Metabolically Healthy Versus Unhealthy Obesity and Risk of Fibrosis Progression in Non-alcoholic Fatty Liver Disease

Yejin Kim; Yoosoo Chang; Yong Kyun Cho; Jiin Ahn; Hocheol Shin; Seungho Ryu


Liver International. 2019;39(10):1884-1894. 

In This Article


Study Participants

This study was conducted as part of the Kangbuk Samsung Health Study, a cohort study of Korean men and women aged 18 years and over who underwent comprehensive annual or biennial examinations at Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea (see Data S1 for further details).[9,11]

The present cohort study included all study participants with fatty liver on abdominal ultrasonography (see below for further details) who underwent a comprehensive health examination between January 2002 and December 2016 and had at least one follow-up visit through 31 December 2017 (n = 90 439). A total of 30 482 subjects were excluded based on the following criteria (Figure 1): missing information on BMI, homoeostasis model assessment of insulin resistance (HOMA-IR), high-sensitive C-reactive protein (hsCRP) or components of NAFLD fibrosis score (NFS) or aspartate transaminase to platelet ratio index (APRI) including aspartate aminotransferase (AST), alanine transaminase (ALT) and platelet count; a history of malignancy; alcohol intake ≥30 g/day for men and ≥20 g/day for women;[12] positive serologic markers for hepatitis B or C virus; use of steatogenic medications such as valproate, amiodarone, methotrexate, tamoxifen or corticosteroids within the past year; history of liver cirrhosis or findings of liver cirrhosis on ultrasound; known liver disease or use of medications for liver disease; and NAFLD with intermediate or high probability of fibrosis based on NFS or APRI at baseline. Because some participants met more than one exclusion criteria, a total of 59 957 participants with NAFLD and low probability of advanced fibrosis at baseline based on both NFS and APRI were included in the analysis. The study was approved by the Kangbuk Samsung Hospital Institutional Review Board (IRB No. KBSMC2018-02-053; protocol title, Risk factors for fibrosis progression in NAFLD: A cohort study; approval date, 28 February 2018), and informed consent was waived for this study since de-identified retrospective data from routine health screening process were used.

Figure 1.

Selection of the study population


Data on physical measurements, abdominal ultrasonography and serum biochemical measurements were collected as a part of the basic health check-up programme at each visit. Information on demographic characteristics, lifestyle factors, medical history and medication use were collected by standardized, self-administered questionnaires as previously described.[9] Current alcohol use was assessed as the frequency of alcohol drinking per week and the amount of alcohol consumed per drinking day (see Data S1 for further details). Average alcohol consumption per day was calculated using frequency and amount of alcohol consumed per drinking day. We also assessed the weekly frequency of moderate intensity or vigorous intensity physical activity.

Sitting blood pressure (BP), height, weight and waist circumference were measured by trained nurses (see Data S1 for further details). BMI was classified into the following criteria specifically applicable to Asian populations:[13] underweight, BMI < 18.5 kg/m2; normal weight, BMI of 18.5-23 kg/m2; overweight, BMI of 23-25 kg/m2; and obese, BMI > 25 kg/m2. Body fat percentage (%) was categorized into the following quartiles: <20.0, 20.0-24.9, 25.0-29.9, 30.0-34.9 and ≥35.0. Diabetes mellitus was defined as fasting serum glucose ≥126 mg/dL or self-reported use of insulin or antidiabetic medications. Hypertension was defined as a systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg or current use of antihypertensive medication. The fasting blood sample measurements included total cholesterol, low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C), triglycerides, AST, ALT, gamma-glutamyltransferase (GGT), glucose, uric acid, hsCRP, albumin and platelet counts. Insulin resistance was assessed with homoeostatic model assessment of insulin resistance (HOMA-IR) according to the following equation: fasting blood insulin (mU/mL) × fasting blood glucose (mmol/L)/22.5.

Definition of Metabolic Health Status

Metabolically unhealthy persons were defined as those having at least one of the following metabolic abnormalities:[14] (a) fasting glucose level ≥100 mg/dL or current use of glucose-lowering agents, (b) BP ≥ 130/85 mm Hg or current use of BP-lowering agents, (c) elevated triglyceride level (≥150 mg/dL) or current use of lipid-lowering agents, (d) low high-density lipoprotein-cholesterol (HDL-C) (<40 mg/dL in men or <50 mg/dL in women) or (e) insulin resistance, defined as an HOMA-IR score ≥2.5. Otherwise, being metabolically healthy was defined as having none of the metabolic abnormalities described above, as previously applied.[14,15]

Diagnosis of NAFLD and Fibrosis Progression

Abdominal ultrasounds (US) were performed with a 3.5-MHz transducer (Logic Q700 MR, GE, Milwaukee, WI, USA; LOGIQ E9, GE, Madison, WI, USA) by 29 experienced radiologists who were blinded to the aim of the present study. Images were captured in a standard manner (ie the patient was in the supine position with the right arm raised above the head). Ultrasonographic diagnosis of fatty liver was defined as the presence of a diffuse increase of fine echoes in the liver parenchyma compared with the kidney or spleen parenchyma.[16,17] Inter- and intra-observer reliability for fatty liver diagnosis, measured in the year 2013, was substantial (kappa statistic of 0.74) and excellent (kappa statistic of 0.94), respectively.[18] Severity of hepatic steatosis on ultrasound was also recorded as (a) mild (diffusely increased hepatic echogenicity without obscuring intrahepatic vessels and diaphragmatic echogenicity), (b) moderate (diffusely increased hepatic echogenicity obscuring intrahepatic vessels but without obscuring diaphragmatic echogenicity) and (c) severe steatosis (diffusely increased hepatic echogenicity obscuring intrahepatic vessels as well as diaphragmatic echogenicity)[19] Liver with any degree of fat accumulation was considered fatty liver in the present study. The definition of NAFLD was the presence of fatty liver in the absence of excessive alcohol use (threshold of <20 g/d for women and <30 g/d for men) or other identifiable causes,[12] as described in the exclusion criteria.

To assess the status of fibrosis progression in NAFLD, we used two noninvasive fibrosis indices: NFS and APRI. The NAFLD fibrosis score (NFS) was calculated according to the following published formula: NFS = −1.675 + 0.037 × age (years) + 0.094 × BMI (kg/m2) + 1.13 × impaired fasting glycaemia or diabetes (yes = 1, no = 0) + 0.99 × AST/ALT ratio-0.013 × platelet (×109/L)-0.66 × albumin (g/dL).[20] Two cut-off points were selected to categorize subjects with NAFLD into three groups according to probability for advanced fibrosis: high (NFS > 0.676), intermediate (NFS: 0.676 to −1.455) and low (NFS ≤ 1.455).[20] APRI was calculated according to the following formula: APRI = 100 × (AST/upper limit of normal)/platelet count (×109/L). The APRI cut-offs for low and high probability of advanced fibrosis were 0.5 and 1.5 respectively.[21]

Statistical Analysis

Descriptive statistics were used to summarize the participants' characteristics according to BMI category (<18.5, 18.5-22.9, 23.0-24.9, 25.0-29.9 or ≥30 kg/m2). The primary endpoint was the development of intermediate to high probability of fibrosis, indicating any progression from low probability of fibrosis to higher degree. Person-years of follow-up accrued from baseline until occurrence of progression of fibrosis or until the final examination conducted prior to 31 December 2017, whichever came first. The incidence rates were calculated as the number of incident cases divided by person-years of follow-up.

A parametric proportional hazard model was used to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI). We initially adjusted for age and sex and then further adjusted for centre (Seoul or Suwon), year of screening exam, smoking status (never, past, current or unknown), alcohol intake (0, <10, ≥10 g/day or unknown), regular exercise (<3 times per week, ≥3 times per week or unknown), education level (high school graduate or less, community college or university graduate, graduate school or higher or unknown) and history of cardiovascular disease (Model 1). In Model 2, further adjustments were made for total cholesterol, HDL-C, triglycerides, glucose, HOMA-IR and hsCRP. To evaluate the impact of change of BMI, metabolic health status and covariates over follow-up, we conducted additional analyses introducing BMI category, smoking status, regular exercise, alcohol intake, total cholesterol, HDL-C, triglycerides, glucose, HOMA-IR and hsCRP as time-varying covariates in the models. The proportional hazards assumption was assessed by examining graphs of estimated log (-log) survival; no violation of the assumption was found. To determine linear trends of incidence, the median value of BMI categories was used as a continuous variable and tested on each model. Additionally, we evaluated the association of body fat percentage and waist circumference with the development of intermediate to high probability of fibrosis.

A series of sensitivity analyses including only metabolically healthy individuals with NAFLD who remained metabolically healthy during follow-up were performed in order to test the robustness of our primary findings (see Data S1 for further details).

Statistical analyses were carried out using STATA version 15.0 (StataCorp LP, College Station, TX, USA). All P-values less than 0.05 were considered statistically significant.