Lean MASLD in U.S. Adults: Undiagnosed Burden and Metabolic Features from NHANES 2017-2020

Metabolic dysfunction-associated steatotic liver disease (MASLD), recently redefined from nonalcoholic fatty liver disease (NAFLD), affects a significant portion of the global population. While typically associated with obesity, MASLD also occurs in lean individuals, a subgroup often overlooked by current screening strategies. Understanding the prevalence and characteristics of lean MASLD is essential to guide appropriate clinical recognition and management.

To estimate the national prevalence of MASLD among lean adults in the USA and assess the burden of undiagnosed cases using a nationally representative dataset.

We analyzed data from the National Health and Nutrition Examination Surveys (NHANES) 2017-March 2020, including adults aged ≥ 18 years with valid liver elastography results and without viral hepatitis or significant alcohol use. MASLD was defined by a controlled attenuation parameter (CAP) ≥ 274 dB/m on vibration-controlled transient elastography (VCTE). Lean status was defined as BMI < 25 kg/m² (or < 23 kg/m² for Asian individuals). Undiagnosed MASLD was determined by imaging evidence without self-reported provider diagnosis. Analyses incorporated survey weights to generate nationally representative estimates.

Among 2086 lean adults analyzed, the estimated national prevalence of MASLD was 6.4% (95% CI 4.1%-8.6%), corresponding to 3.8 million U.S. adults. Of these, 34.6%, approximately 1.18 million individuals-were undiagnosed. MASLD individuals had significantly higher systolic and diastolic blood pressure, triglycerides, fasting glucose, and BMI within the lean range compared to non-MASLD counterparts (all p < 0.01). MASLD prevalence increased with worsening glycemic status, reaching 33% among lean individuals with diabetes.

Lean MASLD affects a substantial number of U.S. adults and is frequently underdiagnosed. These findings underscore the need to refine current screening practices and develop targeted strategies for early detection in lean populations, particularly those with metabolic risk factors. Future research should focus on risk stratification tools to better identify high-risk individuals within this overlooked subgroup.