https://orcid.org/0000-0002-7085-7072
Figures
Abstract
Introduction
There are few epidemiologic studies of the prevalence of metabolic dysfunction-associated steatohepatitis (MASH) among pediatric populations.
Objective
To estimate the cross-sectional prevalence of MASH in the pediatric (<18 years) populations of MerativeTM MarketScan® Commercial Database (Commercial) and MerativeTM MarketScan® Multi-State Medicaid Database (Medicaid).
Methods
Pediatric patients with ≥1 medical encounter from 1/1/2020 to 12/31/2020 and ≥6 months of continuous enrollment before the most recent medical encounter were included. MASH was confirmed by an ICD-10-CM diagnosis code for MASH (K75.81) in the medical history since 1/1/2016.
Results
A total of 1,476 and 410 pediatric MASH patients were identified in Medicaid and Commercial databases respectively, with a prevalence of 0.036% (95% confidence interval (CI): 0.034%, 0.038%) in Medicaid, as compared to 0.011% (95% CI: 0.010%, 0.012%) in Commercial. Prevalence of MASH increased by age. MASH was more prevalent in those who were male, obese, had T2D, and had metabolic syndrome. Among all pediatric MASH patients, the majority were ≥10 years old, male, and obese.
Discussion
MASH is more prevalent among pediatric patients with comorbid conditions such as metabolic syndrome, obesity, and T2D, which appears to be similar to young adults. Rising prevalence of childhood obesity and related comorbid conditions, and the progressive nature of MASH, make this an area of increasing medical need. Prescreening MASH among high-risk patients with these comorbidities is needed for target intervention.
Citation: Peter-Marske KM, Zhang X, Wang T, Liu X, Fernandes G, Engel SS, et al. (2025) Prevalence and characteristics of metabolic dysfunction-associated steatohepatitis among pediatric patients in the MarketScan Databases. PLoS One 20(10): e0334971. https://doi.org/10.1371/journal.pone.0334971
Editor: Mahmoud M. Werfalli, University of Benghazi, LIBYA
Received: March 31, 2025; Accepted: October 3, 2025; Published: October 27, 2025
Copyright: © 2025 Peter-Marske et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Merck & Co. licensed data for this study which are available under license from Merative and subject to data use agreements. The reason that the data cannot be shared publicly are both legal and ethical. The legal piece is due to the data only being available under license and there being license agreements around sharing the data (hence not being able to share with third parties). The ethical part comes in because the license also includes stipulations around data use (specifically attempts to re-identify patients) that are tied into the HIPAA certification and patient confidentiality. Data can be provided upon reasonable request after contacting Rena Manglallan at rmanglal@merative.com.”.
Funding: This analysis and article processing charges were funded by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Xiao Zhang, Tongtong Wang, Xinyue Liu, Gail Fernandes, Samuel S Engel, and Ravi Shankar are employees of Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA, and may own stock and/or hold stock options in Merck & Co., Inc., Rahway, NJ, USA. Kennedy M. Peter-Marske was supported by a Graduate Student Fellowship from Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA and by a National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute National Research Service Award (T32-HL007055) during conduct of this work, and she is currently an employee of Amgen. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
1. Introduction
Metabolic dysfunction-associated steatotic liver disease (MASLD) describes a range of disease states characterized by increased fat accumulation in hepatocytes. MASLD is predominantly the result of obesity-related insulin resistance, metabolic syndrome, type 2 diabetes (T2D), and various environmental and genetic factors [1–3]. Metabolic dysfunction-associated steatohepatitis (MASH), a progressive form of MASLD, consists of steatosis, inflammation, and varying degrees of fibrosis, which may progress further to cirrhosis and liver failure [1,4,5].
Currently, the global prevalence of MASH is estimated to be 5.27%, and the prevalent MASH cases will increase 63% from 16.52 million in 2015 to 27.00 million in 2030 [6,7]. As MASH is the most quickly increasing indication for liver transplant [8–10], the projected increase in prevalence makes this area a growing unmet medical need. MASLD is the most common form of pediatric liver disease and is associated with similar clinical risk factors as in adults [11,12]. While the entire spectrum of MASLD, including MASH, can occur among pediatric population, most existing reports of pediatric patient characteristics and prevalence are on MASLD instead of MASH. The prevalence of pediatric MASLD is estimated to be between 3% and 12%, but may be as high as 85% among pediatric patients with obesity [13–15]; prior reports suggest that the prevalence of MASLD increased by 26% among adolescents ages 15–19 over the past three decades [15]. Previous studies also report that pediatric MASLD is most prevalent among older, male, and Hispanic pediatric patients, as well as those with obesity, diabetes, obstructive sleep apnea, and panhypopituitarism [11]. Due to the need for a liver biopsy to definitively diagnose MASH [16,17], data on pediatric MASH patients are limited to single-center, tertiary care settings, or multicenter specialty networks [18–20].
MASH may progress and lead to greater risk for morbidity and liver-related mortality [4]. Additionally, MASLD and MASH in childhood may also be more severe than the same conditions among adults, and are both associated with worse cardiometabolic health measures and increased cardiac dysfunction in childhood [11,21]. Even though pediatric MASH is associated with serious adverse health outcomes, few pediatric patients are screened for MASH even when they exhibit comorbid conditions such as obesity, diabetes, and metabolic syndrome [22]. Since prior studies project an increase in MASH prevalence mirroring the rise in childhood obesity and obesity-related conditions [23], more research on MASH prevalence and patient characteristics is warranted.
To our knowledge, no published studies have reported the prevalence of MASH among pediatric populations overall and within different subgroups in the United States. A better understanding of the prevalence of MASH and characteristics of MASH pediatric patients may help inform future targeted interventions. Therefore, we conducted a cross-sectional study to assess the prevalence of MASH overall and by subgroups defined by patient demographics and comorbidity conditions, as well as characteristics of MASH patients, among the pediatric population in two separate United States administrative claims databases: MerativeTM MarketScan® Commercial Database (Commercial) and MerativeTM MarketScan® Multi-State Medicaid Database (Medicaid).
2. Methods
2.1 Data sources and study population
This study was conducted among pediatric population (<18 years) using structured, de-identified secondary data from the MerativeTM MarketScan® Commercial and Medicaid databases. These two databases were selected to increase generalizability and diversity of the study population by including pediatric populations that were privately insured and publicly insured. Details of the Commercial and Medicaid databases and their enrollee characteristics have been previously described [24,25]. We utilized data on inpatient and outpatient service dates, procedure codes, and diagnosis codes, along with enrollment records. We included all pediatric patients with at least one encounter from January 1, 2020 to December 31, 2020 (index period), and who had at least 6 months of continuous enrollment before the index date (most recent medical encounter), with a maximum allowable enrollment gap of 45 days. Because all data were de-identified, this study was exempt from review by Institutional Review Boards.
2.2 MASH definition
MASH patients were identified as the presence of an International Classification of Diseases, 10th Revision (ICD-10-CM) diagnosis code of K75.81 in their medical history after January 1st, 2016.
2.3 Subgroups
Predefined subgroups for analyses included age (0- < 2 years, 2- < 10 years, 10- < 15 years, or 15- < 18 years), sex (male or female), and prevalent comorbid conditions (metabolic syndrome, obesity, and T2D). Age groupings were selected based on clinical relevance. Comorbid conditions were assessed using all available data prior to and including the index date during the study period (see S1 Table for relevant codes).
2.4 Patient’s characteristics
MASH patient age, sex, comorbid conditions, medication use, diagnostic procedures, and healthcare utilization were described. Procedures commonly associated with diagnosing MASH were identified using Current Procedural Technology (CPT) codes in the three months prior to and following first MASH diagnosis during the study period, among those who met enrollment criteria during this period. Relevant diagnostic procedures included liver biopsy, computerized tomography (CT) scan of the abdomen, ultrasound of the abdomen, magnetic resonance imaging (MRI) of the abdomen, vibration-controlled transient elastography (FibroScan) with controlled attenuation parameter (CAP), and transient elastography (see S1 Table for information on identification of these procedures). Healthcare utilization measures were assessed, allowing for 6 months of lookback prior to start of the prevalence period (July 1, 2015 to the index date). Use of antidiabetic agents by T2D status was assessed at the index date.
2.5 Exploratory analysis
We also conducted an exploratory analysis among young adults (18- < 25 years) and compared the results to pediatric patients (<18 years).
2.6 Statistical analysis
All analyses were performed separately in the Commercial and Medicaid databases. The overall and subgroup-specific prevalence of MASH and its 95% confidence interval (CI) were calculated. For descriptive analyses of patient characteristics, continuous variables were reported as the mean (standard deviation) and the median. Categorical variables were summarized as the number and proportion of the total study population, and by predefined subgroups. All analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC, United States).
3. Results
3.1 MASH prevalence
We identified 3,756,746 and 4,122,087 pediatric patients in the Commercial and Medicaid databases respectively, 410 and 1476 of whom had a MASH diagnosis. MASH prevalence among pediatric population was 0.011% (95% CI: 0.010%, 0.012%) in the Commercial database and 0.036% (95% CI: 0.034%, 0.038%) in the Medicaid database (Table 1). In both databases, MASH was more prevalent among males compared to females, and the prevalence increased with greater age; compared to the overall pediatric population, MASH was more common among pediatric patients with metabolic syndrome, obesity, and T2D.
3.2 MASH patient characteristics
In both databases, most MASH patients were 10 years or older (>90%) and were more commonly male (>65%) (Table 2). In the Commercial database, metabolic syndrome, obesity, and T2D were observed in 19.5%, 79.3% and 8.5% of the MASH population, as compared to 28.3%, 92.1% and 10.4% in the Medicaid database. Just as the prevalence of comorbidities was higher in the Medicaid database, healthcare service utilization measures were generally higher among pediatric MASH patients in the Medicaid database compared to those in the Commercial database.
As shown in Table 3, among 364 patients in the Commercial database and 1,212 patients in the Medicaid database who had continuous enrollment 3-month prior to and after MASH diagnosis, only 14 (3.9%) and 106 (8.8%) had liver biopsy; approximately half had non-biopsy procedures only, and more than 20% did not have any diagnostic procedures 3-month prior to and after first MASH diagnosis during the study period (who may have had procedures completed outside the specified time frame).
Among all pediatric MASH patients, metformin was the most commonly used antidiabetic agent with 15.1% of the patients from the Commercial database and 18.8% of the patients from the Medicaid database using this drug (Table 4). Eight and a half percent and 10.4% of pediatric MASH patients had T2D in the Commercial and the Medicaid databases respectively. Approximately similar proportions of patients in the two databases were on metformin without a concomitant diagnosis of T2D: 11.2% of patients in the Commercial database and 12.8% of patients in the Medicaid database respectively.
3.3 Exploratory analysis
Prevalence of MASH and characteristics of MASH patients among young adults age 18- < 25 were presented in S2 and S3 Tables. Overall, the prevalence of MASH was higher in young adults; the distribution of co-morbidities in young adults with MASH was similar to that in pediatric patients.
4. Discussion
In this study, an overall MASH prevalence of 0.011% and 0.036% was observed in the pediatric populations based on the Commercial and Medicaid databases, respectively. MASH was more prevalent among older subgroups, males, and patients with comorbidities such as metabolic disease, obesity, and T2D. Overall, MASH prevalence was higher among the pediatric patients from the Medicaid database than among the pediatric patients from the Commercial database.
Previous autopsy studies of pediatric population who died from conditions unrelated to MASH in San Diego and New York City found that 3% and 1.7% of the autopsy subjects had MASH. [26,27] Estimates from these autopsy studies are higher than the prevalence estimates observed in our study likely due to the underlying difference in overall health condition from the source populations. Additionally, liver histology was examined for all subjects in the autopsy studies and established histologic criteria (gold standard) were used to diagnose MASH, while in claims data collected for administrative purpose, cases may be identified using non-invasive procedures and there could be miscoding in diagnosis. Given the predominantly asymptomatic nature of the early stages of the disease, MASH is usually underdiagnosed in clinical practice. The aforementioned potentially led to an underestimation of the true prevalence of MASH in pediatric patients in this study.
Prior studies of pediatric MASH in the United States have predominantly consisted of patients with MASLD, and report the proportion of MASLD patients with confirmed MASH. However, these studies have not reported the prevalence of MASH among the general pediatric population, regardless of MASLD diagnosis. These studies, with sample sizes ranging from 87 to 780 pediatric patients with MASLD, report that 8% to 54% of pediatric patients with MASLD have “confirmed MASH”, while another 35% to 48% have “borderline MASH”, as determined by aggregate presence and degree of individual features of MASLD based on biopsy results [18–20,28–30].
Increased insulin resistance and changes in fatty acid and lipoprotein metabolism may link MASH pathogenesis with obesity, T2Ds, and metabolic syndrome [1,23]. As obesity and obesity-related conditions, along with MASH prevalence projections, have increased in pediatric populations, pre-screening for MASH among these high-risk subgroups may be particularly important [23]. However, few studies have investigated the prevalence of pediatric MASH in subgroups defined by comorbid conditions. In line with our results, others reported that subjects with MASH were more commonly older (average age of 17–18), males, and had a higher BMI. [26,27] A previous study that examined MASH in pediatric patients with T2D using United States healthcare claims data found the prevalence to be 0.6%, similar to the prevalence found among patients with T2D in the Commercial database in this study. [31] The slightly higher prevalence in the Medicaid database was likely due to enrollees characterized by low income and low social economic status, two social factors that are associated with higher risk of obesity and T2D which are important risk factors for MASH [32,33]. The potential discrepancy in race/ethnicity distribution between the two databases might also contribute to the observed difference, given the racial/ethnic disparity in MASH disease burden [34]. However, due to the incomplete information available on race/ethnicity in the claims databases, we were not able to verify our speculation. Additionally, we noticed that higher prevalence of MASH was observed in young adults age 18- < 25 than in pediatric population, and the distribution of comorbidities in young adults age 18- < 25 appeared to be similar to that in pediatric patients. One previous reported a high burden of steatosis among this age group, with prevalence of steatosis levels (S1-S3 Tables) among a population-based sample of United Kingdom young adults of 7.5% (S1 Table), 3.2% (S2 Table), and 10.0% (S3 Table) [35].
This study also characterized healthcare utilization, diagnostic procedures, and medication use among MASH pediatric patients. We found that though most pediatric MASH patients underwent a MASH-related procedure in the 3 months prior to or following first date of MASH diagnosis, very few underwent a liver biopsy. This indicates that while liver biopsy is the gold standard to diagnose MASH, due to its invasive nature, physicians may use other non-invasive tests instead in the pediatric population. This may also be true in the adult population, as one study reported that two thirds of MASLD patients do not undergo liver biopsy [36]. Since the agreement between non-invasive tests (NITs) and liver biopsy findings is less than perfect, it is possible that MASH is over-diagnosed in a patient with MASLD if only NITs are used. Whether non-invasive procedures or lab values can be reliably used to diagnose MASH in place of the gold standard of a liver biopsy in the pediatric population warrants further investigation.
With regard to medication use, we found that among pediatric patients carrying a diagnosis of MASH, metformin was the most commonly prescribed antidiabetic agent with 15% to 19% of MASH patients taking metformin. While patients with MASH and T2D were more likely to be prescribed antidiabetic agents, some patients were prescribed metformin even in the absence of a diagnosis of T2D. As shown in the study, 15.1% and 18.8% MASH patients were on metformin based on the Commercial and Medicaid databases, while only 8.5% and 10.4% MASH patients were diagnosed with T2D. Off-label use of antidiabetic agents among MASH patients without T2D may be for achievement of weight loss in MASH patients [37], which is consistent with the previous report that only 33% of pediatric metformin use was for T2D treatment [38].
4.1 Strengths and limitations
Our study used two healthcare claims databases with large sample sizes to estimate the prevalence of pediatric MASH among two populations with different enrollee makeups. The results of this study are largely generalizable to American pediatric population who are commercially insured and low-income pediatric populations who are supported by Medicaid. However, limitations should be noted. First, results are not representative of uninsured pediatric populations. Second, this study relied on administrative claims data and diagnosis codes collected for billing and record keeping purposes where clinical details and liver histology data are often missing. This limited our ability to assess the accuracy of MASH diagnosis, especially given the low biopsy rates for confirmation of diagnosis. We were also unable to investigate different lab based measures since the data were collected for administrative purposes, and lab values were largely missing. Additionally, use of the first MASH diagnosis code in available claims data may not necessarily reflect the true date of diagnosis, but rather the first encounter in which MASH was observed in that particular healthcare system. Due to this fact, reporting of diagnostic procedures surrounding first diagnosis date may be incomplete. Lastly, this study was limited by the realities of clinical practice. Though the study was able to document pediatric population who were diagnosed with MASH, we acknowledge that many pediatric patients may have remained undiagnosed. The lower prevalence of MASH patients with a diagnostic code versus prevalence estimated in the biopsy series shows potential underdiagnosis of MASH in real-world clinical practice.
5. Conclusions
MASH is more prevalent among pediatric patients with comorbid conditions such as metabolic syndrome, obesity, and T2D, which appears to be similar to young adults. Rising prevalence of childhood obesity and related comorbid conditions, and the progressive nature of MASH, make this an area of increasing medical need. Prescreening for MASH using non-invasive diagnostic measures and lab values among high-risk patients with these comorbidities is needed for target intervention.
Supporting information
S1 Table. Current Procedural Technology (CPT) codes and International Classification of Disease (ICD) codes used to define variables of interest.
https://doi.org/10.1371/journal.pone.0334971.s001
(DOCX)
S2 Table. Prevalence of MASHa (aged 18- < 25), overall, by age, sex, and comorbidity condition, based on the Commercialb and Medicaidc databases.
https://doi.org/10.1371/journal.pone.0334971.s002
(DOCX)
S3 Table. Characteristics of pediatric MASHa (aged 18- < 25), based on the Commercialb and Medicaidc databases.
https://doi.org/10.1371/journal.pone.0334971.s003
(DOCX)
Acknowledgments
IBM Watson Health and MarketScan® are trademarks of IBM Corporation in the United States, other countries or both.
References
- 1. Fabbrini E, Sullivan S, Klein S. Obesity and nonalcoholic fatty liver disease: biochemical, metabolic, and clinical implications. Hepatology. 2010;51(2):679–89. pmid:20041406
- 2. Torres DM, Williams CD, Harrison SA. Features, diagnosis, and treatment of nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2012;10(8):837–58. pmid:22446927
- 3. Pan J-J, Fallon MB. Gender and racial differences in nonalcoholic fatty liver disease. World J Hepatol. 2014;6(5):274–83. pmid:24868321
- 4.
Research FaDACfDEa. Noncirrhotic Nonalcoholic Steatohepatitis With Liver Fibrosis: Developing Drugs for Treatment Guidance for Industry. December 2018.
- 5. Lim GEH, Tang A, Ng CH, Chin YH, Lim WH, Tan DJH, et al. An Observational Data Meta-analysis on the Differences in Prevalence and Risk Factors Between MAFLD vs NAFLD. Clin Gastroenterol Hepatol. 2023;21(3):619-629.e7. pmid:34871813
- 6. Younossi ZM, Golabi P, Paik JM, Henry A, Van Dongen C, Henry L. The global epidemiology of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH): a systematic review. Hepatology. 2023;77(4):1335–47. pmid:36626630
- 7. Estes C, Razavi H, Loomba R, Younossi Z, Sanyal AJ. Modeling the epidemic of nonalcoholic fatty liver disease demonstrates an exponential increase in burden of disease. Hepatology. 2018;67(1):123–33. pmid:28802062
- 8. Wong RJ, Aguilar M, Cheung R, Perumpail RB, Harrison SA, Younossi ZM, et al. Nonalcoholic steatohepatitis is the second leading etiology of liver disease among adults awaiting liver transplantation in the United States. Gastroenterology. 2015;148(3):547–55. pmid:25461851
- 9. Golabi P, Bush H, Stepanova M, Locklear CT, Jacobson IM, Mishra A, et al. Liver Transplantation (LT) for Cryptogenic Cirrhosis (CC) and Nonalcoholic Steatohepatitis (NASH) Cirrhosis: Data from the Scientific Registry of Transplant Recipients (SRTR): 1994 to 2016. Medicine (Baltimore). 2018;97(31):e11518. pmid:30075518
- 10. Noureddin M, Vipani A, Bresee C, Todo T, Kim IK, Alkhouri N, et al. NASH Leading Cause of Liver Transplant in Women: Updated Analysis of Indications For Liver Transplant and Ethnic and Gender Variances. Am J Gastroenterol. 2018;113(11):1649–59. pmid:29880964
- 11. Vos MB, Abrams SH, Barlow SE, Caprio S, Daniels SR, Kohli R, et al. NASPGHAN Clinical Practice Guideline for the Diagnosis and Treatment of Nonalcoholic Fatty Liver Disease in Children: Recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN). J Pediatr Gastroenterol Nutr. 2017;64(2):319–34. pmid:28107283
- 12. Nobili V, Mantovani A, Cianfarani S, Alisi A, Mosca A, Sartorelli MR, et al. Prevalence of prediabetes and diabetes in children and adolescents with biopsy-proven non-alcoholic fatty liver disease. J Hepatol. 2019;71(4):802–10. pmid:31279904
- 13. Bush H, Golabi P, Younossi ZM. Pediatric Non-Alcoholic Fatty Liver Disease. Children (Basel). 2017;4(6):48. pmid:28598410
- 14. Yu EL, Golshan S, Harlow KE, Angeles JE, Durelle J, Goyal NP, et al. Prevalence of Nonalcoholic Fatty Liver Disease in Children with Obesity. J Pediatr. 2019;207:64–70. pmid:30559024
- 15. Hartmann P, Zhang X, Loomba R, Schnabl B. Global and national prevalence of nonalcoholic fatty liver disease in adolescents: An analysis of the global burden of disease study 2019. Hepatology. 2023;78(4):1168–81. pmid:37021791
- 16. Rockey DC, Caldwell SH, Goodman ZD, Nelson RC, Smith AD, American Association for the Study of Liver D. Liver biopsy. Hepatology. 2009;49(3):1017–44.
- 17. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology. 2012;55(6):2005–23. pmid:22488764
- 18. Schwimmer JB, Johnson JS, Angeles JE, Behling C, Belt PH, Borecki I, et al. Microbiome Signatures Associated With Steatohepatitis and Moderate to Severe Fibrosis in Children With Nonalcoholic Fatty Liver Disease. Gastroenterology. 2019;157(4):1109–22. pmid:31255652
- 19. Schwimmer JB, Newton KP, Awai HI, Choi LJ, Garcia MA, Ellis LL, et al. Paediatric gastroenterology evaluation of overweight and obese children referred from primary care for suspected non-alcoholic fatty liver disease. Aliment Pharmacol Ther. 2013;38(10):1267–77. pmid:24117728
- 20. Molleston JP, Schwimmer JB, Yates KP, Murray KF, Cummings OW, Lavine JE, et al. Histological abnormalities in children with nonalcoholic fatty liver disease and normal or mildly elevated alanine aminotransferase levels. J Pediatr. 2014;164(4):707-713.e3. pmid:24360992
- 21. Younossi Z, Tacke F, Arrese M, Chander Sharma B, Mostafa I, Bugianesi E. Global Perspectives on Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis. Hepatology. 2019;69(6):2672–82.
- 22. Riley MR, Bass NM, Rosenthal P, Merriman RB. Underdiagnosis of pediatric obesity and underscreening for fatty liver disease and metabolic syndrome by pediatricians and pediatric subspecialists. J Pediatr. 2005;147(6):839–42. pmid:16356443
- 23. Alisi A, Manco M, Vania A, Nobili V. Pediatric Nonalcoholic Fatty Liver Disease in 2009. The Journal of Pediatrics. 2009;155(4):469–74.
- 24.
IBM. IBM MarketScan Research Databases for Life Sciences Researchers. 2018. https://www.ibm.com/downloads/cas/0NKLE57Y
- 25.
Services C f MM. Medicaid data sources - general information. 2021. https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo
- 26. Schwimmer JB, Deutsch R, Kahen T, Lavine JE, Stanley C, Behling C. Prevalence of fatty liver in children and adolescents. Pediatrics. 2006;118(4):1388–93. pmid:17015527
- 27. Fernandes DM, Pantangi V, Azam M, Salomao M, Iuga AC, Lefkowitch JH, et al. Pediatric Nonalcoholic Fatty Liver Disease in New York City: An Autopsy Study. J Pediatr. 2018;200:174–80.
- 28. Harlow KE, Africa JA, Wells A, Belt PH, Behling CA, Jain AK, et al. Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease. J Pediatr. 2018;198:76-83.e2. pmid:29661561
- 29. Africa JA, Behling CA, Brunt EM, Zhang N, Luo Y, Wells A. In children with nonalcoholic fatty liver disease, zone 1 steatosis is associated with advanced fibrosis. Clin Gastroenterol Hepatol. 2018;16(3):438-46 e1.
- 30. Schwimmer JB, Behling C, Newbury R, Deutsch R, Nievergelt C, Schork NJ, et al. Histopathology of pediatric nonalcoholic fatty liver disease. Hepatology. 2005;42(3):641–9. pmid:16116629
- 31. Parlett L, Ma Q, Shi Q, Crawford G, Herrera Scott L, Willey V, et al. Burden of non-alcoholic steatohepatitis among children with type 2 diabetes mellitus. Diabetol Metab Syndr. 2021;13(1):47. pmid:33883009
- 32. Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social Determinants of Health and Diabetes: A Scientific Review. Diabetes Care. 2020;44(1):258–79.
- 33. Pavela G, Lewis DW, Locher J, Allison DB. Socioeconomic Status, Risk of Obesity, and the Importance of Albert J. Stunkard. Curr Obes Rep. 2016;5(1):132–9.
- 34. Friedman T, Shaheen M, Schrode K, Kermah D, Zarrinpar A, Puri V. PSUN121 Nonalcoholic Steatohepatitis (NASH), Race/Ethnicity, and Gender in Adult US Population of NHANES 17-18. Journal of the Endocrine Society. 2022;6.
- 35. Abeysekera KWM, Fernandes GS, Hammerton G, Portal AJ, Gordon FH, Heron J, et al. Prevalence of steatosis and fibrosis in young adults in the UK: a population-based study. Lancet Gastroenterol Hepatol. 2020;5(3):295–305. pmid:31954687
- 36. Barritt AS, Watkins S, Gitlin N, Klein S, Lok AS, Loomba R, et al. Patient Determinants for Histologic Diagnosis of NAFLD in the Real World: A TARGET-NASH Study. Hepatol Commun. 2021;5(6):938–46. pmid:34141981
- 37. Pardee PE, Lavine JE, Schwimmer JB. Diagnosis and treatment of pediatric nonalcoholic steatohepatitis and the implications for bariatric surgery. Semin Pediatr Surg. 2009;18(3):144–51. pmid:19573756
- 38. Wang T, McNeill AM, Chen Y, Senderak M, Shankar RR. Metformin prescription patterns among US adolescents aged 10-19 years: 2009-2013. J Clin Pharm Ther. 2016;41(2):229–36. pmid:26960965