Author(s):
- Gergely Ráthonyi
- Viktor Takács
- Róbert Szilágy
- Éva Bácsné Bába
- Anetta Müller
- Zoltán Bács
- Mónika Harangi-Rákos
- László Balogh
- Kinga Ráthonyi-Odor
Abstract:
Inadequate physical activity is currently one of the leading risk factors for mortality worldwide. University students are a high-risk group in terms of rates of obesity and lack of physical activity. In recent years, activity trackers have become increasingly popular for measuring physical activity. The aim of the present study is to examine whether university students in Hungary meet the health recommendations (10,000 steps/day) for physical activity and investigate the impact of different variables (semester-exam period, days-weekdays, days, months, sex) on the level of physical activity in free-living conditions for 3 months period. In free-living conditions, 57 healthy university students (male: 25 female: 32 mean age: 19.50 SD = 1.58) wore MiBand 1S activity tracker for 3 months. Independent sample t-tests were used to explore differences between sexes. A One-way analysis of variance (ANOVA) was used to explore differences in measures among different grouping variables and step count. A Two-way ANOVA was conducted to test for differences in the number of steps by days of the week, months, seasons and for sex differences. Tukey HSD post-hoc tests were used to examine significant differences. Students in the study achieved 10,000 steps per day on 17% of days (minimum: 0%; maximum: 76.5%; median: 11.1%). Unfortunately, 70% of the participants did not comply the 10,000 steps at least 80% of the days studied. No statistical difference were found between sexes. However, significant differences were found between BMI categories (underweight <18.50 kg/m2; normal range 18.50–24.99 kg/m2; overweight: 25.00–29.99 kg/m2 obese > 30 kg/m2, the number of steps in the overweight category was significantly lower (F = 72.073, p < 0.001). The average daily steps were significantly higher in autumn (t = 11.457, p < 0.001) than in winter. During exam period average steps/day were significantly lower than during fall semester (t = 13.696, p < 0.001). On weekdays, steps were significantly higher than on weekends (F = 14.017, p < 0.001), and even within this, the greatest physical activity can be done by the middle of the week. Our data suggest that university students may be priority groups for future physical activity interventions. Commercial activity trackers provide huge amount of data for relatively low cost therefore it has the potential to objectively analyze physical activity and plan interventions.
Description:
https://doi.org/10.3389/fpubh.2021.661471
References:
- Központi Statisztikai Hivatal. Egészségi állapot és egészségmagatartás, 2016–2017. Budapest: Központi Statisztikai Hivatal (2018). 23p.
2. GBD 2015 Obesity Collaborators, Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K, et al. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. (2017) 377:13–27. doi: 10.1056/NEJMoa1614362
3. Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants. Lancet Child Adolesc Heal. (2020) 4:23–35. doi: 10.1016/S2352-4642(19)30323-2
4. Ács P, Prémusz V, Melczer CS, Bergier J, Ferdinand S, Jan J, et al. Nemek közötti különbségek vizsgálata a fizikai aktivitás vonatkozásában a V4 országok egyetemista populációjának körében. Magyar Sporttudományi Szemle. (2018) 19:3–9. Available online at: http://mstt.hu/wp-content/uploads/2018/06/MSTT-Szemle-2018-02-honlapra.pdf
5. Street SJ, Wells JCK, Hills AP. Windows of opportunity for physical activity in the prevention of obesity. Obes Rev. (2015) 16:857–70. doi: 10.1111/obr.12306
6. Wilks DC, Besson H, Lindroos AK, Ekelund U. Objectively measured physical activity and obesity prevention in children, adolescents and adults: a systematic review of prospective studies. Obes Rev. (2011) 12:119–29. doi: 10.1111/j.1467-789X.2010.00775.x
7. Wareham NJ, van Sluijs EMF, Ekelund U. Physical activity and obesity prevention: a review of the current evidence. Proc Nutr Soc. (2005) 64:229–47. doi: 10.1079/PNS2005423
8. Magnussen CG, Smith KJ, Juonala M. When to prevent cardiovascular disease? As early as possible: lessons from prospective cohorts beginning in childhood. Curr Opin Cardiol. (2013) 28:561–8. doi: 10.1097/HCO.0b013e32836428f4
9. Warburton DER, Nicol CW, Bredin SSD. Health benefits of physical activity: the evidence. CMAJ. (2006) 174:801–9. doi: 10.1503/cmaj.051351
10. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: updated recommendation for adults from the American college of sports medicine and the American heart association. Med Sci Sports Exerc. (2007) 39:1423–34. doi: 10.1249/mss.0b013e3180616b27
11. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT, et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. (2012) 380:219–29. doi: 10.1016/S0140-6736(12)61031-9
12. Waxman A. WHO global strategy on diet, physical activity and health. Food Nutr. Bull. (2004) 25:292–302. doi: 10.1177/156482650402500310
13. Gracia-Marco L, Moreno LA, Ortega FB, Len F, Sioen I, Kafatos A, et al. Levels of physical activity that predict optimal bone mass in adolescents: the HELENA study. Am J Prev Med. (2011) 40:599–607. doi: 10.1016/j.amepre.2011.03.001
14. Henriksen A, Mikalsen MH, Woldaregay AZ, Muzny M, Hartvigsen G, Hopstock LA, et al. Using fitness trackers and smartwatches to measure physical activity in research: analysis of consumer wrist-worn wearables. J Med Internet Res. (2018) 20:1–19. doi: 10.2196/jmir.9157
15. Booth FW, Roberts CK, Laye MJ. Lack of exercise is a major cause of chronic diseases. Compr Physiol. (2012) 2:1143–211. doi: 10.1002/cphy.c110025
16. WHO. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World. Geneva: World Health Organization (2018).
17. World Health Organization. Hungary Physical Activity Factsheet 2018. Available online at: https://www.euro.who.int/__data/assets/pdf_file/0004/382513/hungary-eng.pdf (accessed January 20, 2020).
18. Craigie AM, Lake AA, Kelly SA, Adamson AJ, Mathers JC. Tracking of obesity-related behaviours from childhood to adulthood: a systematic review. Maturitas. (2011) 70:266–84. doi: 10.1016/j.maturitas.2011.08.005
19. Ortega FB, Konstabel K, Pasquali E, Ruiz JR, Hurtig-Wennlöf A, Mäestu J, et al. Objectively measured physical activity and sedentary time during childhood, adolescence and young adulthood: a cohort study. PLoS ONE. (2013) 8:e60871. doi: 10.1371/journal.pone.0060871
20. Andersson C, Vasan RS. Epidemiology of cardiovascular disease in young individuals. Nat Rev Cardiol. (2018) 15:230–40. doi: 10.1038/nrcardio.2017.154
21. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the global burden of disease study 2013. Lancet. (2014) 384:766–81. doi: 10.1016/S0140-6736(14)60460-8
22. Din-Dzietham R, Liu Y, Bielo MV, Shamsa F. High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation. (2007) 116:1488–96. doi: 10.1161/CIRCULATIONAHA.106.683243
23. Khera A V, Emdin CA, Drake I, Natarajan P, Bick AG, Cook NR, et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N Engl J Med. (2016) 375:2349–58. doi: 10.1056/NEJMoa1605086
24. Gallardo-Escudero A, Alférez MJM, del Pozo EMP, Aliaga IL. The university stage does not favor the healthy life style in women students from granada. Nutr Hosp. (2015) 31:975–9. doi: 10.3305/nh.2015.31.2.8303
25. Arias-Palencia NM, Solera-Martínez M, Gracia-Marco L, Silva P, Martínez-Vizcaíno V, Cañete-García-Prieto J, et al. Levels and patterns of objectively assessed physical activity and compliance with different public health guidelines in university students. PLoS ONE. (2015) 10:e0141977. doi: 10.1371/journal.pone.0141977
26. Clemente FM, Nikolaidis PT, Martins FML, Mendes RS. Physical activity patterns in university students: Do they follow the public health guidelines? PLoS ONE. (2016) 11:e0152516. doi: 10.1371/journal.pone.0152516
27. Varela-Mato V, Cancela JM, Ayan C, Martín V, Molina A. Lifestyle and health among spanish university students: differences by gender and academic discipline. Int J Environ Res Public Health. (2012) 9:2728–41. doi: 10.3390/ijerph9082728
28. Pengpid S, Peltzer K, Kassean HK, Tsala Tsala JP, Sychareun V, Müller-Riemenschneider F. Physical inactivity and associated factors among university students in 23 low-, middle- and high-income countries. Int J Public Health. (2015) 60:539–49. doi: 10.1007/s00038-015-0680-0
29. Castro O, Bennie J, Vergeer I, Bosselut G, Biddle SJH. How sedentary are university students? A systematic review and meta-analysis. Prev Sci. (2020) 21:332–43. doi: 10.1007/s11121-020-01093-8
30. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW, et al. Correlates of physical activity: why are some people physically active and others not? Lancet. (2012) 380:258–71. doi: 10.1016/S0140-6736(12)60735-1
31. Lee PH, Yu YY, McDowell I, Leung GM, Lam TH. A cluster analysis of patterns of objectively measured physical activity in Hong Kong. Public Health Nutr. (2013) 16:1436–44. doi: 10.1017/S1368980012003631
32. Schaben JA, Furness S. Investing in college students: the role of the fitness tracker. Digit Health. (2018) 4:1–10. doi: 10.1177/2055207618766800
33. Behrens TK, Dinger MK. A preliminary investigation of college students’ physical activity patterns. Am J Health Stud. (2003) 18:169–72.
34. Matthews CE, Freedson PS, Hebert JR. Seasonal variations in household, occupational, and leisure time physical activity: longitudinal analyses from the seasonal variation of blood cholesterol study. Am J Epidemiol. (2001) 153:172–83. doi: 10.1093/aje/153.2.172
35. Tucker P, Gilliland J. The effect of season and weather on physical activity: a systematic review. Public Health. (2007) 121:909–22. doi: 10.1016/j.puhe.2007.04.009
36. Romero-Blanco C, Rodríguez-Almagro J, Onieva-Zafra MD, Parra-Fernández ML, Prado-Laguna MDC, Hernández-Martínez A. Physical activity and sedentary lifestyle in university students: changes during confinement due to the covid-19 pandemic. Int J Environ Res Public Health. (2020) 17:6567. doi: 10.3390/ijerph17186567
37. Loney T, Standage M, Thompson D, Sebire SJ, Cumming S. Self-report vs. objectively assessed physical activity: which is right for public health? J Phys Act Health. (2011) 8:62–70. doi: 10.1123/jpah.8.1.62
38. Schaller A, Rudolf K, Dejonghe L, Grieben C, Froboese I. Influencing factors on the overestimation of self-reported physical activity: a cross-sectional analysis of low back pain patients and healthy controls. Biomed Res Int. (2016) 2016:1497213. doi: 10.1155/2016/1497213
39. Kooiman TJM, Dontje ML, Sprenger SR, Krijen WP, van der Schans CP, de Groot M. Reliability and validity of ten consumer activity trackers. BMC Sport Sci Med Rehab. (2015) 7:24. doi: 10.1186/s13102-015-0018-5
40. Hicks JL, Althoff T, Sosic R, Kuhar P, Bostjancic B, King AC, et al. Best practices for analyzing large-scale health data from wearables and smartphone apps. NPJ Digit Med. (2019) 2:45. doi: 10.1038/s41746-019-0121-1
41. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R, et al. Using pedometers to increase physical activity and improve health: a systematic review. J Am Med Assoc. (2007) 298:2296–304. doi: 10.1001/jama.298.19.2296
42. El-Gayar O, Timsina P, Nawar N, Eid W. A systematic review of IT for diabetes self-management: are we there yet? Int J Med Inform. (2013) 82:637–52. doi: 10.1016/j.ijmedinf.2013.05.006
43. Godino JG, Watkinson C, Corder K, Sutton S, Griffin SJ, Van Sluijs EMF. Awareness of physical activity in healthy middle-aged adults: a cross-sectional study of associations with sociodemographic, biological, behavioural, and psychological factors. BMC Public Health. (2014) 14:421. doi: 10.1186/1471-2458-14-421
44. Vooijs M, Alpay LL, Snoeck-Stroband JB, Beerthuizen T, Siemonsma PC, Abbink JJ, et al. Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. J Med Internet Res. (2014) 16:1–10. doi: 10.2196/ijmr.3056
45. Vallance J, Eurich D, Gardiner P, Taylor L, Johnson S. Associations of daily pedometer steps and self-reported physical activity with health-related quality of life: results from the alberta older adult health survey. J Aging Health. (2016) 28:661–74. doi: 10.1177/0898264315609905
46. Ridgers ND, Timperio A, Brown H, Ball K, Macfarlane S, Lai SK, et al. Wearable activity tracker use among Australian adolescents: usability and acceptability study. JMIR mHealth uHealth. (2018) 6:e86. doi: 10.2196/mhealth.9199
47. Lyons EJ, Lewis ZH, Mayrsohn BG, Rowland JL. Behavior change techniques implemented in electronic lifestyle activity monitors: a systematic content analysis. J Med Internet Res. (2014) 16:e192. doi: 10.2196/jmir.3469
48. Maher C, Ryan J, Ambrosi C, Edney S. Users’ experiences of wearable activity trackers: a cross-sectional study. BMC Public Health. (2017) 17:880. doi: 10.1186/s12889-017-4888-1
49. Bassett DR, Toth LP, LaMunion SR, Crouter SE. Step counting: a review of measurement considerations and health-related applications. Sport Med. (2017) 47:1303–15. doi: 10.1007/s40279-016-0663-1
50. El-Amrawy F, Nounou MI. Are currently available wearable devices for activity tracking and heart rate monitoring accurate, precise, and medically beneficial? Healthc Inform Res. (2015) 21:315–20. doi: 10.4258/hir.2015.21.4.315
51. Kaewkannate K, Kim S. A comparison of wearable fitness devices. BMC Public Health. (2016) 16:433. doi: 10.1186/s12889-016-3059-0
52. Evenson KR, Goto MM, Furberg RD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. (2015) 12:1–22. doi: 10.1186/s12966-015-0314-1
53. Sanders JP, Loveday A, Pearson N, Edwardson C, Yates T, Biddle SJH, et al. Devices for self-sonitoring sedentary time or physical activity: a scoping review. J Med Internet Res. (2016) 18:e90. doi: 10.2196/jmir.5373
54. Gualtieri L, Rosenbluth S, Phillips J. Can a free wearable activity tracker change behavior? The impact of trackers on adults in a physician-led wellness group. JMIR Res Protoc. (2016) 5:e237. doi: 10.2196/resprot.6534
55. Mercer K, Li M, Giangregorio L, Burns C, Grindrod K. Behavior change techniques present in wearable activity trackers: a critical analysis. JMIR mHealth uHealth. (2016) 4:e40. doi: 10.2196/mhealth.4461
56. Lim WK, Davila S, Teo JX, Yang C, Pua CJ, Blöcker C, et al. Beyond fitness tracking: The use of consumer-grade wearable data from normal volunteers in cardiovascular and lipidomics research. PLoS Biol. (2018) 16:e2004285. doi: 10.1371/journal.pbio.2004285
57. Li H, Wu J, Gao Y, Shi Y. Examining individuals’ adoption of healthcare wearable devices: an empirical study from privacy calculus perspective. Int J Med Inform. (2016) 88:8–17. doi: 10.1016/j.ijmedinf.2015.12.010
58. Fortune Business Lights. The Global Fitness Tracker Market is Projected to Grow From $36.34 Billion in 2020 to $114.36 Billion in 2028 at a CAGR of 15.4% in Forecast Period 2021–2028. (2020). Available online at: https://www.fortunebusinessinsights.com/fitness-tracker-market-103358 (accessed October 15, 2020).
59. Shin G, Jarrahi MH, Fei Y, Karami A, Gafinowitz N, Byun A, et al. Wearable activity trackers, accuracy, adoption, acceptance and health impact: a systematic literature review. J Biomed Inform. (2019) 93:103–53. doi: 10.1016/j.jbi.2019.103153
60. Wen D, Zhang X, Liu X, Lei J. Evaluating the consistency of current mainstream wearable devices in health monitoring: a comparison under free-living conditions. J Med Internet Res. (2017) 19:e68. doi: 10.2196/jmir.6874
61. Zhao N. Full-featured pedometer design realized with 3-Axis digital accelerometer. Analog Dialogue. (2010). Available online at: https://www.analog.com/en/analog-dialogue/articles/pedometer-design-3-axis-digital-acceler.html (accessed January 12, 2020).
62. Tudor-Locke C, Craig CL, Brown WJ, Clemes SA, De Cocker K, Giles-Corti B, et al. How many steps/day are enough? For adults. Int J Behav Nutr Phys Act. (2011) 8:80. doi: 10.1186/1479-5868-8-79
63. Tudor-Locke C, Bassett DR. How many steps/day are enough? Preliminary pedometer indices for public health. Sport Med. (2004) 34:1–8. doi: 10.2165/00007256-200434010-00001
64. Sears T, Alvalos E, Lawson S, McAlister I, Bunn J. Wrist-Worn physical activity trackers tend to underestimate steps during walking. Int J Exerc Sci. (2017) 10:764–73. Available online at: https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=2033&context=ijes#:~:text=In%20conclusion%2C%20the%20wrist%2Dworn,best%20of%20the%20devices%20tested
65. Korkiakangas EE, Alahuhta MA, Husman PM, Keinänen-Kiukaanniemi S, Taanila AM, Laitinen JH. Pedometer use among adults at high risk of type 2 diabetes, Finland, 2007-2008. Prev Chronic Dis. (2010) 7:A37. Available online at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2831791/pdf/PCD72A37.pdf
66. World Health Organization. Obesity: Preventing and Managing the Global Epidemic: Report on a WHO Consultation (WHO Technical Report Series 894). Geneva: World Health Organization; (2000). 252p.
67. Lazar A, Koehler C, Tanenbaum J, Nguyen DH. Why we use and abandon smart devices. In: UbiComp 2015—Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY: Association for Computing Machinery, 635–46. doi: 10.1145/2750858.2804288
68. Hantke F, Dewald A. How can data from fitness trackers be obtained and analyzed with a forensic approach? In: Proceedings−5th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2020. Genoa. doi: 10.1109/EuroSPW51379.2020.00073
69. Case MA, Burwick HA, Volpp KG, Patel MS. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA. (2015) 313:625–6. doi: 10.1001/jama.2014.17841
70. Hekler EB, Buman MP, Grieco L, Rosenberger M, Winter SJ, Haskell W, et al. Validation of physical activity tracking via android smartphones compared to actigraph accelerometer: laboratory-based and free-living validation studies. JMIR mHealth uHealth. (2015) 3:e36. doi: 10.2196/mhealth.3505
71. Shcherbina A, Mikael Mattsson C, Waggott D, Salisbury H, Christle JW, Hastie T, et al. Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. J Pers Med. (2017) 7:3. doi: 10.3390/jpm7020003
72. Takács VL, Bubnó K, Ráthonyi GG, Bába ÉB, Szilágyi R. Data warehouse hybrid modeling methodology. Data Sci J. (2020) 19:38. doi: 10.5334/dsj-2020-038
74. Molina-García J, Castillo I, Queralt A. Leisure-time physical activity and psychological well-being in university students. Psychol Rep. (2011) 109:453–60. doi: 10.2466/06.10.13.PR0.109.5.453-460
75. Romaguera D, Tauler P, Bennasar M, Pericas J, Moreno C, Martinez S, et al. Determinants and patterns of physical activity practice among Spanish university students. J Sports Sci. (2011) 29:989–97. doi: 10.1080/02640414.2011.578149
76. Hagströmer M, Troiano RP, Sjöström M, Berrigan D. Levels and patterns of objectively assessed physical activity-a comparison between Sweden and the United States. Am J Epidemiol. (2010) 171:1055–64. doi: 10.1093/aje/kwq069
77. Sisson SB, Katzmarzyk PT. International prevalence of physical activity in youth and adults. Obes Rev. (2008) 9:606–14. doi: 10.1111/j.1467-789X.2008.00506.x
78. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, Mcdowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. (2008) 40:181–8. doi: 10.1249/mss.0b013e31815a51b3