Effect of Consuming Beef with Varying Fatty Acid Compositions as a Major Source of Protein in Volunteers under a Personalized Nutritional Program
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Approval
2.2. Volunteers
2.3. Study Design
2.4. Dietary Assessment
2.5. Beef Processing
2.6. Outcome Measures and Follow-Up
2.7. Statistical Analysis
3. Results
3.1. Food Intervention
3.2. Comparison of Anthropometric Characteristics between Groups
3.3. Comparison of Lipid Profiles between Groups
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Berenson, G.S. Health Consequences of Obesity. Pediatr. Blood Cancer 2012, 58, 117–121. [Google Scholar] [CrossRef] [PubMed]
- INEGI. Available online: https://www.inegi.org.mx/contenidos/saladeprensa/aproposito/2020/EAP_Obesidad20.pdf (accessed on 3 May 2022).
- Esposito, L.; Villaseñor, A.; Rodríguez, E.C.; Millett, C. The economic gradient of obesity in Mexico: Independent predictive roles of absolute and relative wealth by gender. Soc. Sci. Med. 2020, 250, 112870. [Google Scholar] [CrossRef] [PubMed]
- Hruby, A.; Manson, J.E.; Qi, L.; Malik, V.S.; Rimm, E.B.; Sun, Q.; Willett, W.C.; Hu, F.B. Determinants and consequences of obesity. Am. J. Public Health 2016, 106, 1656–1662. [Google Scholar] [CrossRef] [PubMed]
- Grave, R.D.; Centis, E.; Marzocchi, R.; El Ghoch, M.; Marchesini, G. Major factors for facilitating change in behavioral strategies to reduce obesity. Psychol. Res. Behav. Manag. 2013, 6, 101–110. [Google Scholar]
- Kim, J.Y. Optimal diet strategies for weight loss and weight loss maintenance. J. Obes. Metab. Syndr. 2021, 30, 20. [Google Scholar] [CrossRef]
- Harbuwono, D.S.; Pramono, L.A.; Yunir, E.; Subekti, I. Obesity and central obesity in Indonesia: Evidence from a national health survey. Med. J. Indones. 2018, 27, 114–120. [Google Scholar] [CrossRef]
- Newby, P.K.; Muller, D.; Hallfrisch, J.; Andres, R.; Tucker, K.L. Food patterns measured by factor analysis and anthropometric changes in adults. Am. J. Clin. Nutr. 2004, 80, 504–513. [Google Scholar] [CrossRef]
- Schulz, M.; Nöthlings, U.; Hoffmann, K.; Bergmann, M.M.; Boeing, H. Identification of a food pattern characterized by high-fiber and low-fat food choices associated with low prospective weight change in the EPIC-Potsdam cohort. J. Nutr. 2005, 135, 1183–1189. [Google Scholar] [CrossRef]
- Aburto, T.C.; Pedraza, L.S.; Sánchez-Pimienta, T.G.; Batis, C.; Rivera, J.A. Discretionary foods have a high contribution and fruit, vegetables, and legumes have a low contribution to the total energy intake of the mexican population. J. Nutr. 2016, 146, 1881S–1887S. [Google Scholar] [CrossRef]
- McNeill, S.H. Inclusion of red meat in healthful dietary patterns. Meat Sci. 2014, 98, 452–460. [Google Scholar] [CrossRef]
- Melanson, K.; Gootman, J.; Myrdal, A.; Kline, G.; Rippe, J.M. Weight loss and total lipid profile changes in overweight women consuming beef or chicken as the primary protein source. Nutrition 2003, 19, 409–414. [Google Scholar] [CrossRef]
- WHO/FAO. Fats and fatty acids in human nutrition. In Report of an Expert Consultation; World Health Organization/Food and Agricultural Organization: Geneva, Switzerland, 2010; ISBN 978-92-5-106733-8. Available online: https://www.fao.org/fileadmin/user_upload/nutrition/docs/requirements/fatsandfattacidsreport.pdf (accessed on 26 August 2022).
- Ruiz-Núñez, B.; Kuipers, R.S.; Luxwolda, M.F.; De Graaf, D.J.; Breeuwsma, B.B.; Dijck-Brouwer, D.J.; Muskiet, F.A. Saturated fatty acid (SFA) status and SFA intake exhibit different relations with serum total cholesterol and lipoprotein cholesterol: A mechanistic explanation centered around lifestyle-induced low-grade inflammation. J. Nutr. Biochem. 2014, 25, 304–312. [Google Scholar] [CrossRef]
- NCSI. Red Meat Genetic Signature for Colorectal Cancer-National Cancer Institute. Available online: https://www.cancer.gov/news-events/cancer-currents-blog/2021/red-meat-colorectal-cancer-genetic-signature (accessed on 21 June 2022).
- de Medeiros, G.C.B.S.; Mesquita, G.X.B.; Lima, S.C.V.C.; Silva, D.F.D.O.; de Azevedo, K.P.M.; Pimenta, I.D.S.F.; Oliveira, A.K.d.S.G.d.; Lyra, C.D.O.; Martínez, D.G.; Piuvezam, G. Associations of the consumption of unprocessed red meat and processed meat with the incidence of cardiovascular disease and mortality, and the dose-response relationship: A systematic review and meta-analysis of cohort studies. Crit. Rev. Food Sci. Nutr. 2022, 1, 1–14. [Google Scholar] [CrossRef] [PubMed]
- Delgado, J.; Ansorena, D.; Van Hecke, T.; Astiasarán, I.; De Smet, S.; Estévez, M. Meat lipids, NaCl and carnitine: Do they unveil the conundrum of the association between red and processed meat intake and cardiovascular diseases? Invited Review. Meat Sci. 2021, 171, 108278. [Google Scholar] [CrossRef] [PubMed]
- Binnie, M.A.; Barlow, K.; Johnson, V.; Harrison, C. Red meats: Time for a paradigm shift in dietary advice. Meat Sci. 2014, 98, 445–451. [Google Scholar] [CrossRef] [PubMed]
- Douglas, S.M.; Lasley, T.R.; Leidy, H.J. Consuming beef vs. soy protein has little effect on appetite, satiety, and food intake in healthy adults. J. Nutr. 2015, 145, 1010–1016. [Google Scholar] [CrossRef]
- Sayer, R.D.; Speaker, K.J.; Pan, Z.; Peters, J.C.; Wyatt, H.R.; Hill, J.O. Equivalent reductions in body weight during the Beef WISE study: Beef’s role in weight improvement, satisfaction and energy. Obes. Sci. Pract. 2017, 3, 298–310. [Google Scholar] [CrossRef]
- Couet, C.; Delarue, J.; Ritz, P.; Antoine, J.M.; Lamisse, F. Effect of dietary fish oil on body fat mass and basal fat oxidation in healthy adults. Int. J. Obes. 1997, 21, 637–643. [Google Scholar] [CrossRef]
- Thorsdottir, I.; Tomasson, H.; Gunnarsdottir, I.; Gisladottir, E.; Kiely, M.; Parra, M.D.; Bandarra, N.M.; Schaafsma, G.; Martinéz, J.A. Randomized trial of weight-loss-diets for young adults varying in fish and fish oil content. Int. J. Obes. 2007, 31, 1560–1566. [Google Scholar] [CrossRef]
- Due, A.; Larsen, T.M.; Mu, H.; Hermansen, K.; Stender, S.; Astrup, A. Comparison of 3 ad libitum diets for weight-loss maintenance, risk of cardiovascular disease, and diabetes: A 6-mo randomized, controlled trial. Am. J. Clin. Nutr. 2008, 88, 1232–1241. [Google Scholar]
- Vela-Vásquez, D.A.; Sifuentes-Rincón, A.M.; Delgado-Enciso, I.; Ordaz-Pichardo, C.; Arellano-Vera, W.; Treviño-Alvarado, V. Improvement of serum lipid parameters in consumers of Mexican Wagyu-Cross beef: A randomized controlled trial. J. Food Sci. 2021, 86, 2713–2726. [Google Scholar] [CrossRef] [PubMed]
- Piers, L.S.; Walker, K.Z.; Stoney, R.M.; Soares, M.J.; O’dea, K.K. The influence of the type of dietary fat on postprandial fat oxidation rates: Monounsaturated (olive oil) vs saturated fat (cream). Int. J. Obes. 2002, 26, 814–821. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Estruch, R.; Ros, E. The role of the Mediterranean diet on weight loss and obesity-related diseases. Rev. Endocr. Metab. Disord. 2020, 21, 315–327. [Google Scholar] [CrossRef] [PubMed]
- Varady, K.A.; Bhutani, S.; Klempel, M.C.; Kroeger, C.M.; Trepanowski, J.F.; Haus, J.M.; Hoddy, K.K.; Calvo, Y. Alternate day fasting for weight loss in normal weight and overweight subjects: A randomized controlled trial. Nutr. J. 2013, 12, 146. [Google Scholar] [CrossRef] [PubMed]
- Howell, S.; Kones, R. “Calories in, calories out” and macronutrient intake: The hope, hype, and science of calories. Am. J. Physiol. Endocrinol. Metab. 2017, 313, E608–E612. [Google Scholar] [CrossRef] [PubMed]
- Alfaia, C.M.M.; Alves, S.P.; Lopes, A.F.; Fernandes, M.J.E.; Costa, A.S.H.; Fontes, C.M.G.A.; Castro, M.L.F.; Bessa, R.J.B.; Pratesa, J.A.M. Effect of cooking methods on fatty acids, conjugated isomers of linoleic acid and nutritional quality of beef intramuscular fat. Meat Sci. 2010, 84, 769–777. [Google Scholar] [CrossRef]
- Aranceta-Bartrina, J.; Pérez-Rodrigo, C.; Alberdi-Aresti, G.; Ramos-Carrera, N.; Lázaro-Masedo, S. Prevalence of General Obesity and Abdominal Obesity in the Spanish Adult Population (Aged 25–64 Years) 2014–2015: The ENPE Study. Rev. Española Cardiol. 2016, 69, 579–587. [Google Scholar] [CrossRef]
- Marfell-Jones, F.E.R.M.; Vaquero-Cristóbal, R. Protocolo Internacional para la Valoración Antropométrica. Perfil Restrito; Universidad Católica de Murcia: Murcia, Spain, 2019. [Google Scholar]
- Vickers, A.J. The use of percentage change from baseline as an outcome in a controlled trial is statistically inefficient: A simulation study. BMC Med. Res. Methodol. 2001, 1, 6. [Google Scholar] [CrossRef]
- Dicker, D.; Alfadda, A.A.; Coutinho, W.; Cuevas, A.; Halford, J.C.G.; Hughes, C.A.; Iwabu, M.; Kang, J.; Nawar, R.; Reynoso, R.; et al. Patient motivation to lose weight: Importance of healthcare professional support, goals and self-efficacy. Eur. J. Intern. Med. 2021, 91, 10–16. [Google Scholar] [CrossRef]
- Kassir, R. Risk of COVID-19 for patients with obesity. Obes. Rev. 2020, 21, e13034. [Google Scholar] [CrossRef]
- Vergnaud, A.C.; Norat, T.; Romaguera, D.; Mouw, T.; May, A.M.; Travier, N.; Luan, J.; Wareham, N.; Slimani, N.; Rinaldi, S.; et al. Meat consumption and prospective weight change in participants of the EPIC-PANACEA study. Am. J. Clin. Nutr. 2010, 92, 398–407. [Google Scholar] [CrossRef] [PubMed]
- Franz, M.J.; VanWormer, J.J.; Crain, A.L.; Boucher, J.L.; Histon, T.; Caplan, W.; Bowman, J.D.; Pronk, N.P. Weight-loss outcomes: A systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J. Am. Diet. Assoc. 2007, 107, 1755–1767. [Google Scholar] [CrossRef] [PubMed]
- Krishnan, S.; Cooper, J.A. Effect of dietary fatty acid composition on substrate utilization and body weight maintenance in humans. Eur. J. Nutr. 2014, 53, 691–710. [Google Scholar] [CrossRef] [PubMed]
- Piers, L.S.; Walker, K.Z.; Stoney, R.M.; Soares, M.J.; O’Dea, K. Substitution of saturated with monounsaturated fat in a 4-week diet affects body weight and composition of overweight and obese men. Br. J. Nutr. 2003, 90, 717–727. [Google Scholar] [CrossRef] [PubMed]
- Sloth, B.; Due, A.; Larsen, T.M.; Holst, J.J.; Heding, A.; Astrup, A. The effect of a high-MUFA, low-glycemic index diet and a low-fat diet on appetite and glucose metabolism during a 6-month weight maintenance period. Br. J. Nutr. 2009, 101, 1846–1858. [Google Scholar] [CrossRef]
- Gonzalez, C.A.; Pera, G.; Quiros, J.R.; Lasheras, C.; Tormo, M.J.; Rodriguez, M.; Navarro, C.; Martinez, C.; Dorronsoro, M.; Chirlaue, M.D.; et al. Types of fat intake and body mass index in a Mediterranean country. Public Health Nutr. 2000, 3, 329–336. [Google Scholar] [CrossRef]
- De Koning, L.; Merchant, A.T.; Pogue, J.; Anand, S.S. Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: Meta-regression analysis of prospective studies. Eur. Heart J. 2007, 28, 850–856. [Google Scholar] [CrossRef]
- Schwingshackl, L.; Strasser, B.; Hoffmann, G. Effects of monounsaturated fatty acids on cardiovascular risk factors: A systematic review and meta-analysis. Ann. Nutr. Metab. 2011, 59, 176–186. [Google Scholar] [CrossRef]
- Bendall, C.L.; Mayr, H.L.; Opie, R.S.; Bes-Rastrollo, M.; Itsiopoulos, C.; Thomas, C.J. Central obesity and the Mediterranean diet: A systematic review of intervention trials. Crit. Rev. Food Sci. Nutr. 2018, 58, 3070–3084. [Google Scholar] [CrossRef]
- Mensink, R.P.; Zock, P.L.; Kester, A.D.M.; Katan, M.B. Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: A meta-analysis of 60 controlled trials. Am. J. Clin. Nutr. 2003, 77, 1146–1155. [Google Scholar] [CrossRef]
- Pelkman, C.L.; Fishell, V.K.; Maddox, D.H.; Pearson, T.A.; Mauger, D.T.; Kris-Etherton, P.M. Effects of moderate-fat (from monounsaturated fat) and low-fat weight-loss diets on the serum lipid profile in overweight and obese men and women. Am. J. Clin. Nutr. 2004, 79, 204–212. [Google Scholar] [CrossRef] [PubMed]
- Lahey, R.; Wang, X.; Carley, A.N.; Lewandowski, E.D. Dietary fat supply to failing hearts determines dynamic lipid signaling for nuclear receptor activation and oxidation of stored triglyceride. Circulation 2014, 130, 1790–1799. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gilmore, L.A.; Walzem, R.L.; Crouse, S.F.; Smith, D.R.; Adams, T.H.; Vaidyanathan, V.; Cao, X.; Smith, S.B. Consumption of high-oleic acid ground beef increases HDL-cholesterol concentration but both high- and low-oleic acid ground beef decrease HDL particle diameter in normocholesterolemic men. J. Nutr. 2011, 141, 1188–1194. [Google Scholar] [CrossRef] [PubMed]
- Alfonso, J.E.F.; Ariza, I.D.S. Elevando el colesterol HDL: ¿Cuál es la mejor estrategia? Rev. Assoc. Med. Bras. 2008, 54, 369–376. [Google Scholar] [CrossRef]
- Lefevre, M.; Redman, L.M.; Heilbronn, L.K.; Smith, J.V.; Martin, C.K.; Rood, J.C.; Greenway, F.L.; Williamson, D.A.; Smith, S.R.; Ravussin, E. Caloric restriction alone and with exercise improves CVD risk in healthy non obese individuals. Atherosclerosis 2009, 203, 206–213. [Google Scholar] [CrossRef]
- Eckel, R.H.; Jakicic, J.M.; Ard, J.D.; de Jesus, J.M.; Miller, N.H.; Hubbard, V.S.; Lee, I.M.; Lichtenstein, A.H.; Loria, C.M.; Millen, B.E.; et al. 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: A report of the American College of cardiology/American Heart Association task force on practice guidelines. Circulation 2014, 129, S76–S99. [Google Scholar] [CrossRef]
- Wolk, A. Potential health hazards of eating red meat. J. Intern. Med. 2017, 281, 106–122. [Google Scholar] [CrossRef]
- Yancey, P.G.; Bortnick, A.E.; Kellner-Weibel, G.; De la Llera-Moya, M.; Phillips, M.C.; Rothblat, G.H. Importance of different pathways of cellular cholesterol efflux. Arter. Thromb. Vasc. Biol. 2003, 23, 712–719. [Google Scholar] [CrossRef]
- Williams, P.T.; Stefanick, M.L.; Vranizan, K.M.; Wood, P.D. The effects of weight loss by exercise or by dieting on plasma high-density lipoprotein (HDL) levels in men with low, intermediate, and normal-to-high HDL at baseline. Metabolism 1994, 43, 917–924. [Google Scholar] [CrossRef]
- Welty, F.K. How do elevated triglycerides and low HDL-cholesterol affect inflammation and atherothrombosis? Curr. Cardiol. Rep. 2013, 15, 400. [Google Scholar] [CrossRef]
- Ganda, O.P. When to lower triglycerides? Curr. Opin. Lipidol. 2020, 31, 238–245. [Google Scholar] [CrossRef] [PubMed]
- Al-Shaar, L.; Satija, A.; Wang, D.D.; Rimm, E.B.; Smith-Warner, S.A.; Stampfer, M.J.; Hu, F.B.; Willett, W.C. Red meat intake and risk of coronary heart disease among US men: Prospective cohort study. BMJ 2020, 371, m4141. [Google Scholar] [CrossRef] [PubMed]
- Takata, Y.; Shu, X.O.; Gao, Y.T.; Li, H.; Zhang, X.; Gao, J.; Cai, H.; Yang, G.; Xiang, Y.-B.; Zheng, W. Red meat and poultry intakes and risk of total and cause-specific mortality: Results from cohort studies of Chinese adults in Shanghai. PLoS ONE 2013, 8, e56963. [Google Scholar]
- Bernstein, A.M.; Pan, A.; Rexrode, K.M.; Stampfer, M.; Hu, F.B.; Mozaffarian, D.; Willett, W.C. Dietary protein sources and the risk of stroke in men and women. Stroke 2012, 43, 637–644. [Google Scholar] [CrossRef]
- Rohrmann, S.; Zoller, D.; Hermann, S.; Linseisen, J. Intake of heterocyclic aromatic amines from meat in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Heidelberg cohort. Br. J. Nutr. 2007, 98, 1112–1115. [Google Scholar] [CrossRef]
- Le Marchand, L. The role of heterocyclic aromatic amines in colorectal cancer: The evidence from epidemiologic studies. Genes Environ. 2021, 43, 20. [Google Scholar] [CrossRef]
- Kim, Y.; Keogh, J.; Clifton, P. A review of potential metabolic etiologies of the observed association between red meat consumption and development of type 2 diabetes mellitus. Metabolism 2015, 64, 768–779. [Google Scholar] [CrossRef]
- Courtney, C.H.; Olefsky, J.M. Insulin resistance. In Mechanisms of Insulin Action: Medical Intelligence Unit; Springer: New York, NY, USA, 2007; pp. 185–209. [Google Scholar]
- Pinillos, M.D.; Paz-Rojas, E.; Montilla, P.; Velasco, M.J.; Blanco-Molina, A.; Perez-Jimenez, F.; Lopez-Miranda, J.; Pinillos, M.D.; Gomez, P.; Paz-Rojas, E.; et al. A Mediterranean and a high-carbohydrate diet improve glucose metabolism in healthy young persons. Diabetologia 2001, 44, 2038–2043. [Google Scholar]
- Paniagua, J.A.; De La Sacristana, A.G.; Romero, I.; Vidal-Puig, A.; Latre, J.M.; Sanchez, E.; Perez-Martinez, P.; Lopez-Miranda, J.; Perez-Jimenez, F. Monounsaturated fat–rich diet prevents central body fat distribution and decreases postprandial adiponectin expression induced by a carbohydrate-rich diet in insulin-resistant subjects. Diabetes Care 2007, 30, 1717–1723. [Google Scholar] [CrossRef]
- Chiu, S.; Williams, P.T.; Dawson, T.; Bergman, R.N.; Stefanovski, D.; Watkins, S.M.; Krauss, R.M. Diets high in protein or saturated fat do not affect insulin sensitivity or plasma concentrations of lipids and lipoproteins in overweight and obese adults. J. Nutr. 2014, 144, 1753–1759. [Google Scholar] [CrossRef]
- Hallström, E.; Röös, E.; Börjesson, P. Sustainable meat consumption: A quantitative analysis of nutritional intake, greenhouse gas emissions and land use from a Swedish perspective. Food Policy 2014, 47, 81–90. [Google Scholar] [CrossRef]
- Nijdam, D.; Rood, T.; Westhoek, H. The price of protein: Review of land use and carbon footprints from life cycle assessments of animal food products and their substitutes. Food Policy 2012, 37, 760–770. [Google Scholar] [CrossRef]
- Greenwood, P.L.; Gardner, G.E.; Ferguson, D.M. Current situation and future prospects for the Australian beef industry—A review. Asian-Australas. J. Anim. Sci. 2018, 31, 992. [Google Scholar] [CrossRef]
- Pierrehumbert, R.T.; Eshel, G. Climate impact of beef: An analysis considering multiple time scales and production methods without use of global warming potentials. Environ. Res. Lett. 2015, 10, 085002. [Google Scholar] [CrossRef] [Green Version]
- Consejo Mexicano De La Carne. Compendio Estadístico. 2022. Available online: https://comecarne.org/compendio-estadistico-2022 (accessed on 21 June 2022).
- Wistar, A.; Hall, M.G.; Bercholz, M.; Taillie, L.S. Designing environmental messages to discourage red meat consumption: An online experiment. Int. J. Environ. Res. Public Health 2022, 19, 2919. [Google Scholar] [CrossRef] [PubMed]
Clinic Characteristic | Group | p Value * | |
---|---|---|---|
Commercial Beef (SD) | Wagyu-Cross Beef (SD) | ||
Age, Years | 34.5 (27.25–42.50) | 42.0 (32.50–49.50) | 0.098 |
Body weight, kg | 81.80 (72.60–100.18) | 75.15 (71.73–94.80) | 0.571 |
BMI (kg/m2) | 30.41 (25.50–32.73) | 30.07 (26.31–34.29) | 1.000 |
Waist circumference, cm | 95.00 (85.88–105.38) | 90.00 (81.50–100.80) | 0.473 |
Hip circumference, cm | 112.45 (99.38–121.73) | 108.85 (102.63–110.75) | 0.571 |
WHR | 0.85 (0.79–0.88) | 0.87 (0.75–0.92) | 0.910 |
Abdominal circumference, cm | 108.25 (91.63–112.00) | 96.75 (93.25–110.78) | 0.678 |
Cholesterol (mg/dL) | 169.0 (155.75–194.75) | 170.50 (150.50–197.0) | 1.000 |
Triglycerides (mg/dL) | 136.50 (99.75–196.00) | 123.0 (88.75–170.48) | 0.678 |
HDL-C (mg/dL) | 38.50 (35.50–46.00) | 40.00 (35.83–47.75) | 0.571 |
LDL-C (mg/dL) | 105.50 (94.00–114.75) | 100.50 (84.50–124.25) | 0.624 |
VLDL-C (mg/dL) | 27.00 (19.75–39.00) | 24.50 (18.00–30.45) | 0.678 |
Non-HDL-C | 129.5 (120.00–150.00) | 128.50 (112.0–153.0) | 0.851 |
TC/HDL-C | 4.41 (3.77–4.86) | 3.98 (3.71–4.82) | 0.571 |
LDL-C/HDL-C | 2.88 (2.10–2.95) | 2.52 (2.05–3.16) | 0.678 |
Non-HDL-C/HDL-C | 3.41 (2.77–3.86) | 2.98 (2.71–3.82) | 0.571 |
TC * TG * LDL-C/HDL-C | 16.20 (10.87–27.77) | 16.07 (10.19–24.06) | 0.851 |
Glucose (mg/dL) | 99.00 (89.25–101.75) | 97.5 (89.88–106.50) | 0.678 |
BMI | Macronutrient | Group | p Value * | |
---|---|---|---|---|
Commercial Beef | Wagyu-Cross Beef | |||
≥25–≤29.9 kg/m2 | Kcal | 1297.17 (88.30) | 1246.55 (49.27) | 0.293 |
Lipids, % | 29.69 (1.57) | 35.26 (1.86) | 0.003 | |
MUFA, g | 15.17 (2.35) | 20.03 (1.10) | 0.003 | |
SFA, g | 12.06 (0.36) | 16.44 (0.53) | 0.000 | |
PUFA, g | 4.45 (0.82) | 4.44 (0.14) | 0.984 | |
MUFA, g (NO BEEF-FAT) | 8.70 (2.78) | 6.52 (2.24) | 0.240 | |
SFA, g (NO BEEF-FAT) | 5.71 (1.66) | 4.83 (1.11) | 0.366 | |
PUFA, g (NO BEEF-FAT) | 3.89 (1.13) | 3.48 (0.33) | 0.414 | |
≥30 kg/m2 | Kcal | 1535.13 (149.85) | 1424.11 (193.06) | 0.323 |
Lipids, % | 28.60 (1.53) | 34.09 (1.44) | 0.000 | |
MUFA, g | 16.30 (1.88) | 21.45 (1.56) | 0.001 | |
SFA, g | 13.37 (1.31) | 17.82 (1.21) | 0.000 | |
PUFA, g | 5.26 (1.03) | 4.91 (0.60) | 0.497 | |
MUFA, g (NO BEEF-FAT) | 8.50 (1.88) | 6.33 (1.56) | 0.541 | |
SFA, g (NO BEEF-FAT) | 6.25 (1.31) | 5.19 (1.21) | 0.863 | |
PUFA, g (NO BEEF-FAT) | 4.48 (1.03) | 3.43 (0.60) | 0.278 |
Clinical Characteristic | Group | p Value † | |
---|---|---|---|
Commercial Beef | Wagyu-Cross Beef | ||
Weight (kg) | |||
Baseline | 81.80 (72.60–100.18) | 75.15 (71.73–94.80) | |
Final | 77.60 (69.73–96.68) | 71.45 (67.93–92.55) | |
p Value ^ | 0.036 | 0.002 | |
Change | −2.90 (−4.25 to −0.93) | −3.75 (−5.38 to −2.95) | 0.297 |
BMI (kg/m2) | |||
Baseline | 30.41 (25.50–32.73) | 30.07 (26.31–34.29) | |
Final | 28.76 (26.00–31.17) | 28.34 (24.78–33.01) | |
p Value ^ | 0.036 | 0.002 | |
Change | −1.03 (−1.66 to −0.30) | −1.49 (−2.05 to −1.06) | 0.203 |
WC * | |||
Baseline | 95.00 (85.88–105.38) | 90.00 (81.50–100.80) | |
Final | 87.00 (79.10–98.50) | 85.00 (74.38–96.48) | |
p Value ^ | 0.012 | 0.002 | |
Change | −6.75 (−7.80 to −4.75) | −4.80 (−9.25 to −3.00) | 0.246 |
HC * | |||
Baseline | 112.45 (99.38–121.73) | 108.85 (102.63–110.75) | |
Final | 106.00 (87.38–118.05) | 104.65 (100.05–108.68) | |
p Value ^ | 0.012 | 0.005 | |
Change | −6.45 (−15.15 to −2.55) | −4.10 (−4.88 to −2.00) | 0.189 |
WHR | |||
Baseline | 0.85 (0.79–0.88) | 0.87 (0.75–0.92) | |
Final | 0.85 (0.81–0.90) | 0.84 (0.74–0.89) | |
p Value ^ | 0.674 | 0.014 | |
Change | −0.02 (−0.04 to 0.07) | −0.02 (−0.06 to −0.01) | 0.430 |
AC * | |||
Baseline | 108.25 (91.63–112.00) | 96.75 (93.25–110.78) | |
Final | 100.20 (98.23–109.43) | 91.15 (87.25–106.00) | |
p Value ^ | 0.484 | 0.004 | |
Change | −3.05 (−7.33 to 5.45) | −5.25 (−6.75 to −3.68) | 0.203 |
Clinical Characteristic | Group | p Value † | |
---|---|---|---|
Commercial Beef | Wagyu-Cross Beef | ||
Cholesterol * | |||
Baseline | 169.0 (155.75–194.75) | 170.50 (150.50–197.0) | |
Final | 174.00 (144.0–182.50) | 161.5 (143.75–186.65) | |
p Value ^ | 0.612 | 0.209 | |
Change | 4.00 (−34.00 to 23.75) | −11.00 (−18.60 to 8.75) | 0.700 |
HDL-C * | |||
Baseline | 38.50 (35.50–46.00) | 40.00 (35.83–47.75) | |
Final | 48.50 (40.75–54.00) | 41.00 (33.80–46.75) | |
p Value ^ | 0.021 | 0.556 | |
Change | 8.50 (4.50 to 11.75) | 1.55 (−4.75 to 8.00) | 0.069 |
LDL-C * | |||
Baseline | 105.50 (94.00–114.75) | 100.50 (84.50–124.25) | |
Final | 101.50 (78.25–114.75) | 90.50 (82.25–122.78) | |
p Value ^ | 0.575 | 0.666 | |
Change | 4.50 (−44.00 to 20.75) | −8.00 (−14.00 to 11.00) | 0.877 |
VLDL-C * | |||
Baseline | 27.00 (19.75–39.00) | 24.50 (18.00–30.45) | |
Final | 20.00 (14.50–29.25) | 20.00 (16.50–25.50) | |
p Value ^ | 0.034 | 0.025 | |
Change | −5.50 (−8.75 to −0.75) | −4.91 (−7.50 to 1.25) | 0.698 |
TG * | |||
Baseline | 136.50 (99.75–196.00) | 123.0 (88.75–170.48) | |
Final | 103.00 (73.00–149.50) | 101.50 (82.00–150.85) | |
p Value ^ | 0.025 | 0.023 | |
Change | −26.00 (−42.25 to −5.50) | −21.75 (−38.00 to 2.50) | 0.616 |
Non-HDL-C | |||
Baseline | 129.5 (120.00–150.00) | 128.50 (112.0–153.0) | |
Final | 131.50 (95.25–135.00) | 124.0 (104.75–144.25) | |
p Value ^ | 0.575 | 0.158 | |
Change | 2.00 (−44.75 to 15.00) | −11.00 (−18.68 to 5.50) | 0.847 |
TC/HDL-C | |||
Baseline | 4.41 (3.77–4.86) | 3.98 (3.71–4.82) | |
Final | 3.75 (2.91–4.36) | 3.83 (3.57–4.42) | |
p Value ^ | 0.069 | 0.041 | |
Change | −0.55 (−1.64 to 0.01) | −0.38 (−0.63 to −0.11) | 0.335 |
LDL-C/HDL-C | |||
Baseline | 2.88 (2.10–2.95) | 2.52 (2.05–3.16) | |
Final | 2.20 (1.60–2.69) | 2.36 (2.08–2.75) | |
p Value ^ | 0.208 | 0.084 | |
Change | −0.39 (−1.54 to 0.28) | −0.25 (−0.50 to 0.03) | 0.512 |
Non-HDL-C/HDL-C | |||
Baseline | 3.41 (2.77–3.86) | 2.98 (2.71–3.82) | |
Final | 2.75 (1.91–3.36) | 2.83 (2.57–3.42) | |
p Value ^ | 0.069 | 0.041 | |
Change | −0.55 (−1.64 to 0.01) | −0.38 (−0.63 to −0.11) | 0.335 |
TC * TG * LDL-C/HDL-C | |||
Baseline | 16.20 (10.87–27.77) | 16.07 (10.19–24.06) | |
Final | 12.88 (4.74–22.25) | 11.48 (9.62–16.75) | |
p Value ^ | 0.050 | 0.084 | |
Change | −2.77 (−9.19 to 0.35) | −4.42 (−7.50 to 1.15) | 0.939 |
Glucose * | |||
Baseline | 99.00 (89.25–101.75) | 97.5 (89.88–106.50) | |
Final | 103.50 (97.50–116.00) | 94.95 (82.50–109.00) | |
p Value ^ | 0.036 | 0.480 | |
Change | 11.50 (0.25 to 14.50) | 0.50 (−15.75 to 7.10) | 0.013 |
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Vela-Vásquez, D.A.; Sifuentes-Rincón, A.M.; Delgado-Enciso, I.; Ordaz-Pichardo, C.; Arellano-Vera, W.; Treviño-Alvarado, V. Effect of Consuming Beef with Varying Fatty Acid Compositions as a Major Source of Protein in Volunteers under a Personalized Nutritional Program. Nutrients 2022, 14, 3711. https://doi.org/10.3390/nu14183711
Vela-Vásquez DA, Sifuentes-Rincón AM, Delgado-Enciso I, Ordaz-Pichardo C, Arellano-Vera W, Treviño-Alvarado V. Effect of Consuming Beef with Varying Fatty Acid Compositions as a Major Source of Protein in Volunteers under a Personalized Nutritional Program. Nutrients. 2022; 14(18):3711. https://doi.org/10.3390/nu14183711
Chicago/Turabian StyleVela-Vásquez, Diana A., Ana M. Sifuentes-Rincón, Iván Delgado-Enciso, Cynthia Ordaz-Pichardo, Williams Arellano-Vera, and Víctor Treviño-Alvarado. 2022. "Effect of Consuming Beef with Varying Fatty Acid Compositions as a Major Source of Protein in Volunteers under a Personalized Nutritional Program" Nutrients 14, no. 18: 3711. https://doi.org/10.3390/nu14183711
APA StyleVela-Vásquez, D. A., Sifuentes-Rincón, A. M., Delgado-Enciso, I., Ordaz-Pichardo, C., Arellano-Vera, W., & Treviño-Alvarado, V. (2022). Effect of Consuming Beef with Varying Fatty Acid Compositions as a Major Source of Protein in Volunteers under a Personalized Nutritional Program. Nutrients, 14(18), 3711. https://doi.org/10.3390/nu14183711