no Condition, Community-dwelling 80+ Older AdultsNCT04821713
Validation of Objectively and Subjectively Measured Physical Activity Against Energy Expenditure in Older Adults
An observational study of no Condition, Community-dwelling 80+ Older Adults, run by University of Southern Denmark at 1 site in Denmark.
Trial summary
Physical inactivity is identified as one of the most important modifiable risk factors for chronic diseases, functional loss and disability and reliable assessment tools of physical activity are crucial in both research and clinical settings. Read more about this study
- Who is it for?
- Ages 80 years and older
- Conditions the study is for
- no Condition, Community-dwelling 80+ Older Adults
- How many people
- 100 participants
- Where
- 1 siteDenmark
- Study dates
- 15 Mar 2019to Mar 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 80 years and older
- All sexes
- Older adult
Study population: Community-dwelling men and women aged 80 and above.
Who may be able to join
- Community-dwelling older adults aged 80+ years old.
- Have intact cognitive function, evaluated by a score ≥ 3 in the short form of the Mini- mental state evaluation (MMSE)14.
- Signed an informed letter of consent.
Who cannot join
- Have severe organic or mental disease as determined by history
- Have terminal cancer.
- Are on chemotherapy.
- Have a drug and/or alcohol abuse (>50 g alcohol a day).
- Have been prescribed new medication within 2 months with potential to alter metabolism.
- Are hospitalized or bed-ridden because they will not be able to perform any of the tasks in the laboratory and movement during the free-living activity would be limited.
- Those who need assistive devices (including wheelchair, cane, walkers etc..) for lab testing.
- Those who are unable to speak and read Danish because they will not be able to follow instructions in the laboratory and during the free-living conditions.
Trial locations and contacts
1 site in 1 country.
Denmark1 site, 1 recruiting
- Recruiting
University of Southern Denmark
Odense, 5230
Li-Tang Tsai, PhD, +45 6550 7572, ltsai@health.sdu.dk
Paolo Caserotti, PhD, +45 6550 3444, pcaserotti@health.sdu.dk
About this study
Official title: ENerGetics in Old AGE (ENGAGE Study) - Validation of Multiple Accelerometers and Physical Activity Questionnaires Against Indirect Calorimetry Under Laboratory and Free-living Conditions in Very Old Adults
Physical inactivity is identified as one of the most important modifiable risk factors for chronic diseases, functional loss and disability and reliable assessment tools of physical activity are crucial in both research and clinical settings.
Traditionally, physical activity and sedentary behavior have been primarily assessed with questionnaires. Recently, accelerometers have been widely used to measure physical activity, sedentary behavior and sleep patterns in ageing. Still, the diversity of brands and models, various assessment protocols (e.g. anatomic locations, sampling frequency), data processing and outcome measures have posed challenges to the interpretation and comparability of results across studies. Therefore, despite some limitations, questionnaires are still considered an important assessment method, especially in large-scale studies. In order to bridge the differences in the interpretation of data from questionnaires to accelerometers among older adults, there is a need to validate existing physical activity and sedentary behavior questionnaires with energy expenditure in this population.
Read more
Energy expenditure has been used to "translate" accelerometer output into physiological outcomes. Nevertheless, several issues remain unresolved, including (1) limited calibration studies focusing on older adults; (2) resting metabolic rate and maximum physiological capacity typically decrease with aging, which makes daily activities "more intense" for an older person compared to a younger person; and (3) the same accelerometer metric measured at different body positions may be linked to completely different physiological outcomes.
Such diverse physiological impact according to the anatomical placement of accelerometers requires a rigorous harmonization of metrics from the accelerometers with energy expenditure during representative activities at different intensities.
The aims of this methodological study focusing on 80+ year-olds are to:
- develop cut-points from accelerometers at different anatomical positions for different intensities of physical activity based on energy expenditure during semi-standardized daily tasks in the lab.
- validate accelerometer at different anatomical positions against energy expenditure measured by double-labelled water (DLW) in free-living conditions.
- validate existing physical activity and sedentary behavior questionnaires against DLW in free-living conditions.
Read the detailed description
Background
Physical inactivity has been estimated to cause 5.3 million deaths per year globally and is identified as one of the most important modifiable risk factors for chronic diseases, functional loss and disability. To correctly identify and study physical inactivity in old age, reliable assessment tools are crucial in both research and clinical settings.
Recent technological advancements in wearable activity monitors have led to a growing number of large, population-based studies using accelerometers to measure physical activity, sedentary behavior (in terms of overall volume, intensity and pattern), and sleep among older adults. However, the wide use of accelerometers also brings challenges when comparing the results across different studies that use different brands and models, various assessment protocols (e.g. anatomic locations, sampling frequency), data processing procedures and report different outcomes. Different accelerometer set-ups (i.e. brand, model, body position, initialization protocol, etc.) may challenge the interpretation of health-enhancing effect of physical activity and detrimental effect of sedentary behavior simply because of methodological issues.
Accelerometers measure acceleration, defined as the change in velocity over time (Δv/t), which quantifies the volume and intensity of movement. In addition, acceleration is a vector quantity with components of magnitude and direction, which can be used to identify the position of accelerometer in relation to gravity. Therefore, accelerometer could also be used to distinguish posture (e.g. sitting, standing, lying down) depending on the site of placement.
Since raw acceleration signals are difficult to interpret, they are typically "translated" by calibration studies to physiological outcomes (e.g. energy expenditure, oxygen consumption) or behavioral categories (e.g. sitting, walking, running). Through regression modelling, calibration studies often produce point estimates of energy expenditure from accelerometer counts or establish a range of accelerometer counts for different physical activity intensity levels. This range of accelerometer counts is referred to as "cut-points" for different intensities of physical activity.
Before the use of accelerometers, physical activity and sedentary behavior has been primarily assessed with questionnaires. Even as the scale of accelerometer studies are growing rapidly, questionnaires are still considered an important assessment method when assessing physical activity and sedentary behavior in large-scale studies. Some accelerometers and questionnaires have been validated by objectively measured energy expenditure. But for physical activity questionnaires, the validity against objective methods (e.g. accelerometry, heart rate monitor and double-labelled water) were found to be moderate at best and very few validation studies focused on older adults. In order to bridge and interpret data from questionnaires to accelerometers among older adults, there is a need to validate existing physical activity and sedentary behavior questionnaires with energy expenditure in this population.
Energy expenditure has earlier been used to validate accelerometers and physical activity questionnaires metrics. Nevertheless, several issues remain unsolved: (1) despite the correlation between these methods has been reported to be high in few studies, the agreement is generally low especially in populations with altered metabolic states such as obese and overweight individuals; (2) while the total volume of physical activity is a clear metric which is presumably positively correlated with total daily energy expenditure, intensity of physical activity in older adults may be affected by a number of physiological determinants such as cardiovascular and neuromuscular function, inflammation status and malnutrition. Resting metabolic rate (RMR) and maximum physiological capacity (e.g. maximum oxygen update (VO2 max) typically decrease with age, which may be particular important as the same daily activities would likely be "more intense" to an older person compared to a younger person; (3) despite that numerous activity monitors provide similar metrics (e.g. counts/minutes), the physiological implication can be highly different depending on what such metrics stand for. For example, despite the output from accelerometers placed on wrist and on the hip may be identical (counts/minutes), the different magnitude of acceleration may have a completely different physiological relationship when assessed by physiological metrics (e.g. energy, oxygen uptake). Such diverse physiological impact according to the anatomical placement of accelerometers requires a rigorous harmonization of metrics from the accelerometers coupled with energy expenditure in representative activities at different intensities.
To date, validation studies with accelerometers worn on multiple body positions are scarce and not all studies uses energy expenditure as the reference. One way to disentangle the physiological meaning of physical activity and sedentary behavior is to anchor accelerometer output to objective measurements of physiological capacity such as VO2 max, oxygen uptake during semi-standardized activities performed at self-selected pace and overall energy expenditure during free-living conditions collected over a representative period of time. This will contribute to a deeper understanding and accurate interpretation of the accelerometer data among community-dwelling older adults and to provide more specific accelerometry-based recommendations for physical activity, especially for the oldest population.
Objectives
The aims of this methodological study are to:
- develop hip-, wrist-, thigh-, and low back- worn accelerometer cut-points for different intensities of physical activity based on energy expenditure during semi-standardized daily tasks for the 80+ year-olds.
- validate accelerometry at the wrist, hip, thigh, and low back for estimating energy expenditure in free-living conditions, measured by the gold standard of energy expenditure, double-labelled water (DLW).
- validate existing physical activity and sedentary behavior questionnaires against gold standard of energy expenditure (DLW) in free-living conditions in the 80+ year-olds.
Recruitment and data collection procedures
The investigators will conduct a cross-sectional study with two modes of data collection: 1) in the laboratory; and 2) in the field. Participants will be recruited through two pathways: 1)(Pathway A) invited personally during the routine preventive home-visits performed by the Municipality of Odense ; (Pathway B)or 2) invited through a letter to community-dwelling older citizens who lives in the Municipality of Odense. Those who show interest to participate will then receive detailed written information about the project and will be invited to a medical screening after signing an informed consent. The entire testing procedure will span across 14 days as urine samples for DLW method is needed on Day 1 and Day 14. In between, participants will be invited to attend one for lab test for measuring energy expenditure during semi-standardized functional tasks.
Statistical considerations and data management A detailed data management plan will be followed in the collection, entering, and analysis of data. In the laboratory examination day, all measurement devices will be synchronized before the measurement begins.
Sample size Assuming that different accelerometers can capture same physical activity behaviour, in a test for agreement between two raters using the Kappa statistic, a sample size of 95 subjects achieves 80% power to detect a true Kappa value of 0.70 when there are 3 categories with frequencies equal to 0.01, 0.20, and 0.79. (representing estimated percentage of time spent in moderate-to-vigorous activity, light activity, and sedentary behavior in this population). This power calculation is based on an alpha of 0.05.
Creation of a research biobank
A research biobank (blood, urine, and saliva samples) will be created for the described project. The blood samples will be destroyed no later than 5 years after the project is ending. Blood samples will be taking at the facilities of the University (SDU). An authorized nurse or biomedical laboratory scientist will be in charge of obtaining blood samples from the participants. The biobank will be stored at SDU. In total, 8 urine samples will be obtained from each participant during the entire project period. Urine samples will be frozen and sent to USA for analysis. The urine samples will be anonymized and stored in the research biobank until the end of the project, when the samples will be destroyed. A trained project personnel will be in charge of collecting urine samples from the subjects. In this protocol, University of Southern Denmark acts as the controller of the biological materials collected (urine samples). Data processing agreements will be made between SDU and the University of Wisconsin, USA; and between SDU and University of California, Berkeley. The US processor shall comply with Danish law governing protection of personal data.
Ethical considerations
The research activities of this study will be carried out in accordance with the Declaration of Helsinki. All subjects will receive the pamphlets from The National Committee on Health Research Ethics regarding personal rights when participating in a health research project and aspects to consider before deciding to participate. This study will involve older adults, who are considered vulnerable individuals. It is important to acknowledge and respect participants' autonomy, i.e., they have to be able to decide by themselves their participation in the study with the right to withdraw at any stage. Moreover, a communication strategy suitable for this population will be applied to prevent any risk of enhancing vulnerability and stigmatization of the older adults.
This project will generate valuable and novel knowledge about how do objectively measure physical activity measured by different accelerometers on the same individual correlate with energy expenditure among in +80-year-old community-dwelling citizens; and whether these patterns differ according to protein level. These knowledges that can be used to optimize and target the preventive and treatment strategies for malnourished older adults hence offer a benefit for the individual older adult and for the health care sector. Thus, the investigators believe that the benefits from the study is greater than the limited discomforts that may follow participation. Subjects are covered by the Danish Patient Insurance Association and can thus receive insurance of financial compensation in case any damage occurs while participating in the research project. This information will be given to participants both verbally and written (in the pamphlets from The National Committee on Health Research Ethics) during recruitment.
All personal data will become anonymized and handled with full confidentiality in compliance with the Personal Data Processing Act. The procedure of personal data processing will be reported to the Danish Data Protection Agency in University of Southern Denmark. In this study protocol, only the anonymized urine and saliva samples will be sent abroad for analysis (details described earlier) with no linkage to any other personal data (e.g. CPR number, address, telephone number etc..).
Participants will not receive any compensation for their participation in the study.
- Keywords
- Accelerometer, Physical Activity, Sedentary behavior, Energy Expenditure, Older Adults
- Medical subject headings
- Motor Activity, Sedentary Behavior
What is being measured
The primary outcome is the main question the study is designed to answer.
Accelerometer-assessed physical activity in free-living condition
Physical activity and sedentary behavior measured from accelerometers at multiple body locations in free-living condition. Raw accelerometer data will be processed in standard protocol and summarized in counts per minutes in vector magnitude.
Measured: Through study completion, an average of 14 days
Energy expenditure in free-living condition
Oxygen uptake measured by doubly labelled water under free-living condition
Measured: Through study completion, an average of 14 days
Accelerometer-assessed physical activity in the lab
Physical activity and sedentary behavior measured from accelerometers at multiple body locations in the lab. Raw accelerometer data will be processed in standard protocol and summarized in counts per minutes in vector magnitude.
Measured: During lab measurement days up to 3 days
Energy expenditure in the lab
Oxygen uptake measured by indirect calorimetry in the lab
Measured: During lab measurement days up to 3 days
Secondary outcomes (9)
Self-reported physical activity
Measured by existing and ad hoc physical activity questionnaires: International Physical Activity Questionnaire--short form (IPAQ--short form), Physical Activity Scale for the Elderly (PASE).
IPAQ-SF: IPAQ-SF is measuring PA across three domains: walking, moderate PA and vigorous PA. The total amount of PA is the sum of the three domains.
- Minimum 0 MET-minutes/week
- Maximum 19278 MET-minutes/week (truncated)
PASE: The instrument is suitable for over 65 years old and comprised of self-reported occupational, household and leisure activities items over a one week period. PASE scores are calculated from weights and frequency values for each of 12 types of activity.
- Minimum 0 PASE score
- Maximum 400 (or more) PASE score
Physical Activity Scale: The physical activity scale is a 24-hours measure and encompasses sleep, sedentary behavior, work, leisure time, and sports activity in one measure.
- Minimum 25 MET-time/day
- Maximum 150 MET-time/day
Measured: During lab measurement days up to 1 day
Self-reported sedentary behavior
Measured by the Sedentary Behaviour Questionnaire (SBQ).
SBQ: The SBQ measures time spent in sedentary behavior across different domains during weekdays and weekend days.
- Minimum 0 hours
- Maximum 24 hours
Measured: During lab measurement days up to 1 day
Protein level
Measured by 4-day food diary, protein screener, biomarkers from blood
Measured: Up to 4 days
Muscle mass with DEXA scan
Measured by DEXA scan
Measured: During lab measurement days up to 1 day
Muscle mass
D3-creatine method
Measured: Up to 4 days
Handgrip Strength
Handgrip strength measured by dynamometer in kg.
Measured: During lab measurement days up to 1 day
Lower extremity function
Short Physical Performance Battery (SPPB), scores from 0 to 12, higher score indicating better function
Measured: During lab measurement days up to 1 day
Functional walking test
Walking speed from 6-minutes walking test
Measured: During lab measurement days up to 1 day
Cardiovascular function
VO2 max test
Measured: During lab measurement days up to 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Mar 2021
- Study start15 Mar 2019
- Primary completionMar 2022 (estimated)
- Study completionMar 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (19)Papers the sponsor has linked to this study.
- Other trials for no Condition, Community-dwelling 80+ Older AdultsStudies of the same condition, open and under way.
- More trials run by University of Southern DenmarkThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Southern Denmark
- Sponsor type
- University, hospital or other
- Collaborators
- Odense University Hospital, National Institutes of Health (NIH), Maastricht University, University of Wisconsin, Madison, University of California, Berkeley, University of Ulster, University Ramon Llull, National Cancer Institute (NCI)
- Responsible party
- Principal investigator, Paolo Caserotti, University of Southern Denmark
- Investigators
- Paolo Caserotti, PhD, Principal investigator, Department of Sports and Clinical Biomechanics, University of Southern Denmark
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04821713
- Sponsor's protocol ID
- 65838
- Other IDs
- 5R01CA183570-05
- Status last verified
- Mar 2021
- First submitted
- 1 Mar 2021
- Last updated
- 29 Mar 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: All personal data will become anonymized and handled with full confidentiality in compliance with the Personal Data Processing Act and GDPR. The procedure of personal data processing will be reported to the Danish Data Protection Agency (Datatilsynet) in University of Southern Denmark. In this study protocol, only the anonymized urine and saliva samples will be sent abroad for analysis (details described earlier) with no linkage to any other personal data (e.g. CPR number, address, telephone number etc..).
Publications
Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT; Lancet Physical Activity Series Working Group. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012 Jul 21;380(9838):219-29. doi: 10.1016/S0140-6736(12)61031-9.
PubMed 22818936Strath SJ, Kaminsky LA, Ainsworth BE, Ekelund U, Freedson PS, Gary RA, Richardson CR, Smith DT, Swartz AM; American Heart Association Physical Activity Committee of the Council on Lifestyle and Cardiometabolic Health and Cardiovascular, Exercise, Cardiac Rehabilitation and Prevention Committee of the Council on Clinical Cardiology, and Council. Guide to the assessment of physical activity: Clinical and research applications: a scientific statement from the American Heart Association. Circulation. 2013 Nov 12;128(20):2259-79. doi: 10.1161/01.cir.0000435708.67487.da. Epub 2013 Oct 14.
PubMed 24126387Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob Health. 2018 Oct;6(10):e1077-e1086. doi: 10.1016/S2214-109X(18)30357-7. Epub 2018 Sep 4.
PubMed 30193830Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S523-30. doi: 10.1249/01.mss.0000185658.28284.ba.
PubMed 16294115Pisanu S, Deledda A, Loviselli A, Huybrechts I, Velluzzi F. Validity of Accelerometers for the Evaluation of Energy Expenditure in Obese and Overweight Individuals: A Systematic Review. J Nutr Metab. 2020 Aug 4;2020:2327017. doi: 10.1155/2020/2327017. eCollection 2020.
PubMed 32832147Doherty A, Jackson D, Hammerla N, Plotz T, Olivier P, Granat MH, White T, van Hees VT, Trenell MI, Owen CG, Preece SJ, Gillions R, Sheard S, Peakman T, Brage S, Wareham NJ. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One. 2017 Feb 1;12(2):e0169649. doi: 10.1371/journal.pone.0169649. eCollection 2017.
PubMed 28146576Hoogendijk EO, Deeg DJ, Poppelaars J, van der Horst M, Broese van Groenou MI, Comijs HC, Pasman HR, van Schoor NM, Suanet B, Thomese F, van Tilburg TG, Visser M, Huisman M. The Longitudinal Aging Study Amsterdam: cohort update 2016 and major findings. Eur J Epidemiol. 2016 Sep;31(9):927-45. doi: 10.1007/s10654-016-0192-0. Epub 2016 Aug 20.
PubMed 27544533Arnardottir NY, Koster A, Van Domelen DR, Brychta RJ, Caserotti P, Eiriksdottir G, Sverrisdottir JE, Launer LJ, Gudnason V, Johannsson E, Harris TB, Chen KY, Sveinsson T. Objective measurements of daily physical activity patterns and sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study. Age Ageing. 2013 Mar;42(2):222-9. doi: 10.1093/ageing/afs160. Epub 2012 Oct 31.
PubMed 23117467Crouter SE, Churilla JR, Bassett DR Jr. Estimating energy expenditure using accelerometers. Eur J Appl Physiol. 2006 Dec;98(6):601-12. doi: 10.1007/s00421-006-0307-5. Epub 2006 Oct 21.
PubMed 17058102Barnett A, van den Hoek D, Barnett D, Cerin E. Measuring moderate-intensity walking in older adults using the ActiGraph accelerometer. BMC Geriatr. 2016 Dec 8;16(1):211. doi: 10.1186/s12877-016-0380-5.
PubMed 27931188Matthew CE. Calibration of accelerometer output for adults. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S512-22. doi: 10.1249/01.mss.0000185659.11982.3d.
PubMed 16294114Koster A, Shiroma EJ, Caserotti P, Matthews CE, Chen KY, Glynn NW, Harris TB. Comparison of Sedentary Estimates between activPAL and Hip- and Wrist-Worn ActiGraph. Med Sci Sports Exerc. 2016 Aug;48(8):1514-1522. doi: 10.1249/MSS.0000000000000924.
PubMed 27031744Santos-Lozano A, Santin-Medeiros F, Cardon G, Torres-Luque G, Bailon R, Bergmeir C, Ruiz JR, Lucia A, Garatachea N. Actigraph GT3X: validation and determination of physical activity intensity cut points. Int J Sports Med. 2013 Nov;34(11):975-82. doi: 10.1055/s-0033-1337945. Epub 2013 May 22.
PubMed 23700330Sharifzadeh M, Bagheri M, Speakman JR, Djafarian K. Comparison of total and activity energy expenditure estimates from physical activity questionnaires and doubly labelled water: a systematic review and meta-analysis. Br J Nutr. 2021 May 14;125(9):983-997. doi: 10.1017/S0007114520003049. Epub 2020 Jul 28.
PubMed 32718378Helmerhorst HJ, Brage S, Warren J, Besson H, Ekelund U. A systematic review of reliability and objective criterion-related validity of physical activity questionnaires. Int J Behav Nutr Phys Act. 2012 Aug 31;9:103. doi: 10.1186/1479-5868-9-103.
PubMed 22938557
Study at a glance
From the registry record, last updated by the sponsor on 29 Mar 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- ENerGetics in Old AGE (ENGAGE Study) - Validation of Multiple Accelerometers and Physical Activity Questionnaires Against Indirect Calorimetry Under Laboratory and Free-living Conditions in Very Old Adults
- ClinicalTrials.gov ID
- NCT04821713
- Acronym / sponsor ID
- 65838
- Keywords
- Accelerometer, Physical Activity, Sedentary behavior, Energy Expenditure, Older Adults
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- University of Southern DenmarkUniversity, hospital or other
- Collaborators
- Odense University Hospital, National Institutes of Health (NIH), Maastricht University, University of Wisconsin, Madison, University of California, Berkeley, University of Ulster, University Ramon Llull, National Cancer Institute (NCI)
- Study start
- 15 Mar 2019 (actual)
- Primary completion
- Mar 2022 (estimated)
- Study completion
- Mar 2022 (estimated)
- First posted
- 29 Mar 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Physical inactivity is identified as one of the most important modifiable risk factors for chronic diseases, functional loss and disability and reliable assessment tools of physical activity are crucial in both research and clinical settings.
Traditionally, physical activity and sedentary behavior have been primarily assessed with questionnaires. Recently, accelerometers have been widely used to measure physical activity, sedentary behavior and sleep patterns in ageing. Still, the diversity of brands and models, various assessment protocols (e.g. anatomic locations, sampling frequency), data processing and outcome measures have posed challenges to the interpretation and comparability of results across studies. Therefore, despite some limitations, questionnaires are still considered an important assessment method, especially in large-scale studies. In order to bridge the differences in the interpretation of data from questionnaires to accelerometers among older adults, there is a need to validate existing physical activity and sedentary behavior questionnaires with energy expenditure in this population.
Energy expenditure has been used to "translate" accelerometer output into physiological outcomes. Nevertheless, several issues remain unresolved, including (1) limited calibration studies focusing on older adults; (2) resting metabolic rate and maximum physiological capacity typically decrease with aging, which makes daily activities "more intense" for an older person compared to a younger person; and (3) the same accelerometer metric measured at different body positions may be linked to completely different physiological outcomes.
Such diverse physiological impact according to the anatomical placement of accelerometers requires a rigorous harmonization of metrics from the accelerometers with energy expenditure during representative activities at different intensities.
The aims of this methodological study focusing on 80+ year-olds are to:
- develop cut-points from accelerometers at different anatomical positions for different intensities of physical activity based on energy expenditure during semi-standardized daily tasks in the lab.
- validate accelerometer at different anatomical positions against energy expenditure measured by double-labelled water (DLW) in free-living conditions.
- validate existing physical activity and sedentary behavior questionnaires against DLW in free-living conditions.
Detailed description
Background
Physical inactivity has been estimated to cause 5.3 million deaths per year globally and is identified as one of the most important modifiable risk factors for chronic diseases, functional loss and disability. To correctly identify and study physical inactivity in old age, reliable assessment tools are crucial in both research and clinical settings.
Recent technological advancements in wearable activity monitors have led to a growing number of large, population-based studies using accelerometers to measure physical activity, sedentary behavior (in terms of overall volume, intensity and pattern), and sleep among older adults. However, the wide use of accelerometers also brings challenges when comparing the results across different studies that use different brands and models, various assessment protocols (e.g. anatomic locations, sampling frequency), data processing procedures and report different outcomes. Different accelerometer set-ups (i.e. brand, model, body position, initialization protocol, etc.) may challenge the interpretation of health-enhancing effect of physical activity and detrimental effect of sedentary behavior simply because of methodological issues.
Accelerometers measure acceleration, defined as the change in velocity over time (Δv/t), which quantifies the volume and intensity of movement. In addition, acceleration is a vector quantity with components of magnitude and direction, which can be used to identify the position of accelerometer in relation to gravity. Therefore, accelerometer could also be used to distinguish posture (e.g. sitting, standing, lying down) depending on the site of placement.
Since raw acceleration signals are difficult to interpret, they are typically "translated" by calibration studies to physiological outcomes (e.g. energy expenditure, oxygen consumption) or behavioral categories (e.g. sitting, walking, running). Through regression modelling, calibration studies often produce point estimates of energy expenditure from accelerometer counts or establish a range of accelerometer counts for different physical activity intensity levels. This range of accelerometer counts is referred to as "cut-points" for different intensities of physical activity.
Before the use of accelerometers, physical activity and sedentary behavior has been primarily assessed with questionnaires. Even as the scale of accelerometer studies are growing rapidly, questionnaires are still considered an important assessment method when assessing physical activity and sedentary behavior in large-scale studies. Some accelerometers and questionnaires have been validated by objectively measured energy expenditure. But for physical activity questionnaires, the validity against objective methods (e.g. accelerometry, heart rate monitor and double-labelled water) were found to be moderate at best and very few validation studies focused on older adults. In order to bridge and interpret data from questionnaires to accelerometers among older adults, there is a need to validate existing physical activity and sedentary behavior questionnaires with energy expenditure in this population.
Energy expenditure has earlier been used to validate accelerometers and physical activity questionnaires metrics. Nevertheless, several issues remain unsolved: (1) despite the correlation between these methods has been reported to be high in few studies, the agreement is generally low especially in populations with altered metabolic states such as obese and overweight individuals; (2) while the total volume of physical activity is a clear metric which is presumably positively correlated with total daily energy expenditure, intensity of physical activity in older adults may be affected by a number of physiological determinants such as cardiovascular and neuromuscular function, inflammation status and malnutrition. Resting metabolic rate (RMR) and maximum physiological capacity (e.g. maximum oxygen update (VO2 max) typically decrease with age, which may be particular important as the same daily activities would likely be "more intense" to an older person compared to a younger person; (3) despite that numerous activity monitors provide similar metrics (e.g. counts/minutes), the physiological implication can be highly different depending on what such metrics stand for. For example, despite the output from accelerometers placed on wrist and on the hip may be identical (counts/minutes), the different magnitude of acceleration may have a completely different physiological relationship when assessed by physiological metrics (e.g. energy, oxygen uptake). Such diverse physiological impact according to the anatomical placement of accelerometers requires a rigorous harmonization of metrics from the accelerometers coupled with energy expenditure in representative activities at different intensities.
To date, validation studies with accelerometers worn on multiple body positions are scarce and not all studies uses energy expenditure as the reference. One way to disentangle the physiological meaning of physical activity and sedentary behavior is to anchor accelerometer output to objective measurements of physiological capacity such as VO2 max, oxygen uptake during semi-standardized activities performed at self-selected pace and overall energy expenditure during free-living conditions collected over a representative period of time. This will contribute to a deeper understanding and accurate interpretation of the accelerometer data among community-dwelling older adults and to provide more specific accelerometry-based recommendations for physical activity, especially for the oldest population.
Objectives
The aims of this methodological study are to:
- develop hip-, wrist-, thigh-, and low back- worn accelerometer cut-points for different intensities of physical activity based on energy expenditure during semi-standardized daily tasks for the 80+ year-olds.
- validate accelerometry at the wrist, hip, thigh, and low back for estimating energy expenditure in free-living conditions, measured by the gold standard of energy expenditure, double-labelled water (DLW).
- validate existing physical activity and sedentary behavior questionnaires against gold standard of energy expenditure (DLW) in free-living conditions in the 80+ year-olds.
Recruitment and data collection procedures
The investigators will conduct a cross-sectional study with two modes of data collection: 1) in the laboratory; and 2) in the field. Participants will be recruited through two pathways: 1)(Pathway A) invited personally during the routine preventive home-visits performed by the Municipality of Odense ; (Pathway B)or 2) invited through a letter to community-dwelling older citizens who lives in the Municipality of Odense. Those who show interest to participate will then receive detailed written information about the project and will be invited to a medical screening after signing an informed consent. The entire testing procedure will span across 14 days as urine samples for DLW method is needed on Day 1 and Day 14. In between, participants will be invited to attend one for lab test for measuring energy expenditure during semi-standardized functional tasks.
Statistical considerations and data management A detailed data management plan will be followed in the collection, entering, and analysis of data. In the laboratory examination day, all measurement devices will be synchronized before the measurement begins.
Sample size Assuming that different accelerometers can capture same physical activity behaviour, in a test for agreement between two raters using the Kappa statistic, a sample size of 95 subjects achieves 80% power to detect a true Kappa value of 0.70 when there are 3 categories with frequencies equal to 0.01, 0.20, and 0.79. (representing estimated percentage of time spent in moderate-to-vigorous activity, light activity, and sedentary behavior in this population). This power calculation is based on an alpha of 0.05.
Creation of a research biobank
A research biobank (blood, urine, and saliva samples) will be created for the described project. The blood samples will be destroyed no later than 5 years after the project is ending. Blood samples will be taking at the facilities of the University (SDU). An authorized nurse or biomedical laboratory scientist will be in charge of obtaining blood samples from the participants. The biobank will be stored at SDU. In total, 8 urine samples will be obtained from each participant during the entire project period. Urine samples will be frozen and sent to USA for analysis. The urine samples will be anonymized and stored in the research biobank until the end of the project, when the samples will be destroyed. A trained project personnel will be in charge of collecting urine samples from the subjects. In this protocol, University of Southern Denmark acts as the controller of the biological materials collected (urine samples). Data processing agreements will be made between SDU and the University of Wisconsin, USA; and between SDU and University of California, Berkeley. The US processor shall comply with Danish law governing protection of personal data.
Ethical considerations
The research activities of this study will be carried out in accordance with the Declaration of Helsinki. All subjects will receive the pamphlets from The National Committee on Health Research Ethics regarding personal rights when participating in a health research project and aspects to consider before deciding to participate. This study will involve older adults, who are considered vulnerable individuals. It is important to acknowledge and respect participants' autonomy, i.e., they have to be able to decide by themselves their participation in the study with the right to withdraw at any stage. Moreover, a communication strategy suitable for this population will be applied to prevent any risk of enhancing vulnerability and stigmatization of the older adults.
This project will generate valuable and novel knowledge about how do objectively measure physical activity measured by different accelerometers on the same individual correlate with energy expenditure among in +80-year-old community-dwelling citizens; and whether these patterns differ according to protein level. These knowledges that can be used to optimize and target the preventive and treatment strategies for malnourished older adults hence offer a benefit for the individual older adult and for the health care sector. Thus, the investigators believe that the benefits from the study is greater than the limited discomforts that may follow participation. Subjects are covered by the Danish Patient Insurance Association and can thus receive insurance of financial compensation in case any damage occurs while participating in the research project. This information will be given to participants both verbally and written (in the pamphlets from The National Committee on Health Research Ethics) during recruitment.
All personal data will become anonymized and handled with full confidentiality in compliance with the Personal Data Processing Act. The procedure of personal data processing will be reported to the Danish Data Protection Agency in University of Southern Denmark. In this study protocol, only the anonymized urine and saliva samples will be sent abroad for analysis (details described earlier) with no linkage to any other personal data (e.g. CPR number, address, telephone number etc..).
Participants will not receive any compensation for their participation in the study.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
Who may qualify
- Ages
- 80 years and older
- Sex
- All
- Age groups
- Older adult
- Study population
- Community-dwelling men and women aged 80 and above.
Key inclusion criteria (3 listed)
- Community-dwelling older adults aged 80+ years old.
- Have intact cognitive function, evaluated by a score ≥ 3 in the short form of the Mini- mental state evaluation (MMSE)14.
- Signed an informed letter of consent.
Key exclusion criteria (8 listed)
- Have severe organic or mental disease as determined by history
- Have terminal cancer.
- Are on chemotherapy.
- Have a drug and/or alcohol abuse (>50 g alcohol a day).
- Have been prescribed new medication within 2 months with potential to alter metabolism.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Accelerometer-assessed physical activity in free-living condition
Time frame: Through study completion, an average of 14 days
Physical activity and sedentary behavior measured from accelerometers at multiple body locations in free-living condition. Raw accelerometer data will be processed in standard protocol and summarized in counts per minutes in vector magnitude.
Energy expenditure in free-living condition
Time frame: Through study completion, an average of 14 days
Oxygen uptake measured by doubly labelled water under free-living condition
Accelerometer-assessed physical activity in the lab
Time frame: During lab measurement days up to 3 days
Physical activity and sedentary behavior measured from accelerometers at multiple body locations in the lab. Raw accelerometer data will be processed in standard protocol and summarized in counts per minutes in vector magnitude.
Energy expenditure in the lab
Time frame: During lab measurement days up to 3 days
Oxygen uptake measured by indirect calorimetry in the lab
9 secondary outcomes
Self-reported physical activity
Time frame: During lab measurement days up to 1 day
Self-reported sedentary behavior
Time frame: During lab measurement days up to 1 day
Protein level
Time frame: Up to 4 days
Muscle mass with DEXA scan
Time frame: During lab measurement days up to 1 day
Muscle mass
Time frame: Up to 4 days
Handgrip Strength
Time frame: During lab measurement days up to 1 day
Lower extremity function
Time frame: During lab measurement days up to 1 day
Functional walking test
Time frame: During lab measurement days up to 1 day
Cardiovascular function
Time frame: During lab measurement days up to 1 day
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Mar 2021.
- Background: PubMed 22818936Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT; Lancet Physical Activity Series Working Group. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012 Jul 21;380(9838):219-29. doi: 10.1016/S0140-6736(12)61031-9.
- Background: PubMed 24126387Strath SJ, Kaminsky LA, Ainsworth BE, Ekelund U, Freedson PS, Gary RA, Richardson CR, Smith DT, Swartz AM; American Heart Association Physical Activity Committee of the Council on Lifestyle and Cardiometabolic Health and Cardiovascular, Exercise, Cardiac Rehabilitation and Prevention Committee of the Council on Clinical Cardiology, and Council. Guide to the assessment of physical activity: Clinical and research applications: a scientific statement from the American Heart Association. Circulation. 2013 Nov 12;128(20):2259-79. doi: 10.1161/01.cir.0000435708.67487.da. Epub 2013 Oct 14.
- Background: PubMed 30193830Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet Glob Health. 2018 Oct;6(10):e1077-e1086. doi: 10.1016/S2214-109X(18)30357-7. Epub 2018 Sep 4.
- Background: PubMed 16294115Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S523-30. doi: 10.1249/01.mss.0000185658.28284.ba.
- Background: PubMed 32832147Pisanu S, Deledda A, Loviselli A, Huybrechts I, Velluzzi F. Validity of Accelerometers for the Evaluation of Energy Expenditure in Obese and Overweight Individuals: A Systematic Review. J Nutr Metab. 2020 Aug 4;2020:2327017. doi: 10.1155/2020/2327017. eCollection 2020.
- Background: PubMed 28146576Doherty A, Jackson D, Hammerla N, Plotz T, Olivier P, Granat MH, White T, van Hees VT, Trenell MI, Owen CG, Preece SJ, Gillions R, Sheard S, Peakman T, Brage S, Wareham NJ. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One. 2017 Feb 1;12(2):e0169649. doi: 10.1371/journal.pone.0169649. eCollection 2017.
- Background: PubMed 27544533Hoogendijk EO, Deeg DJ, Poppelaars J, van der Horst M, Broese van Groenou MI, Comijs HC, Pasman HR, van Schoor NM, Suanet B, Thomese F, van Tilburg TG, Visser M, Huisman M. The Longitudinal Aging Study Amsterdam: cohort update 2016 and major findings. Eur J Epidemiol. 2016 Sep;31(9):927-45. doi: 10.1007/s10654-016-0192-0. Epub 2016 Aug 20.
- Background: PubMed 23117467Arnardottir NY, Koster A, Van Domelen DR, Brychta RJ, Caserotti P, Eiriksdottir G, Sverrisdottir JE, Launer LJ, Gudnason V, Johannsson E, Harris TB, Chen KY, Sveinsson T. Objective measurements of daily physical activity patterns and sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study. Age Ageing. 2013 Mar;42(2):222-9. doi: 10.1093/ageing/afs160. Epub 2012 Oct 31.
- Background: PubMed 17058102Crouter SE, Churilla JR, Bassett DR Jr. Estimating energy expenditure using accelerometers. Eur J Appl Physiol. 2006 Dec;98(6):601-12. doi: 10.1007/s00421-006-0307-5. Epub 2006 Oct 21.
- Background: PubMed 27931188Barnett A, van den Hoek D, Barnett D, Cerin E. Measuring moderate-intensity walking in older adults using the ActiGraph accelerometer. BMC Geriatr. 2016 Dec 8;16(1):211. doi: 10.1186/s12877-016-0380-5.
- Background: PubMed 16294114Matthew CE. Calibration of accelerometer output for adults. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S512-22. doi: 10.1249/01.mss.0000185659.11982.3d.
- Background: PubMed 27031744Koster A, Shiroma EJ, Caserotti P, Matthews CE, Chen KY, Glynn NW, Harris TB. Comparison of Sedentary Estimates between activPAL and Hip- and Wrist-Worn ActiGraph. Med Sci Sports Exerc. 2016 Aug;48(8):1514-1522. doi: 10.1249/MSS.0000000000000924.
- Individual participant dataSharing planned: No. All personal data will become anonymized and handled with full confidentiality in compliance with the Personal Data Processing Act and GDPR. The procedure of personal data processing will be reported to the Danish Data Protection Agency (Datatilsynet) in University of Southern Denmark. In this study protocol, only the anonymized urine and saliva samples will be sent abroad for analysis (details described earlier) with no linkage to any other personal data (e.g. CPR number, address, telephone number etc..).
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Paolo Caserotti, PhD principal investigator
Department of Sports and Clinical Biomechanics, University of Southern Denmark
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of no Condition, Community-dwelling 80+ Older Adults, run by University of Southern Denmark at 1 site in Denmark.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 29 Mar 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Denmark. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Li-Tang Tsai, PhD (+45 6550 7572, ltsai@health.sdu.dk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accelerometer-assessed physical activity in free-living condition (time frame: Through study completion, an average of 14 days). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04821713, which also lists 19 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Mar 2021.