A sociodemographic, anthropometric and lifestyle-based prediction score for screening children with overweight and obesity for hepatic steatosis: The HEPAKID index.
hepatic steatosis
lifestyle behaviors
paediatric obesity
primary care
screening tool
Journal
Pediatric obesity
ISSN: 2047-6310
Titre abrégé: Pediatr Obes
Pays: England
ID NLM: 101572033
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
revised:
30
10
2020
received:
14
07
2020
accepted:
17
12
2020
pubmed:
7
1
2021
medline:
23
11
2021
entrez:
6
1
2021
Statut:
ppublish
Résumé
Hepatic steatosis (HS) is currently the most prevalent hepatic disease in paediatric population and a major risk factor for type 2 diabetes and cardiovascular diseases. The proper identification of children with HS is therefore of great public health interest. To develop a new prediction score using anthropometric, sociodemographic and lifestyle factors to identify children with HS (the HEPAKID index). Previously published biochemical paediatric screening tools were validated in the same cohort. A total of 115 pre-adolescent children aged 8 to 12 years with overweight/obesity, recruited at hospital paediatric units were enrolled in this cross-sectional study. HS (≥5.5% hepatic fat) was assessed by magnetic resonance imaging (MRI). Anthropometric, sociodemographic and lifestyle variables were collected by validated tests/questionnaires. Forty-one children had MRI-diagnosed HS (35.6%, 49% girls). These children had (P < .01) a higher waist-height ratio, a lower cardiorespiratory fitness, a younger gestational age, and consumed more sugar-sweetened beverages than their HS-free peers. Children with HS were more likely to belong to an ethnic minority (P < .01) and to spend longer viewing screens than recommended (P < .05). The addition of these variables to the multivariate logistic regression model afforded a HEPAKID index with high discriminatory capacity (area under the receiver-operating characteristic curve: 0.808, 95% CI 0.715-0.901), and score of ≥25.0 was associated with high sensitivity (82%, 95% CI 68%-96%). Biochemical biomarker-based paediatric tools for identifying HS showed only moderate discriminatory capacity and low sensitivity (5%-41%) in this cohort. The HEPAKID index is the first simple, non-invasive, sensitive, inexpensive and easy-to-perform screening that can identify children with overweight or obesity who have HS.
Sections du résumé
BACKGROUND
Hepatic steatosis (HS) is currently the most prevalent hepatic disease in paediatric population and a major risk factor for type 2 diabetes and cardiovascular diseases. The proper identification of children with HS is therefore of great public health interest.
OBJECTIVE
To develop a new prediction score using anthropometric, sociodemographic and lifestyle factors to identify children with HS (the HEPAKID index). Previously published biochemical paediatric screening tools were validated in the same cohort.
METHODS
A total of 115 pre-adolescent children aged 8 to 12 years with overweight/obesity, recruited at hospital paediatric units were enrolled in this cross-sectional study. HS (≥5.5% hepatic fat) was assessed by magnetic resonance imaging (MRI). Anthropometric, sociodemographic and lifestyle variables were collected by validated tests/questionnaires.
RESULTS
Forty-one children had MRI-diagnosed HS (35.6%, 49% girls). These children had (P < .01) a higher waist-height ratio, a lower cardiorespiratory fitness, a younger gestational age, and consumed more sugar-sweetened beverages than their HS-free peers. Children with HS were more likely to belong to an ethnic minority (P < .01) and to spend longer viewing screens than recommended (P < .05). The addition of these variables to the multivariate logistic regression model afforded a HEPAKID index with high discriminatory capacity (area under the receiver-operating characteristic curve: 0.808, 95% CI 0.715-0.901), and score of ≥25.0 was associated with high sensitivity (82%, 95% CI 68%-96%). Biochemical biomarker-based paediatric tools for identifying HS showed only moderate discriminatory capacity and low sensitivity (5%-41%) in this cohort.
CONCLUSIONS
The HEPAKID index is the first simple, non-invasive, sensitive, inexpensive and easy-to-perform screening that can identify children with overweight or obesity who have HS.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e12770Informations de copyright
© 2021 World Obesity Federation.
Références
Anderson EL, Howe LD, Jones HE, Higgins JPT, Lawlor DA, Fraser A. The prevalence of non-alcoholic fatty liver disease in children and adolescents: a systematic review and meta-analysis. PLoS One. 2015;10(10):e0140908.
Lobstein T, Jackson-Leach R. Planning for the worst: estimates of obesity and comorbidities in school-age children in 2025. Pediatr Obes. 2016;11(5):321-325.
Brown GT, Kleiner DE. Histopathology of nonalcoholic fatty liver disease and nonalcoholic Steatohepatitis. Metabolism. 2016;65(8):1080-1086.
Clemente MG, Mandato C, Poeta M, Vajro P. Pediatric non-alcoholic fatty liver disease: recent solutions, unresolved issues, and future research directions. World J Gastroenterol. 2016;22(36):8078-8093.
Hazlehurst JM, Woods C, Marjot T, Cobbold JF, Tomlinson JW. Non-alcoholic fatty liver disease and diabetes. Metabolism [Internet]. 2016;65(8):1096-1108. Available from:. https://doi.org/10.1016/j.metabol.2016.01.001.
Newton KP, Hou J, Crimmins NA, et al. Prevalence of type 2 diabetes and prediabetes in children with nonalcoholic fatty liver disease Kimberly. JAMA Pediatr. 2016;170(10):e161971.
Holterman AXL, Guzman G, Fantuzzi G, et al. Nonalcoholic fatty liver disease in severely obese adolescent and adult patients. Obesity. 2013;21(3):591-597.
Schwimmer JB, Zepeda A, Newton KP, et al. Longitudinal assessment of high blood pressure in children with nonalcoholic fatty liver disease. PLoS One. 2014;9(11):1-17.
Luttikhuis HO, Baur L, Jansen H, et al. Interventions for treating obesity in children review information authors background. Cochrane Libr. 2009;1(CD001872).
Labayen I, Medrano M, Arenaza L, et al. Effects of exercise in addition to a family-based lifestyle intervention program on hepatic fat in children with overweight. Diabetes Care. 2020;43(2):306-313.
Brunt EM, Tiniakos DG. Histopathology of nonalcoholic fatty liver disease. World J Gastroenterol. 2010;16(42):5286-5296.
Noureddin M, Lam J, Peterson MR, et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology. 2013;58(6):1930-1940.
Ma X, Liu S, Zhang J, et al. Proportion of NAFLD patients with normal ALT value in overall NAFLD patients: a systematic review and meta-analysis. BMC Gastroenterol. 2020;20(1):10.
Kim WR, Flamm SL, Di Bisceglie AM, Bodenheimer HC. Serum activity of alanine aminotransferase (ALT) as an indicator of health and disease. Hepatology. 2008;47(4):1363-1370.
Draijer L, Benninga M, Koot B. Pediatric NAFLD: an overview and recent developments in diagnostics and treatment [internet]. Exp Rev Gastroenterol Hepatol. Taylor & Francis. 2019;13:447-461. https://doi.org/10.1080/17474124.2019.1595589.
Lee JH, Kim D, Kim HJ, et al. Hepatic steatosis index: a simple screening tool reflecting nonalcoholic fatty liver disease. Dig Liver Dis [Internet]. 2010;42(7):503-508. https://doi.org/10.1016/j.dld.2009.08.002.
Bedogni G, Bellentani S, Miglioli L, et al. The fatty liver index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol. 2006;6:1-7.
Kotronen A, Peltonen M, Hakkarainen A, et al. Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and genetic factors. Gastroenterology [Internet]. 2009;137(3):865-872. https://doi.org/10.1053/j.gastro.2009.06.005.
Maffeis C, Banzato C, Rigotti F, et al. Biochemical parameters and anthropometry predict NAFLD in obese children. J Pediatr Gastroenterol Nutr. 2011;53(6):590-593.
Koot BGP, Van Der Baan-Slootweg OH, Bohte AE, et al. Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children. Obesity. 2013;21(3):583-590.
Medrano M, Maiz E, Maldonado-Martín S, et al. The effect of a multidisciplinary intervention program on hepatic adiposity in overweight-obese children: protocol of the EFIGRO study. Contemp Clin Trials [Internet]. 2015;45:346-355. https://doi.org/10.1016/j.cct.2015.09.017.
Cole TJ, Lobstein T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes. 2012;7(4):284-294.
Moons KGM, Altman DG, Reitsma JB, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1-W73.
Browning JD, Szczepaniak LS, Dobbins R, et al. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology. 2004;40(6):1387-1395.
Lo K, Wong M, Khalechelvam P, Tam W. Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis. Obes Rev. 2016;17(12):1258-1275.
European Commission against Racism and Intolerance. ECRI Report on Spain (fifth monitoring cicle) 2018;(2017):46.
Arenaza L, Medrano M, Oses M, et al. Dietary determinants of hepatic fat content and insulin resistance in overweight/obese children: a cross-sectional analysis of the Prevention of Diabetes in Kids (PREDIKID) study. Br J Nutr. 2019;121(10):1158-1165.
Serra-Majem L, Ribas L, Ngo J, et al. Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents. Public Health Nutr. 2004;7(7):931-935.
Léger LA, Mercier D, Gadoury C, Lambert J. The multistage 20 metre shuttle run test for aerobic fitness. J Sports Sci. 1988;6(2):93-101.
Tomkinson GR, Carver KD, Atkinson F, et al. European normative values for physical fitness in children and adolescents aged 9-17 years: results from 2 779 165 Eurofit performances representing 30 countries. Br J Sports Med. 2018;52(22):1445-1456.
Ruiz JR, Castro-Piñero J, España-Romero V, et al. Field-based fitness assessment in young people: the ALPHA health-related fitness test battery for children and adolescents. Br J Sports Med. 2011;45(6):518-524.
Chandler JL, Brazendale K, Beets MW, Mealing BA. Classification of physical activity intensities using a wrist-worn accelerometer in 8-12-year-old children. Pediatr Obes. 2016;11(2):120-127.
Moreno LA, Gottrand F, Huybrechts I, Ruiz JR, González-Gross M, DeHenauw S. Nutrition and lifestyle in European adolescents: the HELENA (healthy lifestyle in Europe by nutrition in adolescence) study. Adv Nutr. 2014;5(5):615S-623S.
American Academy of Pediatrics Committee on Public E, American Academy of Pediatrics. Children, adolescents, and television. Pediatrics. 2001;107:423-426.
Schwimmer JB, Dunn W, Norman GJ, et al. SAFETY study: alanine aminotransferase cutoff values are set too high for reliable detection of pediatric chronic liver disease. Gastroenterology. 2010;138(4):1357-1364.
Vos MB, Abrams SH, Barlow SE, et al. NASPGHAN clinical practice guideline for the diagnosis and treatment of nonalcoholic fatty liver disease in children: recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and nu. J Pediatr Gastroenterol Nutr. 2017;64(2):319-334.
Vajro P, Lenta S, Socha P, et al. Diagnosis of nonalcoholic fatty liver disease in children and adolescents: position paper of the ESPGHAN hepatology committee. J Pediatr Gastroenterol Nutr. 2012;54(5):700-713.
Liu X. Classification accuracy and cut point selection. Stat Med. 2012;31(23):2676-2686.
Schwimmer JB, Deutsch R, Kahen T, Lavine JE, Stanley C, Behling C. Prevalence of fatty liver in children and adolescents. Pediatrics. 2006;118(4):1388-1393.
Bambha K, Belt P, Abraham M, et al. Ethnicity and nonalcoholic fatty liver disease. Hepatology. 2012;55(3):769-780.
Xia MF, Yki-Järvinen H, Bian H, et al. Influence of ethnicity on the accuracy of non-invasive scores predicting non-alcoholic fatty liver disease. PLoS One. 2016;11(8):1-12.
Goran MI, Walker R, Le K, et al. Effects of PNPLA3 on liver fat and metabolic profile in Hispanic children and adolescents. Diabetes. 2010;59:3127-3130.
Martínez LA, Larrieta E, Calva JJ, Kershenobich DTA. The expression of PNPLA3 polymorphism could be the key for severe liver disease in NAFLD in Hispanic population. Ann Hepatol. 2019;16(6):909-915.
Ayala-Marín AM, Iguacel I, Miguel-Etayo P De, Moreno LA. Consideration of social disadvantages for understanding and preventing obesity in children. Front Publ Health. 2020;8(August):423.
Rey-López JP, Bel-Serrat S, Santaliestra-Pasías A, et al. Sedentary behaviour and clustered metabolic risk in adolescents: the HELENA study. Nutr Metab Cardiovasc Dis. 2013;23(10):1017-1024.
Ma J, Fox CS, Jacques PF, et al. Sugar-sweetened beverage, diet soda, and fatty liver disease in the Framingham Heart Study cohorts. J Hepatol. 2015;63(2):462-469.
Barlow SE. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(Suppl):S164-S192.
Draijer LG, Feddouli S, Bohte AE, et al. Comparison of diagnostic accuracy of screening tests ALT and ultrasound for pediatric non-alcoholic fatty liver disease. Eur J Pediatr. 2019;178:863-870.
Dasarathy S, Dasarathy J, Khiyami A, Joseph R, Lopez R. AJM. Validity of real time ultrasound in the diagnosis of hepatic steatosis: a prospective study. J Hepatol. 2009;51(6):1061-1067.
Burgert TS, Taksali SE, Dziura J, et al. Alanine aminotransferase levels and fatty liver in childhood obesity: associations with insulin resistance, adiponectin and visceral fat. J Clin Endocrinol Metab. 2006;91(11):4287-4294.
Yu EL, Golshan S, Harlow KE, et al. Prevalence of nonalcoholic fatty liver disease in children with obesity. J Pediatr [Internet]. 2019;207:64-70. https://doi.org/10.1016/j.jpeds.2018.11.021.