Can transportation infrastructure improve resource misallocation? Evidence from China.

Transportation infrastructure plays a crucial role in the free movement and rational allocation of resources. Utilizing provincial panel data from China spanning from 2000 to 2017, we employ a dynamic spatial Durbin model (DSDM) and a panel threshold model to analyze the impact of transportation infrastructure on resource misallocation. The findings are as follows: (1) Overall, transportation infrastructure serves to correct misallocations of capital and labor, exhibiting spatial effects; (2) Under the influence of spatial spillover effects, transportation infrastructure improves capital misallocation in neighboring regions, yet exacerbates labor misallocation; (3) The impact of transportation infrastructure on capital and labor misallocations shows regional heterogeneity; (4) Transportation infrastructure indirectly ameliorates resource misallocation through three pathways: opening up to external markets, urbanization, and industrial upgrading; (5) There is a threshold effect of transportation infrastructure on labor misallocation - it only improves labor misallocation when it reaches a certain scale.

[Association Between the Aggregate Index of Systemic Inflammation and Albuminuria: A Cross-Sectional Study of National Health and Nutrition Examination Survey 2007-2018]. / å ¨èº«ç‚Žç—‡ç»¼åˆæŒ‡æ•°ä¸Žç™½è›‹ç™½å°¿çš„å ³è”ï¼šåŸºäºŽ2007­2018å¹´å›½å®¶å¥åº·ä¸Žè¥å »è°ƒæŸ¥çš„æ¨ªæ–­é¢ç ”ç©¶.

Objective: Prior studies have established a connection between albuminuria and various inflammatory reactions, highlighting that an increase in C-reactive protein by 1 mg/L increases the likelihood of albuminuria by 2%. Recent investigations indicate a positive correlation between the systemic immune-inflammation index (SII) and increased urinary protein excretion. In addition, elevated levels of the systemic inflammatory response index (SIRI) also correlate with a higher prevalence of albuminuria. The aggregate index of systemic inflammation (AISI) offers a more comprehensive indicator of inflammation, providing an extensive assessment of systemic inflammatory status compared to SII and SIRI. Yet, the specific relationship between AISI and albuminuria remains unclear. This study aims to explore this association in U.S. adults. Methods: We analyzed data from the National Health and Nutrition Examination Survey (NHANES) for 2007-2018, excluding pregnant women and individuals under 18. Cases with missing data on AISI, urinary albumin concentration, and other covariates were also excluded. AISI was computed using the formula: AISI=(platelet count×neutrophil count×monocyte count)/lymphocyte count. Albuminuria was defined as the urinary albumin-to-creatinine ratio exceeding 30 mg/g. Continuous variables were presented in the form of the mean±standard error, and categorical variables in percentages. We utilized weighted t-tests and chi-square tests for baseline comparisons. We applied weighted multivariable logistic regression and generalized additive models (GAM) to explore the association between AISI and albuminuria and to assess potential nonlinear relationships. Results: The study included 32273 participants, with an average age of (46.75±0.24) years old. The cohort comprised 48.73% males and 51.27% females. The prevalence of albuminuria was 9.64%. The average logarithmic value of log2AISI was 7.95±0.01, and were categorized into tertiles as follows: Quartile 1 (Q1) (4.94 to 7.49), Q2 (7.49 to 8.29), and Q3 (8.29 to 10.85). As log2AISI increased, so did the prevalence of hypertension, diabetes, congestive heart failure, and albuminuria, all showing statistically significant increases (P<0.001). Similarly, the use of antihypertensive, lipid-lowering, and hypoglycemic drugs was also more prevalent (P<0.001). Statistically significant differences were observed across the three groups concerning age, race and ethnicity, formal education, alcohol consumption, smoking status, systolic and diastolic blood pressures, body mass index, estimated glomerular filtration rate, HbA1c, alanine aminotransferase, aspartate aminotransferase, albumin, creatinine, uric acid, and high-density lipoprotein cholesterol (P<0.05). However, no significant differences were noted in the total cholesterol or the sex ratios among the groups. The association between log2AISI and albuminuria was assessed using weighted multivariable logistic regression, and the detailed results are presented in Table 2. In model 1, without adjusting for covariates, each unit increase in log2AISI was associated with a 32% increase in the risk of albuminuria (odds ratio [OR]=1.32, 95% confidence interval [CI]: 1.27-1.38, P<0.001). Model 2 was adjusted for age, gender, race, and education level, and showed a similar trend, with each unit increase in log2AISI associated with a 31% increased risk (OR=1.31, 95% CI: 1.26-1.37, P<0.001). Model 3, which was further adjusted for all covariates, revealed that each unit increase in log2AISI was associated with a 20% increase in the risk of albuminuria (OR=1.20, 95% CI: 1.15-1.26, P<0.001). The study also transformed log2AISI from a continuous to a categorical variable for analysis. Compared with Q1, the risk of albuminuria in Q3, after adjusting for all covariates, significantly increased (OR=1.37, 95% CI: 1.22-1.55, P<0.001). Q2 also demonstrated a higher risk compared with Q1 (OR=1.13, 95% CI: 1.06-1.36, P=0.004). The trend test indicated a dose-effect relationship between increasing log2AISI and the rising risk of albuminuria. GAM revealed a nonlinear relationship between log2AISI and albuminuria, with distinct trends noted between sexes. Segmented regression based on turning points showed significant effects among women, although the slope difference between the segments was not significant. In men, a significant threshold effect was observed; below the log2AISI of 7.25, increases in log2AISI did not enhance the risk of albuminuria, but above this threshold, the risk significantly increased. As part of a sensitivity analysis, weighted multivariable logistic regression was performed by changing the outcome variable to macroalbuminuria and adjusting for all covariates. The analysis showed that for every unit increase in log2AISI, the risk of developing macroalbuminuria increased by 31% (OR=1.31, 95% CI: 1.15-1.49, P<0.001). Compared with Q1, the risk of albuminuria in Q3 increased by 69% (OR=1.69, 95% CI: 1.27-2.25, P<0.001), and in Q2, it increased by 40% (OR=1.40, 95% CI: 1.03-1.92, P=0.030). Subgroup analysis and interaction results showed that the positive association between AISI and proteinuria risk was stronger in men than in women. Similarly, the association was stronger in people with hypertension compared with those with normal blood pressure, and higher in overweight people compared with those of normal weight. Furthermore, smokers and drinkers showed a stronger positive association between AISI and the risk of proteinuria than non-smokers and non-drinkers do. These results suggest that sex, blood pressure, body mass index, smoking, and alcohol consumption interact with AISI to influence the risk of proteinuria. Conclusion: There is a robust positive association between AISI and increased risks of albuminuria in US adults. As log2AISI increases, so does the risk of albuminuria. However, further validation of this conclusion through large-scale prospective studies is warranted.

Association between exposure to metalworking fluid aerosols, occupational noise and chronic kidney disease: a cross-sectional study in China.

BACKGROUND: Chronic kidney disease (CKD) carries a high public health burden yet little is known about the relationship between metalworking fluid (MWF) aerosols, occupational noise and CKD. We aimed to explore the relationship between occupational MWF aerosols, occupational noise and CKD. METHODS: A total of 2,738 machinists were sampled from three machining companies in Wuxi, China, in 2022. We used the National Institute for Occupational Safety and Health (NIOSH) method 5524 to collect individual samples for MWF aerosols exposure, and the Chinese national standard (GBZ/T 189.8-2007) method to test individual occupational noise exposure. The diagnostic criteria for CKD were urinary albumin/creatinine ratio (UACR) of ≥ 30 mg/g and reduced renal function (eGFR < 60 mL.min- 1. 1.73 m- 2) lasting longer than 3 months. Smooth curve fitting was conducted to analyze the associations of MWF aerosols and occupational noise with CKD. A segmented regression model was used to analyze the threshold effects. RESULTS: Workers exposed to MWF aerosols (odds ratio [OR] = 2.03, 95% confidence interval [CI]: 1.21-3.41) and occupational noise (OR = 1.77, 95%CI: 1.06-2.96) had higher prevalence of CKD than nonexposed workers. A nonlinear and positive association was found between increasing MWF aerosols and occupational noise dose and the risk of CKD. When daily cumulative exposure dose of MWF aerosols exceeded 8.03 mg/m3, the OR was 1.24 (95%CI: 1.03-1.58), and when occupational noise exceeded 87.22 dB(A), the OR was 1.16 (95%CI: 1.04-1.20). In the interactive analysis between MWF aerosols and occupational noise, the workers exposed to both MWF aerosols (cumulative exposure ≥ 8.03 mg/m3-day) and occupational noise (LEX,8 h ≥ 87.22 dB(A)) had an increased prevalence of CKD (OR = 2.71, 95%CI: 1.48-4.96). MWF aerosols and occupational noise had a positive interaction in prevalence of CKD. CONCLUSIONS: Occupational MWF aerosols and noise were positively and nonlinearly associated with CKD, and cumulative MWF aerosols and noise exposure showed a positive interaction with CKD. These findings emphasize the importance of assessing kidney function of workers exposed to MWF aerosols and occupational noise. Prospective and longitudinal cohort studies are necessary to elucidate the causality of these associations.

Surrogate endpoints in phase III randomized trials of advanced gastroesophageal cancer: A systematic review and meta-analysis.

Overall survival (OS) is the most meaningful endpoint in clinical trials. However, owing to their limitations, surrogate endpoints are commonly used and validation studies are required to assess their reliability. Analysis of phase III randomized controlled trials (RCTs) of advanced gastroesophageal cancer (AGC) with > 100 patients, correlation coefficients (r), and determination coefficients (R²) between OS and surrogates were evaluated through meta-analyses. Progression-free survival (PFS), time to progression (TTP), and objective response rate (ORR) were examined to determine their correlations with OS. Analysis of 65 phase III RCTs (29,766 subjects) showed a moderate correlation between PFS/TTP and OS (r = 0.77, R² = 0.59), while ORR correlation was low (r = 0.56, R² = 0.31). Excluding immunotherapy trials improved the PFS/TTP and OS correlations (r = 0.83, R² = 0.70). These findings suggest the potential use of PFS/TTP in AGC phase III investigations, disregarding the use of ORR as a surrogate endpoint.

The threshold effect of triglyceride glucose index on diabetic kidney disease risk in patients with type 2 diabetes: unveiling a non-linear association.

Background: Previous studies have confirmed that the triglyceride glucose (TyG) index, recognized as a reliable marker of insulin resistance, is an important risk factor for diabetic kidney disease (DKD). However, it is still unclear whether the DKD risk continues to increase linearly with the elevation of TyG index. This study aimed to thoroughly investigated the intrinsic relationship between TyG index and DKD risk in type 2 diabetes (T2D). Methods: This cross-sectional study included 933 patients with T2D in China, who were categorized into DKD and non-DKD groups and stratified by TyG index levels. Logistic regression analysis identified the independent risk factors for DKD. The association between DKD risk and TyG index was evaluated using the restricted cubic spline (RCS) curves analysis. The R package 'CatPredi' was utilized to determine the optimal cut-off point for the relationship between DKD risk and TyG index, followed by threshold effect analysis. Results: The prevalence of DKD was 33.01%. After adjusting for confounding factors, TyG index was identified as a prominent clinical risk factor for DKD, showing the highest odds ratio (OR 1.57 (1.26 - 1.94), P<0.001). RCS analysis revealed a non-linear relationship with a threshold interval effect between the TyG index and DKD risk. When TyG index ≤ 9.35, DKD risk plateaued at a low level; however, when TyG index > 9.35, DKD risk increased gradually with rising TyG index. Among patients with TyG index > 9.35, each 1-unit increase was associated with a 1.94-fold increased DKD risk (OR=1.94 (1.10 - 3.43), P=0.022). Conclusion: The DKD risk presented a threshold effect with the increase of TyG index, initially stable at a low level, and then gradually rising when the TyG index is above 9.35.

Scale or effectiveness? The nonlinear impact of talent agglomeration on high-quality economic development in China.

Talent agglomeration serves as a vital pathway for achieving high-quality economic development. This paper, based on provincial panel data from China spanning 2011-2020, first analyses the impact of talent agglomeration on high-quality economic development from two dimensions: the talent agglomeration scale and effectiveness. Second, with innovation activity as a threshold variable, this paper explores the nonlinear impact of the talent agglomeration scale and effectiveness on economic efficiency improvement and economic structure optimization. This study finds that (1) the main driving force for high-quality economic development within the sample period comes from the talent agglomeration scale, while the promoting role of talent agglomeration effectiveness has not yet passed significant tests. (2) Under different levels of innovation activity, the talent agglomeration scale has a diminishing marginal utility impact on economic efficiency improvement and economic structure optimization; talent agglomeration effectiveness also has different nonlinear effects on economic efficiency improvement and economic structure optimization.

The Relationship Between the Average Decreased Times of Estradiol and Early Miscarriage: An Observational Study.

Decreased estradiol (E2) levels are associated with early miscarriage (EM), but the relationship between decreased times of E2 and EM has not been reported. We aimed to investigate the relationship between the average decreased times of E2 (ADTE) and EM. Women with a history of miscarriage were retrospectively recruited from the Reproductive Center of Lanzhou University Second Hospital (Lanzhou, China) between September 2019 and February 2022. Based on pregnancy outcome, they were divided into ongoing pregnancy group (n = 359) and EM group (n = 104). In addition, subgroup analyses were performed for the number of previous miscarriages and whether E2 levels decreased continuously. The exposure and outcome variables were ADTE and miscarriage before 12 weeks of gestation, respectively. Totally, 1171 patients were recruited and 463 patients were finally analyzed. ADTE was associated with EM (odds ratio [OR] = 1.346, 95% confidence interval [CI]1.154-1.571, P < 0.001). When ADTE ≥ 2.5, the EM risk increased 1.17-fold compared to patients with 0-1.249 times (OR = 2.170, 95% CI 1.144-4.117, P = 0.018). Moreover, a threshold effect existed in the ADTE and the risk of EM with a value of 4.9 times. When exceeding 4.9 times, the EM risk increased 4.713-fold for each increased unit (OR = 5.713, 95% CI 1.255-23.170, P = 0.024). Subgroup analysis showed that ADTE had a greater effect on the occurrence of EM in women with a history of 1-2 miscarriages than in women with 3 miscarriages. Decreased E2 was a risk factor for EM regardless of whether it dropped continuously or not. In conclusion, our study identifies a potential link between ADTE and early miscarriage risk in women with prior miscarriages, yet cautious interpretation is necessary due to inherent design limitations. Further research with prospective designs and large population samples is essential to validate ADTE's utility as a predictive indicator for early miscarriage in clinical settings.

Relationship between triglyceride-glucose index and blood eosinophils among asthmatic individuals in the USA.

BACKGROUND: Presently, the majority of investigations primarily evaluate the correlation between triglyceride-glucose index (TyGI) with lung diseases, such as asthma. However, they did not delve into the correlation between TyGI and inflammatory responses related to the disease. Few studies have explored the association between TyGI and blood eosinophil count (BEOC). Thus, National Health and Nutrition Examination Survey (NHANES) data were used in this study to evaluate the correlation between TyGI and BEOC in individuals with asthma. METHODS: This study investigated 3902 individuals with asthma. Linear regression analysis was performed to investigate the association between TyGI and BEOC in patients with asthma. Subsequently, the GAM and threshold effect models were used to validate the presence of either a nonlinear or linear association between TyGI and BEOC. Finally, stratified analyses were conducted to ascertain the correlations between different subgroups. RESULTS: Four linear regression models confirmed a positive linear correlation between TyGI and BEOC in patients with asthma. In Model D, which controlled for all covariates, BEOC increased by 12.44 cells/uL for every extra unit of TyGI. The GAM and threshold effect models further verified the positive linear correlation between TyGI and BEOC. The XGBoost model indicated that the six most significant variables influencing BEOC, in order of relative importance, were age, cholesterol level, body mass index (BMI), poverty-to-income ratio (PIR), BNEUC, and TyGI. CONCLUSIONS: In patients with asthma, the study discovered a linear positive correlation between TyGI and BEOC. This indicates a potential connection between TyGI and alterations in the immune status of individuals with asthma, which may help detect abnormalities in a timely manner and provide a reference for clinical decision-making. This study offers fresh insights for the future exploration of the management and treatment of asthma.

Impact of agricultural digitalization on carbon emission intensity of planting industry: Evidence from China.

Studying the impact of agricultural digitalization (ADT) on the carbon emission intensity of planting industry (PCI) can help promote sustainable development and realize the "dual carbon" goal. Based on the panel data of 31 provinces in China from 2010 to 2020, this study uses the entropy weight method and emission coefficient method to measure the development level of ADT and PCI, respectively. By using the regression analysis method, as well as the robustness test, heterogeneity test, and spatial spillover effect and threshold tests, the impact of ADT on PCI was examined. The results are as follow: (1) PCI is high in the north and low in the south, and the north-south divide is becoming prominent. (2) ADT in China can significantly reduce PCI, as verified through the robustness test. (3) Regional differences exist in the impact of ADT on PCI, with the most significant effect observed in the northeast region, followed by the western and central regions. (4) ADT exerts a significant spatial spillover effect on PCI and an inhibitory effect on PCI of adjacent provinces. (5) The proportion of urban population exerts a threshold effect in the impact of ADT on PCI. When the urban population ratio crosses 69 %, the inhibitory effect of agricultural carbon emissions decreases marginally. Therefore, promoting the green and low-carbon development of the planting industry is highly recommended.

Threshold and combined effects of heavy metals on the risk of phenotypic age acceleration among U.S. adults.

Accumulation of heavy metals in the body has been shown to affect the phenotypic age (PhenoAge). However, the combined and threshold effects of blood heavy metals on the risk of PhenoAge acceleration (PhenoAgeAccel) are not well understood. A cross-sectional study was conducted using blood heavy metal data (N = 7763, age ≥18 years) from the 2015-2018 National Health and Nutrition Examination Survey. PhenoAgeAccel was calculated from actual age and nine biomarkers. Multiple regression equations were used to describe the relationship between heavy metals and PhenoAgeAccel. Least Absolute Shrinkage and Selection Operator (LASSO) regression modeling was used to explore the relationship between the combined effects of heavy metals and PhenoAgeAccel. Threshold effect and multiple regression analyses were performed to explore the linear and nonlinear relationships between heavy metals and PhenoAgeAccel. Threshold effect analysis showed that blood mercury (Hg) concentration was linearly associated with PhenoAgeAccel. In contrast, lead (Pb), cadmium (Cd), manganese (Mn), and combined exposure were nonlinearly associated with PhenoAgeAccel. In addition, the combination of Pb, Cd, Hg, and Mn significantly affected PhenoAgeAccel. The risk of PhenoAgeAccel was increased by 207% (P < 0.0001). Meanwhile, a threshold relationship was found between blood Pb, Cd, Mn, and the occurrence of PhenoAgeAccel. Overall, our results indicate that combined exposure to heavy metals may increase the risk of PhenoAgeAccel. This study underscores the need to reduce heavy metal pollution in the environment and provides a reference threshold for future studies.

Research on the impact of ESG performance on carbon emissions from the perspective of green credit.

Utilizing panel data from 30 Chinese provinces, this research examines the non-linear relationship between regional environmental, social, and governance (ESG) performance and carbon emissions (CE) from the viewpoint of green credit. The study reveals a single threshold effect between ESG performance and CE, with green credit acting as the threshold variable. When the amount of green credit in a region exceeds the threshold, the growth rate of CE in that region begins to decline with higher ESG scores. Furthermore, green credit acts as a catalyst, playing a negative moderating role between ESG performance and CE, validated by both threshold regression and fixed effects models on panel data. Green credit indirectly influences carbon emissions by supporting green innovation, thus facilitating the transition to a greener economic development framework. Lastly, regional disparities are found in the moderating influence of green credit between ESG performance and CE. In regions with high ESG performance, the moderating impact of green credit is smaller, while in regions with low ESG performance, the effect is more significant. The research findings offer theoretical backing for policymakers regarding the efficacy of ESG in achieving carbon neutrality objectives, and offer valuable strategic recommendations for the diversified formulation of green credit strategies on both national and provincial scales. Regional heterogeneity test results provide valuable support for formulating policies that encourage green credit in provinces with low ESG performance.

Digital financial inclusion and upgrading of consumption structure: Evidence from rural China.

Based on the perspective of spatial economy, this paper focuses on the primary effects and spatial characteristics of Digital Financial Inclusion (DFI) on the upgrading of rural consumption structure (URCS) in China, conducting a literature review and theoretical analysis. It then uses statistical data collected over the years and the Digital Financial Inclusion Index (DFII) of Peking University to prepare panel data for 31 provinces in China (aside from Hong Kong, Macao, and Taiwan) from 2011 to 2020 for empirical testing. The results are as follows: DFI can considerably boost URCS, and there is a strong spatial neighbor impact, that is, it is affected by random shocks in surrounding provinces via its spatial effect; DFI has nonlinear characteristics in the process of fostering URCS, with the threshold variables of income level and family sizes; the impact of DFI on URCS is spatially heterogeneous, and the promotion of the eastern region is better than other zones. These results can inform policymakers about rural development and provide valuable references to push forward rural vitalization.

Environmental regulation influences urban land green use efficiency: Incentive or disincentive effect? Evidence from China.

China's crude economic development has led to high pollution and inefficiency of urban land use. Environmental regulation (Er) is crucial for governments to promote green growth and efficient land use. Using a dataset of 271 cities in China from 2011 to 2020, this paper investigates the threshold effect of green innovation in science and technology and industrial structure optimization on Er impacts of urban land green use efficiency (Ulee). The results show that (1) Er positively affects Ulee. (2) There is a threshold effect of green innovation in science and technology (Gin) and industrial structure upgrading (Ind) in Er affecting Ulee, and the force decreases as the threshold value increases. (3) Within the examination of heterogeneity, the impact of Er on Ulee is more significant in eastern, high levels of urbanization and large cities, but the force of action is smaller. Based on the nonlinear force of Er, it is crucial to maximize the effectiveness of green land use by giving full play to the interactive synergistic effect of the "combination box" and dynamically and flexibly adjusting the intensity of Er according to the time, place, and state of urban development.

Association of Life's Essential 8 with all-cause mortality and risk of cancer: a prospective cohort study.

BACKGROUND: No study has concentrated on the association of LE8 with cancer risk and death. We aim to examine the association of LE8 with death and cancer. METHODS: A total of 94733 adults aged 51.42 ± 12.46 years and 77551 participants aged 54.09±12.06 years were enrolled in longitudinal and trajectory analysis respectively. Baseline LE8 was divided into three groups based on the American Heart Association criteria and three trajectory patterns by latent mixture models. We reviewed medical records and clinical examinations to confirm incident cancer during the period from 2006 to 2020. Death information was collected from provincial vital statistics offices. Cox models were used. RESULTS: 12807 all-cause deaths and 5060 cancers were documented during a 14-year follow-up. Relative to participants with high LE8 at baseline, participants with lower levels of LE8 have a significantly increased risk of mortality and incident cancer. All these risks have an increasing trend with LE8 level decreasing. Meanwhile, the trajectory analysis recorded 7483 all-cause deaths and 3037 incident cancers after approximately 10 years. The associations of LE8 with death and cancer were identical to the longitudinal study. In the subtype cancer analysis, LE8 has a strong effect on colorectal cancer risk. Moreover, the cut point is 56.67 in the association between LE8 and death, while the cut point altered to 64.79 in the association between LE8 and incident cancers. These associations were enhanced among younger adults. CONCLUSIONS: There was a significant association of LE8 with death and cancer risk, especially for the young population.

Non-linear relationship between preoperative albumin-globulin ratio and postoperative pneumonia in patients with hip fracture.

BACKGROUND AND OBJECTIVE: Postoperative pneumonia (POP) is the leading cause of death among patients with hip fractures. Simple and cost-effective markers can be used to assess the risk of these patients. This study aims to investigate the association between POP and preoperative albumin-globulin ratio (AGR) in patients with hip fractures. METHODS: A retrospective analysis was conducted on data from 1417 hip fracture patients admitted to the Department of Orthopaedics at the hospital. Generalized additive and logistic regression models were used to determine both linear and non-linear associations between preoperative AGR and POP. A two-piece regression model was employed to determine the threshold effect. RESULTS: The study included 1417 participants, with a mean age of 77.57 (8.53) years and 26.96% (382/1417) male patients. The prevalence of POP was 6.21%. Following full covariate adjustment, each unit increase in AGR was associated with a 79% reduction in the incidence of POP (OR, 0.23; 95% CI: 0.08-0.63; P = 0.0046). The inflection point was found to be 1.33 using a two-piecewise regression model. For each unit increase in AGR on the left side of the inflection point, the incidence of POP decreased by 93% (OR, 0.07; 95%CI: 0.02-0.34; P = 0.0010). However, there was no statistically significant correlation on the right side of the inflection point (OR, 0.84; 95% CI: 0.17-4.10; P = 0.8287). CONCLUSION: There exists a non-linear association between preoperative AGR and the incidence of POP in elderly hip fracture patients. When AGR is less than 1.33, the incidence of POP is negatively correlated with AGR. However, there is no correlation when AGR is greater than 1.33.

Impact of age, sex, and thyroid autoimmunity on the association between selenium intake and type 2 diabetes mellitus.

BACKGROUND: The association between dietary selenium(Se) intake and type 2 diabetes mellitus (T2DM) remains controversial. The present study aimed to investigate this association using data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2007-2012. METHODS: Three thousand seventy three individuals aged 20 years and above were eligible for inclusion in this cross-sectional study. The average age of the participants was 50.74 years and the proportions of males and females were nearly equal (49.12% vs. 50.88%). The odds ratios (OR) of the association between dietary Se intake (log2-transformed) and T2DM were examined through the multivariate logistic regression model. Subgroup analyses were conducted based on age, sex, and thyroid autoimmunity to assess the potential impact of these variables on the relationship. Fitted smoothing curves and threshold effect analysis were conducted to describe the nonlinear relationship. RESULTS: In the fully adjusted model, a significant positive association between Se intake and T2DM was observed (OR = 1.49, 95% CI: 1.16, 1.90, p = 0.0017). After stratifying the data by age, sex, and thyroid autoimmunity, a significant positive association between Se intake and T2DM was observed in individuals under 65 years of age, males, and those with negative thyroid autoimmunity. A two-segment linear regression model was analyzed for sex stratification, revealing a threshold effect in males with an inflection point of 90.51 µg, and an inverted U-shaped relationship in females with an inflection point of 109.90 µg, respectively. CONCLUSIONS: The present study found a positive relationship between Se intake and the prevalence of T2DM. This association is particularly significant in younger individuals, males, and those with negative thyroid autoimmunity. Our results should be validated in future large prospective studies in different populations.

Promoting sustainable development: Revisiting digital economy agglomeration and inclusive green growth through two-tier stochastic frontier model.

In the global wave of digitization, digital economic agglomeration, as an emerging model, profoundly impacts the economy, environment, and society. Countries worldwide are formulating strategies and policies to promote the development of digital economic agglomeration, yet they also face challenges of widening digital divide and environmental sustainability. Existing research primarily focuses on the positive effects of the digital economy, with limited assessment of the dual effects of digital economic agglomeration on sustainable development. This study utilizes panel data from 282 Chinese cities between 2011 and 2021, employing a two-tier stochastic frontier model. It reexamines the dual impacts and intrinsic mechanisms of digital economic agglomeration, attempting to capture regional and temporal variations in the dual effects to address this research gap. The study shows that: (1) The positive effect of digital economy agglomeration is much more than the negative effect, resulting in a positive net effect that shows an overall increasing trend with significant regional disparities. (2) Digital economic agglomeration has a significant negative spatial spillover effect, promoting local inclusive green growth while inhibiting inclusive green growth in neighboring cities. (3) Regarding the mediating mechanisms, industrial structure, technological innovation and resource allocation efficiency have positive indirect effects on inclusive green growth, while environmental regulation intensity has a negative indirect effect, and it has a nonlinear effect under the threshold constraint of the mediating mechanisms. This study provides policy insights for promoting inclusive green growth, emphasizing the need to consider regional differences in resource distribution, ecological environment, and social demands. It advocates for the organic integration of the digital economy across different regions, reducing polarization effects, and enhancing diffusion effects.

Environmental regulation, land use efficiency and industrial structure upgrading: Test analysis based on spatial durbin model and threshold effect.

Environmental regulation promotes industrial structure change and regional economic transformation through land use adjustment, which gets a new way to explore the path of reforming traditional industrialization and urbanization. Based on the panel data of 128 prefecture-level cities in China 's Yangtze River Economic Belt from 2000 to 2020, this paper uses the spatial Dubin model to analyze the impact of environmental regulation and land use efficiency on the upgrading of industrial structure, and sets the panel threshold model to examine the impact of environmental regulation on the upgrading of industrial structure by affecting land use efficiency. The results show that formal environmental regulation has a significant positive spatial effect on the rationalization and upgrading of industrial structure, which are 0.1734 and 0.2854 respectively. Informal environmental regulation has a negative spillover effect on neighboring provinces but not significant. Heterogeneous environmental regulation has obvious "double threshold effect" on industrial upgrading by affecting land use efficiency. When the threshold of environmental regulation intensity is 0.0315-0.0886, environmental regulation still inhibits land use efficiency and industrial structure upgrading. When the threshold value is greater than 0.0886, environmental regulation has a positive impact on land use efficiency but not significant. With the intensity of environmental regulation from weak to strong, it will produce a double threshold effect of "strong inhibition-weak inhibition-interaction promotion" on the upgrading of manufacturing structure through the adjustment of land use efficiency.

How artificial intelligence affects the labour force employment structure from the perspective of industrial structure optimisation.

To investigate how artificial intelligence (AI) affects the structure of labour force employment, we integrate robotics adoption and employment into this study's model. Based on Chinese provincial panel data from 2010 to 2019, fixed, mediating and threshold effects models and a spatial heterogeneity model were used to empirically test the impact of AI on the employment structure from the perspective of industrial structure optimisation and its mechanisms of action. The findings demonstrate that the impact of AI on the labour force employment structure reflects unique characteristics for China and promotes the advancement of the nation's employment structure. The influence of AI on the labour force employment structure follows a non-linear pattern, fostering labour force employment structure optimisation and upgrading from the perspective of industrial structure optimisation. Further investigation reveals the influence of spatial spillover effects from AI on employment structure optimisation. These research findings have theoretical value and practical significance for optimising China's employment structure in the context of AI.

The impact of green-listed companies on rural ecological environments in China: A spatial heterogeneity and empirical analysis.

Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010-2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions.