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Background: Insulin resistance (IR) and metabolic syndrome (MetS) are significant global health challenges that increase the risk of various chronic diseases. The lymphocyte-to-high-density lipoprotein cholesterol ratio (LHR) has emerged as a novel inflammatory metabolic marker. The present study focused on evaluating the association between the LHR and both IR and MetS. Methods: We analyzed data from 14,779 adults aged ≥ 20 years from the National Health and Nutrition Examination Survey (2007–2018). To investigate the relationship between LHR and both IR and MetS, we conducted multivariable logistic regression analyses. The reliability of the results was validated through both stratified and sensitivity analyses. Furthermore, we thoroughly examined possible nonlinear associations by implementing a restricted cubic spline in conjunction with a threshold effect analysis. Results: Compared to the lowest LHR quartile, individuals in the highest quartile indicated significantly increased prevalence of IR (odds ratio = 3.72, 95% confidence intervals: 3.01–4.59) and MetS (odds ratio = 11.38, 95% confidence intervals: 8.85–14.63) in fully adjusted models. Subgroup analyses demonstrated that the association between the LHR and IR remained consistent across all subgroups, with no significant interaction effect observed. However, the association between LHR and MetS was more pronounced in female participants. Restricted cubic spline analyses revealed nonlinear associations between LHR and both IR and MetS. The threshold effect analyses identified inflection points at 0.055 for these non-linear relationships. Conclusions: An elevated LHR was positively associated with the prevalence of IR and MetS, indicating its promising role in early screening and disease prevention through biological monitoring. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the association of the triglyceride-glucose index (TyG) and its related parameters with the risk of hyperuricemia in patients with obesity of different sexes. Patients and Methods: In this cross-sectional study, a total of 951 patients with obesity were included. They were divided into two groups based on their serum uric acid levels, and separate analyses were conducted for males and females. Binary logistic regression analysis using the backward likelihood ratio (LR) approach was performed to investigate the association between hyperuricemia and indicators related to obesity and lipids. Results: Multivariate logistic regression analysis indicated that, across the overall population, higher quartiles of the TyG and TyG-BMI indexes were significantly associated with an increased risk of hyperuricemia (HUA) after adjusting for confounding factors. Specifically, in the fourth quartile of the TyG index, the odds ratio (OR) for HUA was 3.16 (95% confidence interval [CI]: 1.39– 7.18), and for the TyG-BMI index, the OR was 4.06 (95% CI: 1.73– 9.52) in the fully adjusted model. In sex-specific analyses, for males, those in the third quartile of the TyG-WC index had a higher likelihood of HUA (OR, 8.13; 95% CI, 2.28– 29.01) compared to the lowest quartile. Among females, an elevated TyG index was significantly associated with increased HUA risk, with an OR of 5.13 (95% CI: 1.66– 15.92) in the fourth quartile. Conclusion: Sex-based differences exist regarding the risk factors for hyperuricemia in patients with obesity. An elevated TyG-WC index is linked to an increased risk in males, while an elevated TyG index is associated with an increased risk in females. [ABSTRACT FROM AUTHOR]

Water scarcity poses a significant threat to global supply chains. This study identifies critical sectors and pathways that transmit water scarcity risks using network analysis and a global trade model. Findings show that a few sectors, particularly in China, transmit most global water scarcity risks, with the top 10% responsible for over 60% of the total. Moreover, the rankings of sectors with respect to centrality for transmitting water scarcity risks and centrality for transmitting economic values largely resemble each other, with a Kendall rank correlation coefficient 0.8231 (p < 10−15). Lastly, sectors with high water risk intensity are typically found in Europe. Our findings the need for strategic sector management to mitigate global vulnerabilities. Governments should encourage high-centrality sectors to choose suppliers less exposed to water scarcity risks, while downstream sectors and firms should assess the risks embedded in their inputs. [ABSTRACT FROM AUTHOR]

Aims: To describe weight management and perceptions in China. Materials and methods: Data were from the Adelphi Real World Obesity Disease Specific Programme™, a cross-sectional survey between April and July 2022 of physicians managing people with obesity or overweight (PwO) and PwO in real-world clinical practice in China. At data collection, eligible PwO were aged ≥18 years, under weight management and/or had a body mass index (BMI) ≥28 kg/m2. Results: In total, 100 physicians and 801 PwO were enrolled. More than two thirds of PwO (70.7%; 531/751) were not diagnosed with obesity until a BMI ≥30 kg/m2. Most PwO (78%; 625/801) were on treatment for at least one obesity-related complication (ORC). Physicians commonly initiated weight loss discussions with PwO who already had an ORC (48.0%; 48/100). According to physicians and PwO, the mean target BMI was set at 25.8 kg/m2 and 24.3 kg/m2, and the mean target percentage weight loss was 19.6% and 23.7%, respectively. Over a median 6.4 months of weight management, the mean percentage weight loss was 4.1%. Few PwO achieved the weight loss target set by their physician (9.9%; 69/695) or themselves (2.0%; 14/696). Most physicians and PwO were unsatisfied with the current weight loss (92.3% [739/801] and 82.0% [650/793], respectively). Conclusions: These findings suggest that earlier intervention may be needed to address obesity as a disease. Most physicians and PwO recognized the importance of normal weight, but few PwO achieved weight loss targets, which may suggest an unmet need for improved weight management. [ABSTRACT FROM AUTHOR]

Objectives Arterial stiffness (AS), one of the complications of diabetes, associated with many metabolic factors. This study aimed to investigate the association between 25-hydroxyvitamin D(25(OH)D) and AS in type 2 diabetes mellitus (T2DM). Methods We identified 1335 diabetic patients from the Department of Endocrinology, Shanghai Tenth People's Hospital. Finally, 603 T2DM patients were included in the study. They were divided into two groups: AS group (baPWV [greater than or equal to] 15,500 cm/s) and the control group (baPWV < 1550 cm/s). Results (1) Heart rate (HR) and systolic pressure (SBP) were higher while body weight and body mass index (BMI) were smaller in AS group than the control group (all P < 0.05). (2) Compared to patients without AS, patients with AS showed lower 25(OH)D and higher rate of 25(OH)D deficiency (42 [plus or minus] 16 vs. 45 [plus or minus] 17 mol/l, 68% vs. 64%, all P < 0.05). (3) BaPWV was negatively associated with 25(OH)D (r = -0.12, P = 0.004), while positively associated with age, duration of diabetes, HR, SBP, and low-density lipoprotein cholesterol and negatively associated with body weight and BMI (all P < 0.05). (4) Multiple linear regression showed that 25(OH)D was the negatively influencing factor of baPWV ([beta] = -2.2, P = 0.01). Logistic regression showed that age and SBP were risk factor of AS (OR:1.07, 95% CI: 1.05-1.10, P < 0.001; OR:1.03, 95% CI: 1.02-1.04, P < 0.001) while 25(OH)D was protective factor of AS (OR:0.987, 95% CI: 0.976-0.998, P = 0.024). Conclusions T2DM patients with AS had lower 25(OH)D and higher rate of 25(OH)D deficiency. There was a negative relationship between 25(OH)D and AS assessed by baPWV., Author(s): Bingwei Ma [sup.1] [sup.2] , Yao Chen [sup.3] , Chunjun Sheng [sup.4] , Peng Yang [sup.4] , Xingchun Wang [sup.4] , Shen Qu [sup.1] [sup.4] Author Affiliations: (1) Department [...]

Corporate leverage is an indicator of economic health, and this topic has attracted a great deal of attention since the international financial crisis of 2008. This paper constructs a model of enterprise decision-making under a digital government and theoretically analyzes how the government digital reform impacts corporate leverage and the mechanism of this impact. Theoretical analysis has previously shown that digital reforms by governments help to ease the information asymmetry between banks and enterprises, which in turn affects the actual economic activities of enterprises. Based on these findings, the "one-stop government service" natural experiment used in this paper and the empirical analysis using a multiphase difference-in-differences (DID) method show that digital government can inhibit the short-term debt financing of enterprises while improving their long-term debt financing. This study further finds that the digital government can improve the level of long-term debt for long-term use, thereby reducing corporate leverage. By enriching the theoretical and empirical research on government digital reform, this paper contributes significant theoretical and practical insights to the literature on corporate leverage in the context of government factors. [ABSTRACT FROM AUTHOR]

The input–output (IO) model can be used to examine the flow of products and services within an economy, resembling a network with industries as nodes and transactions as links. Diverging significantly from commonly studied networks such as social, protein, and power grids, IO networks exhibit intricate interconnectivity, involving weighted nodes and both directional and weighted links. This uniqueness necessitates careful consideration when applying complex network analysis techniques to IO systems. We critically review current complex network metrics and attempt to link them with existing IO approaches. Based on our assessment, certain network metrics, such as degree centrality and eigenvector centrality, have been explicitly integrated into the IO theory. In contrast, there exist metrics whose definitions and interpretations expand when applied in the context of IO analysis, including closeness and betweenness centrality. Additionally, network metrics are usually used to study topological features, identify key sectors, and construct novel metrics to study related issues. Network metrics used in IO analysis can identify important driver and transmission sectors in resource flow and environmental emission network, facilitating the development of targeted and reliable strategies. Besides, network metrics are used to quantify topological features and structural changes of the IO network which help strengthen the supply chain and mitigate both direct and indirect impacts of disruptions. Our ultimate goal is to establish connections and offer a roadmap for developing network‐based tools in IO analysis. [ABSTRACT FROM AUTHOR]