Association between cardiorespiratory fitness and cardiometabolic risk factors in Brazilian children and adolescents: the mediating role of obesity parameters

References

• Sapunar J, Aguilar-Farías N, Navarro J, et al. High prevalence of overweight, obesity, insulin resistance and metabolic syndrome in rural children and adolescents. Rev Med Chil. 2018;146:978–986.
   Google Scholar
• Akbari M, Moosazadeh M, Ghahramani S, et al. High prevalence of hypertension among Iranian children and adolescents: a systematic review and meta-analysis. J Hypertens. 2017;35:155–163.
   Google Scholar
• Reuter CP, Brand C, Silva PT, et al. Relationship between dyslipidemia, cultural factors, and cardiorespiratory fitness in schoolchildren. Arq Bras Cardiol. 2019;112:6729–6736.
   Google Scholar
• Vos MB, Kaar JL, Welsh JA, et al. Added sugars and cardiovascular disease risk in children: a scientific statement from the American heart association. Circulation. 2017;135:1017–1034.
   Google Scholar
• Defronzo RA, Blangero J, Hale DE, et al. Genetic and environmental (physical fitness and sedentary activity) interaction effects on cardiometabolic risk factors in Mexican American children and adolescents. Genet Epidemiol. 2019;42:378–393.
   Google Scholar
• Ruiz JR, Cavero-Redondo I, Ortega FB, et al. Cardiorespiratory fitness cutoff points to avoid cardiovascular disease risk in children and adolescents; what level of fitness should raise a red flag? A systematic review and meta-analysis. Br J Sports Med. 2016;50:1451–1458.
   Google Scholar
• Lang AJJ, Belanger K, Poitras V, et al. Systematic review of the relationship between 20 m shuttle run performance and health indicators among children and youth. J Sci Med Sport. 2018;21:383–397.
   Google Scholar
• Ruiz JR, Castro-Piñero J, Artero EG, et al. Predictive validity of health-related fitness in youth: a systematic review. Br J Sports Med. 2009;43:909–923.
   Google Scholar
• Serrano NC, Paola D, Robles A, et al. Association between body fat mass and cardiometabolic risk in children and adolescents in Bucaramanga, Colombia. Int J Pediatr Adolesc Med. 2019;6:135–141.
   Google Scholar
• Quadros TMB, Gordia AP, Silva LR. Anthropometry and clustered cardiometabolic risk factors in young people: a systematic review. Rev Paul Pediatr. 2017;35:340–350.
   Google Scholar
• Agredo-Zúñiga RA, Aguilar-De Plata C, Suárez-Ortegón MF. Waist:height ratio, waist circumference and metabolic syndrome abnormalities in Colombian schooled adolescents: a multivariate analysis considering located adiposity. Br J Nutr. 2015;114:700–705.
   Google Scholar
• Gaya AR, Brand C, Dias AF, et al. Obesity anthropometric indicators associated with cardiometabolic risk in Portuguese children and adolescents. Prev Med Reports. 2017;8:158–162.
   Google Scholar
• Pérez-Bey A, Segura-Jiménez V, Fernández-Santos J, et al. The influence of cardiorespiratory fitness on clustered cardiovascular disease risk factors and the mediator role of BMI in youth: the UP&DOWN study. Pediatr Diabetes. 2019;20:32–40.
   Google Scholar
• Diez-Fernandez A, Sanchez-Lopez M, Mora-Rodriguez R, et al. Obesity as a mediator of the influence of cardiorespiratory fitness on cardiometabolic risk: a mediation analysis. Diabetes Care. 2014;37:855–862.
   Google Scholar
• Bailey D, Savory L, Denton S, et al. The association between cardiorespiratory fitness and cardiometabolic risk in children is mediated by abdominal adiposity: the HAPPY Study. J Phys Act Heal. 2015;12:1148–1152.
   Google Scholar
• Brand C, Dias AF, Fochesatto CF, et al. The role of body fat in the relationship of cardiorespiratory fitness with cardiovascular risk factors in Brazilian children. Motriz. 2018;24:1–6.
   Google Scholar
• Gaya AC, Gaya AR. Manual for the application of measures and tests, standards and evaluation criteria. Porto Alegre: UFRGS; 2016. Available from: https://www.ufrgs.br/proesp/arquivos/manual-proesp-br-2016.pdf
   Google Scholar
• Bergmann G, Bergmann M, Castro A, et al. Use of the 6-minute walk/run test to predict peak oxygen uptake in adolescents. Rev Bras Ativ Fis Saúde. 2014;19:64–73.
   Google Scholar
• Granacher U, Borde R. Effects of sport-specific training during the early stages of long-term athlete development on physical fitness, body composition, cognitive, and academic performances. Front Physiol. 2017;8:810.
   Google Scholar
• World Health Organization. Growth reference data for 5–19 years. Geneva: WHO; 2007.
   Google Scholar
• Slaughter MH, Lohman TG, Boileau RA, et al. Skinfold equations for estimation of body fatness in children and youth. Hum Biol. 1988;60:709–723.
   Google Scholar
• Tanner JM. Normal growth and techniques of growth assessment. Clin Endocrinol Metab. 1986;15:411–451.
   Google Scholar
• Brazilian Society of Nephrology, Brazilian Society of Cardiology, Brazilian Society of Hypertension. VI Brazilian hypertension guidelines. Arq Bras Cardiol. 2010;95:1–51.
   Google Scholar
• Preacher KJ, Haye AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods. 2008;40:879–891.
   Google Scholar
• Nyström CD, Henriksson P, Martínez-Vizcaíno V, et al. Does cardiorespiratory fitness attenuate the adverse effects of severe/morbid obesity on cardiometabolic risk and insulin resistance in children? A pooled analysis. Diabetes Care. 2017;40:1580–1587.
   Google Scholar
• Cornier M, Despre J, Lopez-jimenez F, et al. Assessing adiposity: a scientific statement from the American heart association. Circulation. 2011;124:1996–2019.
   Google Scholar
• Konieczna J, Abete I, Galmés AM, et al. Body adiposity indicators and cardiometabolic risk: cross-sectional analysis in participants from the PREDIMED-Plus trial. Clin Nutr. 2019;38:1883–1891.
   Google Scholar
• Xi B, Zong X, Kelishadi R, et al. International waist circumference percentile cut-offs for central obesity in children and adolescents aged 6–18 years. J Clin Endocrinol Metab. 2020;105:1569–1583.
   Google Scholar
• Ashwell M, Hsieh SD. Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr. 2005;56:303–307.
   Google Scholar
• Rodea-Montero ER, Evia-Viscarra ML, Apolinar-Jiménez E. Waist-to-height ratio is a better anthropometric index than waist circumference and BMI in predicting metabolic syndrome among obese Mexican adolescents. Int J Endocrinol. 2014;2014:195407.
   Google Scholar
• Browning LM, Hsieh SD, Ashwell M. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev. 2010;23:247–269.
   Google Scholar
• Simmonds M, Llewellyn A, Owen CG, et al. Predicting adult obesity from childhood obesity: a systematic review and meta-analysis. Obes Rev. 2016;17:95–107.
   Google Scholar
• Ho M, Garnett SP, Baur L, et al. Effectiveness of lifestyle interventions in child obesity: systematic review with meta-analysis. Pediatrics. 2012;130:1647–1671.
   Google Scholar
• Sbruzzi G, Eibel B, Barbiero SM, et al. Educational interventions in childhood obesity: a systematic review with meta-analysis of randomized clinical trials. Prev Med. 2013;56:254–264.
   Google Scholar