Exposure to Multiple Metal(loid)s and Hypertension in Chinese Older Adults.

Evidence about effects of metal(loid)s on hypertension among adults is insufficient. The aim of our study was to evaluate the individual and joint associations between seven selected metal(loid)s and hypertension, including lead (Pb), manganese (Mn), nickel (Ni), arsenic (As), cadmium (Cd), chromium (Cr), and vanadium (V)) in Chinese older adults. This study included 1009 older adults, and the blood concentrations of seven metal(loid)s were evaluated by inductively coupled plasma mass spectrometry (ICP-MS). The following conditions were considered as hypertension: (1) either systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg, (2) a self-reported history of hypertension, or (3) currently taking antihypertensive medications. Logistic regression was utilized to investigate the association between individual metal(loid) and hypertension, while Bayesian kernel machine regression (BKMR) was employed to investigate the association of the metal(loid) mixture with hypertension. Adjusted single-metal(loid) model showed a significant positive association between Pb and hypertension (OR = 1.24, 95%CI = 1.03-1.50). This significant association still existed in multi-metal(loid) model (OR = 1.22, 95%CI = 1.01-1.47). BKMR further indicated a positive linear association of Pb with hypertension. The metal(loid) mixture was positively associated with hypertension in older adults, although not significant. Within the mixture, Pb had the highest posterior inclusion probabilities value (PIP = 0.9192). There were multiplicative interactions of Pb and Mn on hypertension. In addition, Pb and Mn had additive effects on the association of other blood metal(loid)s with hypertension. The associations of multiple metal(loid)s with hypertension are dependent on diabetes, areas, age, and BMI. The metal(loid) mixture exposure may contribute to hypertension in Chinese older adults, mainly driven by Pb and interactions of Pb and Mn. Reducing exposure to these metal(loid)s may prevent hypertension among older adults, which is especially true for those living with diabetes.

The Association Between the Non-essential Metal Mixture and Handgrip Strength in Chinese Community-Dwelling Older Adults.

There is limited research on the effects of non-essential metal (NEM) mixture on handgrip strength in the elderly. This study aimed to assess the associations of single NEMs and their mixture with handgrip strength in Chinese community-dwelling older adults. A total of 3807 elderly people aged 60 years or above were included in this study. Measurement of urinary aluminum (Al), arsenic (As), barium (Ba), cadmium (Cd), and gallium (Ga) concentrations was conducted by inductively coupled plasma mass spectrometry (ICP-MS). Handgrip strength was measured using a hand dynamometer. Four statistical models, including general linear regression and generalized additive models (GAMs), as well as Bayesian kernel machine regression (BKMR) and quantile-based computation regression (QGC) models, were used to assess the individual and joint effects of urine NEMs with handgrip strength, respectively. After adjusting for covariates, Ga (ß = - 0.27; 95% CI, - 0.54 ~ - 0.01) and As ( ß  = - 0.34; 95% CI, - 0.61 ~ - 0.07) were negatively associated with handgrip strength. The GAMs and BKMR further suggested that the negative associations of Ga and As with handgrip strength were linear and inverted U-shaped, respectively. The BKMR and QGC models showed that the NEM mixture was negatively related to handgrip strength, with Ga and As contributing the most within the mixture. Moreover, we also observed an interaction between As and Ga on handgrip strength. Longitudinal studies are needed to verify these findings.

Predicting the risk of arsenic accumulation in soil-rice system in Asian monsoon region.

Rice is a staple food for a significant portion of the global population. Arsenic (As) accumulated in rice grains influences rice quality which threatens human health. In this study, we used three machine learning models to predict arsenic accumulation in rice based on over 300 surveys. The prediction results of soil arsenic indicate that high-arsenic soil areas are mainly distributed in South and Southeast Asia such as India, China, and Thailand. In addition, higher bioaccumulation factors (BAF), associated with higher temperature, are predominantly observed in eastern India and southern Myanmar. However, arsenic content in soil is relatively lower in these areas. About 5.5 billion population may be threatened by the consumption of high-arsenic rice. It can be concluded that temperatures may influence the BAF except for soil arsenic, and soil physicochemical properties. Further research on the relationship between climate parameters and BAF should be conducted to address and adapt to future climate change. Additionally, understanding the mechanism of arsenic accumulation under different climatic conditions is crucial for developing agricultural technologies to reduce arsenic accumulation in rice.

Assessment of ecological civilization construction from the perspective of environment and health in China.

This study innovatively evaluated ecological civilization in China from the perspective of environment and health. A Composite Environmental Health Index (CEHI) was constructed based on the Driving force-Pressure-State-Impact-Response (DPSIR) and Coupling Coordination Degree (CCD) models. Results showed that significant and sustained improvements were observed in the ecological environment after ecological civilization, while economic development continued to progress at a steady pace. However, the advancement in population health (impact subsystem), exhibited comparatively modest progress, potentially linked to issues such as demographic aging and the enduring consequences of past exposure to environmental pollutants. At the provincial level, the regional development was uneven. The CEHI performance was highest in the eastern regions, followed by the central regions, with the western regions showing the least progress. Beijing, Guangdong, Jiangsu, Shanghai, and Zhejiang emerged as top performers with higher CEHI scores, which can be attributed to their favorable geographical positioning and the response subsystem. Conversely, northeastern regions (Heilongjiang, Jilin, and Liaoning) and northwestern regions (Shanxi, Gansu, Ningxia, and Qinghai) experienced limited advancements in post-ecological civilization implementation. For these underperforming regions, there is a pressing need to intensify efforts aimed at enhancing their response subsystems. In summary, China's pursuit of ecological civilization has yielded significant successes, potentially offering valuable insights for other nations striving for sustainable development. The ecological civilization model's integration of ecological environmental protection into economic, political, cultural, and social constructs may serve as a meaningful reference for the sustainable development of other countries.

Optimizing cropland use to reduce groundwater arsenic hazards in a naturally arsenic-enriched grain-producing region.

In the Hetao Basin, a grain-producing region plagued by naturally occurring arsenic (As) pollution, understanding the role of agricultural cultivation activities in mobilizing As in groundwater is worthwhile. Here we investigated the impact of cropland use characteristics on groundwater As hazards using a model that combines Random Forest (RF) classification with SHapley Additive exPlanation (SHAP). The analysis incorporated eight cropland use characteristics and three natural factors across 1258 groundwater samples as independent variables. Additionally, an optimized cropland use strategy to mitigate groundwater As hazards was proposed. The results revealed that crop cultivation area, especially within a 2500m-radius buffer around sampling points, most significantly influenced the probability of groundwater As concentrations exceeding an irrigation safety threshold of 50 µg/L, achieving an AUC of 0.86 for this prediction. The relative importance of crop areas on As hazards were as follows: sunflower > melon > wheat > maize. Specifically, a high proportion of sunflower area (>30%), particularly in regions with longer cropland irrigation history, tended to elevate groundwater As hazards. Conversely, its negative driving force on groundwater As hazards was more pronounced with the increase in the proportion of wheat area (>5%), in contrast to other crops. Transitioning from sunflower to wheat or melon cultivation in the northeast of the Hetao Basin may contribute to lower groundwater As hazards. This study provides a scientific foundation for balancing food production with environmental safety and public health considerations.

Short-term associations between ambient PM1, PM2.5, and PM10 and hospital admissions, length of hospital stays, and hospital expenses for patients with cardiovascular diseases in rural areas of Fuyang, East China.

Evidence on the impacts of PM1, PM2.5, and PM10 on the hospital admissions, length of hospital stays (LOS), and hospital expenses among patients with cardiovascular disease (CVD) is still limited in China, especially in rural areas. This study was performed in eight counties of Fuyang from 1 January 2015 to 30 June 2017. We use a three-stage time-series analysis to explore the effects of short-term exposure to PM1, PM2.5, and PM10 on hospital admissions, LOS, and hospital expenses for CVDs. An increment of 10 ug/m3 in PM1, PM2.5, and PM10 corresponded to an increment of 1.82% (95% CI: 1.34, 2.30), 0.96% (95% CI: 0.44, 1.48), and 0.79% (95% CI: 0.63%, 0.95%) in CVD hospital admissions, respectively. We observed that daily concentrations of PMs were associated with an increase in hospital admissions, LOS, and expenses for CVDs. Sustained endeavors are required to reduce air pollution so as to attenuate disease burdens from CVDs.

The interaction between physical activity and ambient particulate matters on cognitive function among Chinese community-dwelling older adults.

BACKGROUND: The interaction between physical activity (PA) and ambient particulate matters (PMs) on cognition is rarely investigated. Our study aimed to assess the interactions of PA and PMs on cognitive function in older adults. METHODS: Our study comprised 3937 Chinese community-dwelling older adults. Cognition was evaluated using the Mini-Mental State Examination. PA information was gathered using the International Physical Activity Questionnaire. The data of PMs were obtained from China High Air Pollutants (CHAP). Linear regressions model and interaction plots were applied to assess and visualize the interaction of PA and PMs on cognition, respectively. Bayesian kernel machine regression (BKMR) method was employed to visualize discernible thresholds for the interaction. RESULTS: PMs were negatively associated with MMSE scores (PM1: ß = -0.40, 95 % CI: -0.58, -0.28; PM2.5: ß = -0.46, 95 % CI: -0.64, -0.29; PM10: ß = -0.44, 95 % CI: -0.61, -0.26), and PA was positively affiliated with MMSE scores (ß = 0.18, 95 % CI: -0.01, 0.38). Interaction plots and BKMR demonstrated that adverse connotations of PMs with MMSE increased with the elevated PA levels, and the positive associations of PA with MMSE scores were attenuated by increased PMs (all Pinteraction < 0.20). Discernible thresholds for the interaction between PMs and PA on MMSE were found. CONCLUSIONS: Our findings suggest that PA should not be taken at higher PMs concentrations, and that low level of PA could be performed in PMs polluted environment to improve cognitive function. Further experimental and cohort researches are required to reproduce our discovery.

Associations of toxic metals and their mixture with hyperuricemia in Chinese rural older adults.

Previous studies have related single toxic metals (TMs) to hyperuricemia (HUA) among the general population, however, the association of the TM mixture with HUA, especially in older adults, remains poorly understood. We aimed to examine the relationships between individual TMs and their mixture and HUA in Chinese rural older adults. This study consisted of 2075 rural older adults aged 60 years or over. Blood concentrations of aluminum (Al), arsenic (As), barium (Ba), cadmium (Cd), cesium (Cs), gallium (Ga), mercury (Hg), lead (Pb), thallium (Tl), and uranium (U) were detected using inductively coupled plasma mass spectrometry. The associations of single TMs with HUA were assessed using logistic regression and restricted cubic spline (RCS) models, and the association of TM mixture with HUA was explored using the elastic net with environmental risk score (ENET-ERS), quantile g-computation (QGC), and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted logistic regression model showed that Cs (OR = 1.65, 95% CI 1.37-1.99) and Pb (OR = 1.46, 95% CI 1.28-1.67) were positively related to HUA, and RCS model exhibited a positive linear association of Cs and Pb with HUA. ENET-ERS and QGC models quantified a positive correlation between the TM mixture and the odds of HUA, with estimated ORs of 1.15 (95% CI 1.11-1.19) and 1.84 (95% CI 1.37-2.47), respectively, and Cs and Pb had the most weight. BKMR model demonstrated a significant linear association between the TM mixture and increased odds of HUA, with the posterior inclusion probabilities (PIPs) of both Cs and Pb being 1.00. Moreover, we observed a positive interaction between Cs and Pb on HUA. The TM mixture is associated with increased odds of HUA in rural older adults, which may mainly be driven by Cs and Pb. Subsequent studies are warranted to confirm these findings and clarify the mechanisms linking multiple TMs with HUA.

APOE ε4 allele modifies the associations of toxic metals and their mixture with cognitive impairment among older adults.

BACKGROUND: The evidence of interactive effect of the toxic metal (TM) mixture and apolipoprotein E (APOE) ε4 gene on cognitive impairment in older adults is scarce. We aimed to explore whether the associations of single TMs and their mixture with cognitive impairment depend on APOE ε4 in Chinese community-dwelling older people. METHODS: A total of 1148 older adults from a subset of the baseline survey of a cohort study were included. Blood arsenic (As), cadmium (Cd), lead (Pb), strontium (Sr), and vanadium (V) were detected by inductively coupled plasma mass spectrometry. APOE gene (rs429358, rs7412) polymorphisms were analyzed by the Polymerase Chain Reaction instrument. Mixed effects logistic regression was applied to estimate the relationships of single TMs and APOE genotype with cognitive impairment. Weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were performed to examine joint impacts of the TM mixture, as well as the interaction of the TM mixture with APOE ε4 genotype on cognitive impairment. RESULTS: Pb displayed a significant linear association with an increased odds of cognitive impairment after adjustment for covariates (Ptrend = 0.045). While APOE genotype did not show a significant correlation with cognitive impairment. WQS showed that the TM mixture was associated with an increased risk of cognitive impairment by 31.0% (OR=1.31, 95% CI: 0.92, 1.87) while no significance was found. BKMR exhibited a significant linear association between the TM mixture and cognitive impairment. Moreover, both WQS and BKMR indicated that Pb contributed the most to cognitive impairment within the mixture. Significant interactions of Pb or the TM mixture and APOE genotype on cognitive impairment were observed, contributing to 38.1% and 38.2% of total effects, respectively. CONCLUSIONS: APOE ε4 allele amplifies the associations of single Pb or the TM mixture with cognitive impairment. These findings may help to develop precision prevention.

Research on gradual changes in incomplete technical information and optimization mechanism of innovation factor allocation efficiency.

The innovation factor allocation efficiency (IFAE), indicated by R&D institutions' technical input information and manufacturers' technical output information, is mainly optimized by transformation of incomplete technical information into relatively complete information and finally complete technical information. There are two optimization mechanisms, namely single optimization and continuous optimization. The empirical analysis selected data from 73 listed companies in software development and 596 listed companies in processing and manufacturing, and testified its hypotheses with GMM regression results. The research finds that the differences in benefits are caused by gradual changes in technical information. With shared goals of benefit maximization between R&D institutions and manufacturers, a correct strategy for technical information can optimize the IFAE. Single optimization refers to the one-time recognition or identification of relatively complete technical information and complete information, acquisition of technical information from one-time cognition, and thorough application of resource input, thus realizing high-level technology progress gradually. Continuous optimization, based on single optimization, involves the prioritized reporting of complete technical information by participants, thus achieving optimal IFAE. Therefore, it is necessary to accelerate the improvement in the incentive mechanisms for technology innovation efficiency. R&D institutions should promote original innovation and integrated innovation, expand technical information increment, deepen the cooperation with manufacturers actively, and facilitate the technical information sharing.

Association Between Adverse Childhood Experiences and Academic Performance Among Children and Adolescents: A Global Meta-Analysis.

This study was conducted to quantify the association of adverse childhood experiences (ACEs) and the academic performance of children and adolescents. The literature was systematically searched in six electronic databases, and a meta-analysis was conducted. Twenty studies with a total of 1,196,631 children and adolescents from five countries were included. Meta-analysis showed that ACE score was positively associated with poor academic achievement, grade repetition, and special education support. Compared with children and adolescents without any ACE, those with one or more ACE had a significantly higher risk of poor academic achievement (pooled odds ratio [OR]: 1.45, 95% confidence interval [CI] [1.13, 1.85], I2 = 82.6%) and grade repetition (pooled OR: 1.36, 95% CI [1.29, 1.43], I2 = 71.0%). Moreover, all types of ACEs were positively associated with poor academic achievement and grade repetition. In addition, there was a significant dose-response relationship between the ACE score and the risk of poor academic achievement. This study supported that ACE had a significant impact on the academic performance of children and adolescents. Based on these findings, we recommend that early screening of ACEs for children and adolescent is critical and appropriate support and prevention in education should be developed for those with ACEs. Further studies are needed to further explore the long-term effect of ACEs on education and its gender differences.

Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults.

BACKGROUND: Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults. METHODS: This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions. RESULTS: Three-year (3-y) average NO2 (per 0.64-µg/m3 increment) was positively associated with global PSQI (ß = 0.41, 95 % CI: 0.23, 0.59), sleep duration (ß = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (ß = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (ß = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively). CONCLUSIONS: PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.

Short-term effects of heatwaves on clinical and subclinical cardiovascular indicators in Chinese adults: A distributed lag analysis.

AIMS: Previous studies have related heat waves to morbidity and mortality of cardiovascular diseases; however, potential mechanisms remained limited. Our aims were to investigate the short-term effects of heat waves on a series of clinical/subclinical indicators associated with cardiovascular health. METHODS: Our study used 80,574 health examination records from the Health Management Center of Nanjing Zhongda Hospital during the warm seasons of 2019-2021, including 62,128 participants. A total of 11 recognized indicators of cardiovascular risk or injury were assessed. Air pollution and meteorological data were obtained from the Nanjing Ecological Environment Bureau and the China Meteorological Data Network, respectively. Heat waves were defined as a daily average temperature over the 95th percentile for three or more consecutive days from May to September. We used a combination of linear mixed effects models and distributed lag nonlinear models to assess the lagged effects of heat waves on clinical and subclinical cardiovascular indicators. Stratified analyses based on individuals' characteristics, including gender, age, body mass index (BMI), diabetes, and hypertension, were also performed. RESULTS: Heat waves were related to significant changes in most indicators, with the magnitude of effects generally peaking at a lag of 0 to 3 days. Moreover, the cumulative percentage changes over lag 0-7 days were -0.82 % to -2.55 % in blood pressure, 1.32 % in heart rate, 0.20 % to 2.66 % in systemic inflammation markers, 0.36 % in a blood viscosity parameter, 9.36 % in homocysteine, and 1.35 % to 3.25 % in injuring myocardial enzymes. Interestingly, females and males showed distinct susceptibilities in different indicators. Stronger effects were also found in participants aged 50 years or over, individuals with abnormal BMI status, and patients with diabetes. CONCLUSION: Short-term exposure to heat waves could significantly alter clinical/subclinical cardiovascular indicator profiles, including blood pressure changes, increased heart rate, acute systemic inflammation, elevated blood viscosity, and myocardial injury.

The Association Between Essential Metal Element Mixture and Sleep Quality in Chinese Community-Dwelling Older Adults.

Previous studies have related single essential metal elements (EMEs) to sleep quality among older adults, however, the association of the EME mixture with sleep quality remained poorly understood. This study aimed to investigate the relationships between single EMEs and the EME mixture and sleep quality in older adults living in Chinese communities. This study consisted of 3957 older adults aged 60 years or over. Urinary concentrations of cobalt (Co), vanadium (V), selenium (Se), molybdenum (Mo), strontium (Sr), calcium (Ca), and magnesium (Mg) were detected using inductively coupled plasma mass spectrometry. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). The associations of single EMEs and EME mixture with sleep quality were assessed using logistic regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-element logistic regression models showed that Mo (OR = 0.927, 95%CI:0.867-0.990), Sr (OR = 0.927, 95%CI:0.864-0.994), and Mg (OR = 0.934, 95%CI:0.873-0.997) were negatively related to poor sleep quality. BKMR models exhibited similar results. Also, higher levels of the EME mixture in urine were inversely related to the odds of poor sleep quality after adjustment for covariates, and Mo had the largest conditional posterior inclusion probability (condPIP) value in the mixture. Mo, Sr, and Mg were negatively related to poor sleep quality, separately and as the mixture. The EME mixture in urine was associated with decreased odds of poor sleep quality in older adults, and Mo was the greatest contributor within the mixture. Additional cohort research is warranted to clarify the relationship of multiple EMEs with sleep quality.

Monthly variations of groundwater arsenic risk under future climate scenarios in 2081-2100.

The seasonal variations of shallow groundwater arsenic have been widely documented. To gain insight into the monthly variations and mechanisms behind high groundwater arsenic and arsenic exposure risk in different climate scenarios, the monthly probability of high groundwater arsenic in Hetao Basin was simulated through random forest model. The model was based on arsenic concentrations obtained from 566 groundwater sample sites, and the variables considered included soil properties, climate, topography, and landform parameters. The results revealed that spatial patterns of high groundwater arsenic showed some fluctuations among months under different future climate scenarios. The probability of high total arsenic and trivalent arsenic was found to be elevated at the start of the rainy season, only to rapidly decrease with increasing precipitation and temperature. The probability then increased again after the rainy season. The areas with an increased probability of high total arsenic and trivalent arsenic and arsenic exposure risk under SSP126 were typically found in the high-arsenic areas of 2019, while those with decreased probabilities were observed in low-arsenic areas. Under SSP585, which involves a significant increase in precipitation and temperature, the probability of high total arsenic and trivalent arsenic and arsenic exposure risk was widely reduced. However, the probability of high total arsenic and trivalent arsenic and arsenic exposure risk was mainly observed in low-arsenic areas from SSP126 to SSP585. In conclusion, the consumption of groundwater for human and livestock drinking remains a threat to human health due to high arsenic exposure under future climate scenarios.

Short-term effects of ambient PM1, PM2.5, and PM10 on internal metal/metalloid profiles in older adults: A distributed lag analysis in China.

There is limited evidence linking exposure to ambient particulate matter (PM) with internal doses of metals and metalloids (metal(loid)s). This study aimed to evaluate the effects of short-term exposure to ambient PM on urine metal(loid)s among Chinese older adults. Biological monitoring data of 15 urine metal(loid)s collected in 3, 970 community-dwelling older adults in Fuyang city, Anhui Province, China, from July to September 2018, were utilized. PMs with an aerodynamic diameter ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5), and ≤ 10 µm (PM10) up to eight days before urine collection were estimated by space-time extremely randomized trees (STET) model. Residential greenness was reflected by Normalized Difference Vegetation Index (NDVI). We used generalized additive model (GAM) combined with distributed lag linear/non-linear models (DLMs/DLNMs) to estimate the associations between short-term PM exposure and urine metal(loid)s. The results suggested that the cumulative exposures to PM1, PM2.5, or PM10 over two days (lag0-1 days) before urine collection were associated with elevated urine metal(loid)s in DLMs, while exhibited linear or "inverted U-shaped" relationships with seven urine metal(loid)s in DLNMs, including Gallium (Ga), Arsenic (As), Aluminum (Al), Magnesium (Mg), Calcium (Ca), Uranium (U), and Barium (Ba). Aforementioned results indicated robust rather than spurious associations between PMs and these seven metal(loid)s. After standardizations for three PMs, PM1 was the greatest contributor to U, PM2.5 made the greatest contributions to Ga, As, Al, and Ba, and PM10 contributed the most to Mg and Ca. Furthermore, the effects of three PMs on urine Ga, As, Al, Mg, Ca, and Ba were reduced when exposed to higher levels of NDVI. Overall, short-term exposures to ambient PMs contribute to elevated urinary metal(loid) levels in older adults, and three PMs exhibit various contributions to different urine metal(loid)s. Moreover, residential greenness may attenuate the effects of PMs on urine metal(loid)s.

Spatial distribution of antibiotics and antibiotic resistance genes in tidal flat reclamation areas in China.

Tidal flat areas are important resources for land development and are becoming antibiotic resistance receivers that trigger major health concerns. The spatial distributions of forty-nine antibiotics, nine antibiotic resistance genes (ARGs), one mobile gene element (MGE) gene, and nine available metals in the soils and sediments along the coastlines of the Yellow Sea in China were quantified. Hierarchical linear model analysis was used to explore relationships between the antibiotics and ARGs across multiple effects resulting from human activities and environmental factors. Fish farm sediments and farmland soils showed high levels of quinolones (QNs) (maximum 637 ng·g-1), sulfonamides (SAs) (maximum 221 ng·g-1), and corresponding ARGs. Significant positive correlations (P from 5.47 × 10-14 to 0.0487) were observed between the antibiotics (QNs, SAs, and chlortetracycline) and their corresponding ARGs (qnrA, qnrD, aac(6')-Ib-cr, dfrA, sul2, and tetA), indicating the selective pressure from antibiotics in soils and sediments. Nine available metals had positive correlations with at least one ARG, indicating heavy metal pollution could enhance the ARGs. Sheep and poultry husbandry and marine aquaculture contribute the most to the antibiotic resistance in the coastlines. In conclusion, antibiotic pollutions have promoting effects at sub-inhibitory concentrations and more attention should be given to inhibit the enrichment of ARGs during tidal flat reclamation processes. The study also suggests the induction effects from metal pollutions, MGE spread, and the antibiotic pollutions from the usage in livestock and aquaculture.

Associations of 10 trace element levels in the whole blood with risk of three types of obesity in the elderly.

BACKGROUND: Currently, over 2 billion people worldwide suffer from obesity, which poses a serious health risk. More and more attention is being given to the effects of trace elements on obesity in recent years. Synergistic or antagonistic interactions among these elements can adversely or positively impact human health. However, epidemiological evidence on the relationship between trace element exposure levels and obesity has been inconclusive. METHODS: Baseline data of 994 participants from the Cohort of Elderly Health and Environment Controllable Factors were used in the present study. ICP-MS was used to measure the concentrations of 10 trace elements in the whole blood of the older population. Binary logistic regression, restricted cubic splines (RCS) models, and Bayesian kernel machine regression (BKMR) models were employed to assess single, nonlinear, and mixed relationships between 10 trace element levels and three types of obesity based on body mass index (BMI), waist circumference (WC), and body fat percentage (BFP) in the elderly. RESULTS: Based on BMI, WC and BFP, 51.8% of the included old population were defined as general overweight/obesity, 67.1% as abdominal obesity, and 36.2% as having slightly high/high BFP. After multivariable adjustment, compared with the lowest tertile, the highest tertile of blood selenium (Se) concentration was associated with an increased risk of all three types of obesity. Additionally, compared with the lowest tertile, higher tertiles of strontium (Sr) concentrations were associated with a lower risk of general overweight/obesity and having slightly high/high BFP, and the highest tertile of barium (Ba) was associated with a lower risk of having slightly high BFP, while higher tertiles of arsenic (As) concentrations were associated with an increased risk of having slightly high/high BFP, and the highest tertile of manganese (Mn) was associated with a higher risk of abdominal obesity. BKMR analyses showed a strong linear positive association between Se and three types of obesity. Higher blood levels of trace element mixture were associated with increased obesity risks in a dose-response pattern, with Se having the highest value of the posterior inclusion probability (PIP) within the mixture. CONCLUSIONS: In this study, we found higher Se levels were associated with an elevated risk of obesity and high levels of Ba, Pb and Cr were associated with a decreased risk of obesity. Studies with larger samples are needed to confirm these findings.

The geochemical stability of typical arsenic-bearing sinter in the Tibetan plateau: Implications from quantitative mineralogy.

High­arsenic (As) sinter deposited from geothermal water is a potentially overlooked hazardous matrix and there remain substantial gaps in our comprehension of the stability of As sequestered within it. In this study, qualitative and quantitative analysis of the mineralogy of As-bearing sinter was conducted by Mineral Liberation Analyzer (MLA) in geothermal areas of the Tibetan Plateau to reveal the geochemical stability of As. Our results indicated that the contents of As in sinter were 3 orders of magnitude higher than the local soil. The dominant host minerals of As were calcite (40.9 %), thenardite (22.5 %), calcium silicate (13.0 %), and halite (8.1 %). Additionally, it was found that a relatively higher As bioavailability was extracted by ethylene diamine tetraacetic acid (EDTA), with a leaching rate of 41.2 %. Notably, the X-ray diffraction (XRD) showed that the thenardite and halite were decomposed after the leaching. The combination of mineralogy and geochemistry data suggested that calcite and calcium silicate were a crucial mechanism for As retention in sinter, while the dissolution of saline minerals (e.g., thenardite, halite, and calcium chloride) served as the primary sources for As release. This finding unveils the potential risks and mechanisms associated with high-As sinter, providing scientific guidance for risk management of sinter.

The associations of non-essential metal mixture with fasting plasma glucose among Chinese older adults without diabetes.

The evidence about the effect of non-essential metal mixture on fasting plasma glucose (FPG) levels among older adults without diabetes is limited. This study aims to estimate the individual and joint relationship between five non-essential metals and FPG levels in Chinese older adults without diabetes. This study included 2362 older adults without diabetes. Urinary concentrations of five non-essential metals, i.e., cesium (Cs), aluminum (Al), thallium (Tl), cadmium (Cd), and arsenic (As), were detected by inductively coupled plasma mass spectrometry (ICP-MS). The associations of single metals and the metal mixture with FPG levels were assessed using linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-metal linear regression models showed positive associations of urinary Al (ß = 0.016, 95%CI: 0.001-0.030) and Cs (ß = 0.018, 95%CI: 0.006-0.031) with FPG levels. When comparing the 2th, 3th, and 4th quartiles of urine Cs to its 1th quartile, the significant associations between Cs and FPG levels were found and presented as an "inverted U" trend (ßQ2 vs. Q1: 0.034; ßQ3 vs. Q1:0.054; ßQ4 vs. Q1: 0.040; all P<0.05). BKMR analyses showed urinary level of Cs exhibited an "inverted U" shape association with FPG levels. Moreover, the FPG levels increased linearly with the raised levels of the non-essential metal mixture, and the posterior inclusion probability (PIP) of Cs was the highest (0.92). Potential positive interaction of As and Cs on FPG levels was found in BKMR model. Stratified analysis displayed significant interactions of hyperlipidemia and urine Cs or Tl on FPG levels. An inverse U-shaped association between Cs and FPG was found, individually and as mixture. The FPG levels increased with the raised levels of the non-essential metal mixture, and Cs was the most contributor to FPG levels. Further research is required to confirm the correlation between non-essential metals and FPG levels and to clarify the underlying mechanisms.