Clinical trial NCT06379802: Lifestyle Intervention With Physical Activity and Diet
Official title: Lifestyle Intervention With Physical Activity and Diet for Precision Health in Individuals With Overweight: a 6-month Pilot Randomized Controlled Trial (LI-PAD)
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Overweight
Keywords: Overweight
Healthy Lifestyle
Risk Reduction Behaviour
Randomized Controlled Trial
Lead sponsor: Vastra Gotaland Region
Sponsor class: OTHER_GOV
First posted: 2024-04-23
Enrollment: 120
Sex: ALL
Minimum age (years): 45
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: The aim of this pilot randomized controlled trial LI-PAD is to identify whether a 6-month intervention approach to individually optimize lifestyle behavior, physical activity, and diet, is feasible and leads to larger improvements in body weight, cardiovascular disease risk factors, and health-related quality of life compared to simple written lifestyle advice, in individuals with overweight or obesity.

The intervention group will be offered individual support for lifestyle behavioral change (precision health) and the control group will be offered written lifestyle advice, following national recommendations. In total, 60 population-based participants and 60 controls from the Gothenburg area, aged 45-65 years, will be recruited.

Detailed description: Individualized lifestyle Intervention with Physical Activity and Diet as precision health in individuals with overweight: a 6-month pilot randomized controlled trial (LI-PAD)

BACKGROUND Individuals with obesity and type 2 diabetes have an increased risk of cardiovascular disease (CVD). Lifestyle changes with physical activity (PA) and diet have been associated with temporary improvements in these risk factors. However, sustained behavior changes are difficult to achieve. In Sweden and globally, the built environment promotes overweight and obesity through high availability of cheap ultra-processed energy-dense foods and drinks and low possibility of physical activity. Although the recommendation is to apply an individualized approach, few studies have applied this in clinical practice. PA on prescription, using an individualized approach, has been partly implemented into Swedish health care, resulting in short- and long-term favorable effects of PA. However, an individualized approach to modifying diet has not yet been incorporated, despite evidence showing that interventions targeting PA and diet together have a greater effect on obesity. Another crucial limitation is that PA and diet recommendations are not developed for individual application.

Previous research has shown that it is important to consider individual adaption to medical conditions (e.g. risk profile, symptoms, comorbidities) and to psychosocial factors (e.g. preferences, barriers-facilitators, readiness-to-change). It is also know that individuals require support for behavioral change (e.g., counseling/coaching, group activities, education, nudging). Furthermore, there is a link between unhealthy food environments, unhealthy food consumptions, and food-related diseases, but results vary. Previous intervention studies have shown that an unhealthy food environment is a barrier of adherence to intended behavioral changes. However, it is unclear which components are particularly important, how much of each of them should be included, and whether freedom of choice is a more efficient option compared to offering a more standardized solution as in most randomized controlled trials (RCTs).

To prescribe optimal PA for the underlying disease, the investigators are currently developing accelerometer-based PA measures and recommendations adapted to individual fitness. The optimal diet prescription targets weight reduction, primarily as body fat, by restriction energy intake below the energy need. Although rapid early weight loss is important for sustained effects, too great energy restriction (due to unrealistic goals or applying a standard treatment) results in increased hunger and reduced metabolism, not leading to larger weight reduction when clinically applied. Research supports up to 10% weight loss at 6 months by applying a \~500 kcal/d reduction of energy intake below energy need. Energy need is most accurately determined with the doubly labeled water method but is too expensive for clinical use. An alternative method commonly used is to determine resting energy expenditure (REE), calculated from individual characteristics such as body weight, and multiplied with a factor for the PA level. However, REE determined using body weight is not accurate in obesity, and the most optimal equation considering body composition is too imprecise at an individual level. REE based on measured oxygen (O2) and carbon dioxide (CO2) exchange is preferred and can also be used to monitor the respiratory quotient (RQ=CO2/O2), which is an indicator of fat metabolism. Measured O2 and CO2 are inexpensive and can be used together with measured food intake for more individualized diet prescription and to track the effects of the intervention on metabolism and use of body fat.

The present study represents a unique progress of lifestyle intervention programs away from the more standardized randomized controlled trials to approach precision health:1) adaption to medical conditions and psychosocial factors, 2) individualized PA and diet advice based on individual and environmental measurement, 3) aids for achieving goals using education, skills training and supports (Figure 1). Although individual adaptions to medical conditions and psychosocial factors are already performed in health care, individualization of PA, diet, and support for behavioral change has rarely been implemented and evaluated. This individualization requires additional resources in health care. Therefore, it is important to determine the benefits of this approach and in future studies also follow up with cost-benefit analyses.

Previous received funding from the Swedish Heart-Lung Foundation for two successive research projects, "Aerobic fitness for cardiovascular health - a Swedish CArdioPulmonary bioimage study (SCAPIS)" targeting improved physical activity recommendations (20180379) and "Individualized physical activity recommendations for cardiovascular health: a SCAPIS program in precision health" (20210270),is the foundation for refined individualized exercise prescriptions, using the individual fitness levels. Knowledge from this research forms an important part of our current individualized lifestyle intervention program.

OBJECTIVES - PARADIGM AND HYPOTHESES This pilot study aims to identify whether an approach to optimize lifestyle behavior interventions with PA and diet at an individual environmental level leads to larger improvements in body weight, CVD risk factors, and health-related quality of life compared to simple lifestyle advice, and is feasible, in overweight individuals. The hypothesis is that the precision health approach is feasible and superior to simple lifestyle advice. The knowledge gained will be used to design a larger long-term intervention study. The paradigm "one size fits all" is not optimal, why our paradigm shift towards precision health is required.

Work plan - Overview LI-PAD is a randomized controlled trial with two arms (Figure 2). The intervention group will be offered individual precision health (Figure 1) and the control group usual care, defined as written lifestyle advice based on the general recommendations for diet and PA. In total, 60 population-based participants and 60 controls from the Gothenburg area will be recruited. LI-PAD includes outcome evaluation on change in body weight (primary outcome), risk factors for CVD, PA, and diet, and quality of life (secondary), process evaluation of feasibility, and identification of barriers and facilitators from qualitative data.

PARTICIPANTS Men and women aged 45-65 years will be recruited from the census register in the Gothenburg area and invited by mail. Included are individuals with a body mass index (BMI) of ≥28 and equal to or less than 34. Individuals with known coronary artery disease (clinical symptoms/earlier event) or other contraindications such as inability to understand language or unable to perform lifestyle interventions, will be excluded.

OUTCOME MEASURES (Figure 2)

PRIMARY OUTCOME (all participants) Weight reduction from 0 to 6 months.

SECONDARY OUTCOMES (all participants)

1. CVD risk factor change: weight, BMI, waist and hip circumferences; blood pressure, HbA1c, cholesterol, HDL, LDL; aerobic fitness (VO2max).
2. Physical activity by accelerometry, self-reported physical activity level using the Saltin Grimby Physical Activity Level Scale (SGPALS); muscle strength and endurance; diet pattern by the food frequency questionnaire Meal-Q; and measured REE.
3. Health-related quality of life change using the EuroQol Group's EuroQol Five Dimensions and 3 Levels (EQ5D-3L) index score and EQ-Visual Analogue Scale (VAS).

ADDITIONAL OUTCOMES (intervention group)

1. Process evaluation: to determine feasibility of the study by measures of implementation quality, intervention sessions provided, intervention sessions received, satisfaction with intervention components,
2. Qualitative evaluation: perceived barriers and facilitators for behavioral change.

INTERVENTION GROUP Figure 1 presents a detailed description of the Lifestyle Intervention with Physical Activity and Diet (LI-PAD) for precision health.

CONTROL GROUP - one size fits all (Figure 2) The control group will receive usual care defined as simple lifestyle advice based on the general recommendations for diet and PA, including a healthy and varied diet, at least 300 mins/week of medium-intensity aerobic PA, and resistance training 2 times per week.

STATISTICAL ANALYSES Multilevel mixed modeling for repeated measures will be applied, to determine variation both at group and individual levels. Both continuous and categorical variables will be included, therefore both linear and logistic analyses will be employed. Some of the measures may include multiple interrelated categories (e.g., physical activity intensity categories). Therefore, regression models considering multicollinearity will be used (e.g., partial least square modeling). To map interrelationships between intervention components and outcome measures, statistical analyses can be expanded to structural equation modeling with or without partial least square regression for repeated measurement. Peer protocol analyses will be applied.

The primary intervention target is the reduction of body weight. The evidence-based and clinically relevant weight change has been determined to be 5-10% at 6 months. In the previous Look Action for Health in Diabetes (AHEAD) study, the mean (SD) % weight change up to one year in the intervention group was 8.5%. The corresponding value in the control group was 0.6 (10)%. Look AHEAD is one of the most comprehensive, and evaluated lifestyle behavior interventions with diet and physical activity. Data from the previous Look AHEAD study were used to estimate the sample size of each group in the present study:

To detect a mean (standard deviation, SD) reduction of 5 (10)% in the intervention group relative to the control group (effect size) with 80% power would include at least 60 participants in each group.

Our previous extensive research in the field of physical activity and cardiovascular health-epidemiology, measurement, methodology (accelerometry, fitness tests) and clinical aspects are all relevant to the present application. Specifically, the investigators have improved the processing of accelerometer data to useful measures of PA and the statistics to analyze more complex accelerometer data for group differences, individual development over time, and associations with measures of CVD risk. Based on this research, the investigators are currently developing accelerometer-based PA measures and recommendations adapted to individual fitness.

COLLABORATORS AND RESEARCH NETWORKS The affiliated research environment offers expertise in methodological, epidemiological, and clinical research. Collaborations and research networks include the SCAPIS, national network for quality and research (SWEDEHEART), and HPI study networks, the Swedish School of Exercise and Sports Science (GIH) as well as the Department of Food and Nutrition, and Sport Science (IKI), with IKI adding knowledge and skills in health promotion and lifestyle behavior change to the project. Group training will be led by physiotherapists at Sahlgrenska University Hospital/Östra.

Eligibility criteria: Inclusion Criteria:

* Age 45-65 years
* A body mass index (BMI) of ≥28 and \<35

Exclusion Criteria:

* Known coronary artery disease (clinical symptoms/earlier event)
* Other contraindications such as inability to understand language or unable to perform lifestyle interventions

Primary outcomes:
measure: Change in body weight 1
timeFrame: From baseline to 6 months
measure: Change in body weight 2
timeFrame: From baseline to 1 month (intervention group)
measure: Change in body weight 3
timeFrame: From 1 month to 3 months (intervention group)
measure: Change in body weight 4
timeFrame: From 3 months to 6 months (intervention group)
Secondary outcomes:
measure: Length in cm
timeFrame: From baseline to 6 months
measure: Weight in kilograms
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Body Mass Index (BMI)
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Waist-to-hip ratio 1
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Waist-to-hip ratio 2
timeFrame: From baseline to 1 month (intervention group)
measure: Cardiovascular disease risk factor change - Waist-to-hip-ratio 3
timeFrame: From 1 month to 3 months (intervention group)
measure: Cardiovascular disease risk factor change - Waist-hip-ratio 4
timeFrame: From 3 months to 6 months (intervention group)
measure: Cardiovascular disease risk factor change - Blood pressure 1
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Blood pressure 2
timeFrame: From baseline to 1 month (intervention group)
measure: Cardiovascular disease risk factor change - Blood pressure 3
timeFrame: From 1 month to 3 months (intervention group)
measure: Cardiovascular disease risk factor change - Blood pressure 4
timeFrame: From 3 month to 6 months (intervention group)
measure: Cardiovascular disease risk factor change - Long-term blood glucose control using glycated haemoglobin (HbA1c)
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Serum (total) Cholesterol (S-Cholesterol)
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - High density lipoprotein (HDL)
timeFrame: From baseline to 6 months.
measure: Cardiovascular disease risk factor change - Low densitiy lipoprotein (LDL)
timeFrame: From baseline to 6 months.
measure: Cardiovascular disease risk factor change - Triglycerides
timeFrame: From baseline to 6 months.
measure: Cardiovascular disease risk factor change - Aerobic fitness (predicted V02 max)
timeFrame: From baseline to 6 months.
measure: Cardiovascular disease risk factor change - Physical activity level
timeFrame: From baseline to 6 months
measure: Change in functional lower extremity muscle strength
timeFrame: From baseline to 6 months
measure: Change in upper extremity muscle strength - Hand grip strength
timeFrame: From baseline to 6 months
measure: Change in muscle strength - Shoulder flexion
timeFrame: From baseline to 6 months
measure: Change in muscle strength - Ankle Plantar
timeFrame: From baseline to 6 months
measure: Cardiovascular disease risk factor change - Healthy food intake
timeFrame: From baseline to 6 months
measure: Change in resting energy expenditure 1
timeFrame: From baseline to 6 months
measure: Change in resting energy expenditure 2
timeFrame: From baseline to 1 month (intervention group)
measure: Change in resting energy expenditure 3
timeFrame: From 1 month to 3 months (intervention group)
measure: Change in resting energy expenditure 4
timeFrame: From 3 months to 6 months (intervention group)
measure: Change in respiratory quotient 1
timeFrame: From baseline to 6 months
measure: Change in respiratory quotient 2
timeFrame: From baseline to 1 month (intervention group)
measure: Change in respiratory quotient 3
timeFrame: From 1 month to 3 months (intervention group)
measure: Change in respiratory quotient 4
timeFrame: From 3 months to 6 months (intervention group)
measure: Change in health-related quality of life - Proportions of problems in five dimensions
timeFrame: From baseline to 6 months
measure: Change in health-related quality of life - Index score
timeFrame: From baseline to 6 months
measure: Change in health-related quality of life - Visual analog score of present health status
timeFrame: From baseline to 6 months
measure: Change in health-related quality of life - Health status categories
timeFrame: From baseline to 6 months
measure: Change in self-reported physical activity level
timeFrame: From baseline to 6 months
measure: Change in exposure pattern to the food environment
timeFrame: From baseline to 6 months
measure: Change in exposure pattern to the built environment
timeFrame: From baseline to 6 months
measure: Process evaluation measure 1 - Extent to which intervention was implemented as planned
timeFrame: During the 6 months intervention (intervention group)
measure: Process evaluation measure 2 - Number of sessions of each intervention component delivered
timeFrame: During the 6 months intervention (intervention group)
measure: Process evaluation measure 3 - Number of sessions of each intervention component received
timeFrame: During the 6 months intervention (intervention group)
measure: Process evaluation measure 4 - Satisfaction with individual lifestyle counselling
timeFrame: After 6 months intervention (intervention group)
measure: Process evaluation measure 5 - Satisfaction with the lifestyle school
timeFrame: After 6 months intervention (intervention group)
measure: Process evaluation measure 6A - Perceived facilitators
timeFrame: After 6 months intervention (intervention group)
measure: Process evaluation measure 6B - Perceived barriers
timeFrame: After 6 months intervention (intervention group)
measure: Process evaluation measure 7 - Reach
timeFrame: From start of recruitment to end of 6 months followup measurements
Other outcomes:
Locations:
city: Gothenburg
country: Sweden
facility: Centre for lifestyle intervention
Study officials:
affiliation: Sahlgrenska University Hospital (and University of Gothenburg)
name: Mats Börjesson, Professor
role: PRINCIPAL_INVESTIGATOR
References:
citation: Look AHEAD Research Group; Pi-Sunyer X, Blackburn G, Brancati FL, Bray GA, Bright R, Clark JM, Curtis JM, Espeland MA, Foreyt JP, Graves K, Haffner SM, Harrison B, Hill JO, Horton ES, Jakicic J, Jeffery RW, Johnson KC, Kahn S, Kelley DE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montgomery B, Nathan DM, Patricio J, Peters A, Redmon JB, Reeves RS, Ryan DH, Safford M, Van Dorsten B, Wadden TA, Wagenknecht L, Wesche-Thobaben J, Wing RR, Yanovski SZ. Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes: one-year results of the look AHEAD trial. Diabetes Care. 2007 Jun;30(6):1374-83. doi: 10.2337/dc07-0048. Epub 2007 Mar 15.
citation: Look AHEAD Research Group; Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013 Jul 11;369(2):145-54. doi: 10.1056/NEJMoa1212914. Epub 2013 Jun 24.
citation: Thom G, Lean M. Is There an Optimal Diet for Weight Management and Metabolic Health? Gastroenterology. 2017 May;152(7):1739-1751. doi: 10.1053/j.gastro.2017.01.056. Epub 2017 Feb 15.
citation: Hassmén P, Wisén A, Hagströmer M. [Individanpassad rådgivning om fysisk aktivitet]. In: Dohrn I, Jansson E, Börjesson M, Hagström M, editors. FYSS20211, 4th ed. Stockholm: Läkartidningens Förlag; 2021. p. 169-79.
citation: Lundqvist S, Cider A, Larsson MEH, Hagberg L, Bjork MP, Borjesson M. The effects of a 5-year physical activity on prescription (PAP) intervention in patients with metabolic risk factors. PLoS One. 2022 Oct 31;17(10):e0276868. doi: 10.1371/journal.pone.0276868. eCollection 2022.
citation: Nordic Council of Ministers. Nordic Nutrition Recommendations 2012. Integrating nutrition and physical activity. Copenhagen: Nordic Council of Ministers; 2014.
citation: Pratt M. What's new in the 2020 World Health Organization Guidelines on Physical Activity and Sedentary Behavior? J Sport Health Sci. 2021 May;10(3):288-289. doi: 10.1016/j.jshs.2021.02.004. Epub 2021 Feb 27. No abstract available.
citation: Börjesson M. [Riskbedömning vid fysisk aktivitet]. In: Dorn I, Jansson E, Börjesson M, Hagströmer M, editors. FYSS2021, 4th ed. Stockholm: Läkartidningens Förlag; 2021.
citation: Kallings L, Eriksson M, Lundqvist S, Dohrn I. [Fysisk aktivitet på recept - FaR]. In: Dohrn I, Jansson E, Börjesson M, Hagströmer M, editors. FYSS2021, 4th ed. Stockholm: Läkartidningens Förlag; 2021. p. 142-51.
citation: Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM, Millen BE, Nonas CA, Pi-Sunyer FX, Stevens J, Stevens VJ, Wadden TA, Wolfe BM, Yanovski SZ, Jordan HS, Kendall KA, Lux LJ, Mentor-Marcel R, Morgan LC, Trisolini MG, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Smith SC Jr, Tomaselli GF; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. Circulation. 2014 Jun 24;129(25 Suppl 2):S102-38. doi: 10.1161/01.cir.0000437739.71477.ee. Epub 2013 Nov 12. No abstract available.
citation: Most J, Redman LM. Impact of calorie restriction on energy metabolism in humans. Exp Gerontol. 2020 May;133:110875. doi: 10.1016/j.exger.2020.110875. Epub 2020 Feb 11.
citation: McDoniel SO, Hammond RS. A 24-week randomised controlled trial comparing usual care and metabolic-based diet plans in obese adults. Int J Clin Pract. 2010 Oct;64(11):1503-1511. doi: 10.1111/j.1742-1241.2010.02464.x.
citation: Madden AM, Mulrooney HM, Shah S. Estimation of energy expenditure using prediction equations in overweight and obese adults: a systematic review. J Hum Nutr Diet. 2016 Aug;29(4):458-76. doi: 10.1111/jhn.12355. Epub 2016 Feb 29.
citation: Miles-Chan JL, Dulloo AG, Schutz Y. Fasting substrate oxidation at rest assessed by indirect calorimetry: is prior dietary macronutrient level and composition a confounder? Int J Obes (Lond). 2015 Jul;39(7):1114-7. doi: 10.1038/ijo.2015.29. Epub 2015 Mar 16.
citation: Hollis JF, Gullion CM, Stevens VJ, Brantley PJ, Appel LJ, Ard JD, Champagne CM, Dalcin A, Erlinger TP, Funk K, Laferriere D, Lin PH, Loria CM, Samuel-Hodge C, Vollmer WM, Svetkey LP; Weight Loss Maintenance Trial Research Group. Weight loss during the intensive intervention phase of the weight-loss maintenance trial. Am J Prev Med. 2008 Aug;35(2):118-26. doi: 10.1016/j.amepre.2008.04.013.
citation: Cooney C, Daly E, McDonagh M, Ryan L. Evaluation of Measured Resting Metabolic Rate for Dietary Prescription in Ageing Adults with Overweight and Adiposity-Based Chronic Disease. Nutrients. 2021 Apr 8;13(4):1229. doi: 10.3390/nu13041229.
citation: Grimby G, Borjesson M, Jonsdottir IH, Schnohr P, Thelle DS, Saltin B. The "Saltin-Grimby Physical Activity Level Scale" and its application to health research. Scand J Med Sci Sports. 2015 Dec;25 Suppl 4:119-25. doi: 10.1111/sms.12611.
citation: Nybacka S, Berteus Forslund H, Wirfalt E, Larsson I, Ericson U, Warensjo Lemming E, Bergstrom G, Hedblad B, Winkvist A, Lindroos AK. Comparison of a web-based food record tool and a food-frequency questionnaire and objective validation using the doubly labelled water technique in a Swedish middle-aged population. J Nutr Sci. 2016 Oct 3;5:e39. doi: 10.1017/jns.2016.29. eCollection 2016.
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: Fridolfsson J, Arvidsson D, Andersen LB, Thorsson O, Wollmer P, Rosengren B, Karlsson MK, Dencker M. Physical activity spectrum discriminant analysis-A method to compare detailed patterns between groups. Scand J Med Sci Sports. 2021 Dec;31(12):2333-2342. doi: 10.1111/sms.14052. Epub 2021 Sep 23.
citation: Look AHEAD Research Group. Eight-year weight losses with an intensive lifestyle intervention: the look AHEAD study. Obesity (Silver Spring). 2014 Jan;22(1):5-13. doi: 10.1002/oby.20662.
citation: Whitehead AL, Julious SA, Cooper CL, Campbell MJ. Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable. Stat Methods Med Res. 2016 Jun;25(3):1057-73. doi: 10.1177/0962280215588241. Epub 2015 Jun 19.
citation: Fridolfsson J, Borjesson M, Ekblom-Bak E, Ekblom O, Arvidsson D. Stronger Association between High Intensity Physical Activity and Cardiometabolic Health with Improved Assessment of the Full Intensity Range Using Accelerometry. Sensors (Basel). 2020 Feb 18;20(4):1118. doi: 10.3390/s20041118.