open-circuit spirometry system (MedGraphics Corporation, Breezeex Software). Subjects will lye supine for ~45 minutes. The calorimeter device is attached to the mask and breath-by-breath VO2 and VCO2 are measured for a 30 minutes period. Data will be analyzed according to procedures described elsewhere [22].

MC measurement in each testing condition The MC will be estimated using an open-circuit spirometry system (MedGraphics Corporation, Breezeex Software). Each participant will have to complete 4 periods (conditions) of 10 minutes in which the calorimeter device is attached to the mask and breath-by-breath VO2 and VCO2 are measured for 40 minutes. The first condition is to remain seated in a chair, with hands placed on top of the thighs for 10 minutes, remaining motionless. The second condition is identical to the first but the participant is in an upright position (standing). Finally, in the third condition, the participant will perform one sitting-to-stand followed by a stand-to-sitting transition, every minute. The order of the three conditions will be randomly assigned. Heart rate will be measured continuously using a pulse oximeter that is attached to the MedGraphics system. This is a medical device that indirectly monitors the oxygen saturation of a patient's blood (as opposed to measuring oxygen saturation directly through a blood sample). Heart rate and oxygen consumption data will be analyzed minute-by-minute.

Statistical Analysis Statistical analysis will be performed using SPSS Statistics version 22.0, 2013 (SPSS Inc., Chicago, IL). Descriptive statistics (mean ± SD) will be calculated for all outcome measurements. Normality will be verified using the Kolmogorov-Smirnov test. A repeated measure ANCOVA with post hoc analysis will be used to compare the differences between conditions, adjusting for potential covariates (FFM and age) and considering the order of conditions' randomization as a between-subject effect. To test the sphericity or homogeneity of variances, the Mauchly's statistical test will be performed. Statistical significance will be set at (p<0.05)

Risk/benefit analysis The study first aim is to assess the MC associated with sitting, standing, and the sitting-to-stand transitions. By doing this we will be able to estimate the additional contribution of the actual transition to MC comparing to just sitting or standing for longer periods of time. Evidence found SB to have deleterious effects on general health status, specifically associated with a positive energy balance that lead to adiposity and weight gain thus increasing the risk of obesity and related metabolic risk factors. Therefore, participants will only benefit with this intervention [23]. No risk will be added for participating in the study as no risk will be associated with the intervention itself. Recognized and safe techniques will be used to assess MC and body composition.

Privacy and confidentiality of data This research will only take place if approved by the ethics Committee of the Faculdade de Motricidade Humana from Universidade de Lisboa and will be conducted in accordance with the declaration of Helsinki for human studies. All participants will be informed about the possible risks of the investigation before giving their written informed consent to participate. The collected data will be treated and analyzed but confidentiality and privacy will always be kept. Therefore, all the data is collected and treated without any personal identifier and we will never provide the code. The data is kept in excel and SPSS file in the faculty server connected to the Exercise and Health Laboratory. Later the documents received with the data of each participant will be destroyed after the database is constructed.

Participants' compensation and insurance There are no expenses and costs associated with the participation in this study therefore participants will need no insurance. However, as described in the informed consent, transportation to the laboratory will be supported by the participants.

Who to contact in case of emergence? Pedro Júdice.

Conflicts of interest The authors declare that there are no conflicts of interest within this study.