Nomogram for predicting the risk of nonalcoholic fatty liver disease in older adults in Qingdao, China: A cross-sectional study.

BACKGROUND AND OBJECTIVES: To explore the risk factors for non-alcoholic fatty liver disease (NAFLD) and to establish a non-invasive tool for the screening of NAFLD in an older adult population. METHODS AND STUDY DESIGN: A total of 131,161 participants were included in this cross-sectional study. Participants were randomly divided into training and validation sets (7:3). The least absolute shrinkage and selection operator method was used to screen risk factors. Multivariate logistic regression was employed to develop a nomogram, which was made available online. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were used to validate the discrimination, calibration, and clinical practicability of the nomogram. Sex and age subgroup analyses were conducted to further validate the reliability of the model. RESULTS: Nine variables were identified for inclusion in the nomogram (age, sex, waist circumference, body mass index, exercise frequency, systolic blood pressure, fasting plasma glucose, alanine aminotransferase, and low-density lipoprotein cholesterol). The area under the receiver operating characteristic curve values were 0.793 and 0.790 for the training set and the validation set, respectively. The calibration plots and decision curve analyses showed good calibration and clinical utility. Subgroup analyses demonstrated consistent discriminatory ability in different sex and age subgroups. CONCLUSIONS: This study established and validated a new nomogram model for evaluating the risk of NAFLD among older adults. The nomogram had good discriminatory performance and is a non-invasive and convenient tool for the screening of NAFLD in older adults.

Individual and combined associations of alanine aminotransferase and hemoglobin with metabolic syndrome in the elderly in Qingdao, China.

Background and aims: Combined associations of alanine aminotransferase (ALT) and hemoglobin (Hb) with metabolic syndrome (MetS) have not been assessed yet. The current study investigated the independent and combined relationships between ALT, Hb, and MetS in the elderly. Methods: The 37,966 elderly participants aged 65 years and older were recruited from community centers in Qingdao, China. The sampled elderly population visited the health centers once a year where they were offered a free health checkup. Based on a combination of ALT and Hb levels categorized by tertile, participants were grouped into nine groups (Group 1-9). Logistic regression models were used to analyze the individual and combined associations of ALT and Hb with MetS. Results: ALT and Hb were both independently related to MetS in both genders. With the elevation of ALT or Hb levels, risks for MetS and its components increased. Compared to the reference group (the 1st tertiles of both ALT and Hb levels), respective odds ratio of combined ALT and Hb for MetS in Group 2-9 ranged from 1.32-3.38 and 1.14-2.31 in men and women after adjusting for age, sex, education, married status, current smoking, current drinking, physical activity, and diet habit. Conclusion: ALT and Hb were both independently related to MetS and its components. Combined ALT and Hb levels could increase risks of MetS and its components than an elevation in ALT or Hb alone.

Relationship between dietary patterns and prediabetes, undiagnosed or diagnosed diabetes mellitus among adults in Qingdao: A cross-sectional study.

BACKGROUND AND OBJECTIVES: To identify the main dietary patterns of adults and investigate the cross-sectional associations of these dietary patterns with prediabetes and undiagnosed or diagnosed diabetes mellitus (DM) in Qingdao, China. METHODS AND STUDY DESIGN: This study included 4,457 participants who were administered the semi-quantitative food frequency questionnaire (FFQ). Dietary patterns were identified through principal component analysis (PCA). Logistic regression analysis was performed to determine the associations of each pattern with the risks of prediabetes and undiagnosed or diagnosed DM. RESULTS: PCA revealed two major dietary patterns. The Fruits-Vegetables and Poultry-Seafood patterns were not significantly associated with the risk of prediabetes in either crude or adjusted models (all p>0.05). The highest quartile of the Fruits-Vegetables pattern was significantly associated with decreased risks of undiagnosed DM (crude: OR=0.55, 95% CI: 0.41-0.72; Model 1: OR=0.61, 95% CI: 0.46-0.81; Model 2: OR=0.57, 95% CI: 0.42-0.77; Model 3: OR=0.56, 95% CI: 0.41-0.76) and diagnosed DM (crude: OR=0.51, 95% Cl: 0.34-0.75; Model 1: OR=0.59, 95% CI: 0.39-0.88; Model 2: OR=0.60, 95% CI: 0.39-0.93; Model 3: OR=0.59, 95% CI: 0.38-0.91) compared with the lowest quartile in crude and adjusted models. The Poultry-Seafood pattern was not significantly associated with the risk of undiagnosed or diagnosed DM in crude or adjusted models (all p>0.05). CONCLUSIONS: The Fruits-Vegetables pattern was associated with a decreased risk of undiagnosed or diagnosed DM.