臺灣博碩士論文加值系統

運動員與非運動員的能量消耗與身體組成之關係

摘要
目的：探討運動員與非運動員運動時的能量消耗與身體組成之關係。方法：本研究招募120名健康成年人，運動員分為耐力組與非耐力組，非運動員分為坐式生活組與規律運動組，利用身體組成分析儀 (InBody 570, Biospace, Inc. Seoul, Korea) 進行身體組成測量，以及利用跑步機進行走跑測驗，使用固定式運動心肺功能測試系統 (Vmax Encore 29 System, VIASYS Healthcare Inc, Yorba Linda, CA) 作為標準量測，於作業系統上輸出能量消耗數據（卡路里）。統計軟體使用SPSS 24.0進行單因子變異數分析 (One-way ANOVA)，分析不同組別間的身體組成差異與能量消耗的差異，以及使用皮爾森相關係數分析 (Pearson's correlation coefficient)，分析能量消耗與身體組成之間的相關性。結果：透過單因子變異數分析後，在身體組成參數部分發現體重、身體質量指數 (Body Mass Index, BMI)、體脂率、骨骼肌與基礎代謝率 (Basal Metabolic Rate, BMR)，在組間有顯著差異 (p < .05)；在能量消耗部分，在6.42、8.04、9.66與11.28 km/h四個速度設定下，在組間有顯著差異 (p < .05)；另外，經由皮爾森相關係數分析結果發現能量消耗與年齡、體脂率、身高、骨骼肌、BMR有顯著相關性 (r = .05, p < .05)。結論：透過本研究可知，運動員與非運動員間的身體組成與能量消耗分別達到顯著差異，且能量消耗與身體組成有顯著相關性，建議未來可針對不同族群開發新的預測公式，再將身體組成參數作為指標加入能量消耗預測公式中。

關鍵詞：運動、體脂肪、肌肉質量、基礎代謝率、跑步機

Relationship of Energy expenditure and Body Composition in Athletes and Non-athletes

Abstract
Purpose: The aim of the study was to investigate the relationship between the exercise energy expenditure and body composition in athletes and non-athletes. Methods: The 120 healthy adults were recruited in this study. Athletes were divided into endurance group and non-endurance group. Non-athletes were divided into sedentary group and regular exercise group. Body composition (InBody 570, Biospace, Inc. Seoul, Korea) for body composition measurements, and treadmill for walking test, using cardiopulmonary function system (Vmax Encore 29 System, VIASYS Healthcare Inc, Yorba Linda, CA) as a standard measurement, the energy expenditure data (calories) was output on the system. Statistical software using SPSS 24.0 for One-way ANOVA, analyzing differences in body composition differences and energy expenditure between different groups, and using Pearson's correlation coefficient to analyze relationship between energy expenditure and body composition. Results: After analysis by One-way ANOVA, body weight, body mass index (BMI), body fat percentage, skeletal muscle and basal metabolic rate (BMR) were found in the body composition parameters, there were a significant difference (p < .05)；The energy expenditure was analyzed by group at four speeds setting of treadmill, at 6.42, 8.04, 9.66 and 11.28 km/h were significant differences (p < .05). In addition, Pearson Correlation coefficient analysis found that energy expenditure was significantly correlated with age, body fat percentage, height, skeletal muscle, and BMR (r = .05, p < .05). Conclusion: According to the results that the body composition and energy expenditure in athletes and non-athletes are significantly different, and energy expenditure is significantly correlated with body composition. It is suggested that new prediction formulas can be developed for different groups in the future, and then the body composition parameters are used as the indicator is added to the energy expenditure prediction formula.

Keywords: exercise, body fat, muscle mass, BMR, treadmill

目錄
摘要 I
Abstract II
致謝 IV
目錄 V
表目錄 VII
圖目錄 VIII
第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究假設 5
第四節 研究範圍與限制 6
第五節 操作型定義與名詞解釋 7
第貳章 文獻探討 8
第一節 運動員與非運動員族群身體組成之差異 8
第二節 運動員與非運動員族群之能量消耗 10
第三節 文獻總結 12
第參章 研究方法 13
第一節 研究對象 14
第二節 實驗時間與地點 15
第三節 研究設備 16
第四節 實驗步驟與流程 20
第五節 資料處理與統計分析 22
第肆章 結果 23
第伍章 討論 28
第陸章 結論與建議 31
第一節 結論 31
第二節 建議 32
參考文獻 33



表目錄

表3-1 1受試者基本資料 14
表4-1身體組成單因子變異數分析摘要表 23
表4-2能量消耗單因子變異數分析摘要表 24
表4-3能量消耗與身體組成之相關係數分析 25
表4 4坐式生活組的能量消耗與身體組成之相關係數分析 25
表4-5規律運動組的能量消耗與身體組成之相關係數分析 26
表4-6非耐力運動組的能量消耗與身體組成之相關係數分析 26
表4-7耐力運動組的能量消耗與身體組成之相關係數分析 27



圖目錄

圖3-3-1 InBody 570身體組成分析儀 16
圖3-3-2 心率測量儀器 (Polar H10) 17
圖3-3-3 運動心肺功能測試儀系統 18
圖3-3-4 跑步機 (h/p cosmos mercury 4.0) 19
圖3-4-1 實驗流程圖 21

中文文獻

1.衛生福利部國民健康署 (2017)。全民身體活動指引。取自https://www.hpa.gov.tw/Pages/EBook.aspx?nodeid=1411
2.衛生福利部國民健康署 (2018)。中華民國105 年健康促進統計年報。取自https://www.hpa.gov.tw/Pages/Detail.aspx?nodeid=268&pid=8967
3.教育部體育署 (2018)。中華民國107年運動現況調查。取自https://isports.sa.gov.tw/Apps/TIS08/TIS0801M_01V1.aspx?MENU_CD=M07&ITEM_CD=T01&MENU_PRG_CD=12&LEFT_MENU_ACTIVE_ID=26
4.林玫君、周蘭娣、蕭秀鳳 (2016)。間接卡路里測定儀應用於重症病人的營養評估。呼吸治療，15(2)，65-74。
5.林建得、陳坤檸、洪睿聲 (2004)。登階測驗與身體組成預測最大攝氧量。台灣醫學，8(2)，175-183。
6.陳俊華、陳坤檸 (2004)。預估9-12歲男童最大攝氧量之研究。大專體育學刊，6 (1)，263-273。
7.傅正思、黃憲鐘、馬君萍、王耀聰 (2016)。能量消耗與體重控制。興大體育學刊，15，81-89。
8.劉錦謀 (2012)。最大攝氧量與體型的關係。文化體育學刊，15，21-30。
9.劉馨敏、葉晉維、劉宜雯、翁毓禎、蘇蕙芬 (2018)。阻力訓練對女大學生身體組成之影響。休閒運動保健學報，15，64-77。

英文文獻

1.American College of Sports Medicine. (2014). ACSM's Guidelines for Exercise Testing and Prescription 9th edition. Retrieved from http://antoinedl.com/fichiers/public/ACSM-guidelines-2014.pdf
2.American Heart Association. (2018, Apr 18). American Heart Association Recommendations for Physical Activity in Adults and Kids. Retrieved from https://www.heart.org/en/healthy-living/fitness/fitness-basics/aha-recs-for-physical-activity-in-adults
3.Abe, T., Kawamoto, K., Dankel, S. J., Bell, Z. W., Spitz, R. W., Wong, V., & Loenneke, J. P. (2019). Longitudinal associations between changes in body composition and changes in sprint performance in elite female sprinters. Eur J Sport Sci, 20, 1-6.
4.Alvero-Cruz, J. R., Ronconi, M., García Romero, J. C., Carrillo de Albornoz Gil, M., Jíménez López, M., Correas Gómez, L., & Álvarez Carnero, E. (2019). Body composition changes after sport detraining period. Nutr Hosp, 34(3), 632-638.
5.Amorim, M. G. S., de Oliveira, M. D., Soares, D. S., da Silva Borges, L., Dermargos, A., & Hatanaka, E. (2018). Effects of exergaming on cardiovascular risk factors and adipokine levels in women. J Physiol Sci, 68(5), 671-678.
6.Ando, T., Piaggi, P., Bogardus, C., & Krakoff, J. (2019). VO2max is associated with measures of energy expenditure in sedentary condition but does not predict weight change. Metabolism, 90, 44-51.
7.Buch, A., Carmeli, E., Boker, L. K., Marcus, Y., Shefer, G., Kis, O., Berner, Y., & Stern, N. (2016). Muscle function and fat content in relation to sarcopenia, obesity and frailty of old age--An overview. Exp Gerontol, 76, 25-32.
8.Canabrava, K. L. R., Faria, F. R., Lima, J. R. P., Guedes, D. P., & Amorim, P. R. S. (2018). Energy Expenditure and Intensity of Active Video Games in Children and Adolescents. Res Q Exerc Sport, 89(1), 47-56.
9.Creasy, S. A., Rogers, R. J., Byard, T. D., Kowalsky, R. J., & Jakicic, J. M. (2016). Energy Expenditure During Acute Periods of Sitting, Standing, and Walking. J Phys Act Health, 13(6), 573-578.
10.Dimaguila, G. L., Gray, K., & Merolli, M. (2018). Person-Generated Health Data in Simulated Rehabilitation Using Kinect for Stroke: Literature Review. JMIR Rehabil Assist Technol, 5(1), e11, 1-12.
11.Drenowatz, C., Eisenmann, J. C., Pivarnik, J. M., Pfeiffer, K. A., & Carlson, J. J. (2013). Differences in energy expenditure between high- and low-volume training. Eur J Sport Sci, 13(4), 422-430.
12.Frączek, B., Grzelak, A., & Klimek, A. T. (2019). Energy expenditure of athletes' endurance and strength in the light of the Polish energy intake standards. Int J Occup Med Environ Health, 32(1), 1-13.
13.Hirsch, K. R., Smith-Ryan, A. E., Trexler, E. T., & Roelofs, E. J. (2016). Body Composition and Muscle Characteristics of Division I Track and Field Athletes. J Strength Cond Res, 30(5), 1231-1238.
14.Jensen, K. G., Rosthøj, S., Linneberg, A., & Aadahl, M. (2018). The Association Between Self-Rated Fitness and Cardiorespiratory Fitness in Adults. Int J Sports Med, 39(6), 419-425.
15.Koutlianos, N., Dimitros, E., Metaxas, T., Cansiz, M., Deligiannis, A., & Kouidi, E. (2013). Indirect estimation of VO2max in athletes by ACSM’s equation: valid or not? Hippokratia, 17(2), 136–140.
16.Lee, S., & Arslanian, S. (2019). Body Composition and Cardiorespiratory Fitness Between Metabolically Healthy Versus Metabolically Unhealthy Obese Black and White Adolescents. J Adolesc Health, 64(3), 327-332.
17.Lev, S., Cohen, J., & Singer, P. (2010). Indirect Calorimetry Measurements in the Ventilated Critically I l l Patient: Facts and Controversies—The Heat is On. Critical Care Clinics, 26(4), e1-e9.
18.Lin, J. H. (2015). "Just Dance": The Effects of Exergame Feedback and Controller Use on Physical Activity and Psychological Outcomes. Games Health J, 4(3), 183-189.
19.Martin, N. J., Ameluxen-Coleman, E. J., & Heinrichs, D. M. (2015). Innovative Ways to Use Modern Technology to Enhance, Rather than Hinder, Physical Activity among Youth. Journal of Physical Education, Recreation & Dance (JOPERD), 86(4), 46-53.
20.McDonough, D. J., Pope, Z. C., Zeng, N., Lee, J. E., & Gao, Z. (2018). Comparison of College Students’ Energy Expenditure, Physical Activity, and Enjoyment during Exergaming and Traditional Exercise. J Clin Med, 7(11), E433.
21.Mifflin, M. D., St Jeor, S. T., Hill, L. A., Scott, B. J., Daugherty, S. A., & Koh, Y. O. (1990). A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr, 51(2), 241-247.
22.Myles, W. S., & Toft, R. J. (1982). A cycle ergometer test of maximal aerobic power. Eur J Appl Physiol Occup Physiol, 49(1), 121-129.
23.Naderi, A., Degens, H., Rezvani, M. H., & Shaabani, F. (2018). A retrospective comparison of physical health in regular recreational table tennis participants and sedentary elderly men. J Musculoskelet Neuronal Interact, 18(2), 200-207.
24.Ndahimana, D., Lee, S. H., Kim, Y. J., Son, H. R., Ishikawa-Takata, K., Park, J., & Kim, E. K. (2017). Accuracy of dietary reference intake predictive equation for estimated energy requirements in female tennis athletes and non-athlete college students: comparison with the doubly labeled water method. Nutrition Research and Practice, 11(1), 51-56.
25.Verhoeven, K., Abeele, V. V., Gers, B., & Seghers, J. (2015). Energy Expenditure During Xbox Kinect Play in Early Adolescents: The Relationship with Player Mode and Game Enjoyment. Games Health J, 4(6), 444-451.
26.Wen, C. P., Wai, J. P., Tsai, M. K., Yang, Y. C., Cheng, T. Y., Lee, M. C., Chan, H. T., Tsao, C. K., Tsai, S. P., Wu, X. (2011). Minimun amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet, 378(9798), 1244-1253.
27.Wu, P. T., Wu, W. L., & Chu, I. H. (2015). Energy Expenditure and Intensity in Healthy Young Adults during Exergaming. Am J Health Behav, 39(4), 556-561.