Asociación entre el síndrome metabólico y el gasto energético total diario en adultos: Análisis transversal de pobladores peruanos.
DOI:
https://doi.org/10.12873/442guerraPalavras-chave:
Gasto de Energía, Metabolismo Energético, Composición Corporal, Síndrome MetabólicoResumo
Introducción: El gasto energético total (GET) desempeña un papel crucial en el balance energético y la regulación del peso corporal, pero se ha investigado poco sobre su relación con el síndrome metabólico (SM). Recientemente, el Instituto de Medicina (IOM) de los Estados Unidos publicó ecuaciones de regresión actualizadas, validadas con el agua doblemente marcada, ofreciendo herramientas precisas para su aplicación en el escenario clínico.
Objetivo: Analizar la asociación entre el síndrome metabólico y el GET en la población peruana adulta de 30-59 años.
Metodología: Estudio analítico observacional, de corte transversal con datos del estudio PERU MIGRANT. Se incluyeron un total de 700 participantes de 30-59 años (promedio 43,44 y desviación estándar 8,41), sin antecedentes de diabetes e hipertensión. El 53,86% fueron mujeres. Se estimó el GET a través de las ecuaciones del IOM (2023) expresándolo en kcal/día, kcal/kg y kcal/kg de masa libre de grasa (MLG). El SM se definió según el consenso armonizado donde se consideró SM a aquellos con ≥3 factores de riesgo cardio-metabólicos. Se realizó un modelo lineal generalizado con enlace identidad y familia Gaussian, para obtener los coeficientes beta crudos y ajustados con IC95%.
Resultados: La prevalencia de SM fue 23,00%. La regresión múltiple reveló que el SM se asoció positiva y significativamente con el GET absoluto, en ambos sexos. Sin embargo, la presencia de SM mostró asociaciones negativas con el GET relativo a masa total para ambos sexos. El SM y el GET relativo a MLG mostró relación inversa y solo fue significativo en mujeres.
Conclusiones: El SM se asocia positivamente con el GET absoluto. Contrariamente, la presencia de SM se relaciona de forma negativa con el GET relativo a la masa total y MLG.
Referências
Rimbach R, Yamada Y, Sagayama H, Ainslie PN, Anderson LF, Anderson LJ, et al. Total energy expenditure is repeatable in adults but not associated with short-term changes in body composition. Nat Commun. 2022;13(1):99.
Hall KD, Farooqi IS, Friedman JM, Klein S, Loos RJF, Mangelsdorf DJ, et al. The energy balance model of obesity: beyond calories in, calories out. Am J Clin Nutr. 2022;115(5):1243-54.
Vaduganathan M, Mensah George A, Turco Justine V, Fuster V, Roth Gregory A. The Global Burden of Cardiovascular Diseases and Risk. J Am Coll Cardiol. 2022;80(25):2361-71.
Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the Metabolic Syndrome. Circulation. 2009;120(16):1640-5.
Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The Metabolic Syndrome and Cardiovascular Risk: A Systematic Review and Meta-Analysis. J Am Coll Cardiol. 2010;56(14):1113-32.
Márquez-Sandoval F, Macedo-Ojeda G, Viramontes-Hörner D, Fernández Ballart JD, Salas Salvadó J, Vizmanos B. The prevalence of metabolic syndrome in Latin America: a systematic review. Public Health Nutr. 2011;14(10):1702-13.
Calton EK, Pathak K, Soares MJ, Alfonso H, Keane KN,
Newsholme P, et al. Vitamin D status and insulin sensitivity are novel predictors of resting metabolic rate: a cross-sectional analysis in Australian adults. Eur J Nutr. 2016;55(6):2075-80.
Conus F, Allison DB, Rabasa-Lhoret Rm, St-Onge M, St-Pierre DH,
Tremblay-Lebeau Aa, et al. Metabolic and Behavioral
Characteristics of Metabolically Obese but Normal-Weight Women. J Clin Endocrinol Metab. 2004;89(10):5013-20.
Karkhaneh M, Qorbani M, Ataie-Jafari A, Mohajeri-Tehrani MR, Asayesh H, Hosseini S. Association of thyroid hormones with resting energy expenditure and complement C3 in normal weight high body fat women. Thyroid Res. 2019;12(1):9.
Lee JC, Westgate K, Boit MK, Mwaniki DL, Kiplamai FK, Friis H, et al. Physical activity energy expenditure and cardiometabolic health in three rural Kenyan populations. Am J Hum Biol. 2019;31(1):e23199.
Soares M, Zhao Y, Calton E, Pathak K, Chan She Ping-Delfos W, Cummings N, et al. The Impact of the Metabolic Syndrome and
Its Components on Resting Energy Expenditure. Metabolites. 2022; 12(8):722.
Dalleck L VGG, Richardson T, Bredle D, Janot J. A communitybased exercise intervention transitions metabolically abnormal obese adults to a metabolically healthy obese phenotype. Diabetes Metab Syndr Obes 2014;7:369-80.
Kaino W, Daimon M, Sasaki S, Karasawa S, Takase K, Tada K, et al. Lower physical activity is a risk factor for a clustering of metabolic risk factors in non-obese and obese Japanese subjects: The Takahata study. Endocr J. 2013;60(5):617-28.
Karelis AD, Lavoie M-È, Messier V, Mignault D, Garrel D, Prud’homme D, et al. Relationship between the metabolic syndrome and physical activity energy expenditure: a MONET study. Appl Physiol Nutr Metab. 2008;33(2):309-14.
Santos DMV, Katzmarzyk PT, Diego VP, Souza MC, Chaves RN, Blangero J, et al. Genotype by Energy Expenditure Interaction with Metabolic Syndrome Traits: The Portuguese Healthy Family Study. PLoS One. 2013;8(11):e80417.
Macena MdL, Paula DTdC, da Silva Júnior AE, Praxedes DRS, Pureza IRdOM, de Melo ISV, et al. Estimates of resting energy expenditure and total energy expenditure using predictive equations in adults with overweight and obesity: a systematic review with meta-analysis. Nutr Rev. 2022;80(11):2113-35.
National Academies of Sciences Engineering, and Medicine. Dietary Reference Intakes for Energy. Development of Prediction Equations for Estimated Energy Requirements. Washington (DC): Health and Medicine Division; Food and Nutrition Board; Committee on the Dietary Reference Intakes for Energy; 2023.
Miranda JJ, Gilman RH, García HH, Smeeth L. The effect on cardiovascular risk factors of migration from rural to urban areas in Peru: PERU MIGRANT Study. BMC Cardiovasc Disord. 2009;9(1):23.
Pontzer H, Yamada Y, Sagayama H, Ainslie PN, Andersen LF, Anderson LJ, et al. Daily energy expenditure through the human life course. Science. 2021;373(6556):808-12.
Riley L, Guthold R, Cowan M, Savin S, Bhatti L, Armstrong T, et al. The World Health Organization STEPwise Approach to
Noncommunicable Disease Risk-Factor Surveillance: Methods,
Challenges, and Opportunities. Am J Public Health. 2015; 106(1):74-8.
IPAQ website. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)—Short and Long Forms. [Available from: https://sites.google.com/view/ipaq/ score.
Higgins PB, Comuzzie AG. Measures of Waist Circumference. In: Preedy VR, editor. Handbook of Anthropometry: Physical Measures of Human Form in Health and Disease. New York, NY: Springer New York; 2012. p. 881-91.
Durnin JVGA, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 Years. Br J Nutr. 1974;32(1):77-97.
Carrillo-Larco RM, Miranda JJ, Gilman RH, Checkley W, Smeeth L,
Bernabe-Ortiz A, et al. The HOMA-IR Performance to Identify New
Diabetes Cases by Degree of Urbanization and Altitude in Peru: The CRONICAS Cohort Study. J Diabetes Res. 2018;2018:7434918.
Myers GL, Rifai N, Tracy RP, Roberts WL, Alexander RW, Biasucci LM, et al. CDC/AHA Workshop on Markers of Inflammation and Cardiovascular Disease. Circulation. 2004;110(25):e545-e9.
Miranda JJB-O, Antonio; Carrillo Larco, Rodrigo. PERU MIGRANT Study | Baseline and 5yr follow-up dataset. In: Figshare., editor. 2017.
Yépez García MC, Herrera-Cuenca M, Ferrari G, Sanabria LY, Hernández P, Almeida RY, et al. Energy Imbalance Gap,
Anthropometric Measures, Lifestyle, and Sociodemographic
Correlates in Latin American Adults—Results from the ELANS Study. Int J Environ Res Public Health. 2022; 19(3): 1129.
Messier V, Karelis AD, Prud’homme D, Primeau V, Brochu M, Rabasa-Lhoret R. Identifying Metabolically Healthy but Obese Individuals in Sedentary Postmenopausal Women. Obesity. 2010;18(5):911-7.
Leão LSCdS, Moraes MMd, Carvalho GXd, Koifman RJ. Intervenções nutricionais em Síndrome Metabólica: uma revisão sistemática. Arq Bras Cardiol. 2011;97(3): 260-5.
Bettini S, Favaretto F, Compagnin C, Belligoli A, Sanna M, Fabris R, et al. Resting Energy Expenditure, Insulin Resistance and UCP1 Expression in Human Subcutaneous and Visceral Adipose Tissue of Patients With Obesity. Front Endocrinol (Lausanne). 2019;10: 548.
Downloads
Publicado
Como Citar
Licença
Copyright (c) 2024 Nutrición Clínica y Dietética Hospitalaria
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Los lectores pueden utilizar los textos publicados de acuerdo con la definición BOAI (Budapest Open Access Initiative)
