Relationship between obesity related indicators and non-alcoholic fatty liver disease in children: a systematic review and meta-analysis

Introduction

Over the past two decades, childhood obesity has skyrocketed to alarming levels (1). This increase is attributed to socioeconomic progress and better nutritional status for children. Obesity is linked to metabolic syndrome, a condition that includes health problems such as central obesity, high blood pressure, insulin resistance, and abnormal cholesterol levels. These issues can result in cardiovascular disease and type 2 diabetes, posing serious threats to the well-being of adolescents and children (2,3).

Nonalcoholic fatty liver disease (NAFLD) is a clinical condition characterized by the degeneration of over 5% of liver cells, which is not caused by alcohol consumption or other specific factors. This leads to chronic fat accumulation in the liver (4). The worldwide prevalence of NAFLD now exceeds 25%, and due to the rising rates of obesity and changes in lifestyle, it is expected to become the most common liver disease within the next decade (5). The global incidence of NAFLD among children and adolescents currently ranges from 3% to 10% (6). For this population, NAFLD can significantly heighten the risk of severe cardiovascular events in adulthood, such as diabetes, chronic kidney disease, and stroke (7). Consequently, early prevention and intervention for NAFLD in children and adolescents are crucial for enhancing their health and reducing the medical burden later in life.

Factors such as prolonged sitting, physical activity, high sugar diet, intestinal health flora imbalance, and prenatal environment are also associated with the onset of nonalcoholic fatty liver disease in children. A large number of studies have reported the relationship between overweight and NAFLD in children (7-11), however, there is significant heterogeneity among these studies, with different inclusion criteria, observation indicators, and outcomes. Therefore, there are still some controversies regarding the specific relationship between overweight and NAFLD in children. In addition, a standard, evidence-based screening method for NAFLD in obese children is still lacking (9). In addition, nondrug treatment of NAFLD in children is particularly important. However, the most important of the non-pharmacological treatments, exercise, has been studied for its effectiveness in improving NAFLD in children, with mixed results and a lack of systematic analysis. This meta-analysis summarized, analyzed, and compared overweight-related body parameters [height, weight, body mass index (BMI), and waist circumference], related lipid metabolism parameters [total cholesterol, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL)], and glucose metabolism parameters (fasting blood glucose and insulin resistance index) of children with NAFLD and healthy children, and the differences in these overweight-related parameters between children with NAFLD and healthy control children were compared. The relationship between overweight and the onset of NAFLD in children was thus established, thus contributing to the early detection, diagnosis and treatment of NAFLD. We also evaluated the effect of exercise on the degree of NAFLD (0–3) in children, providing new insights for nondrug treatment of NAFLD in children. We present the following article in accordance with the MOOSE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-23-123/rc).

Methods

Literature search strategy

This meta-analysis was conducted in strict accordance with PICOS principles. We extracted English and Chinese literature published form the establishment of the databases to December 2022 from PubMed, Embase, Scopus, China National Knowledge Infrastructure (CNKI), Chongqing VIP Information (VIP), Wanfang databases by adopting a combination of subject terms and unrestricted search. The Chinese and English search terms included “obesity” (OR “overweight” OR “fat”), “diabetes mellitus” (OR “diabetes” OR “glycuresis” OR “insulin resistance”), “exercise” (OR “sports”), “pediatrics” (OR “children” OR “child”), and “Nonalcoholic fatty liver disease” (OR “NAFLD”). This study also checked citation indexes and reference lists of retrieved articles for additional studies not identified in the original database search.

Inclusion and exclusion criteria

Inclusion criteria

• Population: children under the age of 18.
• Intervention or Observation indicators: participants’ weight, height, BMI, waist circumference, total cholesterol, triglyceride content, LDL, HDL, fasting blood glucose, insulin resistance index (homeostasis model assessment of insulin resistance (HOMA-IR)].
• Comparison: the NAFLD group was defined as children who were clinically diagnosed according to international standards through methods such as liver ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and biopsy, and who had no comorbidities; the control group was defined as healthy children without any underlying disease.
• Outcomes: diagnosis of nonalcoholic fatty liver disease, and degree of fatty liver (0–3), with no missing data.
• Study design: case control study, the full text of which was available.

Exclusion criteria

• Duplicate articles or no full text.
• Studies with missing data or errors that could not be completed or corrected.
• Lack of outcome indicators needed for this study.
• Children with any other diseases.
• Letters, case reports, comments, and practical guidelines, etc.
• Studies that did not diagnose NAFLD according to international standards or did not exclude other causes of chronic liver disease (alcohol consumption, chronic viral hepatitis, metabolic liver disease, hereditary hemochromatosis, secondary hepatic steatosis drugs, or liver toxic drugs, etc.).
• All animal experiments.

Outcome indicators

The outcome indicators included: weight, height, BMI, waist circumference, total cholesterol, triglyceride content, LDL, HDL, fasting blood glucose (mg/dL), insulin resistance index (HOMA-IR), and fatty liver classification (0–3) of children in the NAFLD group and the healthy control group.

Data extraction

We collected the following data: article title, first author, year of publication, country of study, type of study design, sample size of experimental and control groups, mean age of experimental and control samples and their standard deviation (if available), and relevant outcomes index.

Quality evaluation

The quality of the studies was assessed by 2 independent researchers and based on the Newcastle-Ottawa Scale (NOS) (12). When opinions differed, discussions were held with a third party to reach agreement. NOS includes 8 items, specifically including study population selection, comparability, exposure evaluation, or outcome evaluation. The total score is 9 points, with 1–3, 4–6, and 7–9 points being low, medium, and high-quality, respectively, with a high, medium, and low risk of bias.

Statistical analysis

Statistical analysis was conducted using Stata/SE 16.0, IBM SPSS Statistics 26, and Review Manager 5.4 software. Weight, height, BMI, waist circumference, total cholesterol value, triglyceride content, LDL content, HDL content, fasting blood glucose, insulin resistance index (HOMA-IR), and fatty liver grade (0–3) were analyzed. Except for fatty liver grade, outcome indicators were continuous variables and represented by the mean and its 95% confidence interval (CI). The Q test was used to assess heterogeneity between studies. I²<50% and P>0.1 indicated that the heterogeneity between the studies was small, and the fixed-effect model was used. Conversely, the random-effects model was used to calculate the size of the combined effect size. As fatty liver disease was a categorical ordinal variable, and therefore differs from a dichotomous variable such as cure/exacerbation of disease, we were not able to calculate the combined effects directly using Stata/SE 16.0 software to calculate the relative risk. Logistic regression was first used to calculate the effect size of each included study and its standard error, followed by the generic inverse variance method in Review Manager 5.4 to combine the effect size for meta-analysis. The statistical results of meta-analysis are depicted by forest plots. Funnel plots were drawn to evaluate publication bias, and the Begg’s test was used to further evaluate publication bias. P<0.05 was considered statistically significant.

Results

Literature search screening results

A total of 1,142 studies were extracted from the databases through the above retrieval methods. By browsing titles, keywords, and abstracts, 156 of these studies were identified as potentially relevant to the research topic. Of these 156 studies, we obtained the full text of 139 studies. Based on the inclusion and exclusion criteria, we excluded a further 124 studies. Ultimately, a total of 15 studies (13-27) were included in this meta-analysis. The document screening process is shown in Figure 1.

Figure 1 Flow chart of literature screening.

Basic characteristics of included studies

All 14 included studies were original. The total sample comprised 1,595 children, including 824 in the experimental group and 771 in the control group. The basic characteristics of the included studies are listed in Table 1.

Quality assessment of included literature

The quality of the studies was evaluated based on NOS, with scores ranging from 0–9 points. Studies with 1–3, 4–6, and 7–9 are low, medium, and high quality research, respectively, with high, medium, and low bias risks. The meta-analysis included 12 high-quality documents, 3 medium quality documents, and 0 low quality documents. The quality evaluation results of the included literature are shown in Table 2.

Meta analysis results and sensitivity analysis

Effect of body weight on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=58.80%, P=0.06, and thus the random-effects model was used for meta-analysis. The results showed that there was no statistically significant difference in body weight between children with NAFLD and healthy children [mean difference (MD) =0.31 kg, 95% CI: −0.07 to 0.69 kg; Figure 2]. Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 2 Forest plot of the impact of body weight on the incidence of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of height on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=21.67%, P=0.28, and thus the fixed-effect model was used for meta-analysis. The results showed that there was no statistically significant difference in height between children with NAFLD and healthy children (MD =0.13 cm, 95% CI: −0.09 to 0.36 cm; Figure 3). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 3 Forest plot of the effect of height on the incidence of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

The influence of body mass index on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=91.18%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that the BMI value of the NAFLD group was significantly higher than that of the control group (MD =1.05 kg/m², 95% CI: 0.36 to 1.73 kg/m²) compared with healthy children (Figure 4). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 4 Forest plot of the impact of BMI on the incidence of NAFLD in children. BMI, body mass index; NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of waist circumference on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=95.18%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that waist circumference of the NAFLD group was significantly larger than that of the control group (MD =1.66 cm, 95% CI: 0.60 to 2.73 cm) compared with healthy children (Figure 5). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 5 Forest plot of the impact of waist circumference on the incidence of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of total cholesterol on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=84.85%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that there was no statistically significant difference in total cholesterol between children with NAFLD and healthy children (MD =0.25 mg/dL, 95% CI: −0.26 to 0.76 mg/dL; Figure 6). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 6 Forest plot of the effect of total cholesterol on the incidence of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of triglyceride level on the development of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=95.68%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that the triglyceride level in the NAFLD group was significantly higher than that in the control group (MD =1.08 mg/dL, 95% CI: 0.05 to 2.12 mg/dL; Figure 7). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 7 Forest plot of the effect of triglyceride level on the incidence of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of LDL level on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=62.32 %, P=0.04, and thus the random-effects model was used for meta-analysis. The results showed that the LDL level in the NAFLD group was significantly higher than that in the control group (MD =0.49 mg/dL, 95% CI: 0.12 to 0.85 mg/dL; Figure 8). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 8 Forest plot of the effect of LDL level on the incidence of NAFLD in children. LDL, low-density lipoprotein; NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of HDL level on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=98.12%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that there was no statistical difference in the HDL level of the NAFLD group compared with the healthy children (MD =−0.61 mg/dL, 95% CI: −2.25 to 1.03 mg/dL; Figure 9). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 9 Forest plot of the effect of HDL level on the incidence of NAFLD in children. HDL, high-density lipoprotein; NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of fasting blood glucose on the development of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=18.92%, P=0.3, and thus the fixed-effect model was used for meta-analysis. The results showed that compared with healthy children, the fasting blood glucose in the NAFLD group was significantly higher than that in the control group (MD =0.31 mg/dL, 95% CI: 0.09 to 0.54 mg/dL; Figure 10). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 10 Forest plot of the effect of fasting blood glucose on the onset of NAFLD in children. NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

Effect of insulin resistance index (HOMA-IR) on the incidence of NAFLD in children

The results of the heterogeneity test of the included studies were: I²=96.59%, P<0.001, and thus the random-effects model was used for meta-analysis. The results showed that the insulin resistance index (HOMA-IR) of the NAFLD group was significantly higher than that of the control group (MD =2.95, 95% CI: 1.41 to 4.49; Figure 11). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 11 Forest plot of the impact of insulin resistance index (HOMA-IR) on the incidence of NAFLD in children. HOMA-IR, homeostasis model assessment of insulin resistance; NAFLD, nonalcoholic fatty liver disease; CI, confidence interval.

The effect of exercise on children with NAFLD (grade 0–3)

The effect size and standard error of the included studies were calculated by ordinal logistic regression (Table 3). The results of the heterogeneity test of the included studies were: I²=0%, P=0.66, and thus the fixed-effect model was used for meta-analysis. The results showed that exercise had a significant effect on improving the degree of NAFLD in children (OR =2.51, 95% CI: 1.83 to 3.43; Figure 12). Sensitivity analysis showed that deleting studies 1 by 1 would not significantly change the size of the overall effect, and the results were relatively stable.

Figure 12 Forest plot of the effect of exercise on nonalcoholic fatty liver disease (0–3 degrees) in children. CI, confidence interval.

Publication bias

The funnel plot showed a slight asymmetry (Figures 13-16), and we speculated that there may have been some publication bias, but it was difficult to quantify. However, when we used Begg’s method to assess publication bias, we found that publication bias was not significant: P_(BMI)=0.4524, P_{(waist circumference)}=0.1329, P_{(triglycerides)}=0.0163, and P_{(insulin resistance index)}=0.1329.

Figure 13 Funnel plot for BMI. BMI, body mass index.

Figure 14 Funnel plot for waist circumference.

Figure 15 Funnel plot for triglycerides.

Figure 16 Funnel plot for insulin resistance index (HOMA-IR). HOMA-IR, homeostasis model assessment of insulin resistance.

Discussion

With rapid economic development and changes in lifestyle, the incidence of overweight and obese children worldwide is increasing at an alarming rate (1-3). This has become an increasingly serious public health problem that is endangering children’s health. As of 2016, the overall prevalence of childhood obesity had reached 18.5% (28). Obesity seriously affects children’s quality of life and physical and mental health and is also a high-risk factor for many chronic diseases. Childhood obesity has a higher probability of persisting into adulthood, potentially resulting in associated chronic conditions, such as diabetes, hypertension, high cholesterol, atherosclerosis, cardiovascular and cerebrovascular diseases, and the development of specific tumors. Additionally, psychological and behavioral disorders may also arise (3,29).

NAFLD refers to a clinicopathological syndrome characterized by excessive fat deposition in liver cells not caused by alcohol or other definite liver damage factors (10) and is associated with insulin resistance and genetic susceptibility. NAFLD is the most common liver disease worldwide and a leading cause of liver-related morbidity and mortality (30). It is now also considered a hepatic manifestation of metabolic syndrome, and experts in the field have recently proposed a new, more representative term, “metabolic-associated fatty liver disease” (MAFLD) (30). NAFLD is the most common liver disease in children (31), usually occurring in the presence of metabolic syndrome and/or obesity in children, while genetic predisposition appears to be associated with more rapid progression, diabetes development, and increased cardiovascular risk. In addition, NAFLD is closely related to increased chances of liver transplantation (6,11,31). Therefore, with the increasing rate of childhood obesity, further control of the incidence of NAFLD in children is urgently needed.

Childhood obesity is known to be an important cause of the progressively increasing incidence of NAFLD in children (30). Although a large number of studies have reported the relationship between obesity and NAFLD in children (30-32), scientifically sound screening methods for NAFLD in obese children are still lacking. Therefore, this meta-analysis collected relevant data from children with NAFLD and healthy children to investigate the differences in anthropometric and biochemical characteristics between children with NAFLD and healthy controls. We determined the obesity-related body parameters (height, weight, BMI, and waist circumference), lipid metabolism parameters (total cholesterol, triglycerides, HDL, and LDL), and glucose metabolism parameters (fasting blood sugar and insulin resistance index) associated with the incidence of NAFLD in children to enable the development of a standard screening method for the early detection, diagnosis, and treatment of the disease in our daily clinical work in pediatrics and provide a solid foundation for the establishment of its screening and diagnostic criteria. In addition, this study further evaluated the effect of exercise on NAFLD in children, providing new insights for controlling the incidence of NAFLD in children.

The results of the meta-analysis showed that BMI and waist circumference (WC) were significantly correlated with the presence of NAFLD in children, and higher BMI and WC values indicated a higher possibility of NAFLD in children. This was consistent with existing research findings. A study (33) from China that used a restricted cubic spline model to explore the dose-response relationship between continuous changes in BMI and fatty liver disease showed that regardless of sex (male/female), age after stratification (<50/≥50 years old), and the prevalence of hypertension (yes/no), the dose-response relationship between BMI and fatty liver disease was J-shaped (nonlinear test, P<0.001). Other study on children with NAFLD (32) has shown that WC, BMI, and the severity of fatty liver are closely related. WC has a stronger predictive power than BMI and is relatively simple to determine. Therefore, an important measure for preventing and reducing the occurrence of fatty liver in children is to control increases in WC and BMI.

The results of this meta-analysis showed that among obesity-related lipid metabolism data, triglyceride content and LDL were significantly associated with the presence of NAFLD in children, suggesting a higher incidence of NAFLD in children. Triglyceride is a type of fat found in the blood that is mainly metabolized by the liver. If triglycerides continue to increase and exceed the metabolic capacity of the liver, excessive fat will accumulate in the liver, and in the long run, cause fatty liver (34). At the same time, the liver function of patients with fatty liver has been damaged, and the ability to metabolize fat has decreased, resulting in the deposition of large amounts of lipids in the liver and blood circulation, which will increase triglycerides in the blood (34). Therefore, high blood triglyceride levels are likely to cause fatty changes in the liver, thereby increasing the incidence of NAFLD (35). LDL is a lipoprotein particle that carries cholesterol into peripheral tissue cells and can become oxidized (36). When the amount of LDL, especially oxidized LDL (OX-LDL) is excessive, the cholesterol it carries accumulates in the liver, leading to the development of hepatic steatosis (34). However, in our study, a correlation between total cholesterol (TC) and NAFLD in children was not observed, although studies of adult patients with NAFLD (36,37) have shown that increased TC is a risk factor for the development of NAFLD in adults. For instance, an analysis examining the relationship between fatty liver and blood sugar, blood lipids, and liver function in a random population of patients undergoing physical examinations (38) revealed that serum total cholesterol (TC) levels increased as fatty liver worsened, indicating a correlation between the two. We hypothesize that the main reasons for the discrepancy with the findings of this study are: (I) our study population consists of children, and there are substantial differences in various parameters between adults and children; (II) the ratio of male to female participants varied significantly among the studies included in this analysis; and (III) the research papers incorporated in our study originated from different countries, potentially leading to considerable variations in the samples.

The results of this study showed that among obesity-related indicators, glucose metabolism, fasting glucose, and insulin resistance index (HOMA-IR) were significantly correlated with the presence of NAFLD in children. Previous studies have reported that as the adipose tissue of patients with fatty liver has insulin deficiency or insulin resistance, the surrounding fat breaks down and releases large quantities of free fatty acids and triglycerides, further depositing fat in the liver (39). Therefore, parameters related to glucose metabolism (fasting blood glucose and insulin resistance index, etc.) are also sensitive indicators for early screening and diagnosis of NAFLD in children.

In addition, this study found that exercise could significantly improve the disease process of children with NAFLD and effectively improve the degree of NAFLD in children. A recent study reported that there is no specific drug for the treatment of NAFLD in children, only exercise and dietary intervention (40). Therefore, we concluded from the results of this meta-analysis that the first step in the treatment of NAFLD in children is to prevent obesity and stimulate lifestyle changes through physical activity and a healthier diet. Another study (41) found that physical exercise, even without weight loss, seemed to reduce the degree of steatosis. Exercise alone, lifestyle changes through a healthier diet, gradual weight loss, and increased physical activity appear to be the only effective treatments for the disease at present.

However, there are certain limitations in this study. In including Chinese research literature, this study only searched against the China National Knowledge Infrastructure (CNKI) database and did not extend the scope to other databases, such as Wanfang medical database, which may result in the retrieved Chinese studies not being comprehensive. Moreover, the heterogeneity of the studies included in this study is high. This may be related to the following factors: (I) the underlying disease characteristics of the population included in the study are different, which may have an impact on the accuracy of the research results. (II) the diagnostic criteria for nonalcoholic fatty liver disease may vary among the studies included. (III) differences in the proportion of male and female subjects included in these studies may also lead to biased results. (IV) the included literature comes from different countries, and the sample may vary.

Conclusions

In summary, this study found that various physical indicators related to obesity have certain predictive effects for children with NAFLD: BMI, WC, triglyceride content, LDL, fasting blood glucose, and insulin resistance index (HOMA-IR) were all significantly correlated with children with NAFLD. In addition, exercise could significantly improve the degree of steatosis in children with NAFLD. Therefore, in the clinical work of pediatrics, the above indicators could be monitored for early prevention, prediction, and diagnosis of NAFLD in children. In addition, effective treatment of NAFLD in children through exercise therapy could be conducted in a timely manner.

Acknowledgments

Funding: This work was supported by the National Natural Science Foundation of China (No. 81300346).

Footnote

Reporting Checklist: The authors have completed the MOOSE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-23-123/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-23-123/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-23-123/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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References

1. Reinehr T, Wabitsch M. Childhood obesity. Curr Opin Lipidol 2011;22:21-5. [Crossref] [PubMed]
2. Nagpal N, Messito MJ, Katzow M, et al. Obesity in Children. Pediatr Rev 2022;43:601-17. [Crossref] [PubMed]
3. Luca AC, Curpan AS, Braha EE, et al. Increasing Trends in Obesity-Related Cardiovascular Risk Factors in Romanian Children and Adolescents-Retrospective Study. Healthcare (Basel) 2022;10:2452. [Crossref] [PubMed]
4. Riazi K, Azhari H, Charette JH, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol 2022;7:851-61. [Crossref] [PubMed]
5. Younossi Z, Tacke F, Arrese M, et al. Global Perspectives on Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis. Hepatology 2019;69:2672-82. [Crossref] [PubMed]
6. Draijer L, Benninga M, Koot B. Pediatric NAFLD: an overview and recent developments in diagnostics and treatment. Expert Rev Gastroenterol Hepatol 2019;13:447-61. [Crossref] [PubMed]
7. de Caprariis PJ, DiMaio A. NAFLD in Children and Adolescents. Am Fam Physician 2021;103:452-3. [PubMed]
8. Zhang X, Wu M, Liu Z, et al. Increasing prevalence of NAFLD/NASH among children, adolescents and young adults from 1990 to 2017: a population-based observational study. BMJ Open 2021;11:e042843. [Crossref] [PubMed]
9. Nobili V, Alisi A, Valenti L, et al. NAFLD in children: new genes, new diagnostic modalities and new drugs. Nat Rev Gastroenterol Hepatol 2019;16:517-30. [Crossref] [PubMed]
10. Neuschwander-Tetri BA. Non-alcoholic fatty liver disease. BMC Med 2017;15:45. [Crossref] [PubMed]
11. Shaunak M, Byrne CD, Davis N, et al. Non-alcoholic fatty liver disease and childhood obesity. Arch Dis Child 2021;106:3-8. [Crossref] [PubMed]
12. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 2010;25:603-5. [Crossref] [PubMed]
13. Nier A, Brandt A, Conzelmann IB, et al. Non-Alcoholic Fatty Liver Disease in Overweight Children: Role of Fructose Intake and Dietary Pattern. Nutrients 2018;10:1329. [Crossref] [PubMed]
14. Verduci E, Pozzato C, Banderali G, et al. Changes of liver fat content and transaminases in obese children after 12-mo nutritional intervention. World J Hepatol 2013;5:505-12. [Crossref] [PubMed]
15. Grønbæk H, Lange A, Birkebæk NH, et al. Effect of a 10-week weight loss camp on fatty liver disease and insulin sensitivity in obese Danish children. J Pediatr Gastroenterol Nutr 2012;54:223-8. [Crossref] [PubMed]
16. Antunes Bde M, Monteiro PA, Silveira LS, et al. Effect of concurrent training on risk factors and hepatic steatosis in obese adolescents. Rev Paul Pediatr 2013;31:371-6. [Crossref] [PubMed]
17. Thompson MD, Cismowski MJ, Serpico M, et al. Elevation of circulating microRNA levels in obese children compared to healthy controls. Clin Obes 2017;7:216-21. [Crossref] [PubMed]
18. Małecki P, Figlerowicz M, Kemnitz P, et al. Estimation of the risk of fibrosis in children with nonalcoholic fatty liver disease. Clin Exp Hepatol 2020;6:220-7. [Crossref] [PubMed]
19. Battal F, Türkön H, Aylanç N, et al. Investigation of Blood Betatrophin Levels in Obese Children with Non-Alcoholic Fatty Liver Disease. Pediatr Gastroenterol Hepatol Nutr 2018;21:111-7. [Crossref] [PubMed]
20. Koot BG, van der Baan-Slootweg OH, Tamminga-Smeulders CL, et al. Lifestyle intervention for non-alcoholic fatty liver disease: prospective cohort study of its efficacy and factors related to improvement. Arch Dis Child 2011;96:669-74. [Crossref] [PubMed]
21. Hattar LN, Wilson TA, Tabotabo LA, et al. Physical activity and nutrition attitudes in obese Hispanic children with non-alcoholic steatohepatitis. World J Gastroenterol 2011;17:4396-403. [Crossref] [PubMed]
22. Gupta N, Jindal G, Nadda A, et al. Prevalence and risk factors for nonalcoholic fatty liver disease in obese children in rural Punjab, India. J Family Community Med 2020;27:103-8. [Crossref] [PubMed]
23. Kurku H, Atar M, Pirgon Ö, et al. Pubertal Status and Gonadal Functions in Obese Boys with Fatty Liver. Metab Syndr Relat Disord 2019;17:102-7. [Crossref] [PubMed]
24. Kwon Y, Jeong SJ. Relative Skeletal Muscle Mass Is an Important Factor in Non-Alcoholic Fatty Liver Disease in Non-Obese Children and Adolescents. J Clin Med 2020;9:3355. [Crossref] [PubMed]
25. Hu W, Wang M, Yin C, et al. Serum complement factor 5a levels are associated with nonalcoholic fatty liver disease in obese children. Acta Paediatr 2018;107:322-7. [Crossref] [PubMed]
26. Elkabany ZA, Hamza RT, Ismail EAR, et al. Serum visfatin level as a noninvasive marker for nonalcoholic fatty liver disease in children and adolescents with obesity: relation to transient elastography with controlled attenuation parameter. Eur J Gastroenterol Hepatol 2020;32:1008-16. [Crossref] [PubMed]
27. Liu F. Risk factors analysis of nonalcoholic fatty liver disease in obese children [D]. Anhui Medical University, 2022. DOI: 10.26921/d.cnki.ganyu.2022.00122710.26921/d.cnki.ganyu.2022.001227
28. Wang Y, Lim H. The global childhood obesity epidemic and the association between socio-economic status and childhood obesity. Int Rev Psychiatry 2012;24:176-88. [Crossref] [PubMed]
29. Sigmund E, Sigmundová D. The Relationship between Obesity and Physical Activity of Children in the Spotlight of Their Parents' Excessive Body Weight. Int J Environ Res Public Health 2020;17:8737. [Crossref] [PubMed]
30. Younossi Z, Anstee QM, Marietti M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol 2018;15:11-20. [Crossref] [PubMed]
31. Eslam M, Alkhouri N, Vajro P, et al. Defining paediatric metabolic (dysfunction)-associated fatty liver disease: an international expert consensus statement. Lancet Gastroenterol Hepatol 2021;6:864-73. [Crossref] [PubMed]
32. Assunção SNF, Sorte NCB, Alves CD, et al. Nonalcoholic fatty liver disease (NAFLD) pathophysiology in obese children and adolescents: update. Nutr Hosp 2017;34:727-30. [Crossref] [PubMed]
33. Wang J, Fan R. The dose-response relationship between BMII and the risk of fatty liver disease: based on restricted cubic samples[C]//The Health Management Branch of Zhejiang Medical Association. Proceedings of the 2018 Annual Conference of the Health Management Branch of Zhejiang Medical Association [Publisher unknown], 2018:2. DOI: 10.26914/c.cnkihy.2018.028090
34. Ipsen DH, Lykkesfeldt J, Tveden-Nyborg P. Molecular mechanisms of hepatic lipid accumulation in non-alcoholic fatty liver disease. Cell Mol Life Sci 2018;75:3313-27. [Crossref] [PubMed]
35. Mori H, Svegliati Baroni G, Marzioni M, et al. Farnesoid X Receptor, Bile Acid Metabolism, and Gut Microbiota. Metabolites 2022;12:647. [Crossref] [PubMed]
36. Wang Q, Zhu M, Li H, et al. Hyperferritinemia Correlates to Metabolic Dysregulation and Steatosis in Chinese Biopsy-Proven Nonalcoholic Fatty Liver Disease Patients. Diabetes Metab Syndr Obes 2022;15:1543-52. [Crossref] [PubMed]
37. Weiss TS, Lupke M, Ibrahim S, et al. Attenuated lipotoxicity and apoptosis is linked to exogenous and endogenous augmenter of liver regeneration by different pathways. PLoS One 2017;12:e0184282. [Crossref] [PubMed]
38. He J, Zhou A, Luo L, et al. Correlation analysis of fatty liver with blood sugar, blood lipid and liver function in a random population of physical examination [C]//Proceedings of the 30th anniversary of the founding of the Chinese Society of Ultrasound Medical Engineering and the 12th National Conference of Ultrasound Medicine [Publisher unknown], 2014:1.
39. Sanyal AJ, Van Natta ML, Clark J, et al. Prospective Study of Outcomes in Adults with Nonalcoholic Fatty Liver Disease. N Engl J Med 2021;385:1559-69. [Crossref] [PubMed]
40. Semmler G, Datz C, Reiberger T, et al. Diet and exercise in NAFLD/NASH: Beyond the obvious. Liver Int 2021;41:2249-68. [Crossref] [PubMed]
41. Romero-Gómez M, Zelber-Sagi S, Trenell M. Treatment of NAFLD with diet, physical activity and exercise. J Hepatol 2017;67:829-46. [Crossref] [PubMed]

(English Language Editor: A. Muijlwijk)