BackgroundThe aim of the study was to assess the association between chronic kidney disease (CKD) and obesity in predicting CKD among Chinese adults, distinguishing between 5 different adiposity indices: visceral fat index (VFI), percentage body fat (PBF), body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR).MethodsA total of 29,516 participants aged 35 years or above were selected using a stratified multistage random sampling method across China during 2012–2015. CKD was defined as an estimated glomerular filtration (eGFR) < 60 ml/min/1.72m2.ResultsThe overall weighted prevalence of CKD was 3.94% (3.62% in males and 4.25% in females). All five adiposity indices had significant negative correlations to eGFR (P < 0.05). The area under the ROC (receiver operating characteristic) curves (AUC) for PBF was almost significantly larger than the other adiposity indices (P < 0.001). In addition, PBF yielded the highest Youden index in identifying CKD (male: 0.15; female: 0.20). In the logistic analysis, PBF had the highest crude odds ratios (ORs) in both males (OR: 1.819, 95% CI 1.559–2.123) and females (OR: 2.268, 95% CI 1.980–2.597). After adjusted for age, smoking status, alcohol use, education level, marital status, rural vs. urban area, geographic regions, and diagnosis of hypertension, diabetes mellitus, myocardial infarction and stroke, the ORs on PBF remained significant for both genders (P < 0.05).ConclusionsObesity is associated with an increased risk of CKD. Furthermore, PBF was a better predictor for identifying CKD than other adiposity indices (BMI, WC, WHtR, and VFI).Electronic supplementary materialThe online version of this article (10.1186/s12882-018-0837-1) contains supplementary material, which is available to authorized users.
An evaluation criterion of micro grid is proposed from the perspective of economy, energy conservation and emission reduction. The heterogeneous energy such as cold, heat and electricity based on the micro grid taking combined cooling heating and power as the core was evaluated based on the energy value through the cascade utilization of energy, and the micro-grid optimization model including the micro-turbine, waste heat boiler, lithium bromide absorption chiller, fan and photovoltaic was established. As compared with the model of cost optimization only, its integrated optimization index increased by 11.547% and the efficiency of exergy increased by 14.651%.
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