Non-alcoholic fatty liver disease (NAFLD), characterised by excessive hepatic fat accumulation in the absence of secondary causes, has become a leading cause of chronic liver disease. Its clinical spectrum extends from isolated steatosis to steatohepatitis, progressive fibrosis, cirrhosis, and hepatocellular carcinoma. Global analyses have estimated that approximately one-quarter of adults have NAFLD, with a continuing increase driven by obesity, sedentary behaviour, insulin resistance, and type 2 diabetes mellitus.1,2 The condition is also recognised as a multisystem disorder because it is closely linked to cardiovascular disease, chronic kidney disease, and metabolic complications that frequently determine long-term outcomes.3 India is experiencing a rapid epidemiological transition marked by increasing adiposity and metabolic disease. A systematic review of Indian studies estimated a pooled adult NAFLD prevalence of 38.6%, with higher estimates in hospital-based and high-risk populations.4 The burden is likely to vary across regions because of differences in diet, physical activity, socioeconomic status, and access to preventive care. Many affected individuals remain asymptomatic and are identified incidentally during abdominal imaging or evaluation of abnormal liver enzymes. Consequently, simple methods that can recognise hepatic steatosis and identify associated risk factors are important in routine clinical practice. Liver biopsy is the reference standard for distinguishing steatosis from steatohepatitis and for accurately staging fibrosis; however, its invasive nature, sampling variability, and limited suitability for population screening restrict its routine use. Conventional ultrasonography is widely available, inexpensive, free from ionising radiation, and capable of detecting moderate-to-severe hepatic steatosis with good diagnostic accuracy.5 Sonographic assessment is based on increased hepatic echogenicity, altered liver-to-kidney contrast, reduced visualisation of intrahepatic vessels, and attenuation of the ultrasound beam.6 Although ultrasonography cannot reliably quantify mild steatosis or determine inflammatory activity and fibrosis, clinical guidelines support its use as a first-line imaging method when fatty liver is suspected.7,8 Body mass index (BMI) is a practical measure of general adiposity and remains central to metabolic risk assessment. Indian studies have consistently reported higher frequencies of fatty liver among overweight and obese adults, although hepatic steatosis also occurs in individuals with normal BMI.9-11 Establishing the local relationship between BMI and ultrasonographic fatty liver can support targeted counselling, metabolic evaluation, and early risk reduction. The present study was therefore undertaken to determine the frequency and ultrasonographic grades of fatty liver among adults evaluated at a tertiary-care teaching hospital and to assess the association between BMI categories and the presence of fatty liver. A secondary objective was to compare mean BMI between participants with and without fatty liver and to examine the trend in BMI across increasing ultrasonographic grades of steatosis.

Study design and setting: This hospital-based cross-sectional observational study was conducted in the Department of Radiodiagnosis at Konaseema Institute of Medical Sciences and Research Foundation, Amalapuram, Andhra Pradesh, India. The institution is a tertiary-care teaching hospital serving urban and rural populations of the Konaseema region. Participant recruitment and data collection were performed from March 2022 to November 2022. Study population: Adults aged 18 years or older who underwent abdominal ultrasonography for routine clinical indications were screened. Consecutive eligible individuals who provided written informed consent were enrolled. Participants with known chronic liver disease, viral hepatitis, decompensated liver disease, significant alcohol consumption, pregnancy, or current use of medicines strongly associated with hepatic steatosis were excluded. Individuals in whom adequate hepatic visualisation could not be achieved were also excluded. Sample size and sampling: The sample size was estimated using the single-proportion formula, n = Z²pq/d². An anticipated fatty liver prevalence of 32% was obtained from an urban South Indian study,9 with a 95% confidence level and 13% absolute precision. The calculated minimum sample was approximately 50; therefore, 50 participants were recruited consecutively. Data collection and anthropometry: Age and sex were documented using a structured form. Weight was measured to the nearest 0.1 kg with light clothing and without footwear, while standing height was measured to the nearest 0.1 cm. BMI was calculated as weight in kilograms divided by height in metres squared. Participants were classified as normal weight (18.5-24.9 kg/m²), overweight (25.0-29.9 kg/m²), or obese (≥30.0 kg/m²). Ultrasonographic assessment: Liver ultrasonography was performed after fasting using a standard abdominal ultrasound system with a curvilinear transducer. Hepatic echogenicity was compared with the right renal cortex, and the visibility of intrahepatic vessels and diaphragm was assessed. Grade I represented a mild diffuse increase in echogenicity with preserved vessel and diaphragm visualisation. Grade II indicated moderate echogenicity with partial obscuration of vascular margins and diaphragm. Grade III was defined by marked echogenicity, posterior beam attenuation, and poor visualisation of intrahepatic structures.5,6 Fatty liver was defined as any ultrasonographic grade. Bias control: Consecutive recruitment, standardised anthropometric measurements, and predefined sonographic criteria were used. Data forms were checked for completeness before analysis. Statistical analysis: Continuous variables were summarised as mean ± standard deviation, and categorical variables as frequency and percentage. Normality was assessed using the Shapiro-Wilk test. Mean BMI was compared between participants with and without fatty liver using the independent-samples t-test. The association between BMI category and fatty liver was evaluated using the Chi-square test. Mean BMI across ultrasonographic grades was compared using one-way analysis of variance. A two-sided p-value <0.05 was considered statistically significant. Ethical considerations: The protocol was reviewed by the Institutional Ethics Committee of Konaseema Institute of Medical Sciences and Research Foundation. Written informed consent was obtained from all participants, and confidentiality was maintained.

A total of 50 adult participants underwent ultrasonographic evaluation and were included in the final analysis. Their mean age was 43.8 ± 12.6 years, with a range of 21-68 years. The largest age group was 41-50 years, comprising 15 (30.0%) participants. Males accounted for 28 (56.0%) participants and females for 22 (44.0%). Mean BMI was 26.6 ± 4.5 kg/m². Fourteen (28.0%) participants had normal weight, 20 (40.0%) were overweight, and 16 (32.0%) were obese. No participant was underweight (Table 1). Table 1. Demographic and anthropometric characteristics of the study participants (N = 50) Characteristic Category Frequency Percentage Age, years Mean ± SD 43.8 ± 12.6 NA Age group ≤30 years 9 18.0 31-40 years 12 24.0 41-50 years 15 30.0 >50 years 14 28.0 Sex Male 28 56.0 Female 22 44.0 BMI, kg/m² Mean ± SD 26.6 ± 4.5 NA BMI category Normal weight 14 28.0 Overweight 20 40.0 Obese 16 32.0 BMI: Body mass index; SD: Standard deviation; NA: Not applicable. Ultrasonographic evidence of fatty liver was observed in 31 (62.0%) participants, whereas 19 (38.0%) had normal hepatic echogenicity. Grade I steatosis was the most frequent abnormality, affecting 18 (36.0%) participants. Grade II fatty liver was present in 10 (20.0%), and Grade III fatty liver was present in 3 (6.0%) participants (Table 2). Table 2. Ultrasonographic grading of fatty liver among the study participants (N = 50) Ultrasonographic finding Frequency Percentage No fatty liver 19 38.0 Grade I fatty liver 18 36.0 Grade II fatty liver 10 20.0 Grade III fatty liver 3 6.0 Any grade of fatty liver 31 62.0 The proportion of participants with fatty liver increased progressively across BMI categories. Fatty liver was detected in 3 of 14 (21.4%) normal-weight participants, 13 of 20 (65.0%) overweight participants, and 15 of 16 (93.8%) obese participants. The association between BMI category and ultrasonographic fatty liver was statistically significant (χ² = 16.70, degrees of freedom = 2, p < 0.001) (Table 3). Table 3. Association between body mass index category and ultrasonographic fatty liver BMI category No fatty liver, n (%) Fatty liver, n (%) Total Normal weight 11 (78.6) 3 (21.4) 14 Overweight 7 (35.0) 13 (65.0) 20 Obese 1 (6.2) 15 (93.8) 16 Total 19 (38.0) 31 (62.0) 50 Chi-square value = 16.70; degrees of freedom = 2; p < 0.001. Mean BMI was significantly higher among participants with fatty liver than among those without fatty liver (28.8 ± 3.8 kg/m² versus 23.1 ± 2.7 kg/m²; p < 0.001). Mean BMI increased from 23.1 ± 2.7 kg/m² in participants without fatty liver to 27.1 ± 2.8 kg/m², 30.2 ± 3.1 kg/m², and 33.8 ± 2.4 kg/m² in Grade I, Grade II, and Grade III fatty liver, respectively. This graded increase was statistically significant (one-way analysis of variance, F = 22.10, p < 0.001) (Table 4). Table 4. Mean body mass index according to ultrasonographic grade of fatty liver Ultrasonographic grade Number BMI, mean ± SD (kg/m²) Statistical result No fatty liver 19 23.1 ± 2.7 Grade I 18 27.1 ± 2.8 Grade II 10 30.2 ± 3.1 Grade III 3 33.8 ± 2.4 F = 22.10; p < 0.001 BMI: Body mass index; SD: Standard deviation. Comparison performed using one-way analysis of variance.

The present study identified ultrasonographic fatty liver in 62.0% of the 50 adults evaluated. Grade I steatosis was the predominant pattern, followed by Grade II and Grade III disease. The principal finding was a strong stepwise association between BMI and fatty liver. Only 21.4% of participants with normal weight had fatty liver, compared with 65.0% of overweight participants and 93.8% of those with obesity. Mean BMI was also substantially higher among participants with fatty liver, and it increased consistently with advancing sonographic grade. The observed prevalence was higher than the pooled adult prevalence of 38.6% reported in an Indian systematic review.4 It also exceeded the 32% prevalence reported among urban South Indians by Mohan et al.9 and the 24.5% prevalence recorded in a preliminary survey from coastal eastern India.10 This difference can be explained partly by the hospital-based sampling frame, the modest sample size, and the high proportion of overweight and obese participants. In contrast, a recent North Indian investigation reported age- and sex-standardised prevalences exceeding 60% in both urban and rural groups, which closely resembles the present estimate.12 Variations in participant selection, metabolic risk profile, diagnostic thresholds, and regional lifestyle patterns should be considered when prevalence estimates are compared. The BMI gradient observed in this study supports the established biological relationship between excess adiposity and hepatic lipid accumulation. Increased delivery of free fatty acids to the liver, insulin resistance, enhanced de novo lipogenesis, and adipose-tissue inflammation contribute to steatosis in overweight and obesity. Uchil et al. similarly found that most Indian adults with ultrasonographic NAFLD were overweight or obese and reported a close association with metabolic syndrome.11 Anand et al. identified BMI as an independent predictor of NAFLD among family members of affected patients, with a model combining age and BMI showing good discriminatory performance.13 These observations reinforce the value of BMI as a simple first-stage risk marker in outpatient practice. Nevertheless, three participants with normal BMI had fatty liver. This finding is clinically relevant because lean or non-obese NAFLD constitutes a substantial component of the global disease burden and can still be accompanied by adverse metabolic outcomes.14 Normal BMI therefore does not exclude hepatic steatosis, particularly in Asian populations with greater visceral adiposity at comparatively lower body weights. Ultrasonography was suitable for this study because it is accessible and demonstrates good performance for moderate-to-severe steatosis.5 However, echogenic grading remains operator dependent and does not establish steatohepatitis or fibrosis. The results support integrating BMI assessment with ultrasonography rather than using either measure alone. Adults with increased BMI and sonographic fatty liver should receive evaluation for glucose intolerance, dyslipidaemia, hypertension, and other metabolic risk factors, alongside structured advice on weight reduction, diet, and physical activity. Limitations This study had a single-centre, hospital-based design and a small sample, limiting population-level generalisability. Consecutive recruitment could not eliminate referral bias. Ultrasonography is operator dependent and has reduced sensitivity for mild steatosis; histological confirmation and quantitative imaging were not performed. Information on waist circumference, biochemical markers, diabetes, lipid abnormalities, dietary intake, and physical activity was unavailable, preventing multivariable assessment of independent predictors

Ultrasonographic fatty liver was identified in nearly two-thirds of the adults included in this study, with mild steatosis being the most frequent grade. The prevalence increased markedly from normal-weight to overweight and obese categories. Participants with fatty liver had a significantly higher mean BMI, and BMI rose progressively with increasing ultrasonographic severity. These findings demonstrate a clear association between general adiposity and hepatic steatosis in adults attending a tertiary-care hospital. Routine calculation of BMI combined with abdominal ultrasonography can assist early recognition of individuals requiring metabolic evaluation. Weight management, dietary modification, regular physical activity, and assessment for diabetes, dyslipidaemia, and hypertension should form part of subsequent clinical care and preventive counselling

1. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease: meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64(1):73-84. doi:10.1002/hep.28431. 2. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018;15(1):11-20. doi:10.1038/nrgastro.2017.109. 3. Byrne CD, Targher G. NAFLD: a multisystem disease. J Hepatol. 2015;62(1 Suppl):S47-64. doi:10.1016/j.jhep.2014.12.012. 4. Shalimar, Elhence A, Bansal B, Gupta H, Anand A, Singh TP, et al. Prevalence of non-alcoholic fatty liver disease in India: a systematic review and meta-analysis. J Clin Exp Hepatol. 2022;12(3):818-829. doi:10.1016/j.jceh.2021.11.010. 5. Hernaez R, Lazo M, Bonekamp S, Kamel I, Brancati FL, Guallar E, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology. 2011;54(3):1082-1090. doi:10.1002/hep.24452. 6. Saverymuttu SH, Joseph AE, Maxwell JD. Ultrasound scanning in the detection of hepatic fibrosis and steatosis. Br Med J (Clin Res Ed). 1986;292(6512):13-15. doi:10.1136/bmj.292.6512.13. 7. European Association for the Study of the Liver; European Association for the Study of Diabetes; European Association for the Study of Obesity. EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016;64(6):1388-1402. doi:10.1016/j.jhep.2015.11.004. 8. 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(1):328-357. doi:10.1002/hep.29367. 9. 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(1):84-91. doi:10.1016/j.diabres.2008.11.039. 10. Singh SP, Nayak S, Swain M, Rout N, Mallik RN, Agrawal O, et al. Prevalence of nonalcoholic fatty liver disease in coastal eastern India: a preliminary ultrasonographic survey. Trop Gastroenterol. 2004;25(2):76-79. 11. Uchil D, Pipalia D, Chawla M, Patel R, Maniar S, Narayani, et al. Non-alcoholic fatty liver disease: the hepatic component of metabolic syndrome. J Assoc Physicians India. 2009;57:201-204. 12. Asadullah M, Shivashankar R, Shalimar, Kandasamy D, Kondal D, Rautela G, et al. Rural-urban differentials in prevalence, spectrum and determinants of non-alcoholic fatty liver disease in North Indian population. PLoS One. 2022;17(2):e0263768. doi:10.1371/journal.pone.0263768. 13. Anand A, Singh AA, Elhence A, Vaishnav M, Biswas S, Gunjan D, et al. Prevalence and predictors of nonalcoholic fatty liver disease in family members of patients with nonalcoholic fatty liver disease. J Clin Exp Hepatol. 2022;12(2):362-371. doi:10.1016/j.jceh.2021.07.013. 14. Ye Q, Zou B, Yeo YH, Li J, Huang DQ, Wu Y, et al. Global prevalence, incidence, and outcomes of non-obese or lean non-alcoholic fatty liver disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2020;5(8):739-752. doi:10.1016/S2468-1253(20)30077-7