Examination of the Effect of E-Health Mobile Application-Supported Nutrition and Exercise Programs on Body Composition and Certain Blood Parameters in Adult Individuals

Abstract

The aim of this study is to determine the effectiveness of nutrition and exercise counseling through e-health mobile applications on the body composition and certain blood parameters of individuals. The study was conducted on 12 sedentary female individuals within the age range of 41.25±6.95 years without any chronic diseases. An 8-week intervention period was planned and implemented. The participants' physical activity level was assessed by using a physical activity detection form. The participants received diet and exercise program support through the e-health mobile application. The participants' anthropometric measurements, body weight, and certain biochemical parameters were analyzed. The presence of any differences before and after exercise and nutrition support was determined using the paired t-test for within-group analysis. In this study, p<0.05 was considered statistically significant. Upon examination of the findings of the study, statistically significant changes were observed in the participants' body weight, body mass index (BMI), waist circumference, hip circumference, waist-to-height ratio, and waist-to-hip ratio measurements (p<0.05). On average, there was a decrease of 4.64±1.03 kg in body weight, and a 6.88% reduction in body weight was observed. A significant decrease was observed in fasting plasma glucose (FPG) and insulin levels (p<0.05), while no significant differences were found in the liver enzymes AST and ALT (p>0.05). When examining the blood lipid profile, significant differences were determined in triglyceride (TG) and cholesterol levels (p<0.05), but no significant differences were found in LDL-C and HDL-C values (p>0.05). There were no significant differences in serum electrolytes (sodium, potassium, calcium, magnesium, phosphorus, and chloride) (p>0.05).

Keywords

• Nutrition
• exercise
• e-health application

Yetişkin Bireylerde E-Sağlık Mobil Uygulama Destekli Beslenme ve Egzersiz Programlarının Vücut Kompozisyonu ve Bazı Kan Parametreleri Üzerine Etkisinin İncelenmesi

Abstract

Bu çalışmanın amacı, e-sağlık mobil uygulamaları üzerinden beslenme ve egzersiz danışmanlığı alan bireylerin vücut kompozisyonu ve bazı kan parametreleri üzerindeki etkinliğini belirlemektir. Çalışma, herhangi bir kronik hastalığı olmayan 41,25±6,95 yaş aralığındaki 12 sedanter kadın birey üzerinde gerçekleştirilmiştir. 8 haftalık bir müdahale süresi planlanmış ve uygulanmıştır. Bireylerin fiziksel aktivite düzeyi fiziksel aktivite saptama formu ile değerlendirilmiştir. Katılımcılar e-sağlık mobil uygulaması üzerinden diyet ve egzersiz programı desteği almıştır. Katılımcıların antropometrik ölçümleri, vücut ağırlığı ve bazı biyokimyasal parametreler analiz edilmiştir. Egzersiz ve beslenme desteği öncesi ve sonrası fark olup olmadığının belirlenmesi için veriler grup içi ‘Paired t testi’ kullanılarak analiz edilmiştir. Çalışmamızda p<0.05 istatistiksel olarak anlamlı kabul edilmiştir. Çalışmanın bulguları incelendiğinde, katılımcıların vücut ağırlığı, vücut kütle indeksi (BKİ), bel çevresi, kalça çevresi, bel/boy ve bel/kalça oranı değerlerinde istatistiksel olarak anlamlı değişiklikler olduğu tespit edilmiştir (p<0,05). Ortalama olarak, bireylerin vücut ağırlığı 4,64±1,03 kg azalmıştır ve vücut ağırlığında %6,88'lik bir azalma saptanmıştır. Açlık plazma glikozu (APG) ve insülin değerlerinde anlamlı bir düşüş tespit edilirken (p<0,05), karaciğer enzimlerinden AST ve ALT değerlerinde anlamlı farklılık bulunmamıştır (p>0,05). Kan lipid profili incelendiğinde, trigliserid (TG) ve kolesterol sonuçlarında anlamlı farklılıklar olduğu belirlenmiştir (p<0,05), ancak LDL-K ve HDL-K değerlerinde anlamlı farklılık tespit edilmemiştir (p>0,05). Serum elektrolitlerinde (sodyum, potasyum, kalsiyum, magnezyum, fosfor ve klor) anlamlı farklılıklar bulunmamıştır (p>0,05). Sonuç olarak, e-sağlık mobil uygulamaları üzerinden verilen beslenme ve egzersiz programının, bireylerin vücut ağırlığı kaybı, antropometrik ölçümleri ve bazı kan parametreleri üzerinde etkili olduğu tespit edilmiştir.

Keywords

• Beslenme
• egzersiz
• e-sağlık uygulaması

References

1. [1] Varshney, U. 2007. Pervasive healthcare and wireless health monitoring. Mobile Networks and Applications, 12(2–3), 113–27.
2. [2] Smartphone and Tablet Penetration. https://www.businessinsider.com/smartphone-and-tablet-penetration-2013-10 (Erişim tarihi: 5.04.22).
3. [3] Eysenbach, G. 2001. What is e-health?. Journal of Medical Internet Research, 3(2), 20.
4. [4] Pires, I. M., Marques, G., Garcia, NM., Flórez-revuelta, F., Ponciano, V., Oniani, S. 2020. A research on the classification and applicability of the mobile health applications. Journal of Personalized Medicine, 10(1), 11.
5. [5] Hong, Y. J., Kim, I. J., Ahn, S. C., Kim, H. G. 2010. Mobile health monitoring system based on activity recognition using accelerometer. Simulation Modelling Practice and Theory, 18(4), 446-455.
6. [6] Joe, J., Demiris, G. 2013. Older adults and mobile phones for health: A review. Journal of Biomedical Informatics, 46(5), 947-954.
7. [7] Brindal, E., Hendrie, G. A., Freyne, J., Noakes, M. 2019. A mobile phone app designed to support weight loss maintenance and well-being (motimate): Randomized controlled trial. JMIR mHealth uHealth, 7(9), e12882.
8. [8] Edney, S. M., Olds, T. S., Ryan, J. C., Vandelanotte, C., Plotnikoff, R. C., Curtis, R.G., et al. 2020. A Social Networking and Gamified App to Increase Physical Activity: Cluster RCT. American journal of preventive medicine, 58(2), 51–62.

9. [9] Wing, R. R., Tate, D. F., Gorin, A. A., Raynor, H. A., Fava, J. L. 2006. A Self-Regulation Program for Maintenance of Weight Loss. N Engl J Med, 355(15), 1563–1571.
10. [10] Fanning, J., Roberts, S., Hillman, C. H., Mullen, S. P., Ritterband, L., McAuley, E. 2017. A smartphone “app”-delivered randomized factorial trial targeting physical activity in adults. Journal of Behavioral Medicine, 40(5), 712–729.
11. [11] Serino, M., Cordrey, K., McLaughlin, L., Milanaik, R. L. 2016. Pokémon Go and augmented virtual reality games: A cautionary commentary for parents and pediatricians. Current Opinion in Pediatrics, 28(5), 673-677.
12. [12] Moberg, C., Niles, A., Beermann, D. 2019. Guided self-help works: Randomized waitlist controlled trial of Pacifica, a mobile app integrating cognitive behavioral therapy and mindfulness for stress, anxiety, and depression. Journal of Medical Internet Research, 21(6), e12556.
13. [13] Muralidharan, S., Ranjani, H., Mohan, Anjana. R., Jena, S., Tandon, N., Gupta, Y., Ambekar, S., Koppikar, V., Jagannathan, N., Allender, S., Mohan, V. 2019. Engagement and Weight Loss: Results from the Mobile Health and Diabetes Trial. Diabetes Technology and Therapeutics, 21(9), 507–513.
14. [14] Hoffman, V., Söderström, L., Samuelsson, E. 2017. Self-management of stress urinary incontinence via a mobile app: two-year follow-up of a randomized controlled trial. Acta Obstetricia et Gynecologica Scandinavica, 96(10), 1180–1187.
15. [15] Azar, K. M. J., Lesser, L. I., Laing, B. Y., Stephens, J., Aurora, M. S., Burke, L. E., et al. 2013. Mobile applications for weight management: Theory-based content analysis. American journal of preventive medicine, 45(5), 583–589.
16. [16] Höchsmann, C., Walz, S. P., Schäfer, J., Holopainen, J., Hanssen, H. Schmidt-Trucksäss, A. 2017. Mobile Exergaming for Health-Effects of a serious game application for smartphones on physical activity and exercise adherence in type 2 diabetes mellitus-study protocol for a randomized controlled trial. Trials, 18(1), 1-17.
17. [17] Ferrara, G., Kim, J., Lin, S., Hua, J., Seto, E. 2019. A focused review of smartphone diet-tracking apps: Usability, functionality, coherence with behavior change theory, and comparative validity of nutrient intake and energy estimates. JMIR mHealth uHealth, 7(5): e9232.
18. [18] Trumbo, P., Schlicker, S., Yates, A. A., & Poos, M. (2002). Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids. Journal of the American Dietetic Association, 102(11), 1621–1630.
19. [19] Hamra, K. A. 2013. Mobilya Üretiminde Çalışan İşçilerin Beslenme Durumlarının Ve Bazı Antropometrik Ölçümlerinin Saptanması. Hacettepe Üniversitesi, Sağlık Bilimleri Enstitüsü, Yüksek Lisans Tezi, 28-30s, Ankara.
20. [20] Food and Agriculture Organization. 2001. 5. Energy requırements of adults In Human energy requirements. https://www.fao.org/3/y5686e/y5686e07.htm#bm07.1 (Erişim Tarihi: 28.03.2023.)
21. [21] Türkay, İ. K., Pepe, K., Dinçer, Ö. (2018). Investigation of waist/height ratio and body mass indexes of sports centers. Turkish Journal of Sport and Exercise, 20(3), 131-136.
22. [22] Ergün, A., & Erten, S. F. (2004). Öğrencilerde vücut kitle indeksi ve bel çevresi değerlerinin incelenmesi. Ankara Üniversitesi Tıp Fakültesi Mecmuası, 57(2).
23. [23] Norman, G. J., Zabinski, M. F., Adams, M. A., Rosenberg, D. E., Yaroch, A. L., & Atienza, A. A. (2007). A review of eHealth interventions for physical activity and dietary behavior change. American Journal of Preventive Medicine, 33(4), 336.
24. [24] Haas, K., Hayoz, S., & Maurer-Wiesner, S. (2019). Effectiveness and feasibility of a remote lifestyle intervention by dietitians for overweight and obese adults: Pilot study. JMIR mHealth uHealth, 7(4).
25. [25] Stephens, J. D., Yager, A. M., & Allen, J. (2017). Smartphone technology and text messaging for weight loss in young adults: A randomized controlled trial. Journal of Cardiovascular Nursing, 32(1), 39.
26. [26] Hurkmans, E., Matthys, C., Bogaerts, A., Scheys, L., Devloo, K., & Seghers, J. (2018). Face-to-face versus mobile versus blended weight loss program: Randomized clinical trial. JMIR mHealth uHealth, 6(1).
27. [27] Martin, C. K., Miller, A. C., Thomas, D. M., Champagne, C. M., Han, H., & Church, T. (2015). Efficacy of SmartLossSM, a smartphone-based weight loss intervention: Results from a randomized controlled trial. Obesity, 23(5), 935.
28. [28] Lim, S. L., Johal, J., Ong, K. W., Han, C. Y., Chan, Y. H., Lee, Y. M., et al. (2020). Lifestyle intervention enabled by mobile technology on weight loss in patients with nonalcoholic fatty liver disease: Randomized controlled trial. JMIR mHealth uHealth, 8(4).
29. [29] Kim, J. W., Ryu, B., Cho, S., Heo, E., Kim, Y., Lee, J., et al. (2019). Impact of personal health records and wearables on health outcomes and patient response: Three-arm randomized controlled trial. JMIR mHealth uHealth, 7(1).
30. [30] Hutchesson, M. J., Rollo, M. E., Krukowski, R., Ells, L., Harvey, J., Morgan, P. J., et al. (2015). eHealth interventions for the prevention and treatment of overweight and obesity in adults: A systematic review with meta-analysis. Obesity Reviews, 16(5), 376–392.
31. [31] Godino, J. G., Merchant, G., Norman, G. J., Donohue, M. C., Marshall, S. J., Fowler, J. H., et al. (2016). Using social and mobile tools for weight loss in overweight and obese young adults (Project SMART): A 2-year, parallel-group, randomized, controlled trial. The Lancet Diabetes & Endocrinology, 4(9), 747–755.
32. [32] Tate, D. F., Jackvony, E. H., & Wing, R. R. (2006). A randomized trial comparing human e-mail counseling, computer-automated tailored counseling, and no counseling in an Internet weight loss program. Archives of Internal Medicine, 166(15), 1620–1625.
33. [33] Mazzotti, A., Caletti, M. T., Brodosi, L., Di Domizio, S., Forchielli, M. L., Petta, S., et al. (2018). An internet-based approach for lifestyle changes in patients with NAFLD: Two-year effects on weight loss and surrogate markers. Journal of Hepatology, 69(5), 1155–1163.
34. [34] Hou, C., Carter, B., Hewitt, J., Francis, T., & Mayor, S. (2016). Do mobile phone applications improve glycemic control (HbA1c) in the self-management of diabetes? A systematic review, meta-analysis, and GRADE of 14 randomized trials. Diabetes Care, 39(11), 2089–2095.
35. [35] Holmen, H., Torbjørnsen, A., Wahl, A. K., Jenum, A. K., Småstuen, M. C., Årsand, E., et al. (2014). A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH. JMIR mHealth uHealth, 2(4), e3882.
36. [36] Yoo, H. J., Park, M. S., Kim, T. N., Yang, S. J., Cho, G. J., Hwang, T. G., et al. (2009). A ubiquitous chronic disease care system using cellular phones and the internet. Diabetic Medicine, 26(6), 628–635.
37. [37] Huo, X., Krumholz, H. M., Bai, X., Spatz, E. S., Ding, Q., Horak, P., et al. (2019). Effects of Mobile Text Messaging on Glycemic Control in Patients With Coronary Heart Disease and Diabetes Mellitus: A Randomized Clinical Trial. Circulation: Cardiovascular Quality and Outcomes, 12(9).
38. [38] Quinn, C. C., Shardell, M. D., Terrin, M. L., Barr, E. A., Ballew, S. H., & Gruber-Baldini, A. L. (2011). Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care, 34(9), 1934–1942.
39. [39] Humalda, J. K., Klaassen, G., de Vries, H., Meuleman, Y., Verschuur, L. C., Straathof, E. J., et al. (2020). A self-management approach for dietary sodium restriction in patients with CKD: A randomized controlled trial. American Journal of Kidney Diseases, 75(6), 847-856.
40. [40] Naseri-Salahshour, V., Sajadi, M., Nikbakht-Nasrabadi, A., Davodabady, F., & Fournier, A. (2020). The effect of nutritional education program on quality of life and serum electrolytes levels in hemodialysis patients: A single-blind randomized controlled trial. Patient Education and Counseling, 103(9), 1774–1779.