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We investigated the prevalence and clinical metabolic characteristics of lean nonalcoholic fatty liver disease (NAFLD) in an elderly Chinese population and assessed the relevance of lipid markers and genetic variation. All 5,338 community subjects underwent detailed clinical and laboratory examinations and were divided into three groups: lean (Body mass index (BMI) < 23 kg/m2, n = 2,012), overweight (BMI = 23–24.9 kg/m2, n = 1,354), and obese (BMI ≥ 25 kg/m2, n = 1,972). Single nucleotide polymorphisms were selected based on those reported in previous NAFLD or obesity genome-wide association studies. The frequencies of alleles and genotypes were calculated and statistically analyzed with Pearson's χ2 tests. One-way ANCOVA was used to test the association between positive SNPs and metabolic parameters in lean NAFLD individuals. Our results showed that the C allele frequency of rs2279026, the G allele of rs2279028, the C allele of rs780093, and the C allele frequency of rs1260326 were higher in obese NAFLD than in lean NAFLD (P < 0.05). In addition, we observed an association between the CC of rs1421085, TT of rs3751812, AA of rs8050136, and AA of rs9939609 genotypes in the FTO gene and low-density lipoprotein levels (P < 0.05). In conclusion, our findings provide a unique perspective on the prevalence, genetic characteristics, and metabolic profile of NAFLD in older lean individuals in China. This is the first study to examine the association between genetic variants in the FTO, TFAP2B and GCKR genes and NAFLD in a cohort of lean individuals. [ABSTRACT FROM AUTHOR]

Background: Dyslipidaemia is a risk factor for abnormal blood glucose. However, studies on the predictive values of lipid markers in prediabetes and diabetes simultaneously are limited. This study aimed to assess the associations and predictive abilities of lipid indices and abnormal blood glucose. Methods: A sample of 7667 participants without diabetes were enrolled in this cross-sectional study conducted in 2016, and all of them were classified as having normal glucose tolerance (NGT), prediabetes or diabetes. Blood glucose, blood pressure and lipid parameters (triglycerides, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; and triglyceride glucose index, TyG) were evaluated or calculated. Logistic regression models were used to analyse the association between lipids and abnormal blood glucose. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of lipid parameters for detecting prediabetes or diabetes. Results: After adjustment for potential confounding factors, the TyG was the strongest marker related to abnormal blood glucose compared to other lipid indices, with odds ratios of 2.111 for prediabetes and 5.423 for diabetes. For prediabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.605, 0.617, 0.481, 0.615, 0.603, 0.590, 0.626 and 0.660, respectively, and the cut-off points were 1.34, 4.59, 1.42, 2.69, 3.39, 1.00, 3.19 and 8.52, respectively. For diabetes, the AUCs of the TG, TC, HDL-C, LDL-C, TC/HDL-C, TG/HDL-C, non-HDL-C and TyG indices were 0.712, 0.679, 0.440, 0.652, 0.686, 0.692, 0.705, and 0.827, respectively, and the cut-off points were 1.35, 4.68, 1.42, 2.61, 3.44, 0.98, 3.13 and 8.80, respectively. Conclusions: The TyG, TG and non-HDL-C, especially TyG, are accessible biomarkers for screening individuals with undiagnosed diabetes. [ABSTRACT FROM AUTHOR]

Background: Obesity is associated with the development of polycystic ovary syndrome (PCOS) and contributes substantially to metabolic abnormalities in women with PCOS. The study aimed to describe and compare the practices of physicians in the diagnosis, evaluation, and treatment of obesity in patients with PCOS. Methods: Reproductive endocrinologists (Repro-Endo) and obstetrician-gynecologists (non-reproductive medicine specialty, OB-Gyn) in China participated in a survey, and their responses were analyzed using χ2 tests, Fisher exact tests, and multivariable logistic regression analysis. Results: The study analyzed 1318 survey responses (85.8% OB-Gyn; 97.3% women). Body mass index was the most common diagnostic criterion for obesity; only 1.3% of participants measured waist circumference to identify abdominal obesity. More Repro-Endo participants (25% of all participants) enquired about the psychological problems of patients with obesity than OB-Gyn participants, and 42.5% of participants reported ordering both a lipid profile and oral glucose tolerance test (OGTT) for patients with obesity and PCOS. Multivariable analysis, that included physician's specialty, age, hospital grade, and number of patients with PCOS seen annually, revealed that OB-Gyn participants were less likely to order OGTT (OR, 0.3; 95% CI, 0.2–0.4) and lipid profile (OR, 0.2; 95% CI, 0.1–0.3) than Repro-Endo participants. The most common treatments for patients with PCOS were lifestyle modification (> 95%) and metformin (> 80%). More Repro-Endo participants prescribed metformin at a dose of 1.5 g/day compared with OB-Gyn (47.6% vs. 26.3%), and more OB-Gyn participants reported being unclear about the appropriate dosage of metformin for patients with obesity and PCOS (8.9% vs. 1.6%). Conclusion: Our survey identified knowledge gaps in metabolic screening for patients with obesity and PCOS and a disparity in the evaluation and treatment of obesity in PCOS among different specialties. Similarly, it highlights the need to improve obesity management education for physicians caring for women with PCOS. [ABSTRACT FROM AUTHOR]