Number of days required to estimate physical activity constructs objectively measured in different age groups: Findings from three Brazilian (Pelotas) population-based birth cohorts

English version

Autoři: Luiza Isnardi Cardoso Ricardo ^aff001; Andrea Wendt ^aff001; Leony Morgana Galliano ^aff002; Werner de Andrade Muller ^aff002; Gloria Izabel Niño Cruz ^aff001; Fernando Wehrmeister ^aff001; Soren Brage ^aff003; Ulf Ekelund ^aff004; Inácio Crochemore M. Silva ^aff001
Působiště autorů: Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil ^aff001; Postgraduate Program in Physical Education, Federal University of Pelotas, Pelotas, Brazil ^aff002; MRC Epidemiology Unit, University of Cambridge, Cambridge, England, United Kingdom ^aff003; Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway ^aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0216017

Souhrn

Purpose

The present study aims to estimate the minimum number of accelerometer measurement days needed to estimate habitual physical activity (PA) among 6- (2010), 18- (2011) and 30- (2012) year-old participants, belonging to three population-based Brazilian birth cohorts.

Method

PA was assessed by triaxial wrist-worn GENEActiv accelerometers and the present analysis is restricted to participants with at least 6 consecutive days of measurement. Accelerometer raw data were analyzed with R-package GGIR. Description of PA measures (overall PA, moderate-to-vigorous PA (MVPA), light PA (LPA)) on weekdays and weekend days were conducted, and statistical differences were tested with chi-squared and Kruskal-Wallis tests. Spearman Brown Formulae was applied to test reliability of different number of days of accelerometer use.

Results

Differences between week and weekend days regarding LPA, MVPA and overall PA, were only observed among 30-year-olds. Higher levels of MVPA (p = 0.006) and overall PA (p<0.001) were identified on weekdays. For overall PA, to achieve a reliability coefficient >0.70, two and three days of measurement were needed in adults and children, respectively. For LPA, a reliability coefficient >0.70 was achieved with five days in 6-year-old children, three days in 18-year-old young adults, and four days in 30-year-old adults. Considering MVPA, four days would be necessary to represent a week of measurement among all cohort groups.

Conclusion

Our results show that four and five measurement days are needed to estimate all habitual PA constructs, for children and adults, respectively. Also, among 30-year-old adults, it is important to make efforts towards weekend days measurement.

Klíčová slova:

Cohort studies – Physical activity – Age groups – Brazil – Exercise – Young adults – Research validity – Accelerometers

Zdroje

1. Arena R, McNeil A, Sagner M, Hills AP. The Current Global State of Key Lifestyle Characteristics: Health and Economic Implications. Prog Cardiovasc Dis. 2017;59: 422–429. doi: 10.1016/j.pcad.2017.02.002 28216110

2. Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380: 219–229. doi: 10.1016/S0140-6736(12)61031-9 22818936

3. Sallis JF, Bull F, Guthold R, Heath GW, Inoue S, Kelly P, et al. Progress in physical activity over the Olympic quadrennium. Lancet. 2016;388: 1325–1336. doi: 10.1016/S0140-6736(16)30581-5 27475270

4. Ainsworth B, Cahalin L, Buman M, Ross R. The Current State of Physical Activity Assessment Tools. Prog Cardiovasc Dis. 2015;57: 387–395. doi: 10.1016/j.pcad.2014.10.005 25446555

5. Troiano RP, McClain JJ, Brychta RJ, Chen KY. Evolution of accelerometer methods for physical activity research. Br J Sports Med. 2014;48: 1019–1023. doi: 10.1136/bjsports-2014-093546 24782483

6. Chen KY, Bassett DR. The technology of accelerometry-based activity monitors: current and future. Med Sci Sports Exerc. 2005;37: S490–500. Available: http://www.ncbi.nlm.nih.gov/pubmed/16294112 doi: 10.1249/01.mss.0000185571.49104.82 16294112

7. Cain KL, Sallis JF, Conway TL, Van Dyck D, Calhoon L. Using Accelerometers in Youth Physical Activity Studies: A Review of Methods. J Phys Act Heal. 2013;10: 437–450. doi: 10.1123/jpah.10.3.437 23620392

8. Ward DS, Evenson KR, Vaughn A, Rodgers AB, Troiano RP. Accelerometer use in physical activity: Best practices and research recommendations. Medicine and Science in Sports and Exercise. 2005. pp. S582–8. doi: 10.1249/01.mss.0000185292.71933.91 16294121

9. Pedišić Ž, Bauman A. Accelerometer-based measures in physical activity surveillance: current practices and issues. Br J Sports Med. 2015;49: 219–223. doi: 10.1136/bjsports-2013-093407 25370153

10. Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nyström C, Mora-Gonzalez J, Löf M, et al. Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations. Sport Med. 2017;47: 1821–1845. doi: 10.1007/s40279-017-0716-0 28303543

11. Dillon CB, Fitzgerald AP, Kearney PM, Perry IJ, Rennie KL, Kozarski R, et al. Number of Days Required to Estimate Habitual Activity Using Wrist-Worn GENEActiv Accelerometer: A Cross-Sectional Study. PLoS One. 2016;11: e0109913. doi: 10.1371/journal.pone.0109913 27149674

12. Addy CL, Trilk JL, Dowda M, Byun W, Pate RR. Assessing Preschool Children’s Physical Activity: How Many Days of Accelerometry Measurement. Pediatr Exerc Sci. 2014;26: 103–109. doi: 10.1123/pes.2013-0021 24092773

13. Hart TL, Swartz AM, Cashin SE, Strath SJ. How many days of monitoring predict physical activity and sedentary behaviour in older adults? Int J Behav Nutr Phys Act. 2011;8: 62. doi: 10.1186/1479-5868-8-62 21679426

14. Matthews CE, Keadle SK, Troiano RP, Kahle L, Koster A, Brychta R, et al. Accelerometer-measured dose-response for physical activity, sedentary time, and mortality in US adults. Am J Clin Nutr. 2016;104: 1424–1432. doi: 10.3945/ajcn.116.135129 27707702

15. Scheers T, Philippaerts R, Lefevre J. Variability in physical activity patterns as measured by the SenseWear Armband: how many days are needed? Eur J Appl Physiol. 2012;112: 1653–1662. doi: 10.1007/s00421-011-2131-9 21874552

16. Trost SG, Pate RR, Freedson PS, Sallis JF, Taylor WC. Using objective physical activity measures with youth: How many days of monitoring are needed? Med Sci Sports Exerc. 2000;32: 426–431. doi: 10.1097/00005768-200002000-00025 10694127

17. Roscoe CMP, James RS, Duncan MJ. Accelerometer-Based Physical Activity Levels Differ between Week and Weekend Days in British Preschool Children. J Funct Morphol Kinesiol. 2019;4: 65. doi: 10.3390/jfmk4030065

18. Treuth MS, Catellier DJ, Schmitz KH, Pate RR, Elder JP, McMurray RG, et al. Weekend and weekday patterns of physical activity in overweight and normal-weight adolescent girls. Obesity. 2007;15: 1782–1788. doi: 10.1038/oby.2007.212 17636097

19. Gonçalves H, Assunção MC, Wehrmeister FC, Oliveira IO, Barros FC, Victora CG, et al. Cohort Profile update: The 1993 Pelotas (Brazil) Birth Cohort follow-up visits in adolescence. Int J Epidemiol. 2014;43: 1082–1088. doi: 10.1093/ije/dyu077 24729426

20. Horta BL, Gigante DP, Goncalves H, dos Santos Motta J, Loret de Mola C, Oliveira IO, et al. Cohort Profile Update: The 1982 Pelotas (Brazil) Birth Cohort Study. Int J Epidemiol. 2015;44: 441–441e. doi: 10.1093/ije/dyv017 25733577

21. Santos IS, Barros AJ, Matijasevich A, Zanini R, Chrestani Cesar MA, Camargo-Figuera FA, et al. Cohort Profile Update: 2004 Pelotas (Brazil) Birth Cohort Study. Body composition, mental health and genetic assessment at the 6 years follow-up. Int J Epidemiol. 2014;43: 1437–1437f. doi: 10.1093/ije/dyu144 25063002

22. Hildebrand M, Van Hees VT, Hansen BH, Ekelund U. Age group comparability of raw accelerometer output from wrist-and hip-worn monitors. Med Sci Sports Exerc. 2014;46: 1816–1824. doi: 10.1249/MSS.0000000000000289 24887173

23. Esliger DW, Rowlands A V., Hurst TL, Catt M, Murray P, Eston RG. Validation of the GENEA accelerometer. Med Sci Sports Exerc. 2011;43: 1085–1093. doi: 10.1249/MSS.0b013e31820513be 21088628

24. van Hees VT, Gorzelniak L, Dean León EC, Eder M, Pias M, Taherian S, et al. Separating Movement and Gravity Components in an Acceleration Signal and Implications for the Assessment of Human Daily Physical Activity. PLoS One. 2013;8: e61691. doi: 10.1371/journal.pone.0061691 23626718

25. da Silva IC, van Hees VT, Ramires V V, Knuth AG, Bielemann RM, Ekelund U, et al. Physical activity levels in three Brazilian birth cohorts as assessed with raw triaxial wrist accelerometry. Int J Epidemiol. 2014;43: 1959–1968. doi: 10.1093/ije/dyu203 25361583

26. World Health Organization. Obesity: preventing and managing the global epidemic. Geneva; 2000.

27. De Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85: 660–667. doi: 10.2471/BLT.07.043497 18026621

28. Rutstein SO. Steps to constructing the new DHS Wealth Index. Usaid. 2015. Available: https://www.dhsprogram.com/programming/wealthindex/Steps_to_constructing_the_new_DHS_Wealth_Index.pdf

29. Eisinga R, Grotenhuis M te, Pelzer B. The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown? Int J Public Health. 2013;58: 637–642. doi: 10.1007/s00038-012-0416-3 23089674

30. Landers R. Computing (ICC) as Intraclass Estimates Correlations of Interrater Reliability in SPSS. The Winnower. 2015; 1–4. doi: 10.15200/winn.143518.81744

31. Doherty A, Jackson D, Hammerla N, Plötz T, Olivier P, Granat MH, et al. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One. 2017;12: e0169649. doi: 10.1371/journal.pone.0169649 28146576

32. Nilsson A, Anderssen SA, Andersen LB, Froberg K, Riddoch C, Sardinha LB, et al. Between- and within-day variability in physical activity and inactivity in 9- and 15-year-old European children. Scand J Med Sci Sports. 2008;19: 10–18. doi: 10.1111/j.1600-0838.2007.00762.x 18248534

33. Bassett DR, Troiano RP, Mcclain JJ, Wolff DL. Accelerometer-based physical activity: Total volume per day and standardized measures. Med Sci Sports Exerc. 2015;47: 833–838. doi: 10.1249/MSS.0000000000000468 25102292

34. Jaeschke L, Steinbrecher A, Jeran S, Konigorski S, Pischon T. Variability and reliability study of overall physical activity and activity intensity levels using 24 h-accelerometry-assessed data. BMC Public Health. 2018;18: 530. doi: 10.1186/s12889-018-5415-8 29678152

35. Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005;37: S531–43. Available: http://www.ncbi.nlm.nih.gov/pubmed/16294116 doi: 10.1249/01.mss.0000185657.86065.98 16294116

36. Brasil. Decreto de lei 5.452—Consolidação das Leis do Trabalho (CLT). 1943.

37. Hislop J, Law J, Rush R, Grainger A, Bulley C, Reilly JJ, et al. An investigation into the minimum accelerometry wear time for reliable estimates of habitual physical activity and definition of a standard measurement day in pre-school children. Physiol Meas. 2014;35: 2213–2228. doi: 10.1088/0967-3334/35/11/2213 25340328

38. van Hees VT, Sabia S, Jones SE, Wood AR, Anderson KN, Kivimäki M, et al. Estimating sleep parameters using an accelerometer without sleep diary. Sci Rep. 2018;8: 12975. doi: 10.1038/s41598-018-31266-z 30154500

39. Kim Y, Beets MW, Welk GJ. Everything you wanted to know about selecting the “right” Actigraph accelerometer cut-points for youth, but…: A systematic review. J Sci Med Sport. 2012;15: 311–321. doi: 10.1016/j.jsams.2011.12.001 22306372

40. Bull F, Armstrong T, Dixon T, Ham S, Neiman A, Pratt M. Comparative Quantification of Health Risks. Global and Regional Burden of Disease Attributable to Selected Major Risk Factors: Physical inactivity. Geneva: World Health Organization; 2004.

41. Barr AL, Young EH, Sandhu MS. Objective measurement of physical activity: Improving the evidence base to address non-communicable diseases in Africa. BMJ Glob Heal. 2018;3. doi: 10.1136/bmjgh-2018-001044 30364334