AIM: To study the prevalence and clinical biochemical, blood cell and metabolic features of lean-non-alcoholic fatty liver disease (lean-NAFLD) and its association with other diseases. METHODS: Demographic, biochemical and blood examinations were conducted in all the subjects in this study. We classified the subjects into four groups according to their weight and NAFLD status: lean-control, lean-NAFLD [body mass index (BMI) < 24 kg/m²], overweight-obese control and overweight-obese NAFLD. One-way analysis of variance (ANOVA) was used to compare the means of continuous variables (age, BMI, blood pressure, glucose, lipid, insulin, liver enzymes and blood cell counts) and the χ² test was used to compare the differences in frequency of categorical variables (sex, education, physical activity, smoking, alcohol consumption and prevalence of hypertension, hyperlipidemia, diabetes, metabolic syndrome central obesity and obesity). Both univariate and multivariate logistic regression models were adopted to calculate odds ratios (ORs) and predict hyperlipidemia, hypertension, diabetes and metabolic syndrome when we respectively set all controls, lean-control and overweight-obese-control as references. In multivariate logistic regression models, we adjusted potential confounding factors, including age, sex, smoking, alcohol consumption and physical activity. RESULTS: The prevalence of NAFLD was very high in China. NAFLD patients were older, had a higher BMI, waist circumference, blood pressure, fasting blood glucose, insulin, blood lipid, liver enzymes and uric acid than the controls. Although lean-NAFLD patients had lower BMI and waist circumstance, they had significantly higher visceral adiposity index than overweight-obese controls. Lean-NAFLD patients had comparable triglyceride, cholesterin and low-density lipoprotein cholesterin to overweight-obese NAFLD patients. In blood cell examination, both lean and overweight-obese NAFLD was companied by higher white blood cell count, red blood cell count, hemoglobin and hematocrit value. All NAFLD patients were at risk of hyperlipidemia, hypertension, diabetes and metabolic syndrome (MetS). Lean-NAFLD was more strongly associated with diabetes (OR = 2.47, 95%CI: 1.14-5.35), hypertension (OR = 1.72, 95%CI: 1.00-2.96) and MetS (OR = 3.19, 95%CI: 1.17-4.05) than overweight-obese-NAFLD (only OR for MetS was meaningful: OR = 1.89, 95%CI: 1.29-2.77). NAFLD patients were more likely to have central obesity (OR = 1.97, 95%CI: 1.38-2.80), especially in lean groups (OR = 2.17, 95%CI: 1.17-4.05). CONCLUSION: Lean-NAFLD has unique results in demographic, biochemical and blood examinations, and adds significant risk for diabetes, hypertension and MetS in lean individuals.

Obesity is closely associated with chronic diseases such as hypertension, type 2 diabetes mellitus (T2DM), and dyslipidemia. We analyzed the optimal obesity index cut-off values for metabolic syndrome (MetS), and identified the obesity index that is more closely associated with these chronic diseases, in a population of northern Chinese. We surveyed 8940 adults (age, 20-74 years) living in northern China for chronic diseases. Receiver operating characteristics (ROC) analysis, relative risk, and multivariate regression were used to develop an appropriate index and optimal cut-off values for MetS and obesity-related chronic diseases. Waist circumference (WC) and body mass index (BMI) were good markers for MetS, WC was a good marker for T2DM and dyslipidemia, and BMI was a good marker for hypertension. The optimal BMI cut-off value of MetS was 24 kg/m², and the optimal WC cut-offs were 86 cm and 78 cm in men and women, respectively. Relative risk regression models showed that BMI was associated with hypertension, T2DM, and hypertriglyceridemia and a higher prevalence ratio (PR) for hypertension: 2.35 (95% CI, 2.18-2.50). WC was associated with T2DM, hypertension, and hypertriglyceridemia, with PRs of 2.05 (1.63-2.55) for T2DM and 2.47 (2.04-2.85) for hypertriglyceridemia. In multivariate regression models, the standardized regression coefficients (SRCs) of BMI were greater for SBP and DBP, and the SRC of WC was greater for fasting blood glucose, 2-hour postload blood glucose, triglyceride, and total cholesterol. Our analysis of a population of northern Chinese indicates that the optimal cut-off values for MetS are WCs of 86 cm in men and 78 cm in women and a BMI of 24 kg/m² in both sexes. BMI was strongly associated with hypertension, while WC was strongly associated with T2DM and dyslipidemia.

Starchy foods are the main sources of carbohydrates; however, there is limited information on their metabolic impact. Therefore, we assessed the association between carbohydrates from starchy foods (Carb-S) intakes and the metabolic disorders of metabolic syndrome (MetS) and hyperlipidemia. In this study, 4,154 participants from Northern China were followed up for 4.2 years. Carb-S included rice, refined wheat, tubers and their products. Multivariable regression models were used to calculate risk ratios (RRs) for MetS and hyperlipidemia from Carb-S, total carbohydrates and carbohydrates from other food sources (Carb-O). Receiver operating characteristic analysis was used to determine a Carb-S cut-off value. High total carbohydrate intake was associated with increased risks of MetS (RR: 2.24, 95% CI: 1.00–5.03) and hyperlipidemia (RR: 3.05, 95% CI: 1.25–7.45), compared with the first quartile. High Carb-S intake (fourth quartile) was significantly associated with MetS (RR: 1.48, 95% CI: 1.01–2.69) and hyperlipidemia (RR: 1.73, 95% CI: 1.05–3.35). No associations with Carb-O were observed. Visceral adiposity, triglyceride levels and high-density lipoprotein cholesterol significantly contributed to the metabolic disorders. The Carb-S cut-off value was 220 g. Both high total carbohydrate and Carb-S intakes were associated with hyperlipidemia and MetS; Carb-S appears to contribute more to these disorders.