Association of Healthy Eating Index-2015 and Dietary Approaches to Stop Hypertension Patterns with Insulin Resistance in Schoolchildren
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Sample
2.2. Anthropometric Study
2.3. Physical Activity
2.4. Dietetic Study
2.5. Biochemical Studies
2.6. Statistical Analysis
3. Results
3.1. Sample Characteristics
3.2. Diet Quality
3.3. Risk of IR
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Liang, Y.; Hou, D.; Zhao, X.; Wang, L.; Hu, Y.; Liu, J.; Cheng, H.; Yang, P.; Shan, X.; Yan, Y.; et al. Childhood obesity affects adult metabolic syndrome and diabetes. Endocrine 2015, 50, 87–92. [Google Scholar] [CrossRef]
- Temneanu, O.; Trandafir, L.; Purcarea, M.R. Type 2 diabetes mellitus in children and adolescents: A relatively new clinical problem within pediatric practice. J. Med. Life 2016, 9, 235–239. [Google Scholar] [PubMed]
- Thumann, B.F.; Michels, N.; Felső, R.; Hunsberger, M.; Kaprio, J.; Moreno, L.A.; Siani, A.; Tornaritis, M.; Veidebaum, T.; De Henauw, S.; et al. Associations between sleep duration and insulin resistance in European children and adolescents considering the mediating role of abdominal obesity. PLoS ONE 2020, 15, e0235049. [Google Scholar] [CrossRef] [PubMed]
- Zupo, R.; Sardone, R.; Donghia, R.; Castellana, F.; Lampignano, L.; Bortone, I.; Misciagna, G.; De Pergola, G.; Panza, F.; Lozupone, M.; et al. Traditional Dietary Patterns and Risk of Mortality in a Longitudinal Cohort of the Salus in Apulia Study. Nutrients 2020, 12, 1070. [Google Scholar] [CrossRef] [PubMed]
- Filippou, C.D.; Tsioufis, C.P.; Thomopoulos, C.G.; Mihas, C.C.; Dimitriadis, K.S.; Sotiropoulou, L.I.; Chrysochoou, C.A.; Nihoyannopoulos, P.I.; Tousoulis, D.M. Dietary Approaches to Stop Hypertension (DASH) Diet and Blood Pressure Reduction in Adults with and without Hypertension: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Adv. Nutr. Int. Rev. J. 2020, 11, 1150–1160. [Google Scholar] [CrossRef]
- Joyce, B.T.; Wu, D.; Hou, L.; Dai, Q.; Castaneda, S.F.; Gallo, L.C.; Talavera, G.A.; Sotres-Alvarez, D.; Van Horn, L.; Beasley, J.; et al. DASH diet and prevalent metabolic syndrome in the Hispanic Community Health Study/Study of Latinos. Prev. Med. Rep. 2019, 15, 100950. [Google Scholar] [CrossRef]
- Corsino, L.; Sotres-Alvarez, D.; Butera, N.M.; Siega-Riz, A.M.; Palacios, C.; Pérez, C.M.; Albrecht, S.S.; Giacinto, R.A.E.; Perera, M.J.; Van Horn, L.; et al. Association of the DASH dietary pattern with insulin resistance and diabetes in US Hispanic/Latino adults: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). BMJ Open Diabetes Res. Care 2017, 5, e000402. [Google Scholar] [CrossRef] [Green Version]
- Conlin, P.R.; Chow, D.; Miller, E.R.; Svetkey, L.P.; Lin, P.-H.; Harsha, D.W.; Moore, T.J.; Sacks, F.M.; Appel, L.J. The effect of dietary patterns on blood pressure control in hypertensive patients: Results from the dietary approaches to stop hypertension (DASH) trial. Am. J. Hypertens. 2000, 13, 949–955. [Google Scholar] [CrossRef] [Green Version]
- Monfort-Pires, M.; Folchetti, L.D.; Previdelli, A.N.; Siqueira-Catania, A.; De Barros, C.R.; Ferreira, S.R.G. Healthy Eating Index is associated with certain markers of inflammation and insulin resistance but not with lipid profile in individuals at cardiometabolic risk. Appl. Physiol. Nutr. Metab. 2014, 39, 497–502. [Google Scholar] [CrossRef]
- Sotos-Prieto, M.; Bhupathiraju, S.; Falcon, L.; Gao, X.; Tucker, K.; Mattei, J. Association between a Healthy Lifestyle Score and inflammatory markers among Puerto Rican adults. Nutr. Metab. Cardiovasc. Dis. 2015, 26, 178–184. [Google Scholar] [CrossRef]
- Krijger, J.A.; Nicolaou, M.; Nguyen, A.N.; Voortman, T.; Hutten, B.A.; Vrijkotte, T.G. Diet quality at age 5–6 and cardiovascular outcomes in preadolescents. Clin. Nutr. ESPEN 2021, 43, 506–513. [Google Scholar] [CrossRef] [PubMed]
- Hooshmand, F.; Asghari, G.; Yuzbashian, E.; Mahdavi, M.; Mirmiran, P.; Azizi, F. Modified Healthy Eating Index and Incidence of Metabolic Syndrome in Children and Adolescents: Tehran Lipid and Glucose Study. J. Pediatr. 2018, 197, 134–139.e2. [Google Scholar] [CrossRef] [PubMed]
- Sal, S.; Bektas, M. Effectiveness of Obesity Prevention Program Developed for Secondary School Students. Am. J. Health Educ. 2022, 53, 45–55. [Google Scholar] [CrossRef]
- Bricarello, L.P.; Souza, A.D.M.; Alves, M.D.A.; Retondario, A.; Fernandes, R.; Trindade, E.B.S.D.M.; Zeni, L.A.Z.R.; Vasconcelos, F.D.A.G.D. Association between DASH diet (Dietary Approaches to Stop Hypertension) and hypertension in adolescents: A cross-sectional school-based study. Clin. Nutr. ESPEN 2020, 36, 69–75. [Google Scholar] [CrossRef] [PubMed]
- Öztürk, Y.E.; Bozbulut, R.; Döğer, E.; Bideci, A.; Köksal, E. The relationship between diet quality and insulin resistance in obese children: Adaptation of the Healthy Lifestyle-Diet Index in Turkey. J. Pediatr. Endocrinol. Metab. 2018, 31, 391–398. [Google Scholar] [CrossRef]
- Rahimi, H.; Yuzbashian, E.; Zareie, R.; Asghari, G.; Djazayery, A.; Movahedi, A.; Mirmiran, P. Dietary approaches to stop hypertension (DASH) score and obesity phenotypes in children and adolescents. Nutr. J. 2020, 19, 112. [Google Scholar] [CrossRef] [PubMed]
- Martínez-González, M.A.; García-Arellano, A.; Toledo, E.; Salas-Salvadó, J.; Buil-Cosiales, P.; Corella, D.; Covas, M.I.; Schröder, H.; Arós, F.; Gómez-Gracia, E.; et al. A 14-Item Mediterranean Diet Assessment Tool and Obesity Indexes among High-Risk Subjects: The PREDIMED Trial. PLoS ONE 2012, 7, e43134. [Google Scholar]
- Trichopoulou, A.; Kouris-Blazos, A.; Wahlqvist, M.L.; Gnardellis, C.; Lagiou, P.; Polychronopoulos, E.; Vassilakou, T.; Lipworth, L.; Trichopoulos, D. Diet and overall survival in elderly people. BMJ 1995, 311, 1457–1460. [Google Scholar] [CrossRef] [Green Version]
- Trichopoulou, A.; Orfanos, P.; Norat, T.; Bueno-De-Mesquita, B.; Ocké, M.C.; Peeters, P.H.; Van Der Schouw, Y.T.; Boeing, H.; Hoffmann, K.; Boffetta, P.; et al. Modified Mediterranean diet and survival: EPIC-elderly prospective cohort study. BMJ 2005, 330, 991. [Google Scholar] [CrossRef] [Green Version]
- De Batlle, J.; Garcia-Aymerich, J.; Barraza-Villarreal, A.; Antó, J.M.; Romieu, I. Mediterranean diet is associated with reduced asthma and rhinitis in Mexican children. Allergy 2008, 63, 1310–1316. [Google Scholar] [CrossRef]
- Aparicio-Ugarriza, R.; Cuenca-García, M.; Gonzalez-Gross, M.; Julián, C.; Bel-Serrat, S.; Moreno, L.A.; Breidenassel, C.; Kersting, M.; Arouca, A.B.; Michels, N.; et al. Relative validation of the adapted Mediterranean Diet Score for Adolescents by comparison with nutritional biomarkers and nutrient and food intakes: The Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study. Public Health Nutr. 2019, 22, 2381–2397. [Google Scholar] [CrossRef] [PubMed]
- Levitan, E.B.; Lewis, C.E.; Tinker, L.F.; Eaton, C.B.; Ahmed, A.; Manson, J.E.; Snetselaar, L.G.; Martin, L.W.; Trevisan, M.; Howard, B.V.; et al. Mediterranean and DASH Diet Scores and Mortality in Women With Heart Failure: The Women’s Health Initiative. Circ. Hear. Fail. 2013, 6, 1116–1123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fung, T.T.; Chiuve, S.E.; McCullough, M.L.; Rexrode, K.M.; Logroscino, G.; Hu, F.B. Adherence to a DASH-Style Diet and Risk of Coronary Heart Disease and Stroke in Women. Arch. Intern. Med. 2008, 168, 713–720. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Krebs-Smith, S.M.; Pannucci, T.E.; Subar, A.F.; Kirkpatrick, S.I.; Lerman, J.L.; Tooze, J.A.; Wilson, M.M.; Reedy, J. Update of the Healthy Eating Index: HEI-2015. J. Acad. Nutr. Diet. 2018, 118, 1591–1602. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kennedy, E.T.; Ohls, J.; Carlson, S.; Fleming, K.; Kennedy, E.T.; Ohls, J.; Carlson, S.; Fleming, K.; Kennedy, E.T.; Ohls, J.; et al. The Healthy Eating Index: Design and Applications. J. Am. Diet. Assoc. 1995, 95, 1103–1108. [Google Scholar] [CrossRef]
- Askari, M.; Daneshzad, E.; Naghshi, S.; Bellissimo, N.; Suitor, K.; Azadbakht, L. Healthy eating index and anthropometric status in young children: A cross-sectional study. Clin. Nutr. ESPEN 2021, 45, 306–311. [Google Scholar] [CrossRef]
- Rodríguez, L.A.; Mundo-Rosas, V.; Méndez-Gómez-Humarán, I.; Pérez-Escamilla, R.; Shamah-Levy, T. Dietary quality and household food insecurity among Mexican children and adolescents. Matern. Child Nutr. 2016, 13, e12372. [Google Scholar] [CrossRef]
- Pérez-Gimeno, G.; Rupérez, A.I.; Vázquez-Cobela, R.; Herráiz-Gastesi, G.; Gil-Campos, M.; Aguilera, C.M.; Moreno, L.A.; Trabazo, M.R.L.; Bueno-Lozano, G. Energy Dense Salty Food Consumption Frequency Is Associated with Diastolic Hypertension in Spanish Children. Nutrients 2020, 12, 1027. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Glenn, A.J.; Hernández-Alonso, P.; Kendall, C.W.; Martínez-González, M.; Corella, D.; Fitó, M.; Martínez, J.; Alonso-Gómez, M.; Wärnberg, J.; Vioque, J.; et al. Longitudinal changes in adherence to the portfolio and DASH dietary patterns and cardiometabolic risk factors in the PREDIMED-Plus study. Clin. Nutr. 2021, 40, 2825–2836. [Google Scholar] [CrossRef]
- Royo-Bordonada, M.A.; Garcés, C.; Gorgojo, L.; Martín-Moreno, J.M.; Lasunción, M.A.; Rodríguez-Artalejo, F.; Fernández, O.; De Oya, M. Saturated fat in the diet of Spanish children: Relationship with anthropometric, alimentary, nutritional and lipid profiles. Public Health Nutr. 2006, 9, 429–435. [Google Scholar] [CrossRef] [Green Version]
- Van der Aa, M.P.; Fazeli Farsani, S.; Knibbe, C.A.J.; de Boer, A.; van der Vorst, M.M.J. Population-Based Studies on the Epidemiology of Insulin Resistance in Children. J. Diabetes Res. 2015, 2015, 362375. [Google Scholar] [CrossRef]
- Moran, A.; Jacobs, D.R., Jr.; Steinberger, J.; Steffen, L.M.; Pankow, J.S.; Hong, C.P.; Sinaiko, A.R. Changes in insulin resistance and cardiovascular risk during adolescence: Establishment of differential risk in males and females. Circulation 2008, 117, 2361–2368. [Google Scholar] [CrossRef] [Green Version]
- Chiarelli, F.; Marcovecchio, M.L. Insulin resistance and obesity in childhood. Eur. J. Endocrinol. 2008, 159 (Suppl. S1), S67–S74. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rodríguez-Rodríguez, E.; Salas-González, M.D.; Ortega, R.M.; López-Sobaler, A.M. Leukocytes and Neutrophil–Lymphocyte Ratio as Indicators of Insulin Resistance in Overweight/Obese School-Children. Front. Nutr. 2022, 8, 1318. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization. Physical Status: The Use and Interpretation of Anthropometry. Report of the WHO Expert Committee; World Health Organization: Geneva, Switzerland, 1995; p. 543. [Google Scholar]
- WHO. WHO/Europe|Nutrition—Body Mass Index—BMI. World Health Organization. 2021. Available online: https://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmi (accessed on 5 September 2022).
- Onis, M.; Onyango, A.; Borghi, E.; Siyam, A.; Nishida, C.; Siekmann, J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007, 85, 660–667. [Google Scholar] [CrossRef] [PubMed]
- Stewart, A.; Marfell-Jones, M.; Olds, T.; de Ridder, H. International Protocol for Anthropometric Assessment; Hutt, L., Ed.; International Society for the Advancement of Kinanthropometry: Glasgow, UK, 2011. [Google Scholar]
- Dezenberg, C.; Nagy, T.; Gower, B.; Johnson, R.; Goran, M. Predicting body composition from anthropometry in pre-adolescent children. Int. J. Obes. 1999, 23, 253–259. [Google Scholar] [CrossRef] [Green Version]
- McCarthy, H.D.; Cole, T.J.; Fry, T.; Jebb, S.A.; Prentice, A.M. Body fat reference curves for children. Int. J. Obes. 2006, 30, 598–602. [Google Scholar] [CrossRef] [Green Version]
- Ortega, R.M.; Requejo, A.M.; López-Sobaler, A.M. Activity questionnaire. In Nutriguía. Manual of Clinical Nutrition in Primary Care; Requejo, R.M., Ortega, R., Eds.; Complutense Madrid: Madrid, Spain, 2006; p. 468. [Google Scholar]
- Peral-Suárez, Á.; Cuadrado-Soto, E.; Perea, J.M.; Navia, B.; López-Sobaler, A.M.; Ortega, R.M. Physical activity practice and sports preferences in a group of Spanish schoolchildren depending on sex and parental care: A gender perspective. BMC Pediatr. 2020, 20, 337. [Google Scholar] [CrossRef] [PubMed]
- Rodríguez-Rodríguez, E.; Ortega, R.M.; Carvajales, P.A.; González-Rodríguez, L.G. Relationship between 24 h urinary potassium and diet quality in the adult Spanish population. Public Health Nutr. 2014, 18, 850–859. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ortega, R.M.; Rodríguez-Rodríguez, E.; Aparicio, A.; Jiménez, A.I.; López-Sobaler, A.M.; González-Rodríguez, L.G.; Andrés, P. Poor zinc status is associated with increased risk of insulin resistance in Spanish children. Br. J. Nutr. 2011, 107, 398–404. [Google Scholar] [CrossRef] [Green Version]
- Ortega, R.M.; Requejo, A.M.; Quintas, E.; Sánchez-Quiles, B.; López-Sobaler, A.M.; Andrés, P. Estimated energy balance in female university students: Differences with respect to body mass index and concern about body weight. Int. J. Obes. 1996, 20, 1127–1129. [Google Scholar]
- WHO. Energy and Protein Requirements: Report of a Joint FAO/WHO/UNU Expert Consultation. 1985. Available online: https://apps.who.int/iris/handle/10665/40157 (accessed on 5 September 2022).
- Institute of Medicine. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids; National Academies Press: Washington, DC, USA, 2005; p. 10490. [Google Scholar] [CrossRef]
- Ortega, R.M.; Requejo, A.M.; López-Sobaler, A.M. Questionnaires for dietetic studies and the assessment of nutritional status. In Nutriguía. Manual of Clinical Nutrition in Primary Care; Requejo, R.M., Ortega, R., Eds.; Complutense Madrid: Madrid, Spain, 2006; pp. 456–459. [Google Scholar]
- Ortega, R.M.; López-Sobaler, A.M.; Andrés, P.; Requejo, A.M.; Aparicio, A.M.L. DIAL Software for Assessing Diets and Food Calculations, for Windows, version 3.0.0.5; Department of Nutrition (UCM) & Alceingeniería, S.A.: Madrid, Spain, 2013. [Google Scholar]
- Ortega, R.; López-Sobaler, A.; Andrés, P.; Aparicio, A. Food nutritional composition. In A Tool for the Design and Evaluation of Food and Diets; Departament of Nutrition and Food Science: Singapore; Comlutense University of Madrid: Madrid, Spain, 2021. [Google Scholar]
- Ortega, R.M.; Perez-Rodrigo, C.; Lopez-Sobaler, A.M. Dietary assessment methods: Dietary records. Nutr. Hosp. 2015, 31, 38–45. [Google Scholar] [CrossRef]
- Neese, J.W.; Duncan, P.B.D. Development and Evaluation of a Hexokinase/Glucose-6-Phosphate Dehydrogenase Procedure for Use as a National Glucose Reference Method; U.S. Public Health Service, Center for Disease Control, Bureau of Laboratories, Clinical Chemistry Division: Atlanta, GA, USA, 1976. [Google Scholar]
- El Kenz, H.; Bergmann, P. Evaluation of immunochemiluminometric assays for the measurement of insulin and C-peptide using the ADVIA Centaur. Clin. Lab. 2004, 50, 171–174. [Google Scholar] [PubMed]
- Hřebícek, J.; Janout, V.; Malincíková, J.; Horáková, D.; Cízek, L. Detection of Insulin Resistance by Simple Quantitative Insulin Sensitivity Check Index QUICKI for Epidemiological Assessment and Prevention. J. Clin. Endocrinol. Metab. 2002, 87, 144. [Google Scholar] [CrossRef] [PubMed]
- Tripathy, D.; Carlsson, M.; Almgren, P.; Isomaa, B.; Taskinen, M.R.; Tuomi, T.; Groop, L.C. Insulin secretion and insulin sensitivity in relation to glucose tolerance: Lessons from the Botnia Study. Diabetes 2000, 49, 975–980. [Google Scholar] [CrossRef] [Green Version]
- Albareda, M.; Rodríguez-Espinosa, J.; Murugo, M.; de Leiva, A.; Corcoy, R. Assessment of insulin sensitivity and beta-cell function from measurements in the fasting state and during an oral glucose tolerance test. Diabetologia 2000, 43, 1507–1511. [Google Scholar] [CrossRef] [Green Version]
- Keskin, M.; Kurtoglu, S.; Kendirci, M.; Atabek, M.E.; Yazici, C. Homeostasis Model Assessment Is More Reliable Than the Fasting Glucose/Insulin Ratio and Quantitative Insulin Sensitivity Check Index for Assessing Insulin Resistance Among Obese Children and Adolescents. Pediatrics 2005, 115, e500–e503. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Manios, Y.; Moschonis, G.; Kourlaba, G.; Bouloubasi, Z.; Grammatikaki, E.; Spyridaki, A.; Hatzis, C.; Kafatos, A.; Fragiadakis, G.A. Prevalence and independent predictors of insulin resistance in children from Crete, Greece: The Children Study. Diabet. Med. 2007, 25, 65–72. [Google Scholar] [CrossRef]
- Kostovski, M.; Simeonovski, V.; Mironska, K.; Tasic, V.; Gucev, Z. Metabolic Profiles in Obese Children and Adolescents with Insulin Resistance. Open Access Maced. J. Med Sci. 2018, 6, 511–518. [Google Scholar] [CrossRef] [Green Version]
- Mat, S.H.C.; Yaacob, N.M.; Hussain, S. Rate of Weight Gain and its Association with Homeostatic Model Assessment-Insulin Resistance (HOMA-IR) among Obese Children attending Paediatric Endocrine Clinic, Hospital Universiti Sains Malaysia. J. ASEAN Fed. Endocr. Soc. 2021, 36, 149–155. [Google Scholar] [CrossRef] [PubMed]
- Wei, J.; Luo, X.; Zhou, S.; He, X.; Zheng, J.; Sun, X.; Cui, W. Associations between iron status and insulin resistance in Chinese children and adolescents: Findings from the China Health and Nutrition Survey. Asia Pac. J. Clin. Nutr. 2019, 28, 819–825. [Google Scholar] [CrossRef] [PubMed]
- Mastrangelo, A.; Martos-Moreno, G.; García, A.; Barrios, V.; Rupérez, F.J.; Chowen, J.A.; Barbas, C.; Argente, J. Insulin resistance in prepubertal obese children correlates with sex-dependent early onset metabolomic alterations. Int. J. Obes. 2016, 40, 1494–1502. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jeffery, S.C.; Hosking, J.; Jeffery, A.N.; Murphy, M.J.; Voss, L.D.; Wilkin, T.J.; Pinkney, J. Insulin resistance is higher in prepubertal girls but switches to become higher in boys at age 16: A Cohort Study (EarlyBird 57). Pediatr. Diabetes 2017, 19, 223–230. [Google Scholar] [CrossRef] [PubMed]
- Tovar, A.; Risica, P.M.; Ramirez, A.; Mena, N.; Lofgren, I.E.; Stowers, K.C.; Gans, K.M. Exploring the Provider-Level Socio-Demographic Determinants of Diet Quality of Preschool-Aged Children Attending Family Childcare Homes. Nutrients 2020, 12, 1368. [Google Scholar] [CrossRef] [PubMed]
- Thomson, J.L.; Landry, A.; Tussing-Humphreys, L.M.; Goodman, M.H. Diet quality of children in the United States by body mass index and sociodemographic characteristics. Obes. Sci. Pract. 2019, 6, 84–98. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Landry, M.J.; Asigbee, F.M.; Vandyousefi, S.; Khazaee, E.; Ghaddar, R.; Boisseau, J.B.; House, B.T.; Davis, J.N. Diet Quality Is an Indicator of Disease Risk Factors in Hispanic College Freshmen. J. Acad. Nutr. Diet. 2019, 119, 760–768. [Google Scholar] [CrossRef] [PubMed]
- Frazier-Wood, A.C.; Kim, J.; Davis, J.S.; Jung, S.Y.; Chang, S. In cross-sectional observations, dietary quality is not associated with CVD risk in women; in men the positive association is accounted for by BMI. Br. J. Nutr. 2015, 113, 1244–1253. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mattei, J.; Sotos-Prieto, M.; Bigornia, S.J.; Noel, S.E.; Tucker, K.L. The Mediterranean Diet Score Is More Strongly Associated with Favorable Cardiometabolic Risk Factors over 2 Years Than Other Diet Quality Indexes in Puerto Rican Adults. J. Nutr. 2017, 147, 661–669. [Google Scholar] [CrossRef] [Green Version]
- Dong, Y.; Chen, L.; Gutin, B.; Zhu, H. Total, insoluble, and soluble dietary fiber intake and insulin resistance and blood pressure in adolescents. Eur. J. Clin. Nutr. 2018, 73, 1172–1178. [Google Scholar] [CrossRef] [PubMed]
- DiNicolantonio, J.J.; O’Keefe, J.H. Good Fats versus Bad Fats: A Comparison of Fatty Acids in the Promotion of Insulin Resistance, Inflammation, and Obesity. Mo. Med. 2017, 114, 303–307. [Google Scholar]
- Malik, V.S.; Popkin, B.M.; Bray, G.A.; Després, J.-P.; Willett, W.C.; Hu, F.B. Sugar-Sweetened Beverages and Risk of Metabolic Syndrome and Type 2 Diabetes: A meta-analysis. Diabetes Care 2010, 33, 2477–2483. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Guillermo, C.; Boushey, C.J.; Franke, A.A.; Monroe, K.R.; Lim, U.; Wilkens, L.R.; Le Marchand, L.; Maskarinec, G. Diet Quality and Biomarker Profiles Related to Chronic Disease Prevention: The Multiethnic Cohort Study. J. Am. Coll. Nutr. 2019, 39, 216–223. [Google Scholar] [CrossRef] [PubMed]
- Jacobs, S.; Boushey, C.J.; Franke, A.A.; Shvetsov, Y.B.; Monroe, K.R.; Haiman, C.A.; Kolonel, L.N.; Le Marchand, L.; Maskarinec, G. A priori-defined diet quality indices, biomarkers and risk for type 2 diabetes in five ethnic groups: The Multiethnic Cohort. Br. J. Nutr. 2017, 118, 312–320. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Asemi, Z.; Esmaillzadeh, A. DASH Diet, Insulin Resistance, and Serum hs-CRP in Polycystic Ovary Syndrome: A Randomized Controlled Clinical Trial. Horm. Metab. Res. 2014, 47, 232–238. [Google Scholar] [CrossRef]
- Shirani, F.; Salehi-Abargouei, A.; Azadbakht, L. Effects of Dietary Approaches to Stop Hypertension (DASH) diet on some risk for developing type 2 diabetes: A systematic review and meta-analysis on controlled clinical trials. Nutrition 2013, 29, 939–947. [Google Scholar] [CrossRef]
- Chiavaroli, L.; Viguiliouk, E.; Nishi, S.K.; Mejia, S.B.; Rahelić, D.; Kahleova, H.; Salas-Salvadó, J.; Kendall, C.W.C.; Sievenpiper, J.L. DASH Dietary Pattern and Cardiometabolic Outcomes: An Umbrella Review of Systematic Reviews and Meta-Analyses. Nutrients 2019, 11, 338. [Google Scholar] [CrossRef] [Green Version]
- Banfield, E.C.; Liu, Y.; Davis, J.S.; Chang, S.; Frazier-Wood, A.C. Poor Adherence to US Dietary Guidelines for Children and Adolescents in the National Health and Nutrition Examination Survey Population. J. Acad. Nutr. Diet. 2015, 116, 21–27. [Google Scholar] [CrossRef]
Total (n = 854) | Girls (n = 441) | Boys (n = 413) | p-Value | |
---|---|---|---|---|
Age (years) | 10.1 ± 0.9 | 10.2 ± 0.9 | 10.1 ± 1.0 | 0.262 |
8–10 years [%(n)] | 63.35 (541) | 61.7 (272) | 65.1 (269) | 0.295 |
11–13 years [%(n)] | 36.65 (313) | 38.3 (169) | 34.9 (144) | |
Madrid [%(n)] | 55.6 (475) | 59.0 (260) | 52.1 (215) | 0.237 |
Barcelona [%(n)] | 7.9 (67) | 7.3 (32) | 8.5 (35) | |
Sevilla [%(n)] | 12.4 (106) | 11.6 (51) | 13.3 (55) | |
A Coruña [%(n)] | 13.4 (114) | 11.3 (50) | 15.5 (64) | |
Valencia [%(n)] | 10.8 (92) | 10.9 (48) | 10.7 (44) | |
Body composition | ||||
Weight (kg) | 39.4 ± 9.3 | 39.6 ± 9.2 | 39.2 ± 9.5 | 0.432 |
Height (m) # | 1.43 ± 0.09 | 1.44 ± 0.09 | 1.43 ± 0.08 | 0.008 |
BMI (kg/m2) | 19.0 ± 3.1 | 18.9 ± 3.0 | 19.1 ± 3.3 | 0.774 |
Z-BMI # | 0.69 ± 1.13 | 0.57 ± 1.04 | 0.81 ± 1.21 | 0.001 |
Nutritional status by BMI | ||||
Underweight [%(n)] | 0.82 (7) | 0.68 (3) | 0.97 (4) | <0.001 |
Normal weight [%(n)] | 59.4 (507) | 63.3 (279) | 55.21 (228) | |
Overweight [%(n)] | 27.4 (234) | 29.0 (128) | 25.7 (106) | |
Obesity [%(n)] | 12.4 (106) | 7.0 (31) | 18.2 (75) | |
Body fat (%) # | 27.6 ± 5.7 | 29.3 ± 4.7 | 25.8 ± 6.1 | <0.001 |
Nutritional status by body fat percentage | ||||
Low fat [%(n)] | 0.35 (3) | 0.23 (1) | 0.49 (2) | <0.001 |
Normal fat [%(n)] | 36.6 (312) | 40.4 (178) | 32.6 (134) | |
Excessive body fat [%(n)] | 31.6 (269) | 33.1 (146) | 29.9 (123) | |
Obesity [%(n)] | 31.5 (268) | 26.3 (116) | 37.0 (152) | |
Physical activity | ||||
Activity coefficient | 1.52 ± 0.11 | 1.53 ± 0.11 | 1.53 ± 0.11 | 0.006 |
Biochemical data | ||||
Glucose (mg/dL) | 84.4 ± 9.7 | 83.4 ± 10.0 | 85.5 ± 9.2 | 0.134 |
Insulin (mcU/mL) | 6.3 ± 4.4 | 7.1 ± 4.8 | 5.5 ± 3.7 | <0.001 |
QUICKI | 0.38 ± 0.05 | 0.38 ± 0.05 | 0.39 ± 0.04 | <0.001 |
HOMA-IR | 1.33 ± 0.97 | 1.48 ± 1.08 | 1.17 ± 0.80 | <0.001 |
IR [%(n)] | 5.27 (45) | 7.03 (31) | 3.39 (14) | <0.001 |
Total (n = 854) | Girls (n = 441) | Boys (n = 413) | p-Value | |
---|---|---|---|---|
Energy intake (EI) (kcal) # | 2105 ± 350 | 2066 ± 338 | 2145 ± 358 | <0.001 |
Energy expenditure (EE) (kcal) | 2125 ± 377 | 1899 ± 265 | 2365 ± 325 | <0.001 |
EI/EE (%) # | 101.7 ± 22.9 | 110.7 ± 22.8 | 92.2 ± 18.7 | <0.001 |
Proteins (% EI) | 15.6 ± 2.3 | 15.6 ± 2.3 | 15.5 ± 2.4 | 0.356 |
Carbohydrates (% EI) | 41.0 ± 5.1 | 40.9 ± 5.0 | 41.1 ± 5.2 | 0.399 |
Lipids (% EI) # | 41.8 ± 4.8 | 41.9 ± 4.7 | 41.8 ± 4.9 | 0.454 |
HEI-2015 (total score) # | 59.2 ± 8.5 | 60.3 ± 8.5 | 57.9 ± 8.4 | <0.001 |
Total Fruits (score) | 3.7 ± 1.5 | 3.8 ± 1.4 | 3.6 ± 1.5 | 0.013 |
Whole Fruits (score) | 3.9 ± 1.5 | 4.0 ± 1.5 | 3.8 ± 1.6 | 0.016 |
Total Vegetables (score) | 3.1 ± 1.4 | 3.2 ± 1.4 | 2.9 ± 1.3 | <0.001 |
Greens and Beans (score) | 3.8 ± 1.7 | 3.94 ± 1.6 | 3.7 ± 1.8 | 0.087 |
Whole Grains (score) | 1.1 ± 1.8 | 1.1 ± 1.7 | 1.2 ± 1.8 | 0.307 |
Dairy (score) | 7.0 ± 2.1 | 6.9 ± 2.1 | 7.1 ± 2.0 | 0.224 |
Total Protein Foods (score) | 4.9 ± 0.4 | 4.9 ± 0.3 | 4.9 ± 0.4 | 0.469 |
Seafood and Plant Proteins (score) | 1.9 ± 1.4 | 2.0 ± 1.4 | 1.8 ± 1.3 | 0.170 |
(PUFAs + MUFAs)/SFAs (score) | 3.2 ± 2.2 | 3.4 ± 2.3 | 2.9 ± 2.0 | 0.001 |
Refined Grains (score) | 6.9 ± 2.4 | 7.0 ± 2.4 | 6.8 ± 2.4 | 0.206 |
Sodium (score) | 8.6 ± 2.0 | 8.8 ± 1.8 | 8.4 ± 2.1 | 0.018 |
Added Sugars (score) | 8.70 ± 1.57 | 8.76 ± 1.55 | 8.63 ± 1.58 | 0.145 |
Saturated Fats (score) | 2.4 ± 2.1 | 2.5 ± 2.2 | 2.2 ± 2.1 | 0.026 |
DASH (total score) | 23.4 ± 3.7 | 23.9 ± 3.7 | 22.8 ± 3.7 | <0.001 |
Red meat (score) | 3.0 ± 1.4 | 3.12 ± 1.4 | 2.8 ± 1.4 | <0.001 |
Sugar drinks (score) | 1.79 ± 0.41 | 1.83 ± 0.38 | 1.75 ± 0.43 | 0.006 |
Sodium (score) | 2.8 ± 1.5 | 3.0 ± 1.4 | 2.6 ± 1.5 | <0.001 |
Whole Grains (score) | 3.6 ± 0.8 | 3.6 ± 0.8 | 3.6 ± 0.8 | 0.502 |
Low-fat dairy (score) | 3.2 ± 1.2 | 3.2 ± 1.2 | 3.2 ± 1.2 | 0.885 |
Vegetables (score) | 3.0 ± 1.4 | 3.1 ± 1.5 | 2.9 ± 1.4 | 0.139 |
Seeds, nuts and legumes (score) | 3.0 ± 1.4 | 3.0 ± 1.4 | 2.9 ± 1.5 | 0.174 |
Fruits (score) | 3.0 ± 1.4 | 3.1 ± 1.4 | 3.0 ± 1.4 | 0.252 |
aDASH (total score) | 23.3 ± 3.9 | 23.9 ± 3.8 | 22.7 ± 4.0 | <0.001 |
Red meat (score) | 3.0 ± 1.4 | 3.1 ± 1.4 | 2.8 ± 1.4 | 0.001 |
Sugar drinks (score) | 1.80 ± 0.40 | 1.83 ± 0.38 | 1.77 ± 0.42 | 0.018 |
Sodium (score) | 2.9 ± 1.5 | 3.0 ± 1.5 | 2.7 ± 1.5 | 0.028 |
Whole Grains (score) | 3.6 ± 0.8 | 3.6 ± 0.8 | 3.6 ± 0.8 | 0.472 |
Low-fat dairy (score) | 3.2 ± 1.2 | 3.2 ± 1.2 | 3.2 ± 1.2 | 0.873 |
Vegetables (score) | 3.0 ± 1.4 | 3.1 ± 1.4 | 2.8 ± 1.4 | 0.001 |
Seeds, nuts and legumes (score) | 3.0 ± 1.4 | 3.0 ± 1.4 | 2.9 ± 1.5 | 0.139 |
Fruits (score) | 3.0 ± 1.4 | 3.1 ± 1.4 | 2.9 ± 1.4 | 0.060 |
Total | Girls | Boys | |||||||
---|---|---|---|---|---|---|---|---|---|
HOMA-IR ≤ 3.16 (n = 809) | HOMA-IR > 3.16 (n = 45) | p | HOMA-IR ≤ 3.16 (n = 410) | HOMA-IR > 3.16 (n = 31) | p | HOMA-IR ≤ 3.16 (n = 399) | HOMA-IR > 3.16 (n = 14) | p | |
Energy intake (kcal) # | 2110 ± 350 | 2002 ± 330 | 0.022 | 2071 ± 336 | 1998 ± 361 | 0.123 | 2150 ± 360 | 2010 ± 261 | 0.076 |
Energy expenditure (kcal) | 2121 ± 372 | 2194 ± 445 | 0.429 | 1892 ± 266 | 1998 ± 237 # | 0.016 | 2356 ± 315 | 2629 ± 495 | 0.029 |
EI/EE (%) | 102.1 ± 22.8 | 94.2 ± 22.7 | 0.150 | 111.4 ± 22.7 | 101.4 ± 22.0 | 0.013 | 92.6 ± 18.6 | 78.4 ± 15.2 # | 0.002 |
Proteins (%) | 15.6 ± 2.3 | 15.8 ± 2.4 | 0.467 | 15.6 ± 2.3 | 15.6 ± 2.1 | 0.983 | 15.5 ± 2.3 | 16.1 ± 2.8 | 0.286 |
Carbohydrates (%) | 41.0 ± 5.1 | 40.3 ± 5.0 | 0.263 | 40.9 ± 5.0 | 40.6 ± 4.4 # | 0.365 | 41.2 ± 5.2 | 39.9 ± 6.3 | 0.237 |
Lipids (%) # | 41.8 ± 4.8 | 42.1 ± 5.1 | 0.336 | 41.8 ± 4.7 | 42.1 ± 4.4 | 0.402 | 41.8 ± 4.8 | 42.3 ± 6.6 | 0.357 |
HEI-2015 (total score) | 59.2 ± 8.5 | 57.5 ± 8.6 | 0.094 | 60.5 ± 8.4 | 57.8 ± 9.4 # | 0.044 | 57.9 ± 8.5 | 56.8 ± 6.7 # | 0.319 |
Total Fruits (score) | 3.7 ± 1.4 | 3.6 ± 1.6 | 0.930 | 3.8 ± 1.4 | 3.8 ± 1.6 | 0.748 | 3.6 ± 1.5 | 3.2 ± 1.5 | 0.402 |
Whole Fruits (score) | 3.9 ± 1.5 | 3.8 ± 1.7 | 0.855 | 4.0 ± 1.5 | 4.0 ± 1.6 | 0.783 | 3.8 ± 1.6 | 3.6 ± 1.7 | 0.703 |
Total Vegetables (score) | 3.1 ± 1.3 | 2.9 ± 1.5 | 0.317 | 3.3 ± 1.3 | 2.7 ± 1.5 | 0.043 | 2.9 ± 1.3 | 3.2 ± 1.4 | 0.409 |
Greens and Beans (score) | 3.8 ± 1.7 | 3.6 ± 1.8 | 0.171 | 4.0 ± 1.6 | 3.3 ± 2.0 | 0.039 | 3.7 ± 1.8 | 4.1 ± 1.3 | 0.716 |
Whole Grains (score) | 1.1 ± 1.8 | 0.6 ± 0.8 | 0.262 | 1.1 ± 1.8 | 0.5 ± 0.7 | 0.122 | 1.2 ± 1.8 | 0.8 ± 1.0 | 0.680 |
Dairy (score) | 7.0 ± 2.1 | 7.2 ± 1.9 | 0.609 | 6.9 ± 2.1 | 7.3 ± 2.0 | 0.354 | 7.1 ± 2.0 | 7.0 ± 1.8 | 0.790 |
Total Protein Foods (score) | 4.9 ± 0.4 | 4.9 ± 0.3 | 0.822 | 4.9 ± 0.3 | 4.9 ± 0.2 | 0.866 | 4.9 ± 0.4 | 4.8 ± 0.5 | 0.954 |
Seafood and Plant Proteins (score) | 1.9 ± 1.4 | 2.1 ± 1.5 | 0.559 | 2.0 ± 1.4 | 2.1 ± 1.4 | 0.767 | 1.8 ± 1.3 | 2.1 ± 1.7 | 0.685 |
(PUFAs + MUFAs)/SFAs (score) | 3.2 ± 2.2 | 2.8 ± 2.3 | 0.247 | 3.5 ± 2.3 | 2.9 ± 2.4 # | 0.088 | 2.9 ± 2.0 | 2.7 ± 2.3 | 0.722 |
Refined Grains (score) | 6.9 ± 2.4 | 6.7 ± 2.4 | 0.633 | 7.0 ± 2.4 | 6.5 ± 2.5 # | 0.111 | 6.8 ± 2.4 | 7.3 ± 2.3 | 0.367 |
Sodium (score)—S | 8.6 ± 2.0 | 8.4 ± 2.2 | 0.716 | 8.8 ± 1.8 | 8.9 ± 1.9 | 0.488 | 8.4 ± 2.1 | 7.3 ± 2.4 | 0.052 |
Added Sugars (score) | 8.7 ± 1.6 | 8.8 ± 1.6 | 0.595 | 8.7 ± 1.6 | 8.9 ± 1.4 | 0.735 | 8.6 ± 1.6 | 8.5 ± 1.9 | 0.802 |
Saturated Fats (score) | 2.4 ± 2.2 | 2.1 ± 1.8 | 0.635 | 2.6 ± 2.2 | 2.2 ± 2.0 # | 0.158 | 2.2 ± 2.1 | 2.1 ± 1.6 | 0.810 |
DASH (total score) | 23.3 ± 3.7 | 23.6 ± 3.6 | 0.605 | 23.9 ± 3.6 | 23.6 ± 3.8 | 0.684 | 22.7 ± 3.7 | 23.6 ± 3.3 | 0.381 |
Red meat (score) | 2.9 ± 1.4 | 3.2 ± 1.5 | 0.316 | 3.1 ± 1.4 | 3.2 ± 1.4 | 0.768 | 2.8 ± 1.4 | 3.1 ± 1.6 | 0.433 |
Sugar drinks (score)—S | 1.8 ± 0.4 | 1.7 ± 0.4 | 0.292 | 1.8 ± 0.4 | 1.8 ± 0.4 | 0.920 | 1.8 ± 0.4 | 1.5 ± 0.5 | 0.024 |
Sodium (score)—S | 2.8 ± 1.5 | 3.2 ± 1.6 | 0.098 | 3.0 ± 1.4 | 3.5 ± 1.5 | 0.073 | 2.6 ± 1.5 | 2.6 ± 1.7 | 0.886 |
Whole Grains (score) | 3.6 ± 0.8 | 3.3 ± 0.6 | 0.035 | 3.6 ± 0.8 | 3.3 ± 0.6 | 0.042 | 3.6 ± 0.8 | 3.4 ± 0.6 | 0.484 |
Low-fat dairy (score)—I | 3.2 ± 1.2 | 3.6 ± 1.1 | 0.034 | 3.2 ± 1.2 | 3.5 ± 1.2 | 0.129 | 3.2 ± 1.2 | 3.7 ± 1.1 | 0.115 |
Vegetables (score) | 3.0 ± 1.4 | 2.8 ± 1.6 | 0.424 | 3.1 ± 1.4 | 2.7 ± 1.6 | 0.142 | 2.9 ± 1.4 | 3.1 ± 1.5 | 0.538 |
Seeds, nuts and legumes (score) | 3.0 ± 1.4 | 3.1 ± 1.5 | 0.656 | 3.1 ± 1.4 | 2.8 ± 1.6 | 0.419 | 2.9 ± 1.5 | 3.6 ± 1.2 | 0.081 |
Fruits (score) | 3.0 ± 1.4 | 2.8 ± 1.3 | 0.212 | 3.1 ± 1.4 | 2.8 ± 1.4 | 0.337 | 3.0 ± 1.4 | 2.6 ± 1.3 | 0.324 |
aDASH (total score) | 23.3 ± 3.9 | 23.5 ± 3.8 | 0.996 | 23.9 ± 3.8 | 23.7 ± 3.8 | 0.480 | 22.7 ± 4.0 | 23.0 ± 3.8 | 0.760 |
Red meat (score) | 2.9 ± 1.4 | 3.1 ± 1.5 | 0.499 | 3.1 ± 1.4 | 3.2 ± 1.4 | 0.827 | 2.8 ± 1.4 | 2.9 ± 1.6 | 0.726 |
Sugar drinks (score)—S, R | 1.8 ± 0.4 | 1.8 ± 0.4 | 0.408 | 1.8 ± 0.4 | 1.9 ± 0.3 | 0.571 | 1.8 ± 0.4 | 1.5 ± 0.5 | 0.015 |
Sodium (score)—S | 2.8 ± 1.5 | 2.8 ± 1.5 | 0.969 | 2.9 ± 1.4 | 3.1 ± 1.5 | 0.477 | 2.7 ± 1.5 | 2.2 ± 1.4 | 0.176 |
Whole Grains (score) | 3.6 ± 0.8 | 3.4 ± 0.6 | 0.073 | 3.6 ± 0.8 | 3.3 ± 0.6 | 0.097 | 3.6 ± 0.8 | 3.4 ± 0.6 | 0.508 |
Low-fat dairy (score)—I | 3.2 ± 1.2 | 3.6 ± 1.1 | 0.028 | 3.2 ± 1.2 | 3.5 ± 1.2 | 0.095 | 3.2 ± 1.2 | 3.6 ± 1.1 | 0.148 |
Vegetables (score) | 3.0 ± 1.4 | 2.9 ± 1.5 | 0.663 | 3.2 ± 1.4 | 2.8 ± 1.5 | 0.162 | 2.8 ± 1.4 | 3.1 ± 1.5 | 0.387 |
Seeds, nuts and legumes (score) | 3.0 ± 1.4 | 3.1 ± 1.5 | 0.517 | 3.1 ± 1.4 | 2.9 ± 1.6 | 0.571 | 2.9 ± 1.5 | 3.6 ± 1.2 | 0.079 |
Fruits (score) | 3.0 ± 1.4 | 2.8 ± 1.4 | 0.431 | 3.1 ± 1.4 | 3.0 ± 1.4 | 0.612 | 2.9 ± 1.4 | 2.6 ± 1.3 | 0.405 |
Model 1 OR (95%CI), p | Model 2 OR (95%CI), p | |
---|---|---|
Total | ||
HEI-2015 | ||
T1 | Ref. | Ref. |
T2 | 0.74 (0.37–1.50) 0.406 | 0.67 (0.32–1.41) 0.294 |
T3 | 0.57 (0.27–1.22) 0.148 | 0.40 (0.17–0.95) 0.038 |
T2 + T3 | 0.66 (0.36–1.21) 0.180 | 0.54 (0.28–1.05) 0.071 |
DASH | ||
T1 | Ref. | Ref. |
T2 | 1.65 (0.79–3.44) 0.179 | 1.51 (0.70–3.26) 0.299 |
T3 | 1.28 (0.59–2.77) 0.531 | 1.09 (0.47–2.52) 0.838 |
T2 + T3 | 1.47 (0.76–2.84) 0.256 | 1.30 (0.65–2.62) 0.456 |
aDASH | ||
T1 | Ref. | Ref. |
T2 | 0.94 (0.44–2.02) 0.871 | 0.90 (0.41–2.00) 0.803 |
T3 | 1.14 (0.53–2.45) 0.743 | 1.02 (0.46–2.30) 0.955 |
T2 + T3 | 0.88 (0.47–1.62) 0.669 | 0.77 (0.40–1.48) 0.430 |
Girls | ||
HEI-2015 | ||
T1 | Ref. | Ref. |
T2 | 0.46 (0.19–1.11) 0.085 | 0.44 (0.17–1.13) 0.086 |
T3 | 0.48 (0.20–1.17) 0.106 | 0.42 (0.16–1.14) 0.088 |
T2 + T3 | 0.47 (0.22–0.98) <0.001 | 0.43 (0.19–0.96) 0.040 |
DASH | ||
T1 | Ref. | Ref. |
T2 | 1.29 (0.54–3.09) 0.567 | 1.42 (0.57–3.55) 0.451 |
T3 | 0.96 (0.38–2.44) 0.932 | 0.83 (0.29–2.37) 0.733 |
T2 + T3 | 1.13 (0.52–2.45) 0.768 | 1.14 (0.49–2.62) 0.766 |
aDASH | ||
T1 | Ref. | Ref. |
T2 | 0.57 (0.22–1.45) 0.236 | 0.56 (0.20–1.55) 0.263 |
T3 | 0.70 (0.30–1.62) 0.510 | 0.70 (0.28–1.75) 0.447 |
T2 + T3 | 0.64 (0.31–1.33) 0.229 | 0.63 (0.29–1.41) 0.264 |
Boys | ||
HEI-2015 | ||
T1 | 1.82 (0.52–6.35) 0.350 | 1.32 (0.35–4.98) 0.683 |
T2 | 0.81 (0.18–3.68) 0.784 | 0.32 (0.05–2.14) 0.242 |
T3 | 1.32 (0.41–4.29) 0.642 | 0.83 (0.24–2.92) 0.777 |
T2 + T3 | 1.82 (0.52–6.35) 0.350 | 1.32 (0.35–4.98) 0.683 |
DASH | ||
T1 | Ref. | Ref. |
T2 | 2.65 (0.65–10.81) 0.174 | 1.79 (0.39–8.11) 0.453 |
T3 | 2.21 (0.22–9.42) 0.285 | 2.44 (0.54–10.99) 0.246 |
T2 + T3 | 2.43 (0.67–8.84) 0.178 | 2.07 (0.54–7.97) 0.289 |
aDASH | ||
T1 | Ref. | Ref. |
T2 | 1.75 (0.46–6.67) 0.660 | 1.07 (0.24–4.76) 0.927 |
T3 | 1.51 (0.40–5.74) 0.558 | 1.47 (0.37–5.89) 0.584 |
T2 + T3 | 1.62 (0.50–5.26) 0.421 | 1.27 (0.37–4.43) 0.703 |
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Salas-González, M.D.; Aparicio, A.; Loria-Kohen, V.; Ortega, R.M.; López-Sobaler, A.M. Association of Healthy Eating Index-2015 and Dietary Approaches to Stop Hypertension Patterns with Insulin Resistance in Schoolchildren. Nutrients 2022, 14, 4232. https://doi.org/10.3390/nu14204232
Salas-González MD, Aparicio A, Loria-Kohen V, Ortega RM, López-Sobaler AM. Association of Healthy Eating Index-2015 and Dietary Approaches to Stop Hypertension Patterns with Insulin Resistance in Schoolchildren. Nutrients. 2022; 14(20):4232. https://doi.org/10.3390/nu14204232
Chicago/Turabian StyleSalas-González, María Dolores, Aranzazu Aparicio, Viviana Loria-Kohen, Rosa M. Ortega, and Ana M. López-Sobaler. 2022. "Association of Healthy Eating Index-2015 and Dietary Approaches to Stop Hypertension Patterns with Insulin Resistance in Schoolchildren" Nutrients 14, no. 20: 4232. https://doi.org/10.3390/nu14204232