Research Article
Austin J Obes & Metab Synd. 2020; 4(2): 1017.
Non-Alcoholic Fatty Liver Disease (NAFLD) in Overweight and Obese Children and Adolescents
Schiel R1*, Heinrichs M1, Stein G2, Bambauer R3 and Steveling A4
1Department of Diabetes and Metabolic Diseases, MEDIGREIF-Inselklinik Heringsdorf GmbH, Ostseebad Heringsdorf, Germany
2Friedrich-Schiller-University, Internal Medicine, Jena, Germany
3Formerly Institute for Blood Purification, Homburg, Germany
4University of Greifswald, Internal Medicine A, Greifswald, Germany
*Corresponding author: Ralf Schiel, MEDIGREIFInselklinik Heringsdorf GmbH, Setheweg 11, D-17424 Ostseebad Heringsdorf, Germany
Received: June 03, 2020; Accepted: July 01, 2020; Published: July 08, 2020
Abstract
Over the last decades overweight, obesity and Non-Alcoholic Fatty Liver Disease (NAFLD) in childhood and adolescence increased. NAFLD is strongly associated with insulin resistance, hypertension, dyslipidemia and other proatherogenic conditions. It was the aim of the trial to analyze the prevalence of NAFLD, risk factors and comorbidities in a cohort of overweight and obese children and adolescents.
Patients and Methods: Totally 79 children and adolescents with overweight/ obesity (age 13.3 ± 2.4 years, BMI 33.4 ± 6.5 kg/m², BMI-SDS 2.72 ± 0.52) participated in a Structured Treatment and Teaching Program [STTP] (36.1 ± 5.9 days) for weight reduction were included.
Results: NAFLD was diagnosed in 42/79 (53%) of patients. Patients with NAFLD were older (14.0±2.2 vs 12.5±2.5 years, p=0.005), had a higher BMI (36.8±6.4 vs 29.6±4.1 kg/m2, p<0.001), BMI-SDS (2.96±0.48 vs 2.45±0.42, p<0.001) and higher fasting C-peptide (0.77±0.33 vs 0.61±0.28 nmol/l, p=0.018), fasting insulin concentrations (23.4±11.4 vs 15.4±12.1 μIU/ml, p=0.004) and HOMA-index (4.80±2.48 vs 3.22±3.46, p=0.022). Moreover patients with NAFLD had higher values in thickness of A. carotis intima. After an in-patient treatment lasting in the mean 5 weeks children/adolescents reached a mean weight reduction of 3.8±2.7 (range, -15.5-+0.8) kg (p<0.001) along with an improvement of risk parameters. The most important factors associated with NAFLD (R-square=0.444) revealed by the multivariate analysis were: body weight (ß=0.407, p<0.001), HOMA (ß=0.265, p=0.014) and HDL-cholesterol (ß=-0.229, p=0.018) at onset of the trial.
Discussion: Children/adolescents with NAFLD were more likely overweight or obese, had more frequently metabolic risk factors and a higher thickness of A. carotis intima media. The data also suggest an improvement in metabolic and cardiovascular risk factors after a significant weight reduction.
Keywords: Body Mass-Index (BMI); C-peptide; HOMA-index; Cardiovascular Disease; Diabetes Mellitus
Introduction
Over the last two decades Non-Alcoholic Fatty Liver Disease (NAFLD) in childhood and adolescence gained more and more interest. Already in 2006 Patton et al. concluded “Although population prevalence is very difficult to establish, Nonalcoholic Fatty Liver Disease (NAFLD) is probably the most common cause of liver disease in the preadolescent and adolescent age group “[1]. A recently published meta-analysis suggested a prevalence ratio for NAFLD in children/adolescents aged 5 to 18 years with obesity relative to those of a “healthy weight” of 26.1 (95% Confidence Interval [CI], 9.4-72.3) [2]. Anderson et al. found a “pooled mean prevalence of NAFLD in children from general population studies” of 7.6% (95% CI: 5.5- 10.3%) and of 34.2% (95% CI 27.8-41.2%) in studies based on child obesity clinics” [3].
Important reasons for the great variability in awareness and prevalence rates of NAFLD are uncertainities in respect of diagnosis and a lack of simple, non-invasive diagnostic tests [4]. According to Bellentani and Marino in NAFLD there is an accumulation of fat in the liver without excessive alcohol consumption or other known liver pathologies [5]. Mostly NAFLD is defined by the ultrasonographic appearance of the liver (mild to severe steatosis) [4,6,7]. But, also biomarkers can play an important role: In some studies Alanine (ALT) and aspartate Aminotransferfase (AST) where used [3,8], although Anderson et al. concluded that “currently” there is “no consensus on the thresholds of liver enzymes that should be used to indicate NAFLD” [3]. Up to day according to Shah et al. [9], Shakir et al. [10], Vos et al. [11] and Chalasani et al. [12] liver biopsy is the gold-standard approach to determine the presence and severity of NAFLD.
A variety of analyses have shown, that additional to overweight and obesity NAFLD is strongly associated with insulin resistance, hypertension, dyslipidemia and other pro-atherogenic conditions (like inflammatory disorders or endothelial dysfunction) [3,4,13,14]. Pacificio et al. [13] wrote in 2011: “Pathological studies have shown that atherosclerosis is an early process beginning in childhood […]. There is a positive correlation between the extent of early atherosclerotic lesions in the […] carotid arteries and cardiovascular risk factors […]”. The “Guide for General Practitioners” [10] concluded: “Successful management of pediatric NAFLD requires that clinicians identify children with the highest risk through early screening, understand the comorbidities, and offer a multidisciplinary treatment approach that emphasizes diet and physical activity modification […].” On this background it was the aim of the present trial to analyze the prevalence of NAFLD, risk factors and comorbidities in a cohort of overweight and obese children and adolescents admitted to a specialized hospital.
Patients and Methods
Totally 79 children and adolescents with overweight and obesity successively admitted to our hospital were included in the trial (inclusion criteria: BMI [Body Mass Index]/BMI-SDS [Body Mass Index Standard Deviation Score] > 97. Percentile [15] and/or diagnosis for admittance: code according to ICD-10- GM-2019 “E66.0”, http://www.icd-code.de/icd/code/ICD-10-GM. html). The patients participated in a Structured Treatment and Teaching Program [STTP] for weight reduction [15,16]. The STTP was evaluated and demonstrated a good long-term effect (weight reduction and stabilization) over a period of 12 months [17,18]. Further details of the study protocol used in the present trial were published in 2019 [19].
Schedule of the trial
At the beginning of the trial and at the end of the inpatient treatment period (36.1±5.9 [22-57] days) the following examinations were performed:
• In all patients physical examinations were performed.
• Measurements of height and weight were assessed with patients wearing light clothing and without shoes. BMI and BMI-SDS were calculated according to the formulae “BMI=kg/m2” and “BMISDS=([ BMI/M(t)]L(t)-1)/(L(t)*S(t)” (M(t), L(t) and S(t) are pre-defined parameters depending on age(t) and sex [15].
• Body composition analyses were done using a Body composition analyzer (BC418MA, TANITA Europe GmbH, Sindelfingen, Germany).
• Blood pressure in the sitting position was measured after the patients had rested for 10 min by using a standard sphygmomanometer according to the World Health Organization (WHO) recommendations [20]. In all patients a 24-hour-monitoring was performed (Premo Trend, Zimmer Elektromedizin, Neu-Ulm, Germany).
• Ultrasound examination (Siemens Acuson X300PE, München, Germany): On ultrasound images the diagnosis steatosis hepatis (fatty liver) was given, if the liver looks brighter than normal (but not lumpy or shrunken like cirrhotic livers). NAFLD was diagnosed according to ultrasonographic appearance of fatty liver [4] without anamnesis of alcohol consumption or other known liver pathologies [5].
• Measurements of carotid Intima-Media Thickness (IMT) were done by one physician performing 5 measurements on each side and calculating the mean. Definition of normal values was according to the German standard [21].
• Blood-glucose (glucose-oxidase-method, Speedy, Müller Gerätebau GmbH, Saalfeld, Germany) and HbA1c-measurements (DCA2000®-method, Bayer Diagnostics, Leverkusen, Germany, following DCCT-standard [HbA1c/mean normal] x mean according to the DCCT-standard [22]) were done directly in the laboratory of the Medigreif Inselklinik Heringsdorf GmbH using blood samples derived from finger pricking. Additionally venous blood samples taken in the morning of the first day after hospital admission (at onset/beginning of the trial) and at the last day of patients’ in-hospital stay (at the end of the trial) following an overnight fasting period were analyzed (Laborgemeinschaft IMD, Prof. Dr. med. G. Menzel, Pappelallee 1, 17489 Greifswald, Germany) from all patients. The parameters analyzed and the methods of measurement are shown in Table 1.
Parameter
Method
Total cholesterol (TC)
Enzymatic color test
Low Density Lipoprotein (LDL) – cholesterol
Enzymatic color test
High Density Lipoprotein (HDL) – cholesterol
Enzymatic color test
Triglycerides (TG)
Enzymatic color test
Uric acid
Enzymatic color test
C-reactive protein
Turbidimetry
Creatinine
Enzymatically
Estimated Glomerular Filtration Rate (GFR)
186 x (creatinine [mgdl])-1.154 x (age [years])-0.203 **
Cystatine C
Immunoturbidimetry
Asparte-aminotransferase (ASAT)
UV-test
Alanine-aminotransferase (ALAT)
UV-test
Gamma-Glutamyl-Transferase (gGT)
Kinetic color test
Insuline
Chemiluminescence assay
Thyroidea stimulating hormone (TSH)*
Chemiluminescence assay
Free triiodothyronine (fT3)*
Chemiluminescence assay
Free thyroxine (fT4)*
Chemiluminescence assay
C-peptide
chemiluminescence assay
*Laboratory parameter was solely measured at onset of the trial.
**MDRD-formula according the recommendations of the Deutsche Diabetes-Gesellschaft (DDG) [23].
Table 1: Laboratory parameter and method of measurement.
The HOMA calculation is an iterative structural model to estimate the ß-cell function together with insulin sensitivity. HOMA was calculated according to the formula: HOMA=(fasting plasma insulin x fasting plasma glucose)/22.5 (http://www.dtu.ox.ac.uk/ homacalculator/index.php, 27.06.2019).
Ethics vote
The trial was approved by the local ethics committee (Auswirkungen einer sechswöchigen spezifischen Rehabilitationsmaßnahme bei Kindern und Jugendlichen mit Übergewicht und Adipositas auf Gewichtsverlauf, Veränderungen von Risikoparametern und Mikrobiom, Reg.-No. BB 119/17, 28.07.2017, Universitätsmedizin Greifswald, Ethikkommission, Greifswald).
Statistical analysis
Statistical analysis was performed using SPSS®22.0 (Statistical Package for Social Science, SPSS, Chicago, IL, USA). Values showing normal distribution were registered as Mean (MW) ± Standard Deviation (SD), non-normal distributed values were given as median and range. Comparisons were evaluated with chi-squaretest or Fisher’s exact test in case of frequencies less than 5. Paired Student’s t-test and Wilcoxon-test were used to compare the mean values. Correlations were calculated according to Pearson and for multivariate analyses ANOVA models were used. Significance was set at p<0.05. Two-tailed significance tests were used throughout.
Results
Baseline characteristics
The baseline characteristics of the patients in respect of age, sex, height, weight, BMI, BMI-SDS and duration of in-house rehabilitation are given in Table 2.
Paramter
MW±SD
Min.
Max.
Number (n)
79
/
/
Age (years)
13.3 ± 2.4
7.4
18
Females (n[%])
38 (48.1)
/
/
Duration of in-house treatment period (days)
36.1 ± 5.9
22
57
Height (m)
1.61 ± 13,3
128
190
Body weight (kg)
88.6 ± 27.4
39,1
182,1
BMI (kg/m²)
33.4 ± 6.5
21,6
50,4
BMI-SDS
2.72 ± 0.52
1,5
3,8
Table 2: Baseline characteristics of 79 patients with overweight and obesity studied.
Apart from overweight/obesity 15 patients have additional diagnoses like diabetes mellitus or arterial hypertension (Table 3).
Code according to ICD-10-GM-2019*
Disease
Number (n/ %)
Medication in n patients
E 03.9
Hypothyreosis
2 (2%)
Thyroxine n=2
E 10.9
Diabetes mellitus type 1
1 (1%)
Insulin n=1
E 11.9
Diabetes mellitus type 2
5 (6%)
Metformin n=4
I 10.9
Arterial hypertension
4 (5%)
ACE-inhibitor n=2
J 45.9
Asthma bronchiale
5 (6%)
ß-Sympatho-mimetic n=5
L 20.9
Atopic dermatitis
1 (1%)
No medication
*(http://www.icd-code.de/icd/code/ICD-10-GM.html), 22.08.2019
Table 3: Additional diagnoses in 79 patients with overweight or obesity studied.
Patients with vs without NAFLD, additional diagnoses and changes of body weight, BMI and body composition
In the present cohort NAFLD was diagnosed in 42/79 (53%) of patients. In respect of additional diagnoses there was a tendency (p<0.05) towards more diagnoses in patients with vs without NAFLD (E 03.9: n=1 vs n=1, E 10.9: n=1 vs n=0; E 11.9: n=4 vs n=1; I 10.9: n=3 vs n=1; J 45.9: n=4 vs n=1, L 20.9: n=1 vs n=0), there were no differences regarding sex (females: with NAFLD vs without NAFLD: 45% vs 51% [p=0.59]).
Patients with NAFLD were older (14.0±2.2 vs 12.5±2.5 years, p=0.005) and higher (1.64±13.6 vs 1.57±12.2 m, p=0.022) than patients without NAFLD. Patients with NAFLD had a higher body weight, BMI, BMI-SDS, body fat mass and percentage of body fat, but also a higher fat-free mass. Moreover, patients with NAFLD had higher fasting C-peptide (0.77±0.33 vs 0.61±0.28 nmol/l, p=0.018), fasting insulin concentrations (23.4±11.4 vs 15.4±12.1 μIU/ml, p=0.004) and HOMA-index (4.80±2.48 vs 3.22±3.46, p=0.022).
After an in-patient treatment lasting in the mean 5 weeks, in the total group children and adolescents reached a mean weight reduction of 3.8±2.7 (range, -15.5-+0.8) kg (p<0.001) accompanied by a reduction of body fat mass. At baseline the mean weight percentile of all patients studied was 98.7±1.83 (range, 83.0-99.5). Both groups, patients with and without NAFLD, reached a significant reduction of body weight, BMI and body fat during the in-patient rehabilitation procedure. In all groups these changes were accompanied by an improvement of HOMA-index (Table 4).
Patients with NAFLD (n=42)
Patients without NAFLD (n=37)
Onset of the trail
End of the trail
Onset vs end
Onset of the trail
End of the trail
Onset vs end
Onset, with vs without NAFLD
End with vs without NFLAD
Parameter
MW±SD
MW±SD
p-value
p-value
p-value
p-value
Weight (kg)
100.9±27.6
96.3±25.7
<0.001
74.7±19.6
71.7±18.7
<0.001
<0.001
<0.001
BMI (kg/m2)
36.8±6.4
35.1±5.8
<0.001
29.6±4.1
28.4±3.9
<0.001
<0.001
<0.001
BMI-SDS
2.96±0.48
2.82±0.52
<0.001
2.45±0.42
2.30±0.44
<0.001
<0.001
0.021
Weight reduction (kg)
/
-4.48±3.01
/
-3.07±2.15
/
/
/
Body Composition
Percentage of body fat (%)
44.6±7.0
41.1±6.2
<0.001
37.2±6.4
34.4±6.1
<0.001
<0.001
<0.001
Fat mass (kg)
45.6±16.1
40.1±13.6
<0.001
28.9±11.6
26.1±9.9
<0.001
<0.001
<0.001
Fat-free mass (kg)
55.2±15.1
56.2±14.9
<0.001
46.2±9.7
46.0±10.8
0.964
0.003
0.001
Table 4: Patients with vs without NAFLD and changes of body weight, BMI and body composition.
Patients with NAFLD had more frequently laboratory abnormalities (i.e. higher concentrations of uric acid, higher triglycerides, lower HDL-cholesterol levels, higher CRP concentrations, higher ALAT, higher ASAT, higher HbA1c, higher C-peptide, higher insulin concentrations, lower beta-cell function, lower insulin sensitivity with a higher level of insulin resistancy). Moreover patients with NAFLD had higher values in thickness of A. carotis intima too, but there were no differences in respect of blood pressure values. After participation in an in-patient treatment programme in both groups most parameters improved (Table 5).
Patients with NAFLD (n=42)
Patients without NAFLD (n=37)
Onset of the trail
End of the trail
Onset vs end
Onset of the trail
End of the trail
Onset vs end
Onset, with vs without NAFLD
End with vs without NFLAD
Parameter
Mean±SD
p-value
Mean±SD
Mean±SD
p-value
p-value
Uric acid (µmol/sl)
383.1±77.5
358.5±85.9
<0.001
354.5±87.2
317.8±69.4
<0.001
0.131
0.029
Triglycerides (mmol/l)
1.42±0.58
1.09±0.33
<0.001
1.13±0.46
1.01±0.42
<0.001
0.018
0.349
Total Cholesterol (mmol/l)
4.36±0.82
3.63±0.69
<0.001
4.29±0.47
3.65±0.61
0.632
0.908
HDL-Cholesterol (mmol/l)
1.14±0.26
1.06±018
<0.001
1.28±0.24
1.16±0.23
0.023
0.043
LDL-Cholesterol (mmol/l)
3.00±0.71
2.37±0.60
<0.001
2.87±0.52
2.29±0.47
0.396
0.569
LDL/HDL-quotient
2.72±0.78
2.27±0.59
<0.001
2.36±0.78
2.03±0.53
0.047
0.083
Fasting blood glucose (mmol/l)
4.64±0.46
4.44±0.59
0.028
4.45±0.61
4.30±0.46
0.001
0.131
0.253
Blood glucose 2h following oGTT (mmol)
6.03±1.19
/
/
5.85±0.79
/
/
0.085
/
HbA1c (%)
5.69±0.93
5.55±0.74
0.006
5.35±0.32
5.26±0.79
0.004
0.042
0.035
HbA1c (mmol/mol)
38.71±10.19
37.12±8.10
0.005
35.04±3.45
33.76±3.08
0.015
0.043
0.022
C-Peptide (nmol/l)
0.77±0.33
0.71±0.25
0.238
0.61±0.28
0.57±0.17
0.001
0.018
0.013
Insulin Concentration (µl U/ml)
23.4±11.4
19.33±9.75
0.071
15.4±12.1
12.25±5.25
0.020
0.004
0.001
ß-cell function (%)
242.98±67.24
229.8±78.5
0.835
181.5±68.9
176,97±55.47
<0.001
<0.005
0.002
Insulin sensitivity (%)
40.7±20.6
52.35±29.10
0.085
77.5±46.0
80.22±41.94
0.003
<0.005
0.002
HOMA
4.80±2.48
2.42±1.11
0.049
3.22±3.46
1.52±0.64
<0.001
0.022
<0.001
TSH (µl U/ml)
2.93±1.08
/
/
3.02±1.55
/
/
0.730
/
fT3 (pg/ml)
3.89±0.66
/
/
3.92±0.61
/
/
0.798
/
fT4 (ng/dl)
1.06±0.11
/
/
1.04±0.13
/
/
0.429
/
GFR
85.7±17.9
91.03±118.10
0.001
83.5±10.9
87.97±12.28
0.001
0.539
0.424
Creatinine (µmol/l)
54.2±10.2
52.67±9.28
0.022
52.1±9.8
49.97±8.36
0.002
0.359
0.211
Cystatin C (mg/l)
1.04±0.18
0.98±0.17
0.001
1.03±0.14
0.98±0.33
0.001
0.989
0.989
ASAT (µmol/sl)
0.52±0.31
0.44±0.20
0.004
0.43±0.12
0.38±0.11
0.027
0.119
0.076
ALAT (µmol/sl)
0.44±0.22
0.65±0.47
0.066
0.38±0.11
0.47±0.33
0.631
0.013
0.498
gGT (µmol/sl)
0.44±0.22
0.34±0.23
<0.001
0.39±0.39
0.29±0.34
0.001
0.448
0.498
Thickness of A.carotisintima media (mm)
0.45±0.08
/
/
0.40±0.07
/
/
0.014
/
Mean systolic blood pressure during 24h (mmHg)
132.5±11.0
/
/
129.4±12.5
/
/
0.255
/
Mean diastolic blood pressure during 24h (mmHg)
77.1±7.7
/
/
76.1±9.6
/
/
0.606
/
Table 5: Laboratory values at hospital admission.
Multivariate analyses
The most important factors associated with NAFLD (R-square=0.444) revealed by the multivariate analysis were: body weight (ß=0.407, p<0.001), HOMA (ß=0.265, p=0.014) and HDLcholesterol (ß=-0.229, p=0.018) at onset of the trial. All other parameters analyzed in the model (sex, age, height, BMI, BMI-SDS, fat mass, percentage of body fat, fasting blood glucose, blood glucose after oGTT [performed not in patients with known diagnosis of diabetes mellitus], C-peptide, insulin concentration, ß-cell function, insulin sensitivity, insulin resistancy, HOMA, triglycerides, total cholesterol, LDL-cholesterol, LDL/HDL-cholesterol-quotient, ASAT, ALAT, gGT, uric acid, CRP, TSH, fT3, fT4, thickness of A. carotis intima-media, systolic and diastolic blood pressure during a 24 hours-period) showed no associations.
Discussion
Following the literature there is still discussion about the diagnostic criteria for NAFLD [3,6,9-12,14]. After the exclusion of other causes of liver disease (such as viral hepatitis, autoimmune liver diseases, Wilson disease, hepatotoxic agents) liver biopsy remains the gold standard for the diagnosis of NAFLD [9,11,12]. However, liver biopsy is associated with some risks. Among these are bleedings, pains, leakages of bile or formation of arteriovenous fistulas [9,11,12]. On this background in multiple studies [3] NAFLD was diagnosed non-invasive. Like in the present study Han et al. [6], Mohamed et al. [7] and Kim et al. [4] used ultrasound imaging for diagnoses of NAFLD. Hence, although ultrasound examination is not a gold standard for diagnosis [9,11,12] the method seems to be suitable in cross-sectional studies like the present one.
During the last decades the prevalence of NAFLD in children and adolescents increased [3]. According to Aggarwal et al. [24] and Goyal et al. [14] it is already one of the leading causes for chronic liver diseases in this age group. In 2008 in a case-control study of 150 overweight and obese children Schwimmer et al. [25] found that NAFLD was strongly associated with metabolic syndrome. In a review published in 2011 Pacifico et al. [13] demonstrated an elevated risk for NAFLD in children and adolescents with abdominal obesity, type 2 diabetes, dyslipidaemia and insulin resistance. In a recently published study with 520 obese children, aged 3.4-17.1 years, Han et al. [6] revealed in those with NAFLD higher fasting C-peptide and insulin concentrations along with a higher HOMA index. In stepwise multiple logistic regression models the authors showed that fasting C-peptide was an independent indicator for NAFLD. Moreover, in children with overweight and obesity the data of Schwimmer et al. [25] also suggest an increased risk for cardiovascular abnormalities. Similar results were found by Mohamed et al. [7]: In their cohort 62% of overweight and obese children with NAFLD had a metabolic syndrome. All the findings of Schwimmer et al. [25], Pacificio et al. [13], Han et al. [6] and Mohamed et al. [7] are in agreement with the results of our present study: Also in our cohort children and adolescents with NAFLD were more likely overweight or obese, had higher concentrations of C-peptide, fasting insulin and a higher HOMA index, along with higher levels of liver enzymes, triglycerides, total and LDL-cholesterol. Additionally as an important marker for the cardiovascular risk profile, patients with NAFLD had a higher thickness of A. carotis intima media too. However, our data also suggest an improvement in metabolic and cardiovascular risk factors after a significant weight reduction.
According to Pacificio et al. [13] “In children, the cardiovascular system remains plastic and damage-reversible if early and appropriate interventions are established effectively.” On this background the weight reduction following a rehabilitation procedure [19] along with the improvement in metabolic and cardiovascular risk profile maybe lead to an improvement in long-term outcome. This suggestion is in accordance with the “Overview of updated practice guidelines for pediatric nonalcoholic fatty liver disease” updated in July 2018 (“Although lifestyle modification (ie, diet and exercise) are recommended as first-line approaches in the management of pediatric NAFLD…” [9]). However, more and more rigorous studies over longer periods of time are required in order to understand these effects and clinical outcome of patients. Additionally Shah et al., [9] “expected that promising therapeutic agents for NAFLD will transform the way clinicians care for children with this disease.”
References
- Patton HM, Sirlin C, Behling C, Middleton M, Schwimmer JB, Lavine JE. Pediatric nonalcoholic fatty liver disease: A critical appraisal of current data and implications for future research. J Pediatr Gastroenterol Nutr. 2006; 43: 413-427.
- Sharma V, Coleman S, Nixon J, Sharples L, Hamilton-Shield J, Rutter H, et al. A systematic review and meta-analysis estimating the population prevalence of comorbidities in children and adolescents aged 5 to 18 years. Obes Rev. 2019.
- Anderson EL, Howe LD, Jones HE, Higgins JP, Lawlor DA, Frager A. The prevalence of non-alcoholic fatty liver disease in children and adolescents: A systematic review and meta-analysis. PLOS ONE. 2015.
- Kim D, Kim WR, Kim HJ, Therneau TM. Association between non-invasive fibrosis markers and mortality among adults with non-alcoholic fatty liver disease in the United States. Hepatology. 2013; 57: 1357-1365.
- Bellentani S, Marino M. Epidemiology and natural history of Non-Alcoholic Fatty Liver Disease (NAFLD). Ann Hepatol. 2009; 8: S4-S8.
- Han X, XU P, Zhou J, Liu Y, Xu H. Fasting C-peptide is a significant indicator of nonalcoholic fatty liver disease in obese children. Diabetes Res Clin Pract. 2020; 108027.
- Mohamed ZR, Jalaludin MY, Anur Zaini A. Predictors of Non-Alcoholic Fatty Liver Disease (NAFLD) among children with obesity. J Pediatr Endocrinol Metab. 2020.
- Goldberg DM. Structural, functional, and clinical aspects of gammaglutamyltransferase. CRC Crit Rev Clin Lab Sci. 1980; 12: 1-58.
- Shah J, Okubote T, Alkouri N. Overview of updated practice guidelines for pediatric nonalcoholic fatty liver disease. Gastr Hepatol. 2018; 14: 407-414.
- Shakir AK, Suneja U, Short KR, Palle SP. Overview of pediatric nonalcoholic fatty liver disease: A Guide for General Practitioners. J Okla State Med Assoc. 2018; 111: 806-811.
- Vos MB, Abrams SH, Barlow SE, Caprio S, Daniels SR, Kohli R, 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 Nutrition (NASPGHAN). J Pediatr Gastroenterol Nutr. 2017; 64: 319-334.
- Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018; 67: 1-60.
- Pacifico L, Nobili V, Anania C, Verdecchia P, Chiesa C. Pediatric nonalcoholic fatty liver disease, metabolic syndrome and cardiovascular risk. World J Gastroenterol. 2011; 17: 3082-3091.
- Goyal NP, Schwimmer JB. The progression and natural history of pediatric nonalcoholic fatty liver disease. Clin Liver Dis. 2016; 20: 325-338.
- Arbeitsgemeinschaft Adipositas im Kindes- und Jugendalter [AGA]. Leitlinien. Verabschiedung auf der Konsensuskonferenz der AGA am 04.10.2012.
- Schiel R, Radón S, Beltschikow W: Telemedizinisches Therapiekonzept bei Stoffwechselerkrankungen (Übergewicht und Adipositas) bei Kindern und Jugendlichen (TeleAdi). Schlussbereicht. Ostseebad Heringsdorf: MEDIGREIF Inselklinik Heringsdorf GmbH, Ostseebad Heringsdorf 2006.
- Egmond-Fröhlich A van, Bräuer W, Goldschmidt H, Hoff-Emden H, Oepen J, Zimmermann E. Effekte eines strukturierten, ambulanten Weiterbehandlungsprogrammes nach stationärer medizinischer Rehabilitation bei Kindern und Jugendlichen mit Adipositas. Multizentrische, randomisierte, kontrollierte Studie. Rehabilitation. 2006; 45: 40-51.
- Schiel R, Beltschikow W, Radón S, Kramer G, Schmiedel R, Berndt RD, et al. Long-term treatment of obese children and adolescents using a telemedicine support programme. J Telemed Telecare. 2008; 14: 13-16.
- Schiel R, Heinrichs M, Stein G, Steveling A. Effects of weight reduction in overweight and obese children and adolescents. Health Edu Care. 2019; 4: 1-7.
- Guidelines Subcommittee: 1999 World Health Organization – International society of hypertension guidelines for the management of hypertension. J Hyperten. 1999; 17: 151-183.
- Buck M. Die Intima-Media-Thickness (IMT) der Arteria carotis communis bei gesunden Kindern und Jugendlichen. Sonographische Methodik, Anwendbarkeit und Referenzwerte. Dissertation, Technische Universität, München, Germany. 2013.
- The Diabetes Control and Complications Trial Research Group, Nathan DM, Genuth S, Lachin J, Cleary P. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulindependent diabetes mellitus. N Engl J Med. 1993; 329: 977-986.
- Rüster C, Hasslacher C, Wolf G. Nephropathie bei Diabetes. Diabetologie. 2015; 10: S113-S118.
- Aggarwal A, Puri K, Thangada S, Zein N, Alkhouri N. Nonalcoholic fatty liver disease in children: Recent practice guidelines, where do they take us? Curr Pediatr Rev. 2014; 10: 151-161.
- Schwimmer JB, Pardee PE, Lavine JE, Blumkin AK, Cook S. Cardiovascular risk factors and the m etabolic syndrome in pediatric nonalcoholic fatty liver disease. Circulation. 2008; 118: 277-283.
Download PDF