ABSTRACT
Background
Nomenclature for steatotic liver disease has been updated to include metabolic dysfunction‐associated steatotic liver disease (MASLD), which requires the presence of hepatic steatosis and at least one cardiometabolic risk factor. The prevalence of MASLD in adolescents is understudied.
Aim
To determine the prevalence of suspected MASLD among adolescents in the United States and to examine the relationships between elevated alanine aminotransferase (ALT) and cardiometabolic risk factors.
Methods
A cross‐sectional analysis of the National Health and Nutrition Examination Survey from 2011 to 2020 was conducted for adolescents aged 12–19 years. Elevated ALT was defined using sex‐specific biological upper limits: > 26 U/L for males and > 22 U/L for females. Suspected MASLD was identified by elevated ALT and at least one cardiometabolic risk factor. Adolescents with elevated ALT were categorised as having suspected MASLD, elevated ALT due to other causes or cryptogenic ALT elevation.
Results
Overall, 14.6% of adolescents had elevated ALT. Of these, 77.2% had suspected MASLD, 20.2% had cryptogenic ALT elevation, 1.9% took hepatotoxic medications and 0.7% had viral hepatitis. Body mass index had the strongest association with elevated ALT (OR 3.55), followed by high triglycerides (OR 2.09), low HDL cholesterol (OR 2.05) and high blood pressure (OR 1.93).
Conclusions
Most adolescents with elevated ALT met MASLD criteria, yet a portion lacked cardiometabolic risk factors or other identifiable causes. These results support the adoption of MASLD criteria in adolescents while indicating a need for further research into cryptogenic ALT elevation in paediatric populations.
Keywords: dyslipidemia, epidemiology, hypertension, obesity, screening
This study determined the prevalence of suspected MASLD among U.S. adolescents using NHANES 2011–2020 data, finding that 14.6% had elevated ALT, of whom 77.2% met MASLD criteria. Elevated BMI, dyslipidemia, and high blood pressure were key predictors, highlighting the importance of screening for cardiometabolic risk factors in this population.
1. Introduction
The nomenclature of steatotic liver disease (SLD), particularly nonalcoholic fatty liver disease (NAFLD), has evolved to reflect a broader understanding of steatosis associated with metabolic dysfunction. Now termed metabolic dysfunction‐associated steatotic liver disease (MASLD), this updated classification emphasises the presence of hepatic steatosis and at least one cardiometabolic risk factor, including obesity, dysglycemia, dyslipidemia and/or hypertension [1]. In most adult populations, NAFLD and MASLD show a high degree of overlap, with MASLD criteria applying to nearly all patients with NAFLD [2]. However, this concordance has not been well characterised in paediatrics, where the relationship between steatosis and metabolic dysfunction may differ due to varying risk factor profiles.
SLD is the most common paediatric liver disease, affecting 1 in 10 children in the United States [3]. Notably, the prevalence of SLD in children with obesity is 25% [4]. The incidence of SLD in children is also on the rise, increasing 62% between 2009 and 2018 [5]. SLD carries significant long‐term risks, including progression to cirrhosis and liver transplantation in adulthood, emphasising its growing public health burden [6]. The worldwide prevalence of cirrhosis is estimated to be 1.3%, highlighting the global impact of advanced liver disease [7]. While MASLD in adults has been extensively studied, there is an urgent need to assess MASLD prevalence in adolescents and determine the role of cardiometabolic risk factors in disease progression, given the distinct characteristics of paediatric populations.
In paediatrics, alanine aminotransferase (ALT) is the primary screening tool for detecting liver disease, including suspected MASLD [8]. Both the North American Society for Paediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN) and the American Academy of Paediatrics (AAP) recommend that children should be screened with ALT due to its cost‐effectiveness and accessibility [9]. Although some studies have used controlled attenuation parameter (CAP), limitations in diagnostic accuracy, particularly in adolescents with obesity, reinforce the need for studies using ALT as the primary screening tool [10, 11]. Guidelines, informed by studies such as the liver SAFETY study, recommend sex‐specific upper limits of normal to improve diagnostic accuracy in children [12]. However, while ALT has been widely used to screen for NAFLD, its role in identifying MASLD in paediatric populations remains underexplored. Understanding how ALT correlates with cardiometabolic risk factors and determining the prevalence of suspected MASLD among adolescents with elevated ALT are essential for guiding public health strategies and clinical management.
This study aimed to determine the prevalence of suspected MASLD among adolescents in the United States. By examining the association between elevated ALT and key cardiometabolic risk factors, it assessed the burden of MASLD in the paediatric population. Additionally, the study identified independent predictors of elevated ALT and differentiated adolescents with suspected MASLD from those with other potential causes of ALT elevation, including cryptogenic ALT elevation. Collectively, these data provide a foundation for implementing the new MASLD nomenclature in paediatric care.
2. Materials and Methods
2.1. Study Population
This cross‐sectional study analysed data from the National Health and Nutrition Examination Survey (NHANES), spanning from 2011 to 2020, to evaluate adolescents aged 12–19 years. Participants were included if they were within this age range and had available ALT data. NHANES is a nationally representative survey that evaluates the health and nutrition of the U.S. population through interviews and physical examinations, conducted by the National Center for Health Statistics (NCHS) under the Centers for Disease Control and Prevention (CDC) [13]. NHANES protocols are reviewed and approved by the NCHS Research Ethics Review Board, and informed consent (parents) and assent (minors) was obtained from all participants by NCHS at the time of data collection. This study did not require additional ethical approval as it involved the use of de‐identified, publicly available data. Due to the COVID‐19 pandemic, data collection for the 2019–2020 cycle was suspended in March 2020, and these data were combined with those from the 2017–2018 cycle to form a nationally representative sample.
2.2. Definitions of Suspected Steatotic Liver Disease
ALT levels were measured using an enzymatic rate method. Elevated ALT was defined using sex‐specific biological upper limits: > 26 U/L for males and > 22 U/L for females [12]. Suspected metabolic‐associated steatotic liver disease (MASLD) was defined by the presence of elevated ALT and at least one cardiometabolic risk factor: body mass index (BMI) indicating overweight or obesity (BMI ≥ 85th percentile for age and sex) or waist circumference ≥ 95th percentile for age and sex, elevated fasting glucose (≥ 100 mg/dL) or haemoglobin A1c (≥ 5.7%), elevated blood pressure (systolic or diastolic > 95th percentile or > 130/85 mmHg), elevated triglycerides (> 150 mg/dL), or low HDL cholesterol (< 40 mg/dL) [1]. Cases with other potential causes of elevated ALT, such as viral hepatitis or medication‐induced hepatotoxicity, were identified and excluded from further analysis. Notably, for participants younger than 18, NHANES does not publicly release alcohol use data due to privacy and ethical concerns. Remaining cases without identifiable causes or cardiometabolic risk factors were classified as having cryptogenic ALT elevation. Adolescents with elevated ALT were categorised into three groups: (1) suspected MASLD, (2) elevated ALT due to other identified causes or (3) cryptogenic ALT elevation.
2.3. Data Analysis
All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Cary, North Carolina). Each participant was assigned an examination sampling weight (WTMEC2YR), strata (SDMVSTRA) and cluster (SDMVPSU) parameters reflecting the survey design. The SAS SURVEY procedures were used to analyse and account for the complex, cluster‐stratified design. All statistical tests were two‐sided, with p < 0.05 considered statistically significant.
Descriptive statistics summarised the demographic, clinical and laboratory characteristics of the study population. Continuous variables, such as age, were expressed as means and standard deviations, while categorical variables, such as sex, race, and ethnicity, were presented as frequencies and proportions. Group differences were assessed using t‐tests for continuous variables and chi‐square tests for categorical variables. The SURVEYMEANS procedure was employed to estimate the prevalence of elevated ALT and suspected MASLD, with sampling weights applied to ensure generalisability to the U.S. adolescent population.
SURVEYLOGISTIC was used to evaluate the associations between cardiometabolic risk factors and elevated ALT levels. The model adjusted for potential confounders, including age, sex and race/ethnicity. Odds ratios (ORs) with 95% CIs were computed to assess the strength of these associations. Model performance was assessed using the likelihood ratio test, with the Akaike Information Criterion (AIC) used to evaluate model fit.
Subgroup analyses were conducted using the DOMAIN statement within SURVEYMEANS to compare the prevalence of cardiometabolic risk factors among adolescents with suspected MASLD, those with elevated ALT but without MASLD, and those with normal ALT levels. This approach preserves the complex, cluster‐stratified design. This analysis included detailed comparisons of cardiometabolic risk factors and other characteristics across these groups. Differences between groups were evaluated using chi‐square tests for categorical variables and ANOVA for continuous variables.
Additionally, specific analyses were performed to evaluate the prevalence and characteristics of suspected MASLD in adolescents with and without overweight or obesity, and to identify other causes of elevated ALT, including viral hepatitis and hepatotoxic medication use. Cases of cryptogenic ALT elevation were identified after excluding adolescents with other identifiable causes or cardiometabolic risk factors. Comparative analyses were conducted to examine differences in demographic and clinical characteristics between adolescents with cryptogenic ALT elevation and those with suspected MASLD.
3. Results
3.1. Study Population
A total of 7080 adolescents aged 12–19 years were evaluated in NHANES between 2011 and 2020. After applying inclusion and exclusion criteria, 5012 adolescents were included in the final study cohort. The mean age of the adolescents was 15.4 years (95% CI: 15.3–15.5) and 51.7% (95% CI: 49.8–53.6) were male. The distribution by race and ethnicity was as follows: 54.6% White, 22.7% Hispanic, 13.7% Black, 4.4% Asian and 4.6% other/multiracial. The prevalence of elevated ALT among adolescents aged 12–19 years was 14.6% (95% CI: 12.8–16.3). Among those with elevated ALT, the mean age was slightly higher at 16.1 years (95% CI: 15.9–16.4), and the proportion of males was also higher at 63.1% (95% CI: 57.4–68.7). Additional demographic and clinical details are presented in Table 1.
TABLE 1.
Characteristics of study population.
| Characteristics | Total (N = 5012) | Elevated ALT (N = 690) | MASLD (N = 540) | Without MASLD (N = 150) | p (MASLD vs. no MASLD) |
|---|---|---|---|---|---|
| Demographics | |||||
| Age, years mean (95% CI) | 15.4 (15.3–15.5) | 16.1 (15.9–16.4) | 16.0 (15.7–16.3) | 16.5 (16.1–16.8) | 0.150 |
| Sex, weighted % (95% CI) | |||||
| Male | 51.7 (49.8–53.6) | 63.1 (57.4–68.7) | 65.8 (60.0–71.6) | 53.8 (42.3–65.4) | 0.071 |
| Female | 48.3 (46.4–50.2) | 36.9 (31.3–42.6) | 34.2 (28.4–40.0) | 46.2 (34.6–57.7) | |
| Race/Ethnicity, weighted % (95% CI) | |||||
| Hispanic | 22.7 (18.4–27.0) | 30.9 (24.1–37.7) | 31.6 (24.6–38.5) | 28.6 (20.5–36.7) | 0.451 |
| Non‐Hispanic, White | 54.6 (48.6–60.6) | 52.0 (42.9–61.2) | 52.1 (41.6–62.6) | 51.8 (41.8–61.9) | |
| Non‐Hispanic, Black | 13.7 (10.1–17.2) | 9.3 (5.0–13.5) | 9.1 (4.3–13.9) | 9.8 (3.6–16.0) | |
| Non‐Hispanic, Asian | 4.4 (3.3–5.6) | 3.8 (2.3–5.3) | 2.9 (1.5–4.3) | 6.7 (4.0–9.4) | |
| Other/Multiracial | 4.6 (3.4–5.7) | 4.0 (2.1–5.9) | 4.3 (1.6–7.0) | 3.1 (2.2–3.9) | |
| Anthropometrics, mean (95% CI) | |||||
| Weight, kg | 66.9 (65.7–68.1) | 84.3 (80.8–87.8) | 91.4 (87.9–95.0) | 59.8 (57.9–61.8) | < 0.0001 |
| Height, cm | 166 (165–166) | 169 (167–170) | 169 (168–171) | 166 (164–168) | 0.031 |
| BMI, kg/m2 | 24.2 (23.8–24.6) | 29.3 (28.2–30.4) | 31.6 (30.5–32.7) | 21.4 (20.9–22.0) | < 0.0001 |
| Waist circumference (cm) | 82.6 (81.7–83.5) | 95.8 (93.1–98.4) | 101.4 (98.8–104.0) | 76.1 (74.9–77.2) | < 0.0001 |
| Blood Pressure, mean (95% CI) | |||||
| Systolic | 109 (109–110) | 113 (111–114) | 114 (113–116) | 107 (106–109) | < 0.0001 |
| Diastolic | 59 (58–60) | 61 (60–63) | 62 (60–63) | 61 (58–64) | 0.727 |
| Liver, mean (95% CI) | |||||
| ALT, U/L | 19.5 (18.7–20.2) | 39.9 (36.7–43.2) | 41.2 (37.2–45.2) | 35.8 (33.2–38.3) | 0.045 |
| AST, U/L | 23.9 (23.3–24.5) | 34.7 (31.3–38.1) | 33.7 (30.4–37.1) | 38.1 (28.4–47.8) | 0.309 |
| GGT, U/L | 14.4 (13.9–14.9) | 23.9 (21.8–25.9) | 25.4 (23.4–27.4) | 18.8 (15.0–22.6) | 0.182 |
| Bilirubin (total), mg/dL | 0.6 (0.6–0.7) | 0.6 (0.6–0.7) | 0.6 (0.6–0.6) | 0.8 (0.7–0.9) | 0.0007 |
| Alkaline phosphatase, U/L | 133 (129–137) | 119 (112–125) | 118 (111–124) | 121 (108–134) | 0.672 |
| Total protein, g/dL | 7.2 (7.2–7.3) | 7.3 (7.2–7.4) | 7.3 (7.2–7.4) | 7.3 (7.2–7.4) | 0.651 |
| Albumin, g/dL | 4.5 (4.5–4.5) | 4.5 (4.4–4.5) | 4.4 (4.4–4.5) | 4.6 (4.5–4.7) | 0.0009 |
| Endocrine, mean (95% CI) | |||||
| Fasting glucose, mg/dL | 94.8 (93.7–95.9) | 95.0 (93.6–96.5) | 96.6 (95.1–98.1) | 89.6 (88.9–90.3) | < 0.0001 |
| Insulin, μU/mL | 13.9 (13.0–14.7) | 21.4 (18.2–24.5) | 24.9 (21.3–28.4) | 9.9 (9.3–10.5) | 0.007 |
| HbA1c, mmol/mol | 5.3 (5.2–5.3) | 5.3 (5.3–5.4) | 5.4 (5.3–5.4) | 5.2 (5.1–5.2) | 0.0001 |
| Haematology, mean (95% CI) | |||||
| Haemoglobin, g/dL | 14.0 (13.9–14.1) | 14.4 (14.3–14.6) | 14.5 (14.3–14.7) | 14.3 (13.9–14.6) | 0.230 |
| Haematocrit, % | 41.3 (41.1–41.6) | 42.5 (41.9–43.0) | 42.7 (42.1–43.2) | 41.9 (40.9–42.9) | 0.156 |
| White blood cell count, 1000 cells/μL | 7.0 (6.8–7.1) | 7.4 (7.1–7.7) | 7.6 (7.3–8.0) | 6.5 (6.1–6.8) | < 0.0001 |
| Platelet count, 1000 cells/μL | 250 (247–253) | 263 (256–270) | 271 (263–279) | 235 (227–243) | < 0.0001 |
| Lipids, mean (95% CI) | |||||
| Total cholesterol, mg/dL | 156 (155–157) | 165 (161–168) | 166 (161–171) | 161 (156–166) | 0.252 |
| Triglycerides, mg/dL | 78.0 (74.2–81.9) | 111 (98.3–123) | 123 (109–138) | 65.4 (59.2–71.6) | < 0.0001 |
| HDL, mg/dL | 51.5 (50.7–52.3) | 45.4 (43.8–47.0) | 42.2 (40.7–43.7) | 56.5 (54.6–58.3) | < 0.0001 |
| LDL, mg/dL | 87.2 (85.8–88.6) | 94.1 (87.0–101) | 96.0 (87.3–105) | 87.3 (84.1–90.5) | 0.147 |
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; CI, confidence interval; GGT, gamma‐glutamyl transferase; HbA1c, haemoglobin A1c; HDL, high density lipoprotein; LDL, low density lipoprotein; MASLD, metabolic dysfunction associated steatotic liver disease.
3.2. Prevalence of Cardiometabolic Risk Factors
Within the cohort, 45.7% (95% CI: 42.7–48.7) had no cardiometabolic risk factors for MASLD. In contrast, 39.6% (95% CI: 36.8–42.5) were classified as having overweight (18.5%) or obesity (21.0%). Additionally, 6.2% (95% CI: 5.7–6.7) met criteria for elevated waist circumference, and all adolescents with elevated waist circumference also met the criteria for overweight or obesity. Furthermore, 14.6% (95% CI: 12.9–16.3) met the criteria for dysglycemia, with 10.8% (95% CI: 9.3–12.3) exhibiting elevated glucose and 4.8% (95% CI: 3.8–5.9) elevated haemoglobin A1c. Elevated blood pressure was observed in 2.9% (95% CI: 2.0–3.7) of adolescents, while 3.6% (95% CI: 2.7–4.5) had elevated triglycerides, and 17.5% (95% CI: 15.3–19.8) had low HDL‐cholesterol.
3.3. Differences in Elevated ALT by Cardiometabolic Risk Factors
Table 2 highlights the prevalence of elevated ALT in adolescents according to cardiometabolic risk factors. Among those without any risk factors, the prevalence of elevated ALT was 7.0% (95% CI: 5.4–8.6). The prevalence increased significantly across BMI categories, from 7.6% (95% CI: 6.0–9.2) in adolescents with a normal BMI to 14.1% (95% CI: 11.0–17.2) in those classified as overweight and 34.8% (95% CI: 29.5–40.1) in those with obesity (p < 0.0001). The prevalence of elevated ALT was also significantly higher in those with elevated waist circumference (46.4%; 95% CI: 36.2–56.6; p < 0.0001) compared to those with normal waist circumference. Elevated ALT was also significantly more common in those with high blood pressure (35.4%; 95% CI: 24.2–46.6; p < 0.0001), high triglycerides (40.3%; 95% CI: 30.8–49.7; p < 0.0001), and low HDL cholesterol (31.5%; 95% CI: 26.3–36.7; p < 0.0001), as compared with those without these risk factors. By contrast, the prevalence of elevated ALT in adolescents with dysglycemia (16.1%; 95% CI: 12.6–19.7) was not significantly different from that in those with normal glycemia (14.5%; 95% CI, 12.7 to 16.2; p = 0.337) (Figure 1).
TABLE 2.
Mean ALT by cardiometabolic risk factor for MASLD.
| Cardiometabolic risk factor | Overall prevalence | Prevalence of elevated ALT | Mean ALT (U/L) | p |
|---|---|---|---|---|
| No risk factor | 45.7 (42.7–48.7) | 7.0 (5.4–8.6) | 16.8 (16.4–17.2) | |
| BMI | ||||
| Normal BMI | 60.3 (57.5–63.2) | 7.6 (6.0–9.2) | 17.1 (16.6–17.7) | < 0.0001 |
| Overweight | 18.5 (16.7–20.3) | 14.1 (11.0–17.2) | 19.8 (18.6–21.0) | |
| Obesity | 21.0 (18.6–23.5) | 34.8 (29.5–40.1) | 25.9 (23.9–27.9) | |
| Waist circumference | ||||
| Normal | 89.9 (89.1–90.7) | 11.1 (9.6–12.6) | 18.3 (17.7–18.9) | < 0.0001 |
| Elevated | 6.2 (5.7–6.7) | 46.4 (36.2–56.6) | 29.0 (26.6–31.3) | |
| Blood pressure | ||||
| Normal blood pressure | 97.1 (96.3–98.0) | 14.6 (12.8–16.3) | 19.5 (18.7–20.2) | < 0.0001 |
| Elevated blood pressure | 2.9 (2.0–3.7) | 35.4 (24.2–46.6) | 26.7 (23.5–30.0) | |
| Triglycerides | ||||
| Normal triglycerides | 96.4 (95.5–97.3) | 13.6 (11.9–15.4) | 19.2 (18.4–19.9) | < 0.0001 |
| Elevated triglycerides | 3.6 (2.7–4.5) | 40.3 (30.8–49.7) | 27.7 (24.6–30.8) | |
| HDL | ||||
| Normal HDL | 82.5 (80.2–84.7) | 11.0 (9.5–12.5) | 18.0 (17.5–18.4) | < 0.0001 |
| Low HDL | 17.5 (15.3–19.8) | 31.5 (26.3–36.7) | 26.5 (23.5–29.4) | |
| Glucose | ||||
| Normal Glycemia | 85.4 (83.7–87.1) | 14.5 (12.7–16.2) | 19.4 (18.6–20.2) | 0.34 |
| Dysglycemia | 14.6 (12.9–16.3) | 16.1 (12.6–19.7) | 20.4 (19.0–21.7) | |
| Normal HbA1c | 95.2 (94.1–96.2) | 14.3 (12.5–16.1) | 19.4 (18.6–20.1) | 0.06 |
| Elevated HbA1c | 4.8 (3.8–5.9) | 20.0 (13.7–26.2) | 21.7 (19.6–23.9) | |
| Normal glucose | 89.2 (87.7–90.7) | 14.6 (12.8–16.4) | 19.5 (18.7–20.2) | 0.37 |
| Elevated glucose | 10.8 (9.3–12.3) | 16.3 (12.4–20.2) | 20.4 (18.9–21.9) | |
Note: This table presents the overall prevalence of cardiometabolic risk factors, the prevalence of elevated ALT levels, and mean ALT values in adolescents, with 95% confidence intervals provided for each estimate. Elevated ALT was defined using sex‐specific thresholds (> 26 U/L for males and > 22 U/L for females). Cardiometabolic risk factors were defined using the updated MASLD classification: body mass index (BMI) indicating overweight or obesity (BMI > 85th percentile for age and sex) or waist circumference > 95th percentile for age and sex, elevated fasting glucose (≥ 100 mg/dL) or haemoglobin A1c (≥ 5.7%), elevated blood pressure (systolic or diastolic > 95th percentile or > 130/85 mmHg), elevated triglycerides (> 150 mg/dL), or low HDL cholesterol (< 40 mg/dL). Combined dysglycemia was defined as elevated fasting glucose or haemoglobin A1c (≥ 5.7%). The p‐values in the final column reflect the results of Rao‐Scott chi‐square tests, evaluating the significance of differences in the prevalence of elevated ALT across categories of each cardiometabolic risk factor.
Abbreviations: ALT, alanine aminotransferase; BMI, body mass index; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; MASLD, metabolic dysfunction‐associated steatotic liver disease.
FIGURE 1.
Prevalence of elevated alanine aminotransferase by cardiometabolic risk factor for metabolic dysfunction‐associated steatotic liver disease. This bar chart presents the prevalence and confidence intervals of elevated ALT by specific cardiometabolic risk factors among the study cohort. Adolescents with no risk factors for MASLD had an elevated ALT prevalence of 7.0% (95% CI: 5.4–8.6). In those with elevated body mass index (BMI), the prevalence was 14.1% (95% CI: 11.0–17.2) among those classified as having overweight and 34.8% (95% CI: 29.5–40.1) among those with obesity. Among adolescents with elevated waist circumference, the prevalence of elevated ALT was 46.4% (95% CI: 36.2–56.6). Elevated ALT prevalence was 35.4% (95% CI: 24.2–46.6) in adolescents with high blood pressure, 40.3% (95% CI: 30.8–49.7) in those with high triglycerides, 31.5% (95% CI: 26.3–36.7) in those with low HDL cholesterol and 16.1% (95% CI: 12.6–19.7) in those with combined dysglycemia (elevated glucose and haemoglobin A1c).
3.4. Association Between Cardiometabolic Risk Factor and Elevated ALT
A logistic regression model shown in Table 3 assessed the independent associations between cardiometabolic risk factors and elevated ALT levels in adolescents, adjusting for age, sex, race and ethnicity. The model had a likelihood ratio of 539.3 (10° of freedom, p < 0.0001) and an AIC of 4018.7. The odds of elevated ALT increased by 19% (OR: 1.19, 95% CI: 1.14–1.24, p < 0.0001) as age increases by 1 year. Males had 62% higher odds of elevated ALT compared to females (OR: 1.62, 95% CI: 1.36–1.94, p < 0.0001). Hispanic adolescents had 50% higher odds of elevated ALT compared to White adolescents (OR: 1.50, 95% CI: 1.21–1.86, p < 0.0001). In contrast, Black adolescents had significantly lower odds (OR: 0.66, 95% CI: 0.50–0.85, p < 0.0001). Asian adolescents had a modest increase in odds compared to White adolescents (OR: 1.28, 95% CI: 0.93–1.75, p = 0.036).
TABLE 3.
Logistic regression model for elevated ALT.
| Characteristics | Logistic regression | |
|---|---|---|
| OR (95% CI) | p | |
| Age | 1.19 (1.14, 1.24) | < 0.0001 |
| Sex | ||
| Male | 1.62 (1.36, 1.94) | < 0.0001 |
| Female | Reference | |
| Race and ethnicity | ||
| Hispanic | 1.50 (1.21, 1.86) | < 0.0001 |
| Black | 0.66 (0.50, 0.85) | < 0.0001 |
| Asian | 1.28 (0.93, 1.75) | 0.036 |
| White | Reference | |
| BMI | 3.55 (2.94, 4.28) | < 0.0001 |
| Blood pressure | 1.93 (1.22, 3.06) | 0.005 |
| Triglycerides | 2.09 (1.43, 3.06) | 0.0001 |
| HDL cholesterol | 2.05 (1.68, 2.49) | < 0.0001 |
Note: Likelihood ratio: 539.3 p < 0.0001 DF 10. AIC 4018.72.
Abbreviations: ALT, alanine aminotransferase; BMI, body mass index; CI, confidence interval; HDL, high density lipoprotein.
Among the cardiometabolic risk factors, BMI had the strongest association with elevated ALT. Adolescents with a BMI at or above the 85th percentile had 3.5 times the odds of elevated ALT compared to those with a BMI below the 85th percentile (OR: 3.55, 95% CI: 2.94–4.28, p < 0.0001). Elevated waist circumference was not included in the model due to significant collinearity with BMI, as all adolescents with elevated waist circumference were already captured by elevated BMI. Elevated blood pressure was also significantly associated with higher odds of elevated ALT (OR: 1.93, 95% CI: 1.22–3.06, p = 0.005). Indices of dyslipidemia contributed significantly: elevated triglycerides more than doubled the odds of elevated ALT (OR: 2.09, 95% CI: 1.43–3.06, p = 0.0001), and low HDL cholesterol had a similar effect (OR: 2.05, 95% CI: 1.68–2.49, p < 0.0001). Finally, dysglycemia was evaluated in the univariate analysis; however, it was not significantly associated with elevated ALT (p = 0.2484) and was therefore excluded from the final multivariate model.
3.5. Prevalence and Characteristics of Suspected MASLD
Among adolescents aged 12–19 years, 54.3% (95% CI: 51.3–57.3) were found to have at least one cardiometabolic risk factor for MASLD. Notably, 50.2% (95% CI: 47.2–53.2) of those with normal ALT levels had at least one such risk factor. In contrast, adolescents with elevated ALT were significantly more likely (p < 0.0001) to present with one or more cardiometabolic risk factors, with a prevalence of 77.2% (95% CI: 72.3–82.1), meeting the criteria for suspected MASLD (Figure 2). The overall prevalence of suspected MASLD within the entire adolescent cohort was 11.3% (95% CI: 9.7–12.8). Adolescents with suspected MASLD had a mean age of 16.0 years (95% CI: 15.7–16.3) and 65.8% (95% CI: 60.0–71.6) were male. Within this group, 88.0% (95% CI: 83.8–92.3) had elevated BMI, 25.6% (95% CI: 20.3–30.9) had elevated waist circumference, 20.8% (95% CI: 15.8–25.8) had elevated glucose or haemoglobin A1c, 9.0% (95% CI: 4.8–13.1) had elevated blood pressure, 12.7% (95% CI: 8.0–17.4) had elevated triglycerides, and 48.3% (95% CI: 40.5–56.2) had low HDL cholesterol.
FIGURE 2.
Causes of elevated alanine aminotransferase in adolescents. This pie chart displays the distribution of causes of elevated alanine aminotransferase (ALT) levels among adolescents aged 12–19 years, based on NHANES data from 2011 to 2020. Elevated ALT was defined by sex‐specific thresholds: > 26 U/L for males and > 22 U/L for females. Among adolescents with elevated ALT, 77.2% met at least one cardiometabolic criterion and were classified as having suspected metabolic dysfunction‐associated steatotic liver disease (MASLD). Additionally, 0.7% of adolescents had viral hepatitis, 1.9% were taking hepatotoxic medications, and 20.2% were classified as having cryptogenic ALT elevation after other causes were excluded.
3.6. Cardiometabolic Risk Factors in Adolescents With Suspected MASLD Without Overweight or Obesity
Among adolescents with suspected MASLD, 12.0% (95% CI: 7.7–16.2) did not have overweight, obesity or elevated waist circumference but met the MASLD criteria based on other cardiometabolic risk factors. In this subgroup, 24.5% (95% CI: 11.8–37.2) had elevated glucose or haemoglobin A1c, 10.9% (95% CI: 0–22.9) had elevated blood pressure, 22.5% (95% CI: 12.1–33.0) had elevated triglycerides, and 65.3% (95% CI: 47.1–83.4) had low HDL‐cholesterol.
3.7. Other Causes of Elevated ALT
In adolescents with elevated ALT, 0.7% (95% CI: 0–2.1) had viral hepatitis, and 1.9% (95% CI: 0.2–3.5) were taking medications associated with hepatotoxicity. After evaluating cardiometabolic risk factors and excluding these other causes, 20.2% (95% CI: 15.8–24.5) of adolescents with elevated ALT were classified as having cryptogenic ALT elevation (Figure 2).
The mean age in those with other causes of ALT elevation was 16.5 years (95% CI: 16.1–16.8) and 53.8% were male. The distribution of race and ethnicity in this group was 52.0% White, 29% Hispanic, 10% Black, 7% Asian and 3% other/multi‐racial. There were no significant differences in age, sex and race/ethnicity between adolescents with and without suspected MASLD (Table 1).
4. Discussion
This study provides a nationally representative analysis of suspected MASLD among adolescents using NHANES data from 2011 to 2020. Our results show that 14.6% of adolescents had elevated ALT levels, with 77.2% meeting criteria for suspected MASLD. The overall prevalence of suspected MASLD in the adolescent population was 11.3%. Additionally, 20.2% of adolescents with elevated ALT had no identifiable cardiometabolic risk factors or other causes, resulting in their classification as having cryptogenic ALT elevation. Four of the five cardiometabolic risk factors—elevated BMI, elevated blood pressure, elevated triglycerides and low HDL cholesterol—were independently associated with higher odds of elevated ALT.
4.1. Comparison of MASLD Prevalence Using ALT and CAP in Adolescents
The prevalence of suspected MASLD, based on ALT elevation, was 11.3% in our study, which aligns with existing data on the prevalence of NAFLD in adolescents. However, two recent studies utilising NHANES data from 2017 to 2020 reported higher MASLD prevalence rates of 24%–26% using CAP cutoffs of 240–248 dB/m [14, 15]. CAP's moderate correlation with liver MRI‐PDFF in children, ranging from 0.17 to 0.53, raises concerns about its accuracy for paediatric populations [10, 15, 16]. For instance, Tas et al. found that CAP had a positive predictive value of only 43% when confirmed by MRI‐PDFF in a cohort of children with obesity [17]. CAP measurements are also known to be confounded by elevated BMI and body composition in paediatric and adult studies, which may account for the higher MASLD prevalence rates reported in CAP‐based studies compared to our findings using ALT [10, 11, 18, 19].
4.2. Majority of Adolescents With Elevated ALT Meet MASLD Criteria
The majority of adolescents with elevated ALT in our study met the criteria for MASLD, demonstrating a significant overlap between ALT elevation and metabolic dysfunction in this population. However, this percentage is lower than what has been observed in adults, where near complete concordance between NAFLD and MASLD has been reported. For example, studies such as those by Ciardullo et al. have shown that 99% of adult NAFLD cases meet MASLD criteria [2]. This discrepancy is likely due to the differing prevalence of cardiometabolic risk factors between adolescents and adults. Metabolic syndrome, a key driver of MASLD, is far less common in adolescents (4.4%) compared to adults (34.7%) [20, 21]. Thus, SLD appears to be more closely linked to cardiometabolic risk factors in adults than in adolescents, raising important questions about how disease progression—specifically the relationship between steatosis and metabolic risk factors—may differ between these age groups.
4.3. Cryptogenic ALT Elevation in Adolescents
In our study, 20.2% of adolescents with elevated ALT had neither identifiable cardiometabolic risk factors nor other discernible causes, leading to their classification of having cryptogenic ALT elevation. This group likely represents a diverse population. Some adolescents in this category may have lean SLD, a clinically significant condition that has been linked to high cardiovascular and all‐cause mortality in adults [22, 23]. A recent study showed that 16.5% of adults with lean SLD did not meet MASLD criteria [24].
Other adolescents in the cryptogenic group may not have chronic liver disease, or they may have conditions not assessed in NHANES, including autoimmune hepatitis and monogenic causes. Additionally, the publicly accessible NHANES datasets lack data on alcohol consumption, which affects at least 9.4% of U.S. adolescents [25]. As a result, some cryptogenic cases could involve alcohol‐related liver disease (ALD). However, since these adolescents do not have any cardiometabolic risk factors, they cannot be classified as having Met‐ALD, which requires both alcohol use and metabolic dysfunction.
4.4. Association Between Cardiometabolic Risk Factors and Elevated ALT
Our study demonstrated a strong association between elevated BMI and elevated ALT levels, confirming obesity as a major risk factor for MASLD. Adolescents with obesity were three times more likely to have elevated ALT compared to those with normal BMI, consistent with existing evidence linking obesity and liver disease in both paediatric and adult populations. Central adiposity, measured by waist circumference, was also strongly associated with elevated ALT, but waist circumference did not identify any adolescents with elevated ALT beyond those already captured by BMI. Hypertriglyceridaemia and low HDL cholesterol were also strongly associated with elevated ALT, highlighting the critical role of lipid abnormalities in hepatic steatosis. Similarly, elevated blood pressure was significantly associated with ALT elevation. In a study of 484 children with NAFLD, children with high blood pressure were significantly more likely to have worse steatosis than children without high blood pressure (p = 0.003) [26]. These findings align with the broader metabolic disturbances seen in MASLD, where dyslipidaemia and insulin resistance contribute to hepatic steatosis and inflammation. Interestingly, despite dysglycaemia being present in 14.6% of the cohort, it was not significantly associated with elevated ALT in our multivariate analysis. This contrasts with adult studies, where type 2 diabetes is a well‐established risk factor for NAFLD progression [27]. One potential explanation is that dysglycaemia may develop later in the disease trajectory in adolescents. Overall, our finding that most of the cardiometabolic risk factors assessed were strongly associated with elevated ALT shows the importance of comprehensive metabolic screening in the adolescent population.
4.5. Strengths and Limitations
This study has several strengths. By using NHANES data, we were able to analyse a nationally representative sample of the U.S. adolescent population, enhancing the generalisability of our findings. The large sample size and standardised methods of data collection add to the reliability of the results. Moreover, the use of ALT as a screening tool is consistent with current guidelines, and the study provides valuable data on the prevalence of suspected MASLD in adolescents.
However, there are limitations to this study. The reliance on ALT as a marker for hepatic steatosis without confirmatory imaging, such as MRI‐PDFF, may result in some diagnostic misclassification. Additionally, the public‐access NHANES dataset does not include alcohol consumption data for participants under 18 years of age, limiting our ability to identify cases of ALT elevation that may be attributable to alcohol‐associated liver disease (ALD) or Met‐ALD. The dataset also lacks comprehensive evaluation for other potential causes of elevated ALT, such as autoimmune liver conditions or rare monogenic disorders, such as lysosomal acid lipase deficiency. These rare conditions could explain a small subset of cryptogenic ALT elevation in adolescents. The study's cross‐sectional design further limits the ability to evaluate causality; a longitudinal investigation would provide valuable insight into the temporal relationship between cardiometabolic risk factors and elevated ALT. Future studies should incorporate advanced diagnostic tools, such as MRI‐PDFF and detailed clinical data to better differentiate causes of ALT elevation and improve the understanding of MASLD in adolescents.
4.6. Conclusion
In conclusion, this nationally representative study highlights the prevalence of suspected MASLD in adolescents, estimated at 11.3%. Moreover, elevated ALT was shown to be a key marker of both metabolic dysfunction and liver disease. The strong association between ALT elevation and cardiometabolic risk factors—with over 77% of adolescents with elevated ALT meeting MASLD criteria—effectively demonstrates the need for metabolic screening in paediatric care. Notably, four out of the five cardiometabolic risk factors were independently associated with ALT elevation, emphasising their relevance in paediatric MASLD. However, a gap persists in fully translating the MASLD nomenclature into paediatric practice. Furthermore, the high proportion of adolescents with cryptogenic ALT elevation points to the need for further investigation into unexplained ALT elevation. These findings support the adoption of MASLD criteria in paediatric hepatology while also highlighting the need for continued research to optimise its application in children.
Author Contributions
Sheila L. Noon: conceptualization, methodology, data curation, writing – original draft, writing – review and editing. Lauren F. Chun: data curation, writing – original draft, writing – review and editing. Tin Bo Nicholas Lam: conceptualization, data curation, writing – review and editing. Nhat Quang N. Thai: methodology, data curation, writing – review and editing. Winston Dunn: conceptualization, methodology, data curation, writing – review and editing. Jeffrey B. Schwimmer: conceptualization, data curation, writing – review and editing, supervision.
Ethics Statement
The data used in this study were obtained from the publicly available National Health and Nutrition Examination Survey (NHANES), conducted by the National Center for Health Statistics (NCHS). The NHANES protocol was reviewed and approved by the NCHS Research Ethics Review Board, and informed consent was obtained from all participants by NCHS at the time of data collection. This study did not require additional ethical approval as it involved the use of de‐identified, publicly available data.
Conflicts of Interest
The authors declare no conflicts of interest.
Handling Editor: Rohit Loomba
Funding: The authors received no specific funding for this work.
Data Availability Statement
The data analysed in this study were obtained from the National Health and Nutrition Examination Survey (NHANES), a publicly available dataset provided by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). NHANES data are accessible at https://www.cdc.gov/nchs/nhanes/index.htm. All analyses in this study adhere to the NHANES data use policy.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data analysed in this study were obtained from the National Health and Nutrition Examination Survey (NHANES), a publicly available dataset provided by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). NHANES data are accessible at https://www.cdc.gov/nchs/nhanes/index.htm. All analyses in this study adhere to the NHANES data use policy.