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Published in final edited form as: Hepatology. 2025 Apr 22;83(3):561–574. doi: 10.1097/HEP.0000000000001357 Search in PMC Search in PubMed View in NLM Catalog Add to search Long-Term Mortality and Extrahepatic Outcomes in 1,096 Children with MASLD: A Retrospective Cohort Study Jeffrey B Schwimmer Jeffrey B Schwimmer , MD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California Find articles by Jeffrey B Schwimmer a, b , Nhat Quang N Thai Nhat Quang N Thai , MPH c University of California San Diego Herbert Wertheim School of Public Health and Human Longevity Science, La Jolla, California d San Diego State University of Public Health, San Diego, California Find articles by Nhat Quang N Thai c, d , Sheila L Noon Sheila L Noon , BA a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California e University of California San Diego School of Medicine, La Jolla, California Find articles by Sheila L Noon a, e , Patricia Ugalde-Nicalo Patricia Ugalde-Nicalo , MD, MAS a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California Find articles by Patricia Ugalde-Nicalo a , Sabina R Anderson Sabina R Anderson , BA a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California f Amherst College, Amherst, Massachusetts g Department of Medicine, Yale University, New Haven, CT Find articles by Sabina R Anderson a, f, g , Lauren F Chun Lauren F Chun , MD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California h Department of Pediatrics, Rady Children’s Hospital, San Diego, California Find articles by Lauren F Chun a, h , Rhys S David Rhys S David , NP b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California Find articles by Rhys S David b , Nidhi P Goyal Nidhi P Goyal , MD, MPH a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California Find articles by Nidhi P Goyal a, b , Kimberly P Newton Kimberly P Newton , MD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California Find articles by Kimberly P Newton a, b , Eleanor G Hansen Eleanor G Hansen , BA a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California I Loma Linda University School of Medicine, Loma Linda, California Find articles by Eleanor G Hansen a, i , Bonnie Lin Bonnie Lin , BA a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California Find articles by Bonnie Lin a , Warren L Shapiro Warren L Shapiro , MD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California j Department of Pediatrics, Southern California Permanente Medical Group, San Diego, California Find articles by Warren L Shapiro a, b, j , Andrew Wang Andrew Wang , DO a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California k Department of Pediatrics, Dell Children’s Medical Center, Austin, Texas Find articles by Andrew Wang a, k , Elizabeth L Yu Elizabeth L Yu , MD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California Find articles by Elizabeth L Yu a, b , Cynthia A Behling Cynthia A Behling , MD, PhD a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California Find articles by Cynthia A Behling a Author information Article notes Copyright and License information a Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, California b Department of Gastroenterology, Rady Children’s Hospital, San Diego, California c University of California San Diego Herbert Wertheim School of Public Health and Human Longevity Science, La Jolla, California d San Diego State University of Public Health, San Diego, California e University of California San Diego School of Medicine, La Jolla, California f Amherst College, Amherst, Massachusetts g Department of Medicine, Yale University, New Haven, CT h Department of Pediatrics, Rady Children’s Hospital, San Diego, California I Loma Linda University School of Medicine, Loma Linda, California j Department of Pediatrics, Southern California Permanente Medical Group, San Diego, California k Department of Pediatrics, Dell Children’s Medical Center, Austin, Texas Author Contributions: Dr. Jeffrey Schwimmer, Nhat Quang Thai, Sheila Noon, Paty Ugalde-Nicalo, Bonnie Lin, and Dr. Cynthia Behling made substantial contributions to conception and design. All authors made substantial contributions to the acquisition of data. Dr. Jeffrey Schwimmer, Nhat Quang Thai, and Bonnie Lin made substantial contributions to analysis and interpretation of data. All authors drafted the article and revised it critically for important intellectual content. All authors had final approval of the version to be published. ✉ Address for correspondence Jeffrey B. Schwimmer, M.D., Department of Pediatrics, UC San Diego and Rady Children’s Hospital San Diego, 3020 Children’s Way, MC 5030 San Diego, CA 92123, [email protected] , fax: 858-560-6798. Issue date 2026 Mar 1. PMC Copyright notice PMCID: PMC12353144 NIHMSID: NIHMS2075192 PMID: 40262118 The publisher's version of this article is available at Hepatology Abstract Background & Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease in children, but its long-term outcomes are poorly understood. This study aimed to quantify mortality rates, identify causes of death, and evaluate the incidence of cirrhosis and extrahepatic outcomes in children with pediatric-onset MASLD. Approach & Results: The Longitudinal InVestigation Evaluating Results of Steatosis (LIVERS) study is a single-center, retrospective cohort study conducted at Rady Children’s Hospital San Diego. We included 1,096 children aged 2–18 years who were diagnosed with MASLD between 2000 and 2017 and followed for a mean of 8.5 years. Mortality was ascertained via the National Death Index, and comorbidities were assessed through follow-up research visits and medical records. Overall, 3.4% of children died, yielding a mortality rate of 398 per 100,000 person-years; nearly half of these deaths were liver-related. Male sex and lower high-density lipoprotein levels independently predicted increased mortality risk. The cumulative incidence of cirrhosis was 4.7%. High incidence rates of extrahepatic comorbidities were observed, including dyslipidemia (3,664 per 100,000 person-years), hypertension (1,901), obstructive sleep apnea (1,185), and type 2 diabetes (911). Conclusions: Pediatric MASLD is associated with significant premature mortality and a substantial burden of hepatic and extrahepatic comorbidities. These findings highlight the need for timely screening, early intervention, and long-term management strategies to improve outcomes for children with MASLD. Keywords: epidemiology, steatohepatitis, cirrhosis, type 2 diabetes, hypertension, dyslipidemia, obstructive sleep apnea Graphical Abstract INTRODUCTION Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease (NAFLD), is characterized by the accumulation of lipid droplets within hepatocytes. 1 MASLD is now recognized as the most common chronic liver disease in children, affecting nearly 10% of the general pediatric population and up to 25% of children with obesity. 2 , 3 In 2007, the American Academy of Pediatrics recommended targeted screening for NAFLD in children aged 9 years and older with obesity. 4 This recommendation coincided with the period during which our study cohort was identified (2000–2017), during which there was a rapid increase in the incidence of pediatric NAFLD. 5 The persistent and growing burden of the disease makes it important to understand its long-term outcomes. The transition from NAFLD to MASLD nomenclature acknowledges the systemic metabolic impact of hepatic steatosis and its strong association with cardiometabolic risk factors. 6 Notably, the updated diagnostic criteria for MASLD include the presence of hepatic steatosis, along with one or more cardiometabolic conditions such as obesity, type 2 diabetes, dyslipidemia, or hypertension. 6 Recent guidelines from the American Association for the Study of Liver Diseases (AASLD), emphasize the impact of this reclassification on clinical management and research. MASLD has become the fastest-growing indication for liver transplantation in adults, highlighting its clinical importance. 7 Addressing MASLD as a public health issue requires enhanced screening, targeted prevention, and effective management to mitigate long-term consequences in children. Given the rising incidence and potential severity, pediatric-onset MASLD is a major public health problem, requiring dedicated research to understand its natural history and outcomes. While studies in adults have demonstrated a significant increase in mortality among individuals with MASLD, evidence regarding the long-term risk of mortality in pediatric patients remains limited. 8 , 9 Preliminary data suggest that children with MASLD may face a heightened risk of premature death, but previous studies have been restricted by small sample sizes or have combined adult and pediatric data, thereby limiting the generalizability of the findings. 10 , 11 Consequently, the true magnitude of mortality risk associated with pediatric-onset MASLD remains unclear. Pediatric MASLD is also associated with significant hepatic and extrahepatic comorbidities that may adversely affect long-term clinical outcomes. Progression to cirrhosis is a major hepatic complication, yet data on cirrhosis in children with MASLD are largely confined to case reports. 12 , 13 On the other hand, a growing body of evidence indicates a significant burden of extrahepatic comorbidities in this population. Cross-sectional studies have demonstrated an elevated risk for type 2 diabetes, hypertension, dyslipidemia, and obstructive sleep apnea in children with MASLD. 14 – 17 Recent findings show a cumulative incidence of 3% per year for type 2 diabetes in children with MASLD over a four-year follow-up, although the incidence of other comorbidities in this population remains largely unexplored. 18 The L ongitudinal I n V estigation E valuating R esults of S teatosis ( LIVERS ) study followed a large cohort over an extended period, tracking patients from childhood into early adulthood. The primary objectives of the study were to quantify the mortality rate and identify the causes of death in individuals with pediatric-onset MASLD. Secondary aims were to evaluate the incidence of cirrhosis and the development of extrahepatic outcomes including type 2 diabetes, hypertension, dyslipidemia, and obstructive sleep apnea. METHODS Study Design and Setting The LIVERS study is a single-center, retrospective cohort study conducted at Rady Children’s Hospital San Diego (RCHSD). The cohort includes children aged 2 to 18 years who were initially diagnosed with steatotic liver disease, such as nonalcoholic fatty liver disease or nonalcoholic steatohepatitis, between January 1, 2000, and December 31, 2017. The updated diagnostic criteria for MASLD were retrospectively applied to this cohort to identify eligible participants. Ethical approval for this study was provided by the Institutional Review Boards (IRBs) of RCHSD and the University of California San Diego (UCSD) (IRB# 050377, approved April 6, 2006, and IRB# 180538, approved May 2, 2018)). Additional approval for the electronic medical records (EMR) search using EPIC’s Clarity platform (Epic Systems Corporation, Verona, WI) was granted under IRB# 190223 on February 22, 2019. The prospective follow-up portion of the study was approved under IRB# 190819 on August 28, 2019. All research was conducted in accordance with the Declarations of Helsinki and Istanbul, and written informed consent or assent was obtained as applicable. For the initial cohort assembly, data were obtained from two sources: a clinical research registry and a comprehensive search of EMRs. For patients identified through the clinical research registry, written informed assent was obtained from minors, and written informed consent was provided by their parents or legal guardians. For the EMR search, the IRBs granted a waiver of informed consent due to the retrospective nature of the data collection and minimal risk to participants. After mortality outcomes were determined, surviving participants were invited for additional follow-up between 2019 and 2022 to assess current health status and the development of comorbid conditions since the initial MASLD diagnosis. For these prospective visits, written informed consent was obtained from participants who had reached the age of majority. For participants who were minors at the time of follow-up, assent was obtained from the child, and written informed consent was provided by a parent or legal guardian. Patient Cohort The cohort was compiled from the clinical research registry and supplemented by the EMR search using International Classification of Diseases codes for NAFLD and nonalcoholic steatohepatitis (NASH) (571.8, K76.0, K75.81), which were appropriate for capturing diagnoses of steatotic liver disease during the study period before reclassification to MASLD. MASLD diagnoses were confirmed after careful review, with rigorous exclusion of other liver disease etiologies, including viral hepatitis, autoimmune liver diseases, and genetic or metabolic liver disorders. Systemic disorders such as cancer, lupus, short bowel syndrome, and inflammatory bowel disease were also excluded. Diagnostic Criteria for MASLD To qualify for a diagnosis of MASLD, patients were required to have histologically confirmed hepatic steatosis, defined as the accumulation of macrovesicular fat in ≥5% of hepatocytes. 19 Other causes of liver disease, including significant alcohol consumption, were excluded. Patients also needed to present at least one cardiometabolic risk factor: body mass index (BMI) ≥85 th percentile for age and sex, fasting serum glucose ≥100 mg/dL, hemoglobin A1c ≥5.7% or a diagnosis of type 2 diabetes, or blood pressure ≥95 th percentile for age or ≥130/80 mmHg if ≥13 years of age. 6 Histological Confirmation The diagnosis of MASLD was confirmed by liver histology, graded and staged according to the NASH Clinical Research Network criteria. 20 Board-certified pediatric pathologists performed the histological assessments, which were independently reviewed by board-certified pediatric gastroenterologists who interpreted the findings alongside the totality of clinical data to make the final determination of the diagnosis. At our institution, the decision to perform a liver biopsy is made on a case-by-case basis by the attending pediatric gastroenterologist after a comprehensive evaluation including clinical history, physical examination, laboratory workup, and imaging studies. This approach ensures that biopsy is offered when persistent abnormalities raise concern for chronic liver disease rather than based solely on a single abnormal enzyme level. Data Collection Data were extracted in duplicate by research assistants trained in the study protocol. The supervising research manager reviewed their chart extraction for accuracy. Two research assistants independently reviewed each chart, with a third assistant involved if discrepancies arose. If uncertainty remained, a pediatric gastroenterologist conducted the final review. Data extracted included all available information from medical records on demographics, clinical encounters, laboratory results, and liver biopsy findings up through 2021. Mortality was determined through the National Death Index from study initiation to December 31, 2018. Causes of death were confirmed using medical records and informational death certificates, which are publicly accessible in California and provide non-authorized but certified information. Additional Follow-Up Surviving participants were invited for follow-up research visits between 2019 and 2022. These visits aimed to assess participants’ current health status, the development of comorbid conditions, and major health events occurring since the initial MASLD diagnosis. Follow-up data were collected during a one-time standardized research visit for each surviving participant. Assessments included demographics, medications, diagnosis, interval health history, anthropometrics (e.g., age, weight, height, BMI, blood pressure), liver function tests (e.g., ALT, AST, GGT, bilirubin), endocrine measures (e.g., glucose, HbA1c), hematology (e.g., hemoglobin, hematocrit, platelets), and lipid panel (e.g., total cholesterol, triglycerides, HDL, LDL). Study Outcomes The primary outcomes were all-cause mortality and liver-related mortality, including deaths due to cirrhosis, hepatic encephalopathy, portal hypertension, hepatorenal syndrome, variceal hemorrhage, hepatocellular carcinoma, or liver failure. Secondary outcomes included progression to cirrhosis, confirmed via liver histology or clinical features of portal hypertension, as well as the development of extrahepatic comorbidities, including type 2 diabetes, hypertension, dyslipidemia, and obstructive sleep apnea. Extrahepatic comorbidities were defined based on new interval diagnoses reported by the participant and confirmed through medical record review and/or numerical criteria defined as follows. Type 2 Diabetes: Evaluated using criteria provided by the American Diabetes Association (ADA) and American Academy of Pediatrics (AAP). 21 , 22 Defined by any one of the following: hemoglobin A1c (HbA1c) ≥6.5%, fasting plasma glucose ≥126 mg/dL or two-hour plasma glucose ≥200 mg/dL during an oral glucose tolerance test (OGTT). Hypertension: Defined according to clinical practice guidelines endorsed by the American College of Cardiology (ACC)/American Heart Association (AHA) and AAP. 23 , 24 Hypertension was defined as blood pressure ≥95 th percentile for patients aged <13 years or ≥130/80 mmHg for patients aged ≥13 years. Dyslipidemia: Defined by guidelines from the National Heart, Lung, and Blood Institute (NHLBI) and AAP. 25 Dyslipidemia was defined as LDL cholesterol ≥130 mg/dL, triglycerides ≥100 mg/dL for patients 0–9 years, triglycerides ≥130 mg/dL for patients aged 10–17, or triglycerides ≥150 mg/dL for patients aged ≥18 years. Obstructive Sleep Apnea (OSA): Defined based on the clinical diagnosis of an evaluating pulmonologist. The apnea-hypopnea index (AHI) was the primary measure, as recommended by the American Academy of Sleep Medicine (AASM) and AAP. 26 , 27 OSA was defined as AHI ≥1 event per hour of sleep for patients ≤12 years, or AHI ≥5 events per hour of sleep for patients ≥13 years. Statistical Analysis Descriptive statistics were used to summarize baseline demographic and clinical characteristics. Continuous variables were expressed as means and standard deviations, while categorical variables were reported as frequencies and proportions. Differences between groups (e.g., survivors vs. non-survivors) were assessed using t-tests for continuous variables and chi-squared tests for categorical variables. Mortality rates were calculated as the total number of deaths per person-years at risk. Standardized mortality ratios (SMRs) were derived by adjusting for age and sex using population-based mortality estimates from the 2018 U.S. Census and California mortality data. 28 , 29 The baseline prevalence of each condition was calculated as the proportion of individuals with the condition at baseline, divided by the total study population. Participants were censored at their last known contact if they did not attend the prospective visit. Cumulative incidence was determined by dividing the number of individuals who developed each outcome by the total number of those at risk. Incidence rates were calculated by dividing the number of new cases of each outcome by the total person-years at risk. To evaluate associations between baseline characteristics and mortality, we used Cox proportional hazards regression models, reporting results as hazard ratios (HRs) and 95% confidence intervals (CI). Stepwise selection was used to build the multivariate models, with entry and exit criteria of p=0.99 and p=0.95, respectively. The Akaike Information Criterion (AIC) was used to select the optimal model. The proportional hazards assumption was tested using Schoenfeld residuals. To address missing data, multiple imputations were performed using 100 iterations, with the imputed datasets combined using the MIANALYZE procedure in SAS version 9.4 (SAS Institute, Cary, NC). Results from the imputed analysis were consistent with those from the complete case analysis, so only the complete case findings are presented here. RESULTS Study Cohort A total of 1,373 children with steatotic liver disease (SLD) were initially identified for inclusion. Following detailed evaluation, exclusions were made for the following reasons: 152 children had systemic diseases (e.g., cancer, inflammatory bowel disease, systemic lupus erythematosus), 60 children were taking hepatotoxic medications, 12 were taking dietary supplements associated with hepatotoxicity, 10 had documented excessive alcohol use, and 14 had viral hepatitis. Of the remaining 1,125 children, 29 did not meet the criteria for a cardiometabolic risk factor. Ultimately, 1,096 children with MASLD were included in the analysis after applying inclusion and exclusion criteria ( Figure 1 ). Figure 1. Selection Criteria for the LIVERS Study. Open in a new tab This figure outlines the selection process for enrolling patients in the LIVERS study. A total of 1,373 children with steatotic liver disease (SLD) were initially identified via a clinical research registry and an EMR-based search. After chart review, 248 were excluded for alternative causes of steatosis (152 with systemic diseases, 60 taking hepatotoxic medications, 14 with viral hepatitis, 12 using hepatotoxic dietary supplements, and 10 with excessive alcohol consumption). Of the remaining 1,125 children, 29 did not meet the cardiometabolic risk factor requirement for a diagnosis of metabolic dysfunction–associated steatotic liver disease (MASLD; see Methods for details). This resulted in a final cohort of 1,096 children with MASLD. Mortality was assessed through the National Death Index, identifying 37 decedents and 1,059 survivors over the study period. The cohort was predominantly male (67.2%, n = 738), with a mean age at diagnosis of 12.9 ± 2.9 years. Hispanic children constituted most of the cohort (80.7%), followed by non-Hispanic White (9.4%) and non-Hispanic Other (10.0%). At the time of MASLD diagnosis, the mean weight was 81.7 ± 25.8 kg, mean BMI was 31.9 ± 6.4 kg/m 2 , with a mean BMI z-score of 2.2 ± 0.5. Liver histology showed that most children had high-grade steatosis, with 55.1% exhibiting grade 3 steatosis. In addition, fibrosis was common, with 58.7% of the children having stage 1 or greater fibrosis. Detailed baseline demographic and clinical characteristics are shown in Table 1 . The mean follow-up duration was 8.5 ± 4.5 years, contributing to a cumulative 9,297 person-years of follow-up. Table 1. Baseline Characteristics of Children with MASLD by Survivorship Characteristics Total (N = 1096) Survivors (N = 1059) Decedents (N = 37) P Value a Demographics Age, mean (SD), years 12.9 (2.9) 12.9 (3.0) 14.0 (2.4) 0.027 Sex, No. (%) <.001 Male 738 (67.2) 703 (66.3) 35 (94.6) Female 360 (32.8) 358 (33.7) 2 (5.4) Ethnicity, No. (%) 0.672 Hispanic 867 (80.7) 837 (80.5) 30 (85.7) Non-Hispanic White 122 (9.4) 117 (9.4) 5 (8.6) Non-Hispanic Other 107 (10.0) 105 (10.1) 2 (5.7) Anthropometrics, mean (SD) Weight, kg 81.7 (25.8) 81.2 (25.6) 94.8 (29.9) 0.008 Height, cm 158.0 (14.3) 157.8 (14.3) 165.0 (13.3) 0.007 BMI, kg/m 2 31.9 (6.43) 31.9 (6.44) 33.9 (6.04) 0.027 BMI z score 2.2 (0.48) 2.2 (0.48) 2.4 (0.44) 0.023 Blood Pressure, No. (%) Systolic 124 (14) 124 (14) 128 (14) 0.082 Diastolic 68 (9) 68 (9) 69 (10) 0.205 Liver, mean (SD) ALT, U/L 104 (96) 104 (95) 117 (974) 0.242 AST, U/L 67 (80) 68 (81) 65 (36) 0.641 GGT, U/L 47 (46) 47 (46) 50 (34) 0.150 Bilirubin (total), mg/dL 0.6 (0.7) 0.6 (0.7) 0.5 (0.2) 0.910 Bilirubin (direct), mg/dL 0.1 (0.4) 0.1 (0.5) 0.1 (0.1) 0.218 Alkaline Phosphatase, mean (SD), U/L 226 (103) 226 (102) 222 (105) 0.965 Total Protein, mean (SD), g/dL 7.8 (0.6) 7.8 (0.6) 7.7 (0.5) 0.170 Albumin, g/dL 4.6 (0.3) 4.6 (0.3) 4.4 (0.3) 0.004 Endocrine, mean (SD) Glucose, mg/dL 95 (27) 95 (27) 97 (24) 0.880 Insulin, μIU/mL 30 (23) 29 (23) 40 (33) 0.003 HbgA1c 5.7 (1.1) 5.7 (1.2) 5.6 (0.6) 0.094 Hematology, mean (SD) Hemoglobin, g/dL 13.8 (1.18) 13.8 (1.2) 14.3 (1.2) 0.004 Hematocrit 40.8 (3.36) 40.7 (3.4) 41.9 (3.4) 0.041 White blood cell 8.4 (2.60) 8.4 (2.6) 9.2 (2.8) 0.081 Platelets 292 (69) 292 (70) 285 (56) 0.476 Prothrombin time 12.5 (1.3) 12.5 (1.3) 12.3 (1.1) 0.199 INR 1.1 (0.1) 1.1 (0.1) 1.0 (0.1) 0.305 Lipids, mean (SD) Total cholesterol, mg/dL 171 (38) 170.9 (38) 173 (33) 0.685 Triglycerides, mg/dL 168 (122) 167 (123) 184 (91) 0.088 HDL, mg/dL 39.9 (9.9) 40.1 (9.97) 35.7 (7.5) 0.006 LDL, mg/dL 100 (31) 100 (31) 109 (37) 0.159 Liver Histology Steatosis Grade, No. (%) 0.541 1 (5–33%) 175 (16.0) 166 (15.7) 9 (24.3) 2 (34–66%) 316 (28.8) 307 (29.0) 9 (24.3) 3 (>66%) 605 (55.2) 586 (55.5) 19 (51.4) Lobular Inflammation, No. (%) 0 (0) 70 (6.4) 67 (6.3) 3 (7.7) 0.593 1 (<2/20x mag) 812 (74.1) 783 (73.9) 29 (78.4) 2 (2–4/20x mag) 199 (18.2) 195 (18.4) 4 (10.3) 3 (>4/20x mag) 15 (1.3) 14 (1.3) 1 (2.7) Portal inflammation, No. (%) 0 (None to minimal) 285 (26.0) 274 (25.8) 11 (29.7) 0.742 1 (Mild) 689 (62.8) 668 (63.0) 21 (56.8) 2 (More than mild) 124 (11.3) 119 (11.2) 5 (13.5) Ballooning degeneration, No. (%) 0 (None) 745 (67.9%) 717 (67.6%) 25 (67.6) 0.334 1 (Few) 314 (28.6%) 306 (28.8%) 9 (24.3) 2 (Many) 39 (3.6%) 38 (3.6%) 3 (8.1) MASH category MASLD, but not MASH 499 (45.5) 485 (45.7) 14 (37.8) 0.79 Borderline MASH 1a 114 (10.4) 109 (10.3) 5 (13.5) Borderline MASH 1c 248 (22.6) 239 (22.5) 9 (24.3) Definite MASH 235 (21.4) 226 (21.3) 9 (24.3) Fibrosis Stage, No. (%) 0.064 0 (None) 453 (41.3) 443 (41.8) 10 (27.0) 1a (Zone 3) 57 (5.2) 57 (5.4) 0 (0.0) 1b (Zone 3) 4 (0.4) 3 (0.3) 1 (2.7) 1c (Portal/Periportal) 274 (25.0) 261 (24.6) 13 (35.1) 2 (Zone 3 and Periportal) 156 (14.2) 151 (14.2) 5 (13.5) 3 (Bridging) 136 (12.4) 130 (12.3) 6 (16.2) 4 (Cirrhosis) 16 (1.5) 14 (1.3) 2 (5.4) Open in a new tab Abbreviations: ALT (Alanine Aminotransferase); AST (Aspartate Aminotransferase); BMI (Body mass index); GGT (Gamma-glutamyl Transferase); HDL (High Density Lipoprotein); LDL (Low Density Lipoprotein); NASH (Nonalcoholic Steatohepatitis); SD (Standard deviation) a Chi-square test for categorical variables and t-test for continuous variables. Mortality Over the study period, 3.4% (37/1,096) of children with MASLD died, corresponding to a mortality rate of 398 per 100,000 person-years (95% CI, 284–543) ( Figure 2 ). The SMR, adjusted for age and sex, was 40.2 (95% CI, 28.7–54.9) relative to the U.S. general population, and 53.9 (95% CI, 48.5–73.5) relative to the California general population. Baseline demographic and clinical characteristics of the children who died are shown in Table 1 . Figure 2. Kaplan Meier Survival Curve for Children with MASLD. Open in a new tab This figure shows the estimated all-cause mortality among 1,096 children diagnosed with metabolic dysfunction–associated steatotic liver disease (MASLD), followed for up to 15 years after diagnosis (t=0). The y-axis indicates survival probability (%), and the shaded region represents the 95% confidence interval around the Kaplan–Meier estimate. Patients were censored at their last known follow-up or at 15 years, whichever occurred first. The table below the x-axis displays the number of patients at risk at each time point, excluding those who died or were lost to follow-up. Children who died during the study had significantly higher BMI (33.9 vs. 31.9 kg/m 2 , p=0.027), higher BMI z-scores (2.4 vs. 2.2, p=0.023), and higher mean weight (94.8 vs. 81.2 kg, p=0.008) at diagnosis compared to survivors. Albumin levels were also lower in decedents (4.4 vs. 4.6 g/dL, p=0.004), while insulin levels were higher (40.1 vs. 28.8 μIU/mL, p=0.003). Additionally, decedents had significantly lower HDL cholesterol levels at diagnosis compared to survivors (35.7 vs. 40.1 mg/dL, p=0.006). In the multivariate analysis, several baseline characteristics were evaluated for their association with mortality ( Table 2 ). Male sex was independently associated with higher mortality risk (aHR: 7.41, 95% CI: 1.63–33.56), a finding consistent with the univariate analysis. Higher HDL levels were significantly associated with lower mortality (aHR: 0.95, 95% CI: 0.90–0.99). Although fibrosis stage was not independently significant in the multivariate analysis (aHR: 1.50, 95% CI: 0.68–3.33, p=0.32), it was included in the final model due to its contribution to optimizing the AIC in the stepwise selection process. Other factors, such as BMI z-score, hemoglobin, and hematocrit, were significant in the univariate analysis but did not remain significant in the multivariate model. Table 2. Association of Baseline Characteristics with Mortality in Children with MASLD Disease Univariate Analysis Multivariate Analysis Characteristics HR (95% CI) P-value HR (95% CI) P-value Age at diagnosis 1.17 (1.03–1.32) 0.01 1.14 (0.97–1.35) 0.11 Sex <0.01 0.01 Male 8.69 (2.09–36.12) 7.41 (1.63–33.56) Female Reference Reference Race/Ethnicity 0.58 Non-Hispanic White 0.75 (0.23–2.47) Non-Hispanic Other 0.49 (0.12–2.06) Hispanic Reference Weight 1.02 (1.01–1.03) <0.01 Height 1.05 (1.02–1.08) <0.01 BMI z score 1.95 (1.05–3.63) 0.03 1.37 (0.62–3.00) 0.44 ALT (20 units) 1.04 (0.98–1.09) 0.20 1.06 (0.97–1.15) 0.20 AST (10 units) 1.00 (0.94–1.06) 0.95 GGT (5 units) 1.01 (0.97–1.04) 0.73 Albumin 0.45 (0.19–1.08) 0.07 0.40 (0.15–1.10) 0.08 HbA1c 0.84 (0.60–1.16) 0.29 Hemoglobin 1.50 (1.14–1.98) <0.01 1.10 (0.78–1.55) 0.60 White blood cell count 1.10 (0.99–1.21) 0.07 Platelets (50 units) 0.85 (0.67–1.07) 0.16 Total cholesterol (10 units) 0.99 (0.90–1.07) 0.76 Triglycerides (20 units) 1.01 (0.97–1.05) 0.73 HDL cholesterol (5 units) 0.78 (0.64–0.94) 0.01 0.95 (0.90–0.99) 0.02 LDL cholesterol (10 units) 1.06 (0.96–1.17) 0.22 Fibrosis Stage, No. (%) 0.21 0.32 0 Reference Reference 1–4 1.57 (0.78–3.18) 1.50 (0.68–3.33) Open in a new tab Abbreviations: ALT (Alanine Aminotransferase); AST (Aspartate Aminotransferase; BMI (Body mass index); GGT (Gamma-glutamyl Transferase); HDL (High Density Lipoprotein); LDL (Low Density Lipoprotein), Among the children who died, 46% (17/37) experienced liver-related mortality, with a cause-specific mortality rate of 183 per 100,000 person-years (95% CI, 110–287). Non-liver-related causes of death included cardiovascular disease (16%), trauma (11%), suicide (11%), other causes (11%), and non-hepatic cancer (5%). Follow-up and Comorbidities After the mortality assessment, 503 surviving participants completed additional follow-up research visits between 2019 and 2022 ( Table 3 ). A comparison of baseline characteristics between survivors who returned for research follow-up and those who did not showed that participants in the follow-up group were younger at baseline (12.3 vs. 13.5 years, p < 0.001), while other demographic, clinical, and histologic variables did not differ significantly. The mean age of participants increased from 12.3 years at baseline to 20.1 years at follow-up (p < 0.0001). During this period, significant increases were observed in anthropometric and clinical measures: mean weight increased from 77.1 kg to 96.4 kg (p < 0.0001), and BMI rose from 31.1 to 34.4 kg/m 2 (p < 0.0001). Table 3. Characteristics of Survivors Participating in Prospective Clinical Research Follow-up Characteristics Baseline (N = 503) Follow-up Visit (N=503) P value Demographics Age, mean (SD), years 12.3 (2.98) 20.1 (5.2) <0.001 Sex, No. (%) Not applicable Male 319 (63.4%) Female 184 (36.6%) Race/Ethnicity, No. (%) Not applicable Hispanic 409 (82.8%) Non-Hispanic White 43 (8.7%) Non-Hispanic Other 42 (8.5%) Missing 9 Anthropometrics, mean (SD) Weight, kg 77.1 (25.5) 96.4 (12.1) <0.001 Height, cm 155.4 (15.3) 166.2 (12.1) <0.001 BMI, kg/m 2 31.1 (6.19) 34.4 (7.7) <0.001 BMI z score 2.2 (0.51) Not applicable Blood Pressure, No. (%) Systolic 122 (14) 129 (14) <0.001 Diastolic 67 (9) 70 (9) <0.001 Liver, mean (SD) ALT, U/L 106 (109) 74 (68) <0.001 AST, U/L 69 (102) 49 (49) <0.001 GGT, U/L 46 (50) 39 (35) 0.032 Bilirubin (total), mg/dL 0.6 (1.0) 0.6 (0.3) 0.572 Bilirubin (direct), mg/dL 0.1 (0.6) 0.1 (0.07) 0.396 Alkaline Phosphatase, mean (SD), U/L 230 (94) 142 (89) <0.001 Total Protein, mean (SD), g/dL 7.8 (0.6) 7.7 (0.5) 0.056 Albumin, g/dL 4.6 (0.3) 4.5 (0.4) 0.007 Endocrine, mean (SD) Glucose, mg/dL 94 (26) 101 (40) 0.004 Insulin, μIU/mL 28 (23) 27 (20) 0.758 HbgA1c 5.7 (1.2) 6.0 (1.7) 0.027 Hematology, mean (SD) Hemoglobin, g/dL 13.7 (1.1) 14.1 (1.6) <0.001 Hematocrit 40.5 (3.21) 41.9 (4.3) <0.001 White blood cell 8.3 (2.53) 7.9 (2.1) 0.046 Platelets 289 (67) 271 (63) <0.001 Prothrombin time 12.6 (1.4) 12.1 (1.4) <0.001 INR 1.1 (0.1) 1.0 (0.1) <0.001 Lipids, mean (SD) Total cholesterol, mg/dL 170 (39) 166 (36) 0.223 Triglycerides, mg/dL 160 (89) 154 (97) 0.353 HDL, mg/dL 40 (11) 40 (11) 0.923 LDL, mg/dL 98 (32) 96 (29) 0.437 Open in a new tab Abbreviations: ALT (Alanine Aminotransferase); AST (Aspartate Aminotransferase; BMI (Body mass index); GGT (Gamma-glutamyl Transferase); HDL (High Density Lipoprotein); LDL (Low Density Lipoprotein); SD (Standard deviation) There were significant reductions in liver enzyme levels over time. ALT decreased from 106 U/L to 74 U/L (p < 0.0001), and AST decreased from 69 U/L to 49 U/L (p = 0.0002). GGT levels also decreased significantly from 46 U/L to 39 U/L (p = 0.0316). However, measures of glycemic control deteriorated over time: mean glucose levels rose from 94 mg/dL to 101 mg/dL (p = 0.0036), and HbA1c increased from 5.7 to 6.0 (p = 0.0274). Significant changes were also observed in hematologic parameters, with hemoglobin increasing from 13.7 g/dL to 14.1 g/dL (p < 0.0001) and hematocrit from 40.5% to 41.9% (p < 0.0001). Platelet counts, however, decreased significantly from 289 to 271 (p = 0.0009). Progression to Cirrhosis At baseline, the prevalence of cirrhosis was 0.9%, with a cumulative incidence of 4.7% during follow-up. The incidence rate of cirrhosis in children with MASLD was 567 new cases per 100,000 person-years (95% CI, 427–740) ( Figure 3 ). Figure 3. Incident Extrahepatic Outcomes in Children with MASLD. Open in a new tab This figure illustrates the cumulative incidence of extrahepatic outcomes among 1,096 children diagnosed with MASLD and followed from baseline (t=0). Panels A–D show the percentage of at-risk participants who developed ( A ) type 2 diabetes, ( B ) hypertension, ( C ) dyslipidemia, or ( D ) obstructive sleep apnea, with shaded areas indicating 95% confidence intervals. Children who had the relevant outcome at baseline were excluded from that outcome’s incidence calculation. Panel E provides a Venn diagram depicting the overlap of these four conditions by the end of follow-up, illustrating the comorbidity burden within the cohort. Diagnostic criteria for each outcome are detailed in the Methods . Incident Extrahepatic Comorbidities At baseline, the prevalence of type 2 diabetes among children with MASLD was 4.8%, with a cumulative incidence of 7.3% over the follow-up period ( Figure 3 ). The incidence rate of type 2 diabetes was 911 new cases per 100,000 person-years (95% CI, 723–1134). The baseline prevalence of hypertension was 9.1%, with a cumulative incidence of 14.3%, and an incidence rate of 1,901 new cases per 100,000 person-years (95% CI, 1607–2234). Dyslipidemia was prevalent in 22.4% of children at baseline, with a cumulative incidence of 26.0% and an incidence rate of 3,664 new cases per 100,000 person-years (95% CI, 3204–4172). The baseline prevalence of obstructive sleep apnea was 6.8%, with a cumulative incidence of 9.5% and an incidence rate of 1,185 new cases per 100,000 person-years (95% CI, 966–1439). Figure 3 illustrates the overlapping distribution of these incident comorbidities. DISCUSSION This study demonstrated that children with MASLD are at increased risk of both premature mortality and a high burden of extrahepatic comorbidities. In this retrospective cohort of 1,096 children, followed for an average of 8.5 years, we observed a mortality rate of 398 per 100,000 person-years, with nearly half of the deaths attributed to liver-related causes. Strikingly, the mortality rate in children with MASLD was 40 times higher than that of age- and sex-matched peers in the U.S. general population. Our findings also demonstrated that male sex and lower HDL levels at diagnosis were independently associated with an increased risk of mortality. Additionally, we identified a high cumulative incidence of extrahepatic comorbidities in this population namely, dyslipidemia, hypertension, obstructive sleep apnea, and type 2 diabetes. The observed mortality rate in our cohort aligns with findings from previous, smaller studies. For example, Feldstein et al. reported a 3.0% mortality rate over 6.4 years of follow-up in a cohort of 66 children in Minnesota with MASLD, with a mean age of 13.9 years. 11 Similarly, Cioffi et al. found a 6.8% mortality rate over 4.5 years in 44 children with MASLD, with a mean age of 14.8 years in Georgia. 30 Our mortality rate of 3.5%, observed in a much larger cohort with an extended follow-up period, corroborates these findings and confirms that children with MASLD are at significant risk of premature death. To provide a broader context for our findings, we compared them to large-scale studies conducted in adults with MASLD. In our cohort of 1,096 children, with a total follow-up of 9,297 person-years, the mortality rate was 398 deaths per 100,000 person-years — somewhat lower but still consistent with rates reported in adults. Simon et al. observed a mortality rate of 549 per 100,000 person-years in a cohort of 718 older adolescents and young adults in Sweden with MASLD. 10 Furthermore, Sanyal et al reported a rate of 570 per 100,000 person-years in a cohort of 1773 adults with MASLD in the U.S. with 8120 person-years of follow-up. 31 Although the annual death rate in children appears only slightly lower, this similarity is alarming when considering the potential lifetime impact. Children diagnosed with MASLD face decades of exposure to metabolic risk factors, meaning that even a marginally lower annual mortality rate translates into a substantially higher cumulative risk over their lifespan. From a public health perspective, this suggests that pediatric MASLD could impose a greater long-term burden than adult-onset disease. Moreover, the mortality rate in our pediatric MASLD cohort exceeded that observed in children with obesity or type 2 diabetes alone diagnosed at a similar mean age and followed for a comparable duration. 32 , 33 Specifically, the Swedish Childhood Obesity Treatment Register reported a mortality rate of 120 deaths per 100,000 person-years in children with obesity over a mean of 9.5 years, while the SEARCH for Diabetes in Youth Study reported a mortality rate of 162 deaths per 100,000 person-years in children with type 2 diabetes over a mean of 8.5 years. 32 , 33 These findings indicate that children with MASLD are at increased risk of mortality compared to their peers with obesity or type 2 diabetes, suggesting that MASLD may confer an independent risk of mortality beyond that of its comorbidities. In addition to mortality, our study provides some of the first incidence estimates of extrahepatic comorbidities in children with MASLD, adding important insights beyond previous cross-sectional associations. Our findings support hepatic steatosis as a catalyst for metabolic dysfunction that predisposes children to comorbid conditions. The incidence rate of type 2 diabetes among children with MASLD (911 per 100,000 person-years) was significantly higher than that previously reported for children with obesity (103 per 100,000 person-years). 34 Although pediatric data on hypertension incidence are limited, relevant data exist in adults, and our results indicated that the cumulative incidence of hypertension in children with MASLD (14.3%) was nearly three-fold greater than that in adults in the general population (5.7%). 35 Moreover, the cumulative incidence of obstructive sleep apnea in children with MASLD (9.5%) was substantially higher than that of a broad sample of children followed from ages 8–11 to ages 16–19 (4%). 36 Dyslipidemia is also common in children with MASLD, with hypertriglyceridemia being more prevalent than hypercholesterolemia. 16 In our study, the annual incidence of dyslipidemia approached 4%, compounding the inherent cardiometabolic risk of MASLD. This aligns with recent research showing a higher incidence rate of major adverse cardiovascular events in young adults with hepatic steatosis (310 per 100,000 person-years) compared to matched controls without hepatic steatosis (90 per 100,000 person-years). 37 Overall, the high burden of comorbidities in children with MASLD may further amplify the risk of premature mortality. Mortality rates are high in pediatric patients with MASLD, and many experience multiple comorbidities. However, clinical care can lead to improvements in liver health, as evidenced by observed changes in liver enzyme levels. Specifically, we observed significant reductions in liver enzyme levels over time; for example, the group mean ALT decreased by approximately 30%. This decrease in liver enzyme levels may reflect a treatment response in a subset of children, as suggested by recent longitudinal data on standard of care in pediatric MASLD. 38 Although our study did not systematically capture treatment details, the magnitude of change across a large number of patients suggests that clinical care may benefit liver biochemistry in these children. The potential for improvement with diagnosis and clinical care, along with the possible consequences of this condition reinforce the critical need for effective screening of pediatric MASLD. In prior work within a large integrated health system, we found that only 54% of children with obesity and 24% of children with overweight underwent NAFLD screening, and among those with an elevated ALT level, only 12.3% received further evaluation. 5 These data suggest that while the current screening guidelines are valid, the challenge lies in improving their implementation to ensure early detection and timely management of MASLD in children. This study has several strengths, including the use of rigorously validated MASLD diagnoses, a large cohort size, and an extended follow-up period from childhood into early adulthood. Mortality rates were estimated using the National Death Index, and causes of death were validated through medical records and death certificates. Although from a single center, the cohort reflects the demographic landscape of pediatric MASLD in the U.S., enhancing the generalizability of our findings. When comparing our baseline characteristics with those from large multicenter studies, our cohort appears broadly reflective of the clinical condition. At the time of diagnosis, 4.8% of children in our cohort had type 2 diabetes, which is comparable to the 4% reported by Sahota et al. in a community-based cohort and the 6.5% observed in the NASH CRN. 5 , 14 Furthermore, our rate of histologically confirmed fibrosis (58.7%) is slightly lower than that reported in the NASH CRN (65%) and in a European multicenter study (77%). 5 , 39 These comparisons indicate that our cohort is not skewed toward higher disease severity but rather mirrors the clinical spectrum of MASLD seen across various care settings. There are also several limitations that must be acknowledged. Referral bias is the primary limitation for a study based in a pediatric gastroenterology clinic. This introduces the biases associated with how children are referred for evaluation in subspecialty care, likely leading to an overrepresentation of more severe cases. In addition, the high percentage of Hispanic children in this cohort may influence the findings and limit their generalizability to regions with different ethnic or racial demographics. We also did not capture data on renal function. Given that recent data by Mouzaki et al. demonstrate that renal impairment, including hyperfiltration, is prevalent in pediatric MASLD and is associated with disease severity, future studies should incorporate routine renal function assessments to better elucidate its role in MASLD outcomes. 40 Finally, loss to follow-up may have resulted in underestimation or overestimation of the estimated comorbidity incidence rates. Future studies are needed to confirm these findings in broader populations. Conclusion Pediatric MASLD is a serious health concern with considerable long-term risks for both morbidity and mortality. Our study revealed high rates of liver-related death, cirrhosis, and cardiometabolic comorbidities such as dyslipidemia, hypertension, obstructive sleep apnea, and type 2 diabetes. These findings emphasize the urgent need for greater awareness of this disease among healthcare providers and the public, as well as the development of effective prevention and management strategies for pediatric MASLD. Supplementary Material Supplemental Digital Content NIHMS2075192-supplement-Supplemental_Digital_Content.pdf (82.5KB, pdf) Acknowledgements We thank Dr. Richard Shaffer from the San Diego State University School of Public Health for his guidance on the statistical analysis plan and Andrew Richardson for clinical informatics support at Rady Children’s Hospital San Diego. We also extend our gratitude to Janis Durelle from UC San Diego for administrative support, and to Carissa Carrier, Jenny Sanford, and Stephenie Tinoco Calvillo from UC San Diego for their contributions to study coordination. Funding support and sponsorship: The project described was partially supported by the National Institutes of Health, Grant UL1TR001442; the Rady Children’s Hospital San Diego Physician Fund; and a research grant from Intercept Pharmaceuticals to UC San Diego. The funders did not participate in the design of the study, conduct of the study, or drafting the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. List of abbreviations: AASLD American Association for the Study of Liver Diseases AASM American Academy of Sleep Medicine AAP American Academy of Pediatrics ACC American College of Cardiology AHR Apnea-Hypopnea Ratio ALT Alanine Aminotransferase AST Aspartate Aminotransferase BMI Body Mass Index CI Confidence Interval CRN Clinical Research Network EMR Electronic Medical Records GGT Gamma-Glutamyl Transferase HbA1c Hemoglobin A1c HDL High-Density Lipoprotein HR Hazard Ratio INR International Normalized Ratio LDL Low-Density Lipoprotein MASLD Metabolic Dysfunction-Associated Steatotic Liver Disease NAFLD Nonalcoholic Fatty Liver Disease NASH Nonalcoholic Steatohepatitis NHLBI National Heart, Lung, and Blood Institute OSA Obstructive Sleep Apnea OGTT Oral Glucose Tolerance Test RCHSD Rady Children’s Hospital San Diego SMR Standardized Mortality Ratio U.S. United States Footnotes Conflict of Interest: Cynthia Behling consults for and has service contracts with Akero, ICON CRO, and Boehringer Ingelheim. She is employed by and owns stock in Pacific Rim Pathology Lab. She is employed by and consults for Pathology Institute. She consults for 89 Bio. She is an unpaid consultant for Histoindex and Pharmanest. The remaining authors have no conflicts to report. REFERENCES 1. Schwimmer JB, Behling C, Newbury R, et al. Histopathology of pediatric nonalcoholic fatty liver disease. Hepatol Baltim Md. 2005;42(3):641–649. [ DOI ] [ PubMed ] [ Google Scholar ] 2. 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. [ DOI ] [ PubMed ] [ Google Scholar ] 3. Yu EL, Golshan S, Harlow KE, et al. Prevalence of Nonalcoholic Fatty Liver Disease in Children with Obesity. J Pediatr. 2019;207:64–70. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Barlow SE. Expert Committee Recommendations Regarding the Prevention, Assessment, and Treatment of Child and Adolescent Overweight and Obesity: Summary Report. Pediatrics. 2007;120(Supplement 4):S164–S192. [ DOI ] [ PubMed ] [ Google Scholar ] 5. Sahota AK, Shapiro WL, Newton KP, Kim ST, Chung J, Schwimmer JB. Incidence of Nonalcoholic Fatty Liver Disease in Children: 2009–2018. Pediatrics. 2020;146(6). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Rinella ME, Lazarus JV, Ratziu V, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. Hepatol Baltim Md. 2023;78(6):1966–1986. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 7. Younossi ZM, Stepanova M, Ong J, et al. Nonalcoholic Steatohepatitis Is the Most Rapidly Increasing Indication for Liver Transplantation in the United States. Clin Gastroenterol Hepatol Off Clin Pract J Am Gastroenterol Assoc. 2021;19(3):580–589.e5. [ DOI ] [ PubMed ] [ Google Scholar ] 8. Simon TG, Roelstraete B, Khalili H, Hagström H, Ludvigsson JF. Mortality in biopsy-confirmed nonalcoholic fatty liver disease: results from a nationwide cohort. Gut. 2021;70(7):1375–1382. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Paik James M., Henry L, De Avila L, Younossi E, Racila A, Younossi ZM. Mortality Related to Nonalcoholic Fatty Liver Disease Is Increasing in the United States. Hepatol Commun. 2019;3(11):1459–1471. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Simon TG, Roelstraete B, Hartjes K, et al. Non-alcoholic fatty liver disease in children and young adults is associated with increased long-term mortality. J Hepatol. 2021;75(5):1034–1041. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Feldstein AE, Charatcharoenwitthaya P, Treeprasertsuk S, Benson JT, Enders FB, Angulo P. The natural history of non-alcoholic fatty liver disease in children: a follow-up study for up to 20 years. Gut. 2009;58(11):1538–1544. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Molleston JP, White F, Teckman J, Fitzgerald JF. Obese children with steatohepatitis can develop cirrhosis in childhood. Am J Gastroenterol. 2002;97(9):2460–2462. [ DOI ] [ PubMed ] [ Google Scholar ] 13. Khan HH, Klingert CE, Kumar S, Lyons H. Cirrhosis in a Young Child Due to Fatty Liver; Importance of Early Screening: A Case Report and Review of the Literature. Am J Case Rep. 2020;21:e923250–1–e923250–6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Newton KP, Hou J, Crimmins NA, et al. Prevalence of Prediabetes and Type 2 Diabetes in Children With Nonalcoholic Fatty Liver Disease. JAMA Pediatr. 2016;170(10):e161971. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. 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):e112569. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Harlow KE, Africa JA, Wells A, et al. Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease. J Pediatr. 2018;198:76–83.e2. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Sundaram SS, Sokol RJ, Capocelli KE, et al. Obstructive Sleep Apnea and Hypoxemia Are Associated with Advanced Liver Histology in Pediatric Nonalcoholic Fatty Liver Disease. J Pediatr. 2014;164(4):699–706.e1. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. Newton KP, Wilson L, Crimmins NA, et al. Incidence of Type 2 Diabetes in Children with Nonalcoholic Fatty Liver Disease. Clin Gastroenterol Hepatol. 2022;0(0). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Schwimmer JB. Definitive diagnosis and assessment of risk for nonalcoholic fatty liver disease in children and adolescents. Semin Liver Dis. 2007;27(3):312–318. [ DOI ] [ PubMed ] [ Google Scholar ] 20. Kleiner DE, Brunt EM, Natta MV, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313–1321. [ DOI ] [ PubMed ] [ Google Scholar ] 21. American Diabetes Association. Introduction: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2021;45(Supplement_1):S1–S2. [ DOI ] [ PubMed ] [ Google Scholar ] 22. Copeland KC, Silverstein J, Moore KR, et al. Management of Newly Diagnosed Type 2 Diabetes Mellitus (T2DM) in Children and Adolescents. Pediatrics. 2013;131(2):364–382. [ DOI ] [ PubMed ] [ Google Scholar ] 23. Flynn JT, Kaelber DC, Baker-Smith CM, et al. Clinical Practice Guideline for Screening and Management of High Blood Pressure in Children and Adolescents. Pediatrics. 2017;140(3):e20171904. [ DOI ] [ PubMed ] [ Google Scholar ] 24. Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018;71(6):e13–e115. [ DOI ] [ PubMed ] [ Google Scholar ] 25. EXPERT PANEL ON INTEGRATED GUIDELINES FOR CARDIOVASCULAR HEALTH AND RISK REDUCTION IN CHILDREN AND ADOLESCENTS. Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents: Summary Report. Pediatrics. 2011;128(Supplement_5):S213–S256. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 26. Marcus CL, Brooks LJ, Draper KA, et al. Diagnosis and Management of Childhood Obstructive Sleep Apnea Syndrome. Pediatrics. 2012;130(3):576–584. [ DOI ] [ PubMed ] [ Google Scholar ] 27. Aurora RN, Zak RS, Karippot A, et al. Practice parameters for the respiratory indications for polysomnography in children. Sleep. 2011;34(3):379–388. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Centers for Disease Control and Prevention. CDC WONDER: Underlying Cause of Death, 1999–2020. 29. California Department of Public Health. Death Statistical Master File (Static), 1970–2024. Compiled by Center for Helath Statistics and Informatics. [ Google Scholar ] 30. Cioffi CE, Welsh JA, Cleeton RL, et al. Natural History of NAFLD Diagnosed in Childhood: A Single-Center Study. Children. 2017;4(5):34. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 31. 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(17):1559–1569. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Lawrence JM, Reynolds K, Saydah SH, et al. Demographic Correlates of Short-Term Mortality Among Youth and Young Adults With Youth-Onset Diabetes Diagnosed From 2002 to 2015: The SEARCH for Diabetes in Youth Study. Diabetes Care. 2021;44(12):2691–2698. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 33. Lindberg L, Danielsson P, Persson M, Marcus C, Hagman E. Association of childhood obesity with risk of early all-cause and cause-specific mortality: A Swedish prospective cohort study. PLOS Med. 2020;17(3):e1003078. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Abbasi A, Juszczyk D, van Jaarsveld CHM, Gulliford MC. Body Mass Index and Incident Type 1 and Type 2 Diabetes in Children and Young Adults: A Retrospective Cohort Study. J Endocr Soc. 2017;1(5):524–537. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Garrison RJ, Kannel WB, Stokes J, Castelli WP. Incidence and precursors of hypertension in young adults: The Framingham offspring study. Prev Med. 1987;16(2):235–251. [ DOI ] [ PubMed ] [ Google Scholar ] 36. Spilsbury JC, Storfer-Isser A, Rosen CL, Redline S. Remission and Incidence of Obstructive Sleep Apnea from Middle Childhood to Late Adolescence. Sleep. 2015;38(1):23–29. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 37. Simon TG, Roelstraete B, Alkhouri N, Hagström H, Sundström J, Ludvigsson JF. Cardiovascular disease risk in paediatric and young adult non-alcoholic fatty liver disease. Gut. Published online December 15, 2022. [ DOI ] [ PubMed ] [ Google Scholar ] 38. Newton KP, Jayasekera D, Blackford AL, et al. Longitudinal response to standard of care in pediatric metabolic dysfunction–associated steatotic liver disease: Rates of improvement and worsening, and factors associated with outcomes. Hepatology.: 10.1097/HEP.0000000000001216. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 39. Kalveram L, Baumann U, De Bruyne R, et al. Noninvasive scores are poorly predictive of histological fibrosis in paediatric fatty liver disease. J Pediatr Gastroenterol Nutr. 2024;78(1):27–35. [ DOI ] [ PubMed ] [ Google Scholar ] 40. Mouzaki M, Yates KP, Arce-Clachar AC, et al. Renal impairment is prevalent in pediatric NAFLD/MASLD and associated with disease severity. J Pediatr Gastroenterol Nutr. 2024;79(2):238–249. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. 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