Secondary Logo

Journal Logo

Original Articles: Hepatology

Prevalence of Suspected Nonalcoholic Fatty Liver Disease in Lean Adolescents in the United States

Conjeevaram Selvakumar, Praveen Kumar; Kabbany, Mohammad Nasser; Lopez, Rocio; Rayas, Maria S§; Lynch, Jane L§; Alkhouri, Naim∗,†,‡,§

Author Information
Journal of Pediatric Gastroenterology and Nutrition: July 2018 - Volume 67 - Issue 1 - p 75-79
doi: 10.1097/MPG.0000000000001974
  • Free

Abstract

What Is Known/What Is New

What Is Known

  • Nonalcoholic fatty liver disease is considered the hepatic manifestation of obesity.
  • However, recent adult studies suggest evidence of development of nonalcoholic fatty liver disease in lean subjects, which is referred to as lean nonalcoholic fatty liver disease.
  • Population-based studies looking at the prevalence of nonalcoholic fatty liver disease in lean adolescents are lacking.
  • What Is New
  • Suspected nonalcoholic fatty liver disease affects approximately 8% of the lean adolescents in the United States.
  • Lean adolescents with suspected nonalcoholic fatty liver disease are older and associated with more metabolic derangements compared with lean healthy adolescents.
  • Insulin resistance significantly increases the risk of suspected nonalcoholic fatty liver disease in lean adolescents.

Nonalcoholic fatty liver disease (NAFLD) is characterized by the presence of macrovesicular hepatic steatosis in the absence of alternate causes such as excessive alcohol consumption, viral hepatitis, or medications. NAFLD encompasses a broad clinicopathologic spectrum ranging from simple fat accumulation in liver (nonalcoholic fatty liver or NAFL) to varying degrees of necroinflammation called nonalcoholic steatohepatitis (NASH) leading to fibrosis and eventually cirrhosis (1,2). The prevalence of NAFLD has increased dramatically in the past 2 decades corresponding to a global increase in the prevalence of obesity, type 2 diabetes and metabolic syndrome in both adults and children (3–5). The reported prevalence of NAFLD in children and adolescents is about 3% to 10% in the general pediatric population and up to 50% to 70% in obese children (6–8). With this substantial increase in the reported prevalence rates, NAFLD is now recognized as the most common cause of chronic liver disease among children and adolescents in the United States (4).

NAFLD is usually linked with obesity and its comorbidities such as metabolic syndrome, dyslipidemia, and hypertension. However, recent adult data demonstrated that NAFLD could develop in adult subjects with body mass index (BMI) less than 25 kg/m2, which has been referred to as “lean NAFLD.” The prevalence of lean NAFLD in adults varies widely ranging from 3% to 30% depending on the study population, diagnostic modality, and BMI cut-offs used to define lean subjects. Most of the evidence on lean NAFLD are based on Asian population or community-based adult studies (9–11). In a large Korean study including 29,994 adults, NAFLD (based on ultrasound evidence of hepatic steatosis) was found in 12.6% of nonobese subjects (BMI <25 kg/m2) (10). A prospective epidemiological study comprising of 1911 adults from rural India showed a prevalence of NAFLD of 5.1% in those with BMI <23 kg/m2 and 6.9% in those with BMI <25 kg/m2(12). Recently, lean NAFLD has also been evaluated among Western adult population in few studies. A population-based analysis based on the National Health and Nutrition Examination Survey (NHANES) data showed that ultrasound evidence of hepatic steatosis was found in 7% of lean adults (BMI <25 kg/m2) whereas in a cross-sectional analysis involving a cohort of 2500 adults, hepatic steatosis was found only in 2.2% of lean subjects (13,14). Population-based pediatric studies evaluating NAFLD in lean subjects are very limited. In a study by Manco et al (15), biopsy-proven NAFLD was found in 21% of Italian children with BMI <85th percentile but this data is based on small sample size from a single tertiary center.

In this study, we aimed to estimate the population-based prevalence of NAFLD among lean US adolescents (12–18 years) using NHANES data and to assess the characteristics and risk factors of NAFLD in this unique population.

METHODS

Study Population

We performed a retrospective data analysis of adolescent participants ages 12 to 18 years with BMI <85th percentile who were enrolled in NHANES database during the 2005 to 2014 cycles. NHANES is a cross-sectional survey of US civilian, noninstitutionalized population conducted by National Center for Health Statistics (NCHS) to assess the health and nutrition status of adults and children (16). This program conducts an annual survey of a nationally representative sample of about 5000 persons from different counties in the US.

Definitions

A BMI cut-off of less than 85th percentile for specific age and sex was used to define lean adolescent subjects in this study based on the information from Center for Disease Control (CDC) (17,18). Suspected NAFLD was defined as alanine aminotransferase (ALT) >25.8 U/L for boys and >22.1 U/L for girls as proposed by SAFETY study (19). Components of metabolic syndrome were defined based on consensus definitions from International Diabetes Federation (IDF) (20). Hypertriglyceridemia was defined as triglycerides (TG) ≥150 mg/dL and high-density lipoprotein cholesterol (HDL-C) <40 mg/dL was considered to be low HDL-C. Hypertension was defined as systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg. We defined prediabetes or diabetes as at least one of the following: fasting blood glucose ≥100 mg/dL or self-reported prediabetes or diabetes. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as the product of fasting glucose (mg/dL) and insulin (μU/mL) divided by 405 (21) and insulin resistance was defined as HOMA-IR ≥3.

Inclusion Criteria and Exclusion Criteria

Adolescent participants ages 12 to 18 years with BMI <85th percentile who had demographic (sex, age, and ethnicity) and clinical (BMI, blood pressure, and waist circumference) parameters available in NHANES database were included. Age- and sex-specific waist circumference percentiles were analyzed using established information from CDC (22). Laboratory data including aspartate aminotransferase (AST), γ-glutamyl transpeptidase (GGT), albumin, total bilirubin, total cholesterol, low-density lipoprotein cholesterol (LDL-C), glycated hemoglobin (HbA1c), and platelet count were also analyzed. We excluded subjects with viral hepatitis (B or C), use of hepatotoxic medications, and those missing ALT to define NAFLD. We also excluded participants who were missing metabolic syndrome components such as fasting glucose, insulin, TG, HDL-C, and blood pressure. Adolescents included for final study analysis were stratified based on the definition of NAFLD into 2 groups such as suspected NAFLD and no NAFLD to assess the characteristics and risk factors of NAFLD among lean adolescents.

Statistical Analysis

A univariable analysis was performed to assess differences between lean adolescents with and without suspected NAFLD; continuous variables were compared using t tests and categorical variables were compared using Rao-Scott chi-square tests. In addition, logistic regression analysis was performed with suspected NAFLD as the modeled outcome and all demographic and clinical characteristics were considered for inclusion in the model. A backward elimination process was used to choose the final model and all variables with P values <0.10 were kept in the model. All analyses were performed using SAS survey procedures (version 9.4, The SAS Institute, Cary, NC), which account for the complex sampling design of NHANES and appropriately weighed participants in statistical models. The fasting subsample mobile examination center (MEC) weights were used in all analyses; weights for combined cycles were constructed following the guidelines provided in the NHANES analytic guidelines (23,24). Informed consent was obtained by NCHS from the parents or guardians of all participants and assent was obtained from all participants.

RESULTS

Study Population

Three thousand nine-hundred and four lean adolescent participants were identified from NHANES during the 2005 to 2014 cycles. After excluding subjects with viral hepatitis (n = 3) and those who were missing ALT (n = 493) and metabolic syndrome components (n = 1926), a total of 1482 lean adolescents were included for study analysis corresponding to weighted US population of over 18 million.

Estimated Prevalence of Suspected Nonalcoholic Fatty Liver Disease Among Lean Adolescents

The prevalence of suspected NAFLD in lean adolescents was estimated by calculating the percentage of subjects meeting the definition of suspected NAFLD. The weighted prevalence of suspected NAFLD in lean adolescents for 5 cycles during 2005 to 2014 were 6.9%, 8.8%, 8.1%, 5%, and 11.5%, respectively. Therefore, the mean estimated prevalence of suspected NAFLD among the lean US adolescents during 2005 to 2014 was 8% (Table 1). There was no specific trend in the prevalence of suspected NAFLD among lean US adolescents during the 2005 to 2014 cycles.

T1
TABLE 1:
Prevalence of suspected nonalcoholic fatty liver disease among lean United States adolescents

Comparison of Lean Adolescents With and Without Suspected Nonalcoholic Fatty Liver Disease

Demographic and Clinical Features

Table 2 shows the demographic and clinical features of lean adolescents with and without suspected NAFLD. Lean adolescents with suspected NAFLD were significantly older compared with lean adolescents with no NAFLD (15.5 vs 15 years; P value 0.025). However, we did not find any significant difference with regards to sex, ethnicity, BMI percentile, waist circumference percentile, and blood pressure between the 2 groups. Hypertension was slightly more common in lean adolescents with suspected NAFLD (3% vs 1.1%) approaching statistical significance (P value 0.052).

T2
TABLE 2:
Demographic, clinical, and laboratory features of lean adolescents with and without suspected nonalcoholic fatty liver disease

Laboratory Parameters

Laboratory parameters for both the groups are outlined in Table 2. Lean adolescents with suspected NAFLD were found to have higher AST (35.6 vs 22.6; P value <0.001) and GGT (22.9 vs 12.4; P value 0.003) compared with those without NAFLD. There was no significant difference in total cholesterol, LDL-C, HDL-C, and TG between the 2 groups. However, hypertriglyceridemia was more frequent among lean adolescents with suspected NAFLD compared with those without NAFLD (10% vs 3.9%; P value 0.028). Similarly, low HDL-C was also more common among lean subjects with suspected NAFLD than lean healthy controls (15.5% vs 6.8%; P value 0.016). Insulin resistance was found to be more prevalent among lean adolescents with suspected NAFLD compared with lean healthy controls (29.9% vs 20.4%) with the analysis close to statistical significance (P value 0.053).

Multivariate Analysis

On a multivariate analysis (Table 3), non-Hispanic black lean adolescents were less likely to have suspected NAFLD compared with non-Hispanic white lean adolescents (odds ratio [OR] 0.37; P value <0.05) after adjusting for all factors in the model. More importantly, lean adolescents with suspected NAFLD were associated with significantly higher odds of having IR compared with lean healthy controls (OR 4.2; P value <0.001).

T3
TABLE 3:
Multivariate analysis

DISCUSSION

The main findings of our study are: suspected NAFLD affects approximately 8% of the lean US adolescents; metabolic syndrome components such as low HDL-C, hypertriglyceridemia, and IR are more frequent among lean adolescents with suspected NAFLD compared with lean healthy adolescents; non-Hispanic black lean adolescents had lower rates of suspected NAFLD than their Caucasian counterparts. To our knowledge, this is the first study to estimate the prevalence of suspected NAFLD among lean adolescents using a nationwide representative sample of the US population.

As expected, the estimated prevalence of suspected NAFLD in lean adolescents in this population-based study is lower than in obese and overweight adolescents as established in another cross-sectional analysis of NHANES data using the same cut-off points for elevated ALT (5). However, it is important to recognize that suspected NAFLD prevalence among lean US adolescents is comparable with some of the previously established prevalence rates of NAFLD among lean adults (BMI <25 kg/m2) in the Western population (13,25,26). This development of NAFLD in the lean population highlights the limitation of BMI as a marker of fat distribution and metabolic disease as free fatty acids and cytokines from visceral adipose tissue are believed to play a key role in the pathogenesis of NAFLD rather than subcutaneous fat or total body fat content (27,28). This is further supported by recent evidence of low adiponectin levels suggestive of adipose tissue dysfunction in a cohort of lean Caucasian adults (14). Similar to previous adult studies, lean adolescents with NAFLD in our study were older and less likely to be non-Hispanic blacks (13).

Multiple adult studies have consistently shown strong association of IR and metabolic risk factors in lean adults with NAFLD (13,29,30). Furthermore, a community-based Korean study including 29,994 adults reported higher adjusted prevalence ratios for certain metabolic syndrome components in lean NAFLD than obese NAFLD subjects especially among women (10). Sinn et al (30) suggested that lean NAFLD is independently associated with IR regardless of the presence of metabolic syndrome or the number of metabolic syndrome components in nonobese and nondiabetic Korean adults. In a more recent cross-sectional analysis of Caucasian adults, lean NAFLD subjects were in between healthy and obese NAFLD subjects with regards to the severity of metabolic derangements such as low HDL-C, TG levels, fasting glucose, fasting insulin, and IR but displayed similar impaired response to oral glucose as obese NAFLD subjects (14). Similarly, our study also showed that IR increased the risk of suspected NAFLD by approximately four-fold among US lean adolescents who also had more frequent hypertriglyceridemia and low HDL-C compared with their lean healthy controls. In addition to IR, a potential genetic background could also play a role in the development of NAFLD in this unique population.

We recognize that our study was subject to few limitations. First, we used elevated ALT alone as a surrogate marker to diagnose NAFLD. Some patients with NAFLD can have normal ALT, which could have led to the underestimation of the prevalence of NAFLD among lean adolescents. Ultrasound data on hepatic steatosis is not available for all the cycles in NHANES so we were not able to include that in the definition of NAFLD. We did not have histologic confirmation of NAFLD in this cohort. However, ALT has been recommended as a screening tool for NAFLD (31,32) and has been previously used in population-based prevalence studies (5). Second, long-term outcome and natural progression of NAFLD in lean adolescents could not be studied because of the cross-sectional nature of NHANES.

In summary, we herein report a population-based estimate on the prevalence of suspected NAFLD among lean US adolescents and show its association with other components of the metabolic syndrome such as hypertriglyceridemia and low HDL levels. Lean NAFLD most likely represents a distinctive phenotypic spectrum of NAFLD. The complex interplay of physical inactivity, unhealthy lifestyle, gut microbiota, and genetic predisposition is still believed to play a role in the development of NAFLD in lean subjects but the contribution of each factor might be different from that of in obese NAFLD. In the absence of traditional obesity, hepatic steatosis in these lean subjects could be under-recognized. Hence it is important to be aware of this unique phenotype of NAFLD and identify lean patients at risk for NAFLD as they might have the same or even worse outcome compared with obese patients with NAFLD (33,34).

REFERENCES

1. Kleiner DE, Makhlouf HR. Histology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis in adults and children. Clin Liver Dis 2016; 20:293–312.
2. Brown GT, Kleiner DE. Histopathology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Metabolism 2016; 65:1080–1086.
3. Khashab MA, Liangpunsakul S, Chalasani N. Nonalcoholic fatty liver disease as a component of the metabolic syndrome. Curr Gastroenterol Rep 2008; 10:73–80.
4. Loomba R, Sirlin CB, Schwimmer JB, et al. Advances in pediatric nonalcoholic fatty liver disease. Hepatology 2009; 50:1282–1293.
5. Welsh JA, Karpen S, Vos MB. Increasing prevalence of nonalcoholic fatty liver disease among United States adolescents, 1988-1994 to 2007-2010. J Pediatr 2013; 162:496–500. e1.
6. Roberts EA. Pediatric nonalcoholic fatty liver disease (NAFLD): a ‘growing’ problem? J Hepatol 2007; 46:1133–1142.
7. Fraser A, Longnecker MP, Lawlor DA. Prevalence of elevated alanine aminotransferase among US adolescents and associated factors: NHANES 1999-2004. Gastroenterology 2007; 133:1814–1820.
8. Patton HM, Sirlin C, Behling C, et al. Pediatric nonalcoholic fatty liver disease: a critical appraisal of current data and implications for future research. J Pediatr Gastroenterol Nutr 2006; 43:413–427.
9. Feng R-N, Du S-S, Wang C, et al. Lean-non-alcoholic fatty liver disease increases risk for metabolic disorders in a normal weight Chinese population. World J Gastroenterol 2014; 20:17932–17940.
10. Kwon Y-M, Oh S-W, Hwang S, et al. Association of nonalcoholic fatty liver disease with components of metabolic syndrome according to body mass index in Korean adults. Am J Gastroenterol 2012; 107:1852–1858.
11. Alam S, Gupta U. Das, Alam M, et al. Clinical, anthropometric, biochemical, and histological characteristics of nonobese nonalcoholic fatty liver disease patients of Bangladesh. Indian J Gastroenterol 2014; 33:452–457.
12. Das K, Das K, Mukherjee PS, et al. Nonobese population in a developing country has a high prevalence of nonalcoholic fatty liver and significant liver disease. Hepatology 2010; 51:1593–1602.
13. Younossi ZM, Stepanova M, Negro F, et al. Nonalcoholic fatty liver disease in lean individuals in the United States. Medicine (Baltimore) 2012; 91:319–327.
14. Feldman A, Eder SK, Felder TK, et al. Clinical and metabolic characterization of lean Caucasian subjects with non-alcoholic fatty liver. Am J Gastroenterol 2017; 112:102–110.
15. Manco M, Alisi A, Fernandez Real J-M, et al. Early interplay of intra-hepatic iron and insulin resistance in children with non-alcoholic fatty liver disease. J Hepatol 2011; 55:647–653.
16. National Center for Health Statistics. National Health and Nutrition Examination Survey, 2013–2014 overview. 2013.
17. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United States. Adv Data 2000; 1–27.
18. Baker S, Barlow S, Cochran W, et al. Overweight children and adolescents: a clinical report of the North American Society for Pediatric Gastroenterology, Hepatology and Nutrition. J Pediatr Gastroenterol Nutr 2005; 40:533–543.
19. Schwimmer JB, Dunn W, Norman GJ, et al. SAFETY study: alanine aminotransferase cutoff values are set too high for reliable detection of pediatric chronic liver disease. Gastroenterology 2010; 138:1357–1364.
20. Zimmet P, Alberti G, Kaufman F, et al. The metabolic syndrome in children and adolescents. Lancet 2007; 369:2059–2061.
21. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28:412–419.
22. National Center for Health Statistics. Anthropometric reference data for children and adults: United States. Available at: https://www.cdc.gov/nchs/data/series/sr_11/sr11_252.pdf. (2007, Accessed April 5, (2017)
23. Content S. National Health and Nutrition Examination Survey: analytic guidelines, 2010; 1999–2010.
24. National Center for Health Statistics. Vital and Health Statistics Reports Series 2, Number 161, September 2013. National Health Nutrition Examination Survey Analytical Guidelines.
25. Browning JD, Szczepaniak LS, Dobbins R, et al. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology 2004; 40:1387–1395.
26. Cohen JC, Horton JD, Hobbs HH. Human fatty liver disease: old questions and new insights. Science 2011; 332:1519–1523.
27. Park BJ, Kim YJ, Kim DH, et al. Visceral adipose tissue area is an independent risk factor for hepatic steatosis. J Gastroenterol Hepatol 2008; 23:900–907.
28. Ayonrinde OT, Olynyk JK, Beilin LJ, et al. Gender-specific differences in adipose distribution and adipocytokines influence adolescent nonalcoholic fatty liver disease. Hepatology 2011; 53:800–809.
29. Kim HJ, Kim HJ, Lee KE, et al. Metabolic significance of nonalcoholic fatty liver disease in nonobese, nondiabetic adults. Arch Intern Med 2004; 164:2169–2175.
30. Sinn DH, Gwak G-Y, Park HN, et al. Ultrasonographically detected non-alcoholic fatty liver disease is an independent predictor for identifying patients with insulin resistance in non-obese, non-diabetic middle-aged Asian adults. Am J Gastroenterol 2012; 107:561–567.
31. Barlow SE, Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 2007; S164–S192.
32. Vajro P, Lenta S, Socha P, et al. Diagnosis of nonalcoholic fatty liver disease in children and adolescents. J Pediatr Gastroenterol Nutr 2012; 54:700–713.
33. Cruz AC Dela, Bugianesi E, George J, et al. 379 characteristics and long-term prognosis of lean patients with nonalcoholic fatty liver disease. Gastroenterology 2014; 146:S–909.
34. Kim D, Kim WR. Nonobese fatty liver disease. Clin Gastroenterol Hepatol 2017; 15:474–485.
Keywords:

lean nonalcoholic fatty liver disease; metabolic syndrome; nonalcoholic fatty liver disease prevalence; nonobese nonalcoholic fatty liver disease; pediatric nxonalcoholic fatty liver disease

Copyright © 2018 by European Society for Pediatric Gastroenterology, Hepatology, and Nutrition and North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition