ESTIMASI KALORI EKSPENDITURE BERDASARKAN ACCELEROMETER ACTIGRAPH DAN TREADMILL

Aulia Anshari, Jajat Jajat, Kuston Sultoni, Adang Suherman, Yati Ruhayati, Widy Dewi Nuryanti

Abstract


Penelitian ini bertujuan untuk membandingkan pengeluaran kalori yang diukur menggunakan Accelerometer Actigraph GT3X dan Treadmill dalam aktivitas fisik terkontrol. Populasi penelitian terdiri dari 50 mahasiswa Ilmu Keolahragaan Universitas Pendidikan Indonesia, yang terdiri dari 27 laki-laki dan 23 perempuan. Penelitian dilakukan dengan metode cross-sectional di laboratorium Fakultas Pendidikan Olahraga dan Kesehatan (FPOK UPI). Partisipan menjalani tiga sesi aktivitas di atas treadmill dengan kecepatan berbeda: 2,5 km/jam (jalan lambat), 4,5 km/jam (jalan cepat), dan 5,5 km/jam (jogging lambat). Pengumpulan data dilakukan dengan merekam pengeluaran kalori dari Accelerometer Actigraph GT3X dan Treadmill, yang kemudian dianalisis menggunakan SPSS versi 26. Hasil penelitian menunjukkan bahwa rata-rata estimasi pengeluaran kalori dari treadmill (3,13 METS) lebih tinggi dibandingkan dengan Actigraph (2,07 METS). Analisis korelasi Spearman menunjukkan hubungan yang lemah dan tidak signifikan antara kedua perangkat (r = 0,245; p > 0,05). Kesimpulannya, kedua perangkat memberikan hasil yang berbeda dalam memperkirakan pengeluaran kalori, sehingga tidak dapat digunakan secara bergantian. Actigraph lebih cocok untuk memantau aktivitas sehari-hari dengan intensitas rendah hingga sedang, sedangkan Treadmill lebih akurat untuk aktivitas fisik intensitas tinggi seperti lari atau jogging. Penelitian ini memberikan kontribusi dalam memahami perbedaan perangkat dalam mengukur pengeluaran kalori dan pentingnya memilih alat yang sesuai dengan kebutuhan pengguna.


Keywords


Accelerometer Actigraph GT3X; Treadmill; Pengeluaran Kalori; Aktivitas Fisik

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References


Albuquerque, D., Nóbrega, C., Manco, L., & Padez, C. (2017). The contribution of genetics and environment to obesity. British Medical Bulletin, 123(1), 159-173. https://doi.org/10.1093/bmb/ldx022

Arvidsson, D., Fridolfsson, J., & Börjesson, M. (2019). Measurement of physical activity in clinical practice using accelerometers. Journal of Internal Medicine, 286(2), 137-153. https://doi.org/10.1111/joim.12908

Asumadu-Sarkodie, S. (2014). Facts on Overweight and Obesity. October 2012, 1-4. https://doi.org/10.13140/2.1.3104.5121

Bassett, D. R. (2000). Validity and reliability issues in objective monitoring of physical activity. Research Quarterly for Exercise and Sport, 71(November), 30-36. https://doi.org/10.1080/02701367.2000.11082783

Berger, M., Bertrand, A. M., Robert, T., & Chèze, L. (2023). Measuring objective physical activity in people with chronic low back pain using accelerometers: a scoping review. Frontiers in Sports and Active Living, 5(November), 1-14. https://doi.org/10.3389/fspor.2023.1236143

Black, C. K., Vartanian, L. R., & Faasse, K. (2024). Lay beliefs about the perceived harmfulness of excess weight: Influence of weight status and the cause of weight. Applied Psychology: Health and Well-Being, 16(2), 653-671. https://doi.org/10.1111/aphw.12509

Black, C., Vartanian, L. R., & Faasse, K. (2019). An Experimental Test of the Effects of a Target Person's Body Weight and Engagement with Health Behaviours on Perceptions of Overall Health. Applied Psychology: Health and Well-Being, 11(2), 240-261. https://doi.org/10.1111/aphw.12151

Chu, D. T., Minh Nguyet, N. T., Dinh, T. C., Thai Lien, N. V., Nguyen, K. H., Nhu Ngoc, V. T., Tao, Y., Son, L. H., Le, D. H., Nga, V. B., Jurgoński, A., Tran, Q. H., Van Tu, P., & Pham, V. H. (2018). An update on physical health and economic consequences of overweight and obesity. Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 12(6), 1095-1100. https://doi.org/10.1016/j.dsx.2018.05.004

D, H., K, M., C, B., E, D., & P, F. (2000). Validity of accelerometry for the assessment of moderate intensity physical activity in the field. Medicine and Science in Sports and Exercise, 32(9), S442-S449.

Ellulu, M., Abed, Y., Rahmat, A., Ranneh, Y., & Ali, F. (2014). Epidemiology of obesity in developing countries: challenges and prevention. Global Epidemic Obesity, 2(1), 2. https://doi.org/10.7243/2052-5966-2-2

Fotouhi-Ghazvini, F., & Abbaspour, S. (2020). Wearable wireless sensors for measuring calorie consumption. Journal of Medical Signals and Sensors, 10(1), 19-34. https://doi.org/10.4103/jmss.JMSS_15_18

Jackson, D. M., Reilly, J. J., Kelly, L. A., Montgomery, C., Grant, S., & Paton, J. Y. (2003). Objectively measured physical activity in a representative sample of 3- to 4-year-old children. Obesity Research, 11(3), 420-425. https://doi.org/10.1038/oby.2003.57

Kelly, L. A., Reilly, J. J., Jackson, D. M., Montgomery, C., Grant, S., & Paton, J. Y. (2007). Tracking physical activity and sedentary behavior in young children. Pediatric Exercise Science, 19(1), 51-60. https://doi.org/10.1123/pes.19.1.51

Kementerian Kesehatan RI. (2018). Laporan Riskesdas 2018 Nasional. In Badan Penelitian dan Pengembangan Kesehatan.

King, G. A., Torres, N., Potter, C., Brooks, T. J., & Coleman, K. J. (2004). Comparison of activity monitors to estimate energy cost of treadmill exercise. Medicine and Science in Sports and Exercise, 36(7), 1244-1251. https://doi.org/10.1249/01.MSS.0000132379.09364.F8

Knight, J. A. (2011). Diseases and disorders associated with excess body weight. Annals of Clinical and Laboratory Science, 41(2), 107-121.

Ludwig, D. S. (2023). Carbohydrate-insulin model: Does the conventional view of obesity reverse cause and effect? Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1888). https://doi.org/10.1098/rstb.2022.0211

Must, A., Spadano, J., Coakley, E. H., Field, A. E., Colditz, G., & Dietz, W. H. (1999). The disease burden associated with overweight and obesity. Journal of the American Medical Association, 282(16), 1523-1529. https://doi.org/10.1001/jama.282.16.1523

Rahaman, H., & Dyo, V. (2020). Counting calories without wearables : Device-free Human Energy Expenditure Estimation. International Conference on Wireless and Mobile Computing, Networking and Communications.

Rothney, M. P., Brychta, R. J., Meade, N. N., Chen, K. Y., & Buchowski, M. S. (2010). Validation of the ActiGraph Two-Regression Model for Predicting Energy Expenditure. Med Sci Sports Exerc., 42(9), 1785-1792. https://doi.org/10.1016/j.earlhumdev.2006.05.022

Salam, R, Y., MW, S., & M, H. (2022). Obesity and Overweight : A Global Public Health Issue. 2022-2024.

Sasaki, J. E., John, D., & Freedson, P. S. (2011). Validation and comparison of ActiGraph activity monitors. Journal of Science and Medicine in Sport, 14(5), 411-416. https://doi.org/10.1016/j.jsams.2011.04.003

WHO. (2003). Diet, Nutrition and the Prevention ofChronic Diseases. Report of a Joint WHO/FAO Expert Consultation. WHO Technical Report Series 916. Geneva: World Health Organisation.

Xiao, L., Wu, K., Tian, X., & Luo, J. (2020). Activity-specific caloric expenditure estimation from kinetic energy harvesting in wearable devices. Pervasive and Mobile Computing, 67, 101185. https://doi.org/10.1016/j.pmcj.2020.101185




DOI: https://doi.org/10.37311/jjsc.v7i1.30049

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