|Year : 2021 | Volume
| Issue : 2 | Page : 218-223
Non-alcoholic fatty liver disease in Asian Indian adolescents and young adults: Prevalence and its associated risk factors
Thaharullah Shah Mehreen1, Ranjani Harish1, Rajan Kamalesh2, Ranjit Mohan Anjana3, Viswanathan Mohan3
1 Department of Translational Research, Madras Diabetes Research Foundation, Chennai, India
2 Department of Research Operations, Madras Diabetes Research Foundation, Chennai, India
3 Department of Diabetology, Madras Diabetes Research Foundation, Chennai, India
|Date of Submission||09-Dec-2020|
|Date of Decision||10-Feb-2021|
|Date of Acceptance||11-Feb-2021|
|Date of Web Publication||31-Mar-2021|
Dr. Viswanathan Mohan
Chairman and Chief of Diabetology, Dr Mohan’s Diabetes Specialities Centre, IDF Centre of Excellence in Diabetes Care, President and Chief of Diabetes Research, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, No. 4, Conran Smith Road, Gopalapuram, Chennai.
Source of Support: None, Conflict of Interest: None
Background: Non-alcoholic fatty liver disease (NAFLD) is the most common form of chronic liver disease in the youth. The aim of the study was to conduct a metabolic risk factor profiling of NAFLD in adolescents and young adults in Chennai city in south India. Materials and Methods: The study participants included adolescents (n = 188) and young adults (n = 201). Ultrasonographic examination of the abdomen was done using a high-resolution B mode ultrasonography system. Based on the intensity of echogenicity, various grades of fatty liver were classified. Anthropometry, fasting plasma glucose, serum insulin, total cholesterol, triglycerides, and HDL and LDL cholesterol were estimated. χ2 analysis was performed to compare frequencies and t-tests on continuous or measurable data. Odds ratio (OR) was used as an indicator for strength of association. Results: From the total of 389 study participants, 70 had NAFLD which includes 48 with grade I, 21 with grade II, and one participant with grade III NAFLD. About 80% of the participants with NAFLD were adults (≥20 years) and more males were affected (70%) than females (30%). Generalized obesity was present in 90% of the participants with NAFLD. After adjusting for age and gender, obesity [OR: 5.88; 95% confidence interval (CI): 2.53–13.69; P-value: <0.001] and hyperglycemia [OR: 4.20; 95% CI: 1.75–10.08; P-value: <0.001] were significantly associated with NAFLD. Conclusion: With the higher prevalence rates of NAFLD noted in the study participants, prevention modalities should be adopted in the community by reducing obesity, healthy diet, and increased physical activity.
Keywords: NAFLD, prevalence, risk, youth
|How to cite this article:|
Mehreen TS, Harish R, Kamalesh R, Anjana RM, Mohan V. Non-alcoholic fatty liver disease in Asian Indian adolescents and young adults: Prevalence and its associated risk factors. J Diabetol 2021;12:218-23
|How to cite this URL:|
Mehreen TS, Harish R, Kamalesh R, Anjana RM, Mohan V. Non-alcoholic fatty liver disease in Asian Indian adolescents and young adults: Prevalence and its associated risk factors. J Diabetol [serial online] 2021 [cited 2021 Dec 2];12:218-23. Available from: https://www.journalofdiabetology.org/text.asp?2021/12/2/218/312655
| Introduction|| |
Non-alcoholic fatty liver disease (NAFLD) is defined as the presence of hepatic steatosis by imaging or histology after the exclusion of secondary causes of hepatic fat accumulation such as significant alcohol consumption, long-term use of steatogenic medication, or monogenic hereditary disorders. This is the most common form of chronic liver disease in adolescence affecting nearly 10–20% of the adolescent population. The major risk factors associated with NAFLD among adolescents and young adults are excess weight gain and obesity which are linked to excessive refined foods intake and physical inactivity.
Visceral adipose mass is an important predictor of NAFLD. Compared with Caucasians, South Asians have increased visceral adiposity which contributes to higher prevalence of NAFLD in Asian Indians. Elevated liver enzymes are usually seen in children after 9 years of age which may be a warning sign for possible liver damage or inflammation and hence it is of cardinal importance to make the diagnosis at an earlier stage in adolescence.
Ultrasonographic (USG) examination of the abdomen is the most commonly used imaging technique for diagnosing NAFLD as it is safe and relatively inexpensive. Other studies have used body mass index (BMI) and serum alanine aminotransferase and aspartate aminotransferase levels and various formulae as surrogate markers for the assessment of NAFLD.
The present study was undertaken to conduct a metabolic risk factor profiling of NAFLD in adolescents and young adults in Chennai city in south India.
| Materials and Methods|| |
The participants for the present study were from two sources. The first cohort was from a longitudinal follow-up of Obesity Reduction and Awareness of Non communicable diseases through Group Education (ORANGE)—community component study, carried out among children and adolescents in the urban areas of Chennai, India. The present age group of the cohort was between 10 and 30 years. For the purpose of this paper, we defined adolescents as those <20 years and adults as those ≥20 years of age. In parallel, another cross-sectional study cohort involving adolescents in the age group of 12–17 years formed the secondary source of data collection. The adolescents were recruited from the urban areas within the 15 zones of Chennai city. The participants were approached through their schools and also by “door-to-door” recruitment. The total number of study participants from the two study cohorts was 389 comprising of adolescents (n = 188) and young adults (n = 201). Written informed assent was obtained from study participants less than 18 years of age along with the written consent from parents. Written informed consent was obtained from participants above 18 years of age. The study was approved by the Institutional Ethics Committee of Madras Diabetes Research Foundation with Registration no. ECR/194/Inst./TN/2013.
Anthropometric measurements such as height, weight, and waist measurements were measured using standardized techniques. Height was measured in centimeters using a stadiometer and weight was measured in kilograms using an electronic scale. BMI was calculated using the formula: weight (kg)/height squared (m2). Waist circumference was measured in centimeters using a non-stretchable or fibro-elastic measuring tape. Blood pressure was recorded in the sitting position from the right arm with a mercury sphygmomanometer and rounded off to the nearest 2 mmHg.
Venous blood samples were drawn from participants after an overnight fasting of at least 8 h. Plasma glucose estimations were done using the hexokinase method and total cholesterol, triglycerides, HDL cholesterol, and LDL cholesterol were estimated on Hitachi 912 Autoanalyzer (Tokyo, Japan) using commercial kits. Fasting serum insulin concentration was estimated using the electrochemiluminescence method (COBAS E 411 Immunology Analyzer; Roche Diagnostics). The intra- and interassay coefficients of variation for the biochemical assays ranged between 3.1% and 7.6%.
USG examination of the abdomen was done using a high-resolution B mode ultrasonography system (Seimens Healthineers Acuson Juniper) having an electric linear transducer with mid frequency of 3.5–5 MHz by an experienced radiologist who was blinded to all the study characteristics of the participants. Based on the intensity of echogenicity, various grades of fatty liver have been classified:
Grade I (mild)—when the echogenicity is just increased with normal visualization of the diaphragm and intrahepatic vessel borders;
Grade II (moderate)—when the echogenic liver obscures the echogenic walls of portal vein branches with slightly impaired visualization of the diaphragm or intrahepatic vessels;
Grade III (severe)—when the echogenic liver obscures the diaphragmatic outline which was markedly increased with poor visualization of the diaphragm, the intrahepatic vessels, and the posterior portion of the right lobe.
Generalized obesity was defined based on the WHO Asia Pacific guidelines, wherein adult subjects with BMI <18.5 kg/m2 were considered as underweight, ≥18.5 to ≤ 22.9 kg/m2 were considered as normal, BMI ≥23.0–24.9 kg/m2 as overweight, and BMI ≥ 25 kg/m2 as obese. In adolescents (<20 years), obesity was defined based on age and gender-specific BMI cut points. Abnormal fasting plasma glucose (FPG) was defined when the value exceeds 100 mg/dL which is inclusive of prediabetes and diabetes. Dyslipidemia is characterized by hypercholesterolemia (≥200 mg/dL), hypertriglyceridemia (≥150 mg/dL), low HDL cholesterol (<40 mg/dL), and high LDL cholesterol (≥100 mg/dL) levels.
Statistical analysis was done using IBM Statistical Package of Social Sciences, version 23. The participants were divided into NAFLD and non-NAFLD groups, and the two groups were compared with respect to demographic, anthropometric, biochemical, and clinical parameters. NAFLD participants were further stratified based on the three grades of NAFLD, which is in turn based on severity. χ2 analysis was performed to compare frequencies and t-tests on continuous or measurable data. Continuous data were represented as mean ± standard deviation and categorical data were expressed in percentages. Odds ratio (OR) was used as an indicator for strength of association. Fasting insulin levels of the study participants were categorized equally into four quartiles based on their fasting insulin values. The outcome measure was the participant having NAFLD or not. A multivariate binary logistic regression was performed with four quartiles of fasting insulin levels and the binary outcome of NAFLD. The relationship was depicted with OR where the first quartile of the fasting insulin levels was set as reference. P-value of 0.05 at 95% confidence interval (CI) was considered statistically significant for the study.
| Results|| |
[Table 1] describes the general characteristics of the study participants with and without NAFLD. From the total of 389 study participants, 70 had NAFLD which includes 48 with grade I, 21 with grade II, and one participant with grade III NAFLD. The mean BMI was significantly higher in the NAFLD group (mean BMI 28.8±4.9 kg/m2) compared with the non-NAFLD group (23.1±4.5 kg/m2, P < 0.001). In the NAFLD group, the mean FPG was 99±38 mg/dL which was higher than that of the non-NAFLD group (FPG 88±7 mg/dL, P < 0.001). Serum triglycerides were significantly higher in the NAFLD group when compared with non-NAFLD group (114 vs. 80 mg/dL, P < 0.001).
|Table 1: Anthropometric and biochemical parameters among participants with and without NAFLD (n = 389)|
Click here to view
About 80% of the participants with NAFLD were adults (≥20 years) and more males were affected (70%) than females (30%). Generalized obesity was present in 90% of the NAFLD participants. There were 70% of NAFLD participants with abdominal obesity compared with 19.4% in those without NAFLD (P < 0.001); 68.6% of the NAFLD participants had low HDL cholesterol compared with 45.8% in non-NAFLD group. Systolic hypertension was present in 18.6% of the NAFLD and 9.1% of the non-NAFLD participants, whereas diastolic hypertension was observed in 17.1% of the NAFLD and 5.6% of non-NAFLD participants [Table 2].
|Table 2: Demographic and metabolic risk factors among participants with and without NAFLD (n = 389)|
Click here to view
The prevalence of different grades of NAFLD according to gender and age groups is presented in [Figure 1]. It is seen that the prevalence of grade I NAFLD was higher in adolescents (71.4%), whereas prevalence of grades II and III NAFLD was more common in adults (32.6%) than in adolescents (28.6%). In females, the prevalence of grade I NAFLD was higher (76.2%) when compared with males (65.3%). However, grades II and III of NAFLD were more common in the male gender (34.6%).
|Figure 1: Prevalence of different grades of NAFLD based on age and gender|
Click here to view
[Table 3] shows the binary logistic regression analysis done using NAFLD as dependent variable to determine the association of NAFLD with obesity, hyperglycemia, and dyslipidemia. NAFLD showed a significant association with all three variables: obesity [OR: 6.11; 95% CI: 2.71–13.77; P-value: <0.001], hyperglycemia [OR: 4.18; 95% CI: 1.97–8.89; P-value: <0.001], and dyslipidemia [OR: 3.57; 95% CI: 1.49–8.56; P-value: 0.004] in the unadjusted model. After adjusting for age and gender, only obesity [OR: 5.88; 95% CI: 2.53–13.69; P-value: <0.001] and hyperglycemia [OR: 4.20; 95% CI: 1.75–10.08; P-value: <0.001] were significantly associated with NAFLD.
|Table 3: Association of NAFLD with obesity, hyperglycemia, and dyslipidemia|
Click here to view
[Figure 2] shows the association of NAFLD and fasting insulin levels. The prevalence of NAFLD increased from 9.8% in the first quartile of fasting insulin to 66.7% in the fourth quartile.
|Figure 2: Prevalence of NAFLD based on quartiles of fasting plasma insulin|
Click here to view
| Discussion|| |
In this study, we report the prevalence of NAFLD in adolescents and young adults belonging to a wide age group of 10–30 years and evaluated the risk profile for metabolic syndrome in participants with and without NAFLD. Overall, 18% were diagnosed to have NAFLD on ultrasound. Our results suggested that participants with NAFLD had an increased tendency for generalized obesity (90%), abdominal obesity (70%), and low HDL (68.6%). Moreover, NAFLD was most prevalent in adults (80%) than adolescents and in male gender (70%) when compared with females.
The prevalence of NAFLD is quite variable across countries, and there are huge regional differences noted even within India. A population-based study conducted in South India among adults reported the overall prevalence of NAFLD to be 32% which is considerably higher than the current study. Liver biopsy and ultrasound-based studies in India have reported the prevalence to be ranging from 9% in rural to 32% in urban population. Studies from Asia Pacific reported that one-third of their general population has NAFLD. The high prevalence of NAFLD in our study could be attributed to the higher proportion of metabolic risk factors in the NAFLD group.
It is well known that those with increased BMI are more susceptible to be diagnosed with fatty liver. Similar findings were observed in our study. In a systematic review and meta-analysis conducted in children and adolescents aged between 1 and 19 years, a higher mean prevalence of 34.2% was found in obese population when compared with a prevalence of 7.6% in the normal weight population. A clinic-based prospective study conducted in severely obese participants with BMI ˃40 kg/m2 at Illinois found that adolescents had a higher incidence of the inflammatory form of NAFLD, i.e., NASH when compared with their adult counterparts (63% adolescents vs. 25% adults). The Study of Children and Adolescent Liver Epidemiology (SCALE) reported that 38% of the obese participants aged between 2 and 19 years had fatty liver. In a cross-sectional study done in Delhi, nearly two-thirds of overweight adolescents were diagnosed with NAFLD. A similar finding was reported in a school-based cross-sectional study carried out in Mumbai among 11–15-year-old adolescents.
Pang et al. based on a meta-analysis reported that waist circumference is the strongest anthropometric variable in predicting NAFLD (OR=3.14, 95% Cl: 2.07–4.77) more than BMI. This is supported by our finding that the waist circumference was higher in the NAFLD group. Moreover, Asian Indians are prone to develop central adiposity and insulin resistance from a young age, combined with cardiometabolic risk factors including high body fat percentage, dyslipidemia, and fasting glucose.
In terms of gender distribution, males had a higher prevalence of NAFLD which is consistent with the studies from Korean, Malaysian, and Iranian population. In females, the involvement of estrogen as a potent antioxidant is protective against fatty acid accumulation. Gender-related differences in visceral fat distribution with females having less fat than males would also contribute to this finding. Our results revealed that the prevalence of NAFLD increased with age. A follow-up study done for a median time of 8.5 years revealed that advancing age increases the extrahepatic manifestations of NAFLD causing a higher risk for morbidity and mortality in older age groups.
We noted that the prevalence of NAFLD markedly increased with increasing insulin quartiles. Similarly, in a longitudinal follow up study done for a period of 5 years, it was found that the OR for developing NAFLD was higher as the quartiles of fasting insulin increased from the first to fourth quartile. It is known that hyperinsulinemia is an important marker in triglyceride synthesis and its deposition in the liver. Consistent with these findings, hyperinsulinemia was a significant contributor to NAFLD in our study.
Several studies have shown a strong association between NAFLD and the risk for development of cardiovascular diseases,, and this is consistent with our findings in which NAFLD was associated with hyperglycemia and dyslipidemia. Our observations are similar to results from north India reporting elevated fasting blood glucose and hypercholesterolemia as independent predictors associated with the presence and severity of NAFLD.
One of the limitations of our study is that liver biopsy was not done to diagnose fatty liver. Liver biopsy is an invasive procedure and hence USG is the choice of screening in a clinical and population setting.
In summary, this study highlights the clinical and biochemical characteristics of south Indian adolescents and young adults with and without NAFLD. With the higher prevalence rates of NAFLD noted in the study participants, prevention modalities should be adopted in the community by reducing obesity, healthy diet, and increased physical activity. Such lifestyle modifications will not only help in the prevention of NAFLD but also could help prevent obesity, type 2 diabetes, and cardiovascular diseases.
Financial support and sponsorship
This research did not receive any specific grant from funding institutions in the public, commercial, or non-profit sectors.
Conflicts of interest
The authors do not have any conflicts of interest to disclose.
| References|| |
Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al
. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases. Hepatology 2018;67:328-57.
Temple JL, Cordero P, Li J, Nguyen V, Oben JA A guide to non-alcoholic fatty liver disease in childhood and adolescence. Int J Mol Sci 2016;17:947.
Nanney MS, Lytle LA, Farbakhsh K, Moe SG, Linde JA, Gardner JK, et al
. Weight and weight-related behaviors among 2-year college students. J Am Coll Health 2015;63:221-9.
Deurenberg P, Deurenberg-Yap M, Guricci S Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev 2002;3:141-6.
Moran JR, Ghishan FK, Halter SA, Greene HL Steatohepatitis in obese children: A cause of chronic liver dysfunction. Am J Gastroenterol 1983;78:374-7.
Vos MB NAFLD in the transition from adolescence to young adulthood. Clin Liver Dis 2014;4:93-5.
Dasarathy S, Dasarathy J, Khiyami A, Joseph R, Lopez R, McCullough AJ Validity of real time ultrasound in the diagnosis of hepatic steatosis: A prospective study. J Hepatol 2009;51:1061-7.
Alisi A, Cianfarani S, Manco M, Agostoni C, Nobili V Non-alcoholic fatty liver disease and metabolic syndrome in adolescents: Pathogenetic role of genetic background and intrauterine environment. Ann Med 2012;44:29-40.
Sonya J, Ranjani H, Pradeepa R, Mohan V Obesity reduction and awareness and screening of noncommunicable diseases through group education in children and adolescents (ORANGE): Methodology paper (ORANGE-1). J Diabetes Sci Technol 2010;4:1256-64.
Kingsly A, Timperio A, Veitch J, Salmon J, Pradeepa R, Ranjani H, et al
. Individual, social and environmental correlates of active school travel among adolescents in India. Int J Environ Res Public Health 2020;17:7496. doi: 10.3390/ijerph17207496. PMID: 33076299; PMCID: PMC7602439.
Consultation WE. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157-63.
Khadilkar VYS, Agrawal KK, Tamboli S, Banerjee M, Cherian A, Goyal JP, et al
. Revised IAP growth charts for height, weight and body mass index for 5- to 18-year-old Indian children. Indian Pediat 2015;52:47-55.
Mohan V, Farooq S, Deepa M, Ravikumar R, Pitchumoni CS Prevalence of non-alcoholic fatty liver disease in urban South Indians in relation to different grades of glucose intolerance and metabolic syndrome. Diabetes Res Clin Pract 2009;84:84-91.
Chatterjee A, Basu A, Chowdhury A, Das K, Sarkar-Roy N, Majumder PP, et al
. Comparative analyses of genetic risk prediction methods reveal extreme diversity of genetic predisposition to nonalcoholic fatty liver disease (NAFLD) among ethnic populations of India. J Genet 2015;94:105-13.
Chitturi S, Farrell GC, George J Non-alcoholic steatohepatitis in the Asia-Pacific region: Future shock? J Gastroenterol Hepatol 2004;19:368-74.
Anderson EL, Howe LD, Jones HE, Higgins JP, Lawlor DA, Fraser A The prevalence of non-alcoholic fatty liver disease in children and adolescents: A systematic review and meta-analysis. PLoS One 2015;10:e0140908.
Holterman AX, Guzman G, Fantuzzi G, Wang H, Aigner K, Browne A, et al
. Nonalcoholic fatty liver disease in severely obese adolescent and adult patients. Obesity (Silver Spring) 2013;21:591-7.
Schwimmer JB, Deutsch R, Kahen T, Lavine JE, Stanley C, Behling C Prevalence of fatty liver in children and adolescents. Pediatrics 2006;118:1388-93.
Jain V, Jana M, Upadhyay B, Ahmad N, Jain O, Upadhyay AD, et al
. Prevalence, clinical & biochemical correlates of non-alcoholic fatty liver disease in overweight adolescents. Indian J Med Res 2018;148:291-301.
] [Full text]
Pawar SV, Zanwar VG, Choksey AS, Mohite AR, Jain SS, Surude RG, et al
. Most overweight and obese Indian children have nonalcoholic fatty liver disease. Ann Hepatol 2016;15:853-61.
Pang Q, Zhang JY, Song SD, Qu K, Xu XS, Liu SS, et al
. Central obesity and nonalcoholic fatty liver disease risk after adjusting for body mass index. World J Gastroenterol 2015;21:1650-62.
Misra A, Shrivastava U Obesity and dyslipidemia in South Asians. Nutrients 2013;5:2708-33.
Jeong EH, Jun DW, Cho YK, Choe YG, Ryu S, Lee SM, et al
. Regional prevalence of non-alcoholic fatty liver disease in Seoul and Gyeonggi-do, Korea. Clin Mol Hepatol 2013;19:266-72.
Khammas ASA, Hassan HA, Salih SQM, Kadir H, Ibrahim RM, Nasir NNM, et al
. Prevalence and risk factors of sonographically detected non alcoholic fatty liver disease in a screening centre in Klang valley, Malaysia: An observational cross-sectional study. Porto Biomed J 2019;4:e31.
Moghaddasifar I, Lankarani KB, Moosazadeh M, Afshari M, Ghaemi A, Aliramezany M, et al
. Prevalence of non-alcoholic fatty liver disease and its related factors in Iran. Int J Organ Transplant Med 2016;7:149-60.
Lee C, Kim J, Jung Y Potential therapeutic application of estrogen in gender disparity of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Cells2019;8:1259.
Bedogni G, Miglioli L, Masutti F, Castiglione A, Crocè LS, Tiribelli C, et al
. Incidence and natural course of fatty liver in the general population: The Dionysos study. Hepatology 2007;46:1387-91.
Rhee EJ, Lee WY, Cho YK, Kim BI, Sung KC Hyperinsulinemia and the development of nonalcoholic fatty liver disease in nondiabetic adults. Am J Med 2011;124:69-76.
Lewis GF, Carpentier A, Adeli K, Giacca A Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr Rev 2002;23:201-29.
Targher G, Byrne CD Clinical review: Nonalcoholic fatty liver disease: A novel cardiometabolic risk factor for type 2 diabetes and its complications. J Clin Endocrinol Metab 2013;98:483-95.
Sung KC, Wild SH, Kwag HJ, Byrne CD Fatty liver, insulin resistance, and features of metabolic syndrome: Relationships with coronary artery calcium in 10,153 people. Diabetes Care 2012;35:2359-64.
Duseja A, Najmy S, Sachdev S, Pal A, Sharma RR, Marwah N, et al
. High prevalence of non-alcoholic fatty liver disease among healthy male blood donors of urban India. JGH Open 2019;3:133-9.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]