Research article

Comparing the prolonged effect of interval versus continuous aerobic exercise on blood inflammatory marker of Visfatin level and body mass index of sedentary overweigh/fat female college students

  • Received: 11 October 2019 Accepted: 03 December 2019 Published: 16 December 2019
  • History and objectives: Over weightiness and obesity are usually defined as inflammatory conditions. High ratio of body mass index and Visfatin level recently discovered as markers involved in inflammatory process of obesity. Aerobic exercise is one of the safe interventions to decrease such condition. The purpose of this research was to compare the effect of interval versus continuous aerobic exercise on Visfatin and BMI of sedentary overweight female college students. Materials and Methods: Thirty-six healthy sedentary overweight female college students with BMI over 25 or more were randomly assigned into three groups including continuous, interval aerobic exercise and control conditions for eight weeks, three sessions per week. Serum visfatin level was assessed before and after the exercise protocol. The exercise protocol included running a distance of 1200 meters continuously or with rest intervals at 60 to 75 percent of reserved heart rate in the first week that gradually increased by 400 meters on every subsequent week. Results: Our study indicated that both aerobic exercise conditions significantly decrease the serum level of visfatin (P = 0.000, P = 0.025, respectively). Both exercise groups also showed a decrease in BMI compared to the control group (P = 0.006, P = 0.004). Conclusion: Aerobic exercise has a beneficiary effect on both serum visfatin level and BMI variables involved in inflammation process of obesity regardless of being performed with rest interval or continuously.

    Citation: Alireza Moravveji, Mansour Sayyah, Elham Shamsnia, Zarichehr Vakili. Comparing the prolonged effect of interval versus continuous aerobic exercise on blood inflammatory marker of Visfatin level and body mass index of sedentary overweigh/fat female college students[J]. AIMS Public Health, 2019, 6(4): 568-576. doi: 10.3934/publichealth.2019.4.568

    Related Papers:

    [1] Bernard C.K. Choi . What Could Be Future Scenarios?—Lessons from the History of Public Health Surveillance for the Future. AIMS Public Health, 2015, 2(1): 27-43. doi: 10.3934/publichealth.2015.1.27
    [2] Mohammed A. Soghaier, Khwaja M.I. Saeed, Khushhal K. Zaman . Public Health Emergency of International Concern (PHEIC) has Declared Twice in 2014; Polio and Ebola at the Top. AIMS Public Health, 2015, 2(2): 218-222. doi: 10.3934/publichealth.2015.2.218
    [3] Seyedeh Fatemeh Ghafari, Jamileh Mahdizadeh, Ali Valinejadi, Esmaeil Mehraeen, Ali Mohammadpour, Hamid Bouraghi, Mehdi Kahouei . Iranian physicians’ expectations of telemedicine development and implementation infrastructures in teaching hospitals. AIMS Public Health, 2019, 6(4): 514-522. doi: 10.3934/publichealth.2019.4.514
    [4] Stefano Campostrini, David McQueen, Anne Taylor, Alison Daly . World Alliance for Risk Factor Surveillance White Paper on Surveillance and Health Promotion. AIMS Public Health, 2015, 2(1): 10-26. doi: 10.3934/publichealth.2015.1.10
    [5] Rosemary Mamka Anyona, Maximilian de Courten . An Analysis of the Policy Environment Surrounding Noncommunicable Diseases Risk Factor Surveillance in Kenya. AIMS Public Health, 2014, 1(4): 256-274. doi: 10.3934/publichealth.2014.4.256
    [6] Testimony J Olumade, Oluwafolajimi A Adesanya, Iyanuoluwa J Fred-Akintunwa, David O Babalola, Judith U Oguzie, Olusola A Ogunsanya, Uwem E George, Oluwawapelumi D Akin-Ajani, Damilola G Osasona . Infectious disease outbreak preparedness and response in Nigeria: history, limitations and recommendations for global health policy and practice. AIMS Public Health, 2020, 7(4): 736-757. doi: 10.3934/publichealth.2020057
    [7] Julia Metelka, Colin Robertson, Craig Stephen . Japanese Encephalitis: Estimating Future Trends in Asia. AIMS Public Health, 2015, 2(4): 601-615. doi: 10.3934/publichealth.2015.4.601
    [8] Mehreen Tariq, Margaret Haworth-Brockman, Seyed M Moghadas . Ten years of Pan-InfORM: modelling research for public health in Canada. AIMS Public Health, 2021, 8(2): 265-274. doi: 10.3934/publichealth.2021020
    [9] Luke Stanisce, Donald H Solomon, Liam O'Neill, Nadir Ahmad, Brian Swendseid, Gregory J Kubicek, Yekaterina Koshkareva . Transportation considerations in underserved patient populations receiving multidisciplinary head and neck cancer care. AIMS Public Health, 2024, 11(4): 1125-1136. doi: 10.3934/publichealth.2024058
    [10] Ana Gama, Maria O. Martins, Sónia Dias . HIV Research with Men who Have Sex with Men (MSM): Advantages and Challenges of Different Methods for Most Appropriately Targeting a Key Population. AIMS Public Health, 2017, 4(3): 221-239. doi: 10.3934/publichealth.2017.3.221
  • History and objectives: Over weightiness and obesity are usually defined as inflammatory conditions. High ratio of body mass index and Visfatin level recently discovered as markers involved in inflammatory process of obesity. Aerobic exercise is one of the safe interventions to decrease such condition. The purpose of this research was to compare the effect of interval versus continuous aerobic exercise on Visfatin and BMI of sedentary overweight female college students. Materials and Methods: Thirty-six healthy sedentary overweight female college students with BMI over 25 or more were randomly assigned into three groups including continuous, interval aerobic exercise and control conditions for eight weeks, three sessions per week. Serum visfatin level was assessed before and after the exercise protocol. The exercise protocol included running a distance of 1200 meters continuously or with rest intervals at 60 to 75 percent of reserved heart rate in the first week that gradually increased by 400 meters on every subsequent week. Results: Our study indicated that both aerobic exercise conditions significantly decrease the serum level of visfatin (P = 0.000, P = 0.025, respectively). Both exercise groups also showed a decrease in BMI compared to the control group (P = 0.006, P = 0.004). Conclusion: Aerobic exercise has a beneficiary effect on both serum visfatin level and BMI variables involved in inflammation process of obesity regardless of being performed with rest interval or continuously.



    Acknowledgments



    The researcher wishes to express his appreciation to the sincere contribution of college girls who fully cooperated in the completion of the exercise protocol.

    Conflict of interest



    All authors declare no conflicts of interest in this paper.

    [1] Poirier P, Giles TD, Bray GA, et al. (2006) Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 113: 898–918. doi: 10.1161/CIRCULATIONAHA.106.171016
    [2] Zalesin KC, Franklin BA, Miller WM, et al. (2011) Impact of obesity on cardiovascular disease. Med Clin North Am 95: 919–937. doi: 10.1016/j.mcna.2011.06.005
    [3] Pandey A, Berry JD, Lavie CJ (2015) Cardiometabolic disease leading to heart failure: better fat and fit than lean and lazy. Curr Heart Fail Rep 12: 302–308. doi: 10.1007/s11897-015-0265-5
    [4] Aune D, Sen A, Norat T, et al. (2016) Body mass index, abdominal fatness, and heart failure incidence and mortality: a systematic review and dose-response meta-analysis of prospective studies. Circulation 133: 639–649. doi: 10.1161/CIRCULATIONAHA.115.016801
    [5] Ndumele CE, Matsushita K, Lazo M, et al. (2016) Obesity and Subtypes of Incident Cardiovascular Disease. J Am Heart Assoc DOI: 10.1161/JAHA.116.003921
    [6] Yatsuya H, Yamagishi K, North KE, et al. (2010) Associations of obesity measures with subtypes of ischemic stroke in the ARIC Study. J Epidemiol 20: 347–354. doi: 10.2188/jea.JE20090186
    [7] Lu Y, Hajifathalian K, Ezzati M, et al. (2014) Metabolic mediators of the effects of body‐mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 383: 970–983.
    [8] Morkedal B, Vatten LJ, Romundstad PR, et al. (2014) Risk of myocardial infarction and heart failure among metabolically healthy but obese individuals: HUNT [Nord‐Trondelag Health Study], Norway. J Am Coll Cardiol 63:1071–1078. doi: 10.1016/j.jacc.2013.11.035
    [9] Guh DP, Zhang W, Bansback N, et al. (2009) The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 9: 88. doi: 10.1186/1471-2458-9-88 doi: 10.1186/1471-2458-9-88
    [10] Everson SA, Goldberg DE, Helmrich SP, et al. (1998) Weight gain and the risk of developing insulin resistance syndrome. Diabetes Care 21: 1637–1643. doi: 10.2337/diacare.21.10.1637
    [11] Abdullah A, Peeters A, de Courten M, et al. (2010) The magnitude of association between overweight and obesity and the risk of diabetes: a meta-analysis of prospective cohort studies. Diabetes Res Clin Pract 89: 309–319. doi: 10.1016/j.diabres.2010.04.012 doi: 10.1016/j.diabres.2010.04.012
    [12] Dudina A, Cooney MT, Bacquer DD, et al. (2011) SCORE Investigators. Relationships between body mass index, cardiovascular mortality, and risk factors: a report from the SCORE investigators. Eur J Cardiovasc Prev Rehabil 18: 731–742. doi: 10.1177/1741826711412039
    [13] Nejmeddine O, Marwa K, Sami B, et al. (2014) Effects of a high-intensity interval training program on aerobic capacity and lipid profile in trained subjects. J Sports Med 5: 243–248. doi: 10.2147/OAJSM.S68701PMCID: PMC4207574
    [14] Bouassida A, Chamari K, Zaouali M, et al. (2008) Review on leptin and adiponectin responses and adaptations to acute and chronic exercise. Br J Sports Med 44: 620–630.
    [15] Hayashino Y, Jackson JL, Hirata T, et al. (2014) Effects of exercise on C-reactive protein, inflammatory cytokine and adipokine in patients with type 2 diabetes: a meta-analysis of randomized controlled trials. Metabolism 63: 431–440. doi: 10.1016/j.metabol.2013.08.018
    [16] Jamurtas AZ, Stavropoulos-Kalinoglou A, Koutsias S, et al. (2015) Adiponectin, Resistin, and Visfatin in Childhood Obesity and Exercise. Pediatr Exerc Sci 27: 454–462. doi: 10.1123/pes.2014-0072
    [17] Raygan F, Sayyah M, Janesar Qamsari SMR, et al. (2017) Effects of Submaximal Aerobic Exercise on Regulatory T Cell Markers of Male Patients Suffering from Ischemic Heart Disease. Iran J Allergy Asthma Immunol 16: 14–20.
    [18] Ahmadizadeh R, Bassami M, Tahmasbi V (2012) Relationship rest level of visfatin and its change in response of acute endurance training with aerobic fitness and body composition in healthy men. Sport Physiplogy 15: 27–38.
    [19] Vadeboncoeur C, Foster C, Townsend N (2016) Freshman 15 in England: a longitudinal evaluation of first year university student's weight change. BMC Obesity 3: 45 DOI: 10.1186/s40608-016-0125-1 doi: 10.1186/s40608-016-0125-1
    [20] Fukuhara A, Matsuda M, Nishizawa M, et al. (2005) Visfatin: a protein secreted by visceral fat that mimics the effects of insulin. Science 307: 426 – 430. doi: 10.1126/science.1097243
    [21] Berndt J, Kl Ö ting N, Kralisch S, et al. (2005) Plasma visfatin concentrations and fat depot-specific mRNA expression in humans. Diabetes 54: 2911–2916. doi: 10.2337/diabetes.54.10.2911
    [22] Taghian F, Zolfaghary M, Hedayati M (2014) Effect of 12 weeks aerobic exercise on visfatin level and insulin resistance in obese women. Razi J Med Sci 20: 35–44.
    [23] Fantuzzi G, Faggioni R (2000) Leptin in the regulation of immunity, inflammation, and hematopoiesis. J Leukoc Biol 68: 437–446.
    [24] Irving AJ, Wallace L, Durakoglugil D, et al. (2006) Leptin enhances NR2B-mediated N-methyl-D-aspartate responses via a mitogenactivated protein kinase-dependent process in cerebellar granule cells. Neuroscience 138: 1137–1148. doi: 10.1016/j.neuroscience.2005.11.042
    [25] Fukuhara A, Matsuda M, Nishizawa M, et al. (2005) Visfatin: a protein secreted by visceral fat that mimics the effects of insulin. Science 307: 426–430. doi: 10.1126/science.1097243
    [26] Choi KM, Kim JH, Cho GJ, et al. (2007) Effect of exercise training on plasma visfatin and eotaxin levels. Eur J Endocrinol 157: 437–442. doi: 10.1530/EJE-07-0127
    [27] Haider DG, Mittermayer F, Schaller G, et al. (2006) Free fatty acids normalize arosiglitazone-induced visfatin release. Am J Physiol Endocrinol Metab 291: E885–890. doi: 10.1152/ajpendo.00109.2006
    [28] Brema I, Hatunic M, Finucane F, et al. (2008) Plasma visfatin is reduced after aerobic exercise in early onset type 2 diabetes mellitus. Diabetes Obes Metab 10: 600–602. doi: 10.1111/j.1463-1326.2008.00872.x
    [29] Gao Y, Wang C, Pan T, et al. (2014) Impact of metformin treatment and swimming exercise on visfatin levels in high-fat-induced obesity rats. Arq Bras Endocrinol Metab 58: 42–47. doi: 10.1590/0004-2730000002840
    [30] Seifi L, Daryanoosh F, Samadi M (2016) The effect of 12 weeks aerobic exercise training on visfatin, chemerin serum changes in 45–60 years old obese women with diabetes type 2. J Shahid Sadoughi Univ Med Sci 24: 55–64.
    [31] Finkelstein EA, Khavjou OA, Thompson H, et al. (2012) Obesity and severe obesity forecasts through 2030. Am J Prev Med 42: 563–570. doi: 10.1016/j.amepre.2011.10.026
    [32] Sayyah M, Rahimi SM, Bigdeli M, et al. (2011) Comparing the anthropometric characteristics of injured and non-injured girl student athletes participating in the sport olympiads held by the ministry of health and medical education in the summer of 2009 in the city of Yazd. Biosci Biotechnol Res Asia 8: 367–371. doi: 10.13005/bbra/875
    [33] Salehi A, Ehtram H, SaeidSoukhtehzari MS, et al. (2013) Effects of two months of physical activity on the copper level of overweight sedentary young male and female measured at nano scale level. Life Sci J 3: 10.
  • This article has been cited by:

    1. Bertony Bornelus, Hongmei Chi, Guillermo A. Francia, 2020, Integrating Blockchain Technology in Healthcare via Active Learning, 9781450371056, 122, 10.1145/3374135.3385275
    2. Vranda Jain, Nidhi Singh, Sajeet Pradhan, Prashant Gupta, 2020, Chapter 56, 978-3-030-64848-0, 635, 10.1007/978-3-030-64849-7_56
    3. Nicola Luigi Bragazzi, Haijiang Dai, Giovanni Damiani, Masoud Behzadifar, Mariano Martini, Jianhong Wu, How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic, 2020, 17, 1660-4601, 3176, 10.3390/ijerph17093176
    4. Diego Cagigas, Judith Clifton, Daniel Diaz-Fuentes, Marcos Fernandez-Gutierrez, Blockchain for Public Services: A Systematic Literature Review, 2021, 9, 2169-3536, 13904, 10.1109/ACCESS.2021.3052019
    5. Abhishek Royal, MarceloAmaral Mali, Vaibhav Kumar, IndraniAlhad Wagh, Shashi Bhushan, AvishkarNitin Mokal, Kedar Mehta, Sudip Bhattacharya, Harnessing the potential of the primary healthcare facilities in India to respond COVID-19 pandemic: A scoping evidence-based research synthesis, 2021, 10, 2249-4863, 116, 10.4103/jfmpc.jfmpc_1609_20
    6. A. Egli, J. Schrenzel, G. Greub, Digital microbiology, 2020, 26, 1198743X, 1324, 10.1016/j.cmi.2020.06.023
    7. Simran Kaur, Yasha Hasija, 2021, Chapter 2, 978-981-15-8533-3, 19, 10.1007/978-981-15-8534-0_2
    8. Hanaa A. Fatoum, Sam Hanna, John D. Halamka, Douglas C. Sicker, Peter Spangenberg, Shahrukh K. Hashmi, Blockchains integrated with digital technology revolution: The future of healthcare ecosystems. (Preprint), 2020, 1438-8871, 10.2196/19846
    9. Francesco Burrai, Valentina Micheluzzi, Luigi Apuzzo, Governance nell’innovazione: Sanità Digitale, Mobile Health, Big Data, Virtual Reality, 2021, 33, 2705-0076, 42, 10.33393/gcnd.2021.2240
    10. P. S. Aithal, Edwin Dias, 2021, chapter 3, 9781799896067, 48, 10.4018/978-1-7998-9606-7.ch003
    11. Sudip Bhattacharya, Saurabh Varshney, Shailesh Tripathi, Harnessing public health with “metaverse” technology, 2022, 10, 2296-2565, 10.3389/fpubh.2022.1030574
    12. Mohamad Kassab, Giuseppe Destefanis, 2021, Blockchain and Contact Tracing Applications for COVID-19: The Opportunity and The Challenges, 978-1-7281-9630-5, 723, 10.1109/SANER50967.2021.00092
    13. Zhang Wenhua, Faizan Qamar, Taj-Aldeen Naser Abdali, Rosilah Hassan, Syed Talib Abbas Jafri, Quang Ngoc Nguyen, Blockchain Technology: Security Issues, Healthcare Applications, Challenges and Future Trends, 2023, 12, 2079-9292, 546, 10.3390/electronics12030546
    14. Seval Capraz, Adnan Ozsoy, 2021, A Review of Blockchain Based Solutions for Fight Against Pandemics, 978-1-6654-2908-5, 1, 10.1109/UBMK52708.2021.9558911
    15. Mohamad Hassan Kassab, Valdemar Vicente Graciano Neto, Giuseppe Destefanis, Tarek Malas, Could Blockchain Help With COVID-19 Crisis?, 2021, 23, 1520-9202, 44, 10.1109/MITP.2021.3072585
    16. Fidelia Cascini, Flavia Beccia, Francesco Andrea Causio, Natasha Azzopardi Muscat, Walter Ricciardi, Editorial: Digitalization for precision healthcare, 2022, 10, 2296-2565, 10.3389/fpubh.2022.1078610
    17. Mohammed Baz, Sabita Khatri, Abdullah Baz, Hosam Alhakami, Alka Agrawal, Raees Ahmad Khan, Blockchain and Artificial Intelligence Applications to Defeat COVID-19 Pandemic, 2022, 40, 0267-6192, 691, 10.32604/csse.2022.019079
    18. Mark Gaynor, Rhonda BeLue, J E Tuttle-Newhall, Maxwell Martin, Frank Patejdl, Clare Vogt, Blockchain and population health, 2022, 44, 1741-3842, e530, 10.1093/pubmed/fdac028
    19. Madhuri Hiwale, Vijayakumar Varadarajan, Rahee Walambe, Ketan Kotecha, NikshayChain: A Blockchain-Based Proposal for Tuberculosis Data Management in India, 2022, 11, 2227-7080, 5, 10.3390/technologies11010005
    20. P. S. Aithal, Architha Aithal, Edwin Dias, Blockchain Technology - Current Status and Future Research Opportunities in Various Areas of Healthcare Industry, 2021, 2581-6411, 130, 10.47992/IJHSP.2581.6411.0070
    21. Mavis Hong-Yu Yik, Vivian Chi-Woon Taam Wong, Tin-Hang Wong, Pang-Chui Shaw, HerBChain, a blockchain-based informative platform for quality assurance and quality control of herbal products, 2021, 11, 22254110, 598, 10.1016/j.jtcme.2021.07.005
    22. Sudip Bhattacharya, Saurabh Varshney, Petra Heidler, Shailesh K. Tripathi, Expanding the horizon for breast cancer screening in India through artificial intelligent technologies -A mini-review, 2022, 4, 2673-253X, 10.3389/fdgth.2022.1082884
    23. Lei Su, Mengqi Fang, Gaoxiang He, Mathematical media art protection and paper-cut animation design under blockchain technology, 2024, 33, 2191-026X, 10.1515/jisys-2023-0329
    24. Ayodeji Samuel Makinde, Samuel Omaji, Abayomi O. Agbeyangi, Mayowa Samuel Alade, 2023, chapter 14, 9781668489130, 319, 10.4018/978-1-6684-8913-0.ch014
    25. Rita Issa, Chloe Wood, Srivatsan Rajagopalan, Roman Chestnov, Heather Chesters, Geordan Shannon, Addressing Planetary Health through the Blockchain—Hype or Hope? A Scoping Review, 2023, 15, 2078-1547, 3, 10.3390/challe15010003
    26. Roben C. Lunardi, Regio A. Michelin, Maher Alharby, Volkan Dedeoglu, Henry C. Nunes, Eduardo Arruda, Avelino F. Zorzo, Aad van Moorsel, 2024, Chapter 14, 978-3-031-32145-0, 423, 10.1007/978-3-031-32146-7_14
    27. Abu Sayed Md Latiful Hoque, Md Raihan Mia, Mohammad Sajid Abdullah, Md. Jahedul Islam, Bipul Chandra Dev Nath, Muhammad Tanvir Rahman, Sheikh Iqbal Ahamed, 2024, BlockPRLS: Blockchain-Based Patient Record Linkage System for Big Data Analytics, 979-8-3503-7696-8, 877, 10.1109/COMPSAC61105.2024.00121
    28. Neelu Khare, 2023, chapter 6, 9781668476970, 72, 10.4018/978-1-6684-7697-0.ch006
    29. Meshack N. Bida, Sylvia Motlalepule Mosito, Thabiso Victor Miya, Demetra Demetriou, Kim R. M. Blenman, Zodwa Dlamini, 2023, Chapter 10, 978-3-031-36460-0, 223, 10.1007/978-3-031-36461-7_10
    30. Vincent Schiarelli, Marc Dupuis, 2023, Evaluating the Public Perception of a Blockchain-Based Election, 9798400701306, 157, 10.1145/3585059.3611439
    31. Jiao Wang, Vivek Chavda, Riddhi Prajapati, Anjali Bedse, Jinita Patel, Sagar Popat, Gargi Jogi, Lakshmi Vineela Nalla, Keshava Jetha, Bairong Shen, Rajeev K. Singla, An amalgamation of bioinformatics and artificial intelligence for COVID-19 management: From discovery to clinic, 2023, 6, 25902628, 100159, 10.1016/j.crbiot.2023.100159
    32. Shefali Arora, Ruchi Mittal, Avinash K. Shrivastava, Shivani Bali, Blockchain-based deep learning in IoT, healthcare and cryptocurrency price prediction: a comprehensive review, 2024, 41, 0265-671X, 2199, 10.1108/IJQRM-12-2022-0373
  • Reader Comments
  • © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4507) PDF downloads(289) Cited by(4)

Article outline

Figures and Tables

Figures(2)  /  Tables(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog