Metabolic Cost Clinical Trial
Official title:
What is the Metabolic Cost of Sitting, Standing, and Sit/Stand Transitions? A Randomized Controlled Trial
There is already a lot of scientific evidence supporting the benefits of public health
recommendations regarding physical activity (the accumulation of at least 150 minutes of at
least moderate intensity physical activity per week). However, these 30 daily minutes
represent only about 3% of the waking period. Recent data suggest that most of the
population spends on average 8-9 hours / day of sedentary behavior (SB). SB is characterized
by any activity with a metabolic cost (MC) below 1.5 METs, mainly actions in the sitting
position. In fact, there is evidence that the more time spent sitting higher the risk of
disease and mortality, with sitting directly associated with diseases such as type II
diabetes, cardiovascular diseases and even cancer. The average life expectancy may increase
by ~ 2 years if the investigators reduce sitting about 3h/ day. Additionally, how people
accumulate sitting time seems to be a major factor, with prolonged sitting associated with a
higher risk of disease. Short-term experimental studies indicate that sedentary lifestyles
affect energy balance enhancing weight gain. While there is some research regarding the MC
associated with "sitting" and "standing" behaviors, the results are contradictory. Besides
these conflicting results, the impact of transitions between these two types of behavior and
how these transitions can contribute to MC increase have never been investigated.
Our hypothesis is that, in both men and women, the simple replacement of sitting for
"standing" may not substantially increase MC, but instead, the largest contribution may
reside on the transitions between these two states of behavior. Therefore, the investigators
will perform a study with the following purposes:
Examine MC and HR associated with "sitting", "standing", and transitions between these two
types of behavior in adults of both gender, apparently healthy with variable body
composition profiles.
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.
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Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Crossover Assignment, Masking: Open Label, Primary Purpose: Basic Science