Clinical trial NCT02377037: Metabolic Cost of Sitting, Standing, and Transitions
Official title: What is the Metabolic Cost of Sitting, Standing, and Sit/Stand Transitions? A Randomized Controlled Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Metabolic Cost
Keywords: Sitting
Standing
Transitions
Lead sponsor: Technical University of Lisbon
Sponsor class: OTHER
First posted: 2015-03-03
Enrollment: 50
Sex: ALL
Minimum age (years): 18
Maximum age (years): 64
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Primary purpose: BASIC_SCIENCE

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* Men and women aged 18-64 years and without major metabolic, pulmonary, and cardiac disorders and general health guaranteed.
* Physically independent and able to perform all the conditions without limitations.

Exclusion Criteria:

* Pregnancy or engagement in any weight loss program that may affect energy balance.

Primary outcomes:
measure: Metabolic cost
timeFrame: 60 minutes (30 from metabolic rest and 30 from conditions)
Secondary outcomes:
measure: Heart rate
timeFrame: 60 minutes (30 from metabolic rest and 30 from conditions)
Other outcomes:
Locations:
city: Cruz Quebrada
country: Portugal
facility: Exercise and Health Laboratory, Faculdade de Motricidade Humana, Universidade de Lisboa
state: Lisboa
Study officials:
affiliation: Laboratory of Exercise and Health, Faculadde Motricidade Humana, Universidade de Lisboa
name: Analiza M Silva, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Dempsey PC, Owen N, Biddle SJ, Dunstan DW. Managing sedentary behavior to reduce the risk of diabetes and cardiovascular disease. Curr Diab Rep. 2014;14(9):522. doi: 10.1007/s11892-014-0522-0.
citation: Hu FB, Li TY, Colditz GA, Willett WC, Manson JE. Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. JAMA. 2003 Apr 9;289(14):1785-91. doi: 10.1001/jama.289.14.1785.
citation: Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, Khunti K, Yates T, Biddle SJ. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia. 2012 Nov;55(11):2895-905. doi: 10.1007/s00125-012-2677-z. Epub 2012 Aug 14.
citation: Church TS, Thomas DM, Tudor-Locke C, Katzmarzyk PT, Earnest CP, Rodarte RQ, Martin CK, Blair SN, Bouchard C. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS One. 2011;6(5):e19657. doi: 10.1371/journal.pone.0019657. Epub 2011 May 25.
citation: Ford ES, Li C, Zhao G, Pearson WS, Tsai J, Churilla JR. Sedentary behavior, physical activity, and concentrations of insulin among US adults. Metabolism. 2010 Sep;59(9):1268-75. doi: 10.1016/j.metabol.2009.11.020. Epub 2010 Jan 13.
citation: Owen N, Salmon J, Koohsari MJ, Turrell G, Giles-Corti B. Sedentary behaviour and health: mapping environmental and social contexts to underpin chronic disease prevention. Br J Sports Med. 2014 Feb;48(3):174-7. doi: 10.1136/bjsports-2013-093107.
citation: Mummery WK, Schofield GM, Steele R, Eakin EG, Brown WJ. Occupational sitting time and overweight and obesity in Australian workers. Am J Prev Med. 2005 Aug;29(2):91-7. doi: 10.1016/j.amepre.2005.04.003.
citation: Bann D, Kuh D, Wills AK, Adams J, Brage S, Cooper R; National Survey of Health and Development scientific and data collection team. Physical activity across adulthood in relation to fat and lean body mass in early old age: findings from the Medical Research Council National Survey of Health and Development, 1946-2010. Am J Epidemiol. 2014 May 15;179(10):1197-207. doi: 10.1093/aje/kwu033. Epub 2014 Apr 9.
citation: Vandelanotte C, Sugiyama T, Gardiner P, Owen N. Associations of leisure-time internet and computer use with overweight and obesity, physical activity and sedentary behaviors: cross-sectional study. J Med Internet Res. 2009 Jul 27;11(3):e28. doi: 10.2196/jmir.1084.
citation: de Rezende LF, Rodrigues Lopes M, Rey-Lopez JP, Matsudo VK, Luiz Odo C. Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS One. 2014 Aug 21;9(8):e105620. doi: 10.1371/journal.pone.0105620. eCollection 2014.
citation: Judice PB, Silva AM, Magalhaes JP, Matias CN, Sardinha LB. Sedentary behaviour and adiposity in elite athletes. J Sports Sci. 2014;32(19):1760-7. doi: 10.1080/02640414.2014.926382. Epub 2014 Jun 10.
citation: Larsen BA, Allison MA, Kang E, Saad S, Laughlin GA, Araneta MR, Barrett-Connor E, Wassel CL. Associations of physical activity and sedentary behavior with regional fat deposition. Med Sci Sports Exerc. 2014 Mar;46(3):520-8. doi: 10.1249/MSS.0b013e3182a77220.
citation: Levine JA, Vander Weg MW, Hill JO, Klesges RC. Non-exercise activity thermogenesis: the crouching tiger hidden dragon of societal weight gain. Arterioscler Thromb Vasc Biol. 2006 Apr;26(4):729-36. doi: 10.1161/01.ATV.0000205848.83210.73. Epub 2006 Jan 26.
citation: Tudor-Locke C, Schuna JM Jr, Frensham LJ, Proenca M. Changing the way we work: elevating energy expenditure with workstation alternatives. Int J Obes (Lond). 2014 Jun;38(6):755-65. doi: 10.1038/ijo.2013.223. Epub 2013 Nov 28.
citation: Healy GN, Matthews CE, Dunstan DW, Winkler EA, Owen N. Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003-06. Eur Heart J. 2011 Mar;32(5):590-7. doi: 10.1093/eurheartj/ehq451. Epub 2011 Jan 11.
citation: Henson J, Yates T, Biddle SJ, Edwardson CL, Khunti K, Wilmot EG, Gray LJ, Gorely T, Nimmo MA, Davies MJ. Associations of objectively measured sedentary behaviour and physical activity with markers of cardiometabolic health. Diabetologia. 2013 May;56(5):1012-20. doi: 10.1007/s00125-013-2845-9. Epub 2013 Mar 1.
citation: Peddie MC, Bone JL, Rehrer NJ, Skeaff CM, Gray AR, Perry TL. Breaking prolonged sitting reduces postprandial glycemia in healthy, normal-weight adults: a randomized crossover trial. Am J Clin Nutr. 2013 Aug;98(2):358-66. doi: 10.3945/ajcn.112.051763. Epub 2013 Jun 26.
citation: Reiff C, Marlatt K, Dengel DR. Difference in caloric expenditure in sitting versus standing desks. J Phys Act Health. 2012 Sep;9(7):1009-11. doi: 10.1123/jpah.9.7.1009.
citation: Elmer SJ, Martin JC. A cycling workstation to facilitate physical activity in office settings. Appl Ergon. 2014 Jul;45(4):1240-6. doi: 10.1016/j.apergo.2014.03.001. Epub 2014 Mar 27.
citation: Swartz AM, Squires L, Strath SJ. Energy expenditure of interruptions to sedentary behavior. Int J Behav Nutr Phys Act. 2011 Jun 27;8:69. doi: 10.1186/1479-5868-8-69.
citation: Lohman TG, Roche AF, Martorell R (1988) Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Publichers.
citation: Compher C, Frankenfield D, Keim N, Roth-Yousey L; Evidence Analysis Working Group. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc. 2006 Jun;106(6):881-903. doi: 10.1016/j.jada.2006.02.009.
citation: Haines DJ, Davis L, Rancour P, Robinson M, Neel-Wilson T, Wagner S. A pilot intervention to promote walking and wellness and to improve the health of college faculty and staff. J Am Coll Health. 2007 Jan-Feb;55(4):219-25. doi: 10.3200/JACH.55.4.219-225.