Anthropometric Measures as Predictive Indicators of Metabolic Risk in a Population of “Holy Week Costaleros”
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Procedure
- Body mass index (BMI): with the participant standing upright, with bare feet, and with his head at the height level, it was calculated to the nearest 1mm using the portable stadiometer Seca 217 (Medical Measuring Systems and Scales, Germany). The BMI is calculated by dividing the weight (in kilograms) by the height (in square metres) and categorising the sample according to the World Health Organization classification, being under-weight: <18.5 kg/m2; standard weight: 18.5–24.9 kg/m2; overweight: 25–29.9 kg/m2; and obese ≥ 30 kg/m2.
- Body fat percentage and muscle mass percentage: Data output, calculated by the manufacturer’s algorithm, includes the amount of body fat measured in Kg as well as the percentage of tissue at body level. The normality data of this variable and the following ones were obtained according to the recommendations of the Spanish Society for the Study of Obesity (SEEDO) [8].
- For the WHR calculation, manual measurements of these circumferences were performed on all participants bare chested. Normality and non-normality figures were calculated through studies analysed in the previous revision [11].
- The Ruffier–Dickson squat test consisted of a 45-s squat exercise (40 pushups/min), followed by a 3-min recovery period. The parameters assessed were: resting heart rate before the squats exercise, heart rate at the end of the exercise, and recovery heart rate after 1 and 3 min. In addition, the RDI was calculated according to the following equation: RDI = (P1 − 70) + 2 (P2 − P0)/10 [27]. According to this equation, P0 is the resting heart rate after 15 s, P1 is the maximum heart rate recorded during the first 15 s of recovery, and heart rate is the average of 15 s after the first minute of recovery (the period from 1 min and 00 s to 1 min and 15 s) [24].
- To know the anaerobic power of the sample, the Abalakov test was performed [28]. This test consists of evaluating the ability to jump by the flexion-extension of the legs in a coordinated manner and synchronised with the action of the arms. This test was carried out, prior to the action of the jump, with the subjects in a bipedal position with a free position of hands and arms, in order for the limbs to be used in a coordinated way.
2.3. Statistical Analysis
2.4. Ethical Considerations
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Lavie, C.J.; McAuley, P.A.; Church, T.S.; Milani, R.V.; Blair, S.N. Obesity and Cardiovascular Diseases Implications Regarding Fitness, Fatness, and Severity in the Obesity Paradox. J. Am. Coll. Cardiol. 2014, 63, 1345–1354. [Google Scholar] [CrossRef] [PubMed]
- Channanath, A.M.; Farran, B.; Behbehani, K.; Thanaraj, T.A. Association between body mass index and onset of hypertension in men and women with and without diabetes: A cross-sectional study using national health data from the State of Kuwait in the Arabian Peninsula. BMJ Open 2015, 5, e007043. [Google Scholar] [CrossRef] [PubMed]
- Liu, M.; Wang, J.; Zeng, J.; Cao, X.; He, Y. Association of NAFLD with Diabetes and the Impact of BMI Changes: A 5-Year Cohort Study Based on 18,507 Elderly. J. Clin. Endocrinol. Metab. 2017, 102, 1309–1316. [Google Scholar] [CrossRef] [PubMed]
- McAllister, E.J.; Dhurandhar, N.V.; Keith, S.W.; Aronne, L.J.; Barger, J.; Baskin, M.; Benca, R.M.; Biggio, J.; Boggiano, M.M.; Eisenmann, J.C.; et al. Ten Putative Contributors to the Obesity Epidemic. Crit. Rev. Food Sci. Nutr. 2009, 49, 868–913. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yalcin, B.M.; Sahin, E.M.; Yalcin, E. Which anthropometric measurements is most closely related to elevated blood pressure? Fam. Pract. 2005, 22, 541–547. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Myint, P.K.; Kwok, C.S.; Luben, R.N.; Wareham, N.J.; Khaw, K.-T. Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease. Heart 2014, 100, 1613–1619. [Google Scholar] [CrossRef] [PubMed]
- Jiang, S.Z.; Lu, W.; Zong, X.F.; Ruan, H.Y.; Liu, Y. Obesity and hypertension. Exp. Ther. Med. 2016, 12, 2395–2399. [Google Scholar] [CrossRef] [Green Version]
- WHO. Obesity and Overweight. Published 2017. Available online: http://www.who.int/mediacentre/factsheets/fs311/en/ (accessed on 2 January 2018).
- Despres, J.-P.; Lemieux, I.; Bergeron, J.; Pibarot, P.; Mathieu, P.; Larose, E.; Rodés-Cabau, J.; Bertrand, O.F.; Poirier, P. Abdominal Obesity and the Metabolic Syndrome: Contribution to Global Cardiometabolic Risk. Arterioscler. Thromb. Vasc. Biol. 2008, 28, 1039–1049. [Google Scholar] [CrossRef] [Green Version]
- Paleczny, B.; Siennicka, A.; Zacharski, M.; Jankowska, E.A.; Ponikowska, B.; Ponikowski, P. Increased body fat is associated with potentiation of blood pressure response to hypoxia in healthy men: Relations with insulin and leptin. Clin. Auton. Res. 2016, 26, 107–116. [Google Scholar] [CrossRef]
- Church, D.D.; Hoffman, J.R.; Mangine, G.T.; Jajtner, A.R.; Townsend, J.R.; Beyer, K.S.; Wang, R.; La Monica, M.B.; Fukuda, D.H.; Stout, J.R. Comparison of High Intensity versus High Volume Resistance Training on the BDNF Response to Exercise. J. Appl. Physiol. 2016, 121, 123–128. [Google Scholar] [CrossRef] [Green Version]
- Lee, C.D.; Blair, S.N.; Jackson, A.S. Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men. Am J Clin Nutr. 1999, 69, 373–380. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ekblom-Bak, E.; Hellenius, M.-L.; Ekblom, Ö.; Engström, L-M.; Ekblom, B. Fitness and abdominal obesity are independently associated with cardiovascular risk. J. Intern. Med. 2009, 266, 547–557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Katzmarzyk, P.T.; Church, T.S.; Blair, S.N. Cardiorespiratory Fitness Attenuates the Effects of the Metabolic Syndrome on All-Cause and Cardiovascular Disease Mortality in Men. Arch. Intern. Med. 2004, 164, 1092. [Google Scholar] [CrossRef]
- Sui, X.; Laditka, J.N.; Hardin, J.W.; Blair, S.N. Estimated Functional Capacity Predicts Mortality in Older Adults. J. Am. Geriatr. Soc. 2007, 55, 1940–1947. [Google Scholar] [CrossRef] [Green Version]
- Davison, K.; Bircher, S.; Hill, A.; Coates, A.M.; Howe, P.R.C.; Buckley, J.D. Relationships between Obesity, Cardiorespiratory Fitness, and Cardiovascular Function. J. Obes. 2010. [Google Scholar] [CrossRef]
- Arena, R.; Myers, J.; Williams, M.A.; Gulati, M.; Kligfield, P.; Balady, G.J.; Collins, E.; Fletcher, G.; American Heart Association Committee on Exercise, Rehabilitation, and Prevention of the Council on Clinical Cardiology; American Heart Association Council on Cardiovascular Nursing. Assessment of Functional Capacity in Clinical and Research Settings: A Scientific Statement from the American Heart Association Committee on Exercise, Rehabilitation, and Prevention of the Council on Clinical Cardiology and the Council on Cardiovascular Nursing. Circulation 2007, 116, 329–343. [Google Scholar] [CrossRef] [PubMed]
- Goff, D.C.; Lloyd-Jones, D.M.; Bennett, G.; Coady, S.; D’Agostino, R.B.; Gibbons, R.; Greenland, P.; Lackland, D.T.; Levy, D.; O’Donnell, C.J.; et al. 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk. Circulation 2013, 129, S49–S73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ross, R.; Blair, S.N.; Arena, R.; Church, T.S.; Després, J.P.; Franklin, B.A.; Haskell, W.L.; Kaminsky, L.A.; Levine, B.D.; Lavie, C.J.; et al. Importance of Assessing Cardiorespiratory Fitness in Clinical Practice: A Case for Fitness as a Clinical Vital Sign: A Scientific Statement from the American Heart Association. Circulation 2016, 134, e653–e699. [Google Scholar] [CrossRef]
- Fletcher, G.F.; Ades, P.A.; Kligfield, P.; Arena, R.; Balady, G.J.; Bittner, V.A.; Coke, L.A.; Fleg, J.L.; Forman, D.E.; Gerber, T.C.; et al. Exercise standards for testing and training: A scientific statement from the American heart association. Circulation 2013, 128, 873–934. [Google Scholar] [CrossRef]
- Kaminsky, L.A.; Arena, R.; Beckie, T.M.; Brubaker, P.H.; Church, T.S.; Forman, D.E.; Franklin, B.A.; Gulati, M.; Lavie, C.J.; Myers, J.; et al. The Importance of Cardiorespiratory Fitness in the United States: The Need for a National Registry: A Policy Statement from the American Heart Association. Circulation 2013, 127, 652–662. [Google Scholar] [CrossRef]
- Poole, D.C.; Wilkerson, D.P.; Jones, A.M. Validity of criteria for establishing maximal O2 uptake during ramp exercise tests. Eur. J. Appl. Physiol. 2008, 102, 403–410. [Google Scholar] [CrossRef] [PubMed]
- Sartor, F.; Vernillo, G.; de Morree, H.M.; Bonomi, A.G.; La Torre, A.; Kubis, H.P.; Veicsteinas, A. Estimation of Maximal Oxygen Uptake via Submaximal Exercise Testing in Sports, Clinical, and Home Settings. Sport Med. 2013, 43, 865–873. [Google Scholar] [CrossRef]
- Piquet, L.; Dalmay, F.; Ayoub, J.; Vandroux, J.C.; Menier, R.; Antonini, M.T.; Pourcelot, L. Study of blood flow parameters measured in femoral artery after exercise: Correlation with maximum oxygen uptake. Ultrasound Med. Biol. 2000, 26, 1001–1007. [Google Scholar] [CrossRef]
- Mancia, G.; Fagard, R.; Narkiewicz, K.; Redon, J.; Zanchetti, A.; Böhm, M.; Christiaens, T.; Cifkova, R.; de Backer, G.; Dominiczak, A.; et al. Guía de práctica clínica de la ESH/ESC para el manejo de la hipertensión arterial. Rev. Esp. Cardiol. 2013, 66, 842–847. [Google Scholar] [CrossRef]
- Whelton, P.K.; Carey, R.M.; Aronow, W.S.; Casey, D.E., Jr.; Collins, K.J.; Dennison Himmelfarb, C.; DePalma, S.M.; Gidding, S.; Jamerson, K.A.; Jones, D.W.; et al. ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension 2018, 71, 1269–1324. [Google Scholar] [CrossRef] [PubMed]
- Blair, S.N.; Kohl, H.W., III; Paffenbarger, R.S., Jr.; Clark, D.G.; Cooper, K.H.; Gibbons, L.W. Physical fitness and all-cause mortality. A prospective study of healthy men and women. JAMA 1989, 262, 2395–2401. [Google Scholar] [CrossRef] [PubMed]
- Markovic, G.; Dizdar, D.; Jukic, I.; Cardinale, M. Reliability and Factorial Validity of Squat and Countermovement Jump Tests. J. Strength Cond. Res. 2004, 18, 551. [Google Scholar] [CrossRef]
- Menéndez, E.; Delgado, E.; Fernández-Vega, F.; Prieto, M.A.; Bordiú, E.; Calle, A.; Carmena, R.; Castaño, L.; Catalá, M.; Franch, J.; et al. Prevalencia, diagnóstico, tratamiento y control de la hipertensión arterial en España. Resultados del estudio Di@bet.es. Rev. Española Cardiol. 2016, 69, 572–578. [Google Scholar] [CrossRef]
- Jatoi, N.A.; Jerrard-Dunne, P.; Feely, J.; Mahmud, A. Impact of Smoking and Smoking Cessation on Arterial Stiffness and Aortic Wave Reflection in Hypertension. Hypertension 2007. [Google Scholar] [CrossRef]
- Leone, A. Does Smoking Act as a Friend or Enemy of Blood Pressure? Let Release Pandora’s Box. Cardiol. Res. Pract. 2011. [Google Scholar] [CrossRef]
- Marqueta de Salas, M.; Martín-Ramiro, J.J.; Juárez Soto, J.J. Características sociodemográficas como factores de riesgo para la obesidad y el sobrepeso en la población adulta española. Med. Clin. (Barc). 2016, 146, 471–477. [Google Scholar] [CrossRef] [PubMed]
- Mellado, F. Los Portadores de los Pasos en la Semana Santa de Córdoba durante el siglo XX. De los Faeneros a los Hermanos Costaleros. Aproximación a la técnica y Entrenamiento; Diputación de Córdoba: Córdoba, Spain, 2003. [Google Scholar]
- Moraga, C. Prescripción de ejercicio en pacientes con hipertensión arterial. Rev. Costarr. Cardiol. 2008, 10, 19–23. [Google Scholar]
- Laukkanen, J.A.; Kurl, S.; Rauramaa, R.; Lakka, T.A.; Venalainen, J.M.; Salonen, J.T. Systolic blood pressure response to exercise testing is related to the risk of acute myocardial infarction in middle-aged men. Eur. J. Cardiovasc. Prev. Rehabil. 2006, 13, 421–428. [Google Scholar] [CrossRef] [PubMed]
Blood Pressure Levels | ||||||
---|---|---|---|---|---|---|
Population n = 101 | Normotension SBP < 120 DBP < 80 (n = 29; 28.7%) | Pre-Hypertension SBP = 120 y ≤ 139 DBP = 80 y ≤ 89 (n = 60; 59.4%) | High Blood Pressure Stage 1 SBP = 140 y ≤ 159 DBP = 90 y ≤ 99 (n = 10; 9.9%) | High Blood Pressure Stage 2 SBP ≥ 160 DBP ≥ 100 (n = 2; 2%) | ||
M ± SD | M ± SD | M ± SD | M ± SD | M ± SD | p | |
Age (year) | 28.89 ± 8.60 | 26.31 ± 8.21 | 29.08 ± 8.30 | 33.20 ± 7.89 | 39.00 ± 16.97 | 0.831 |
Weight (kg) | 82.96 ± 14.71 | 74.48 ± 11.88 | 84.98 ± 13.47 | 88.80 ± 14.42 | 116.30 ± 14.28 | 0.001 |
Height (cm) | 173.78 ± 5.74 | 172.25 ± 4.56 | 174.24 ± 5.93 | 174.93 ± 6.76 | 175.55 ± 10.68 | 0.243 |
Smoker (yes/no) | 1.67 ± 0.47 32.7% | 1.72 ± 0.455 27.6% | 1.67 ± 0.48 33.3% | 1.50 ± 0.53 50% | 2.00 ± 0.00 0% | 0.452 |
BMI (kg/m2) | 27.44 ± 4.41 | 25.08 ± 3.69 | 27.99 ± 4.12 | 28.98 ± 4.06 | 37.65 ± 0.07 | 0.001 |
Fat mass percentage (%) | 25.90 ± 7.88 | 21.61 ± 7.13 | 26.87 ± 7.48 | 30.22 ± 7.05 | 37.40 ± 1.70 | 0.001 |
Muscle mass percentage (%) | 69.91 ± 7.48 | 74.04 ± 6.78 | 68.96 ± 7.08 | 65.76 ± 6.62 | 59.16 ± 1.49 | 0.001 |
WHR | 0.92 ± 0.05 | 0.90 ± 0.05 | 0.92 ± 0.05 | 0.94 ± 0.04 | 0.99 ± 0.04 | 0.017 |
RDI | 4.94 ± 2.75 | 4.67 ± 2.65 | 5.03 ± 2.99 | 5.08 ± 1.69 | 5.20 ± 0.85 | 0.784 |
Jump height (cm) | 32.66 ± 6.47 | 33.24 ± 7.01 | 32.57 ± 6.20 | 31.80 ± 5.77 | 31.50 ± 14.85 | 0.869 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Robles-Romero, J.M.; Fernández-Ozcorta, E.J.; Gavala-González, J.; Romero-Martín, M.; Gómez-Salgado, J.; Ruiz-Frutos, C. Anthropometric Measures as Predictive Indicators of Metabolic Risk in a Population of “Holy Week Costaleros”. Int. J. Environ. Res. Public Health 2019, 16, 207. https://doi.org/10.3390/ijerph16020207
Robles-Romero JM, Fernández-Ozcorta EJ, Gavala-González J, Romero-Martín M, Gómez-Salgado J, Ruiz-Frutos C. Anthropometric Measures as Predictive Indicators of Metabolic Risk in a Population of “Holy Week Costaleros”. International Journal of Environmental Research and Public Health. 2019; 16(2):207. https://doi.org/10.3390/ijerph16020207
Chicago/Turabian StyleRobles-Romero, José Miguel, Eduardo J. Fernández-Ozcorta, Juan Gavala-González, Macarena Romero-Martín, Juan Gómez-Salgado, and Carlos Ruiz-Frutos. 2019. "Anthropometric Measures as Predictive Indicators of Metabolic Risk in a Population of “Holy Week Costaleros”" International Journal of Environmental Research and Public Health 16, no. 2: 207. https://doi.org/10.3390/ijerph16020207
APA StyleRobles-Romero, J. M., Fernández-Ozcorta, E. J., Gavala-González, J., Romero-Martín, M., Gómez-Salgado, J., & Ruiz-Frutos, C. (2019). Anthropometric Measures as Predictive Indicators of Metabolic Risk in a Population of “Holy Week Costaleros”. International Journal of Environmental Research and Public Health, 16(2), 207. https://doi.org/10.3390/ijerph16020207