Multiple metal exposure and obesity: A prospective cohort study of adults living along the Yangtze River, China

The association between PM2.5 components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models

BACKGROUND

PM2.5 is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develop an analytical methodology combining traditional and novel machine learning models to evaluate PM2.5's combined effects on blood pressure (BP) and identify the most toxic components.

METHODS

We measured late-pregnancy BP of 1138 women from the Heshan cohort while simultaneously analyzing 31 PM2.5 components. We utilized multiple linear regression modeling to establish the relationship between PM2.5 components and late-pregnancy BP and applied Random Forest (RF) and generalized Weighted Quantile Sum (gWQS) regression to identify the most toxic components contributing to elevated BP and to quantitatively evaluate the cumulative effect of the PM2.5 component mixtures.

RESULTS

The results revealed that 16 PM2.5 components, such as EC, OC, Ti, Fe, Mn, Cu, Cd, Mg, K, Pb, Se, Na+, K+, Cl-, NO3-, and F-, contributed to elevated systolic blood pressure (SBP), while 26 components, including two carbon components (EC, OC), fourteen metallics (Ti, Fe, Mn, Cr, Mo, Co, Cu, Zn, Cd, Na, Mg, Al, K, Pb), one metalloid (Se), and nine water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO42-, F-), contributed to elevated diastolic blood pressure (DBP). Mn and Cr were the most toxic components for elevated SBP and DBP, respectively, as analyzed by RF and gWQS models and verified against each other. Exposure to PM2.5 component mixtures increased SBP by 1.04 mmHg (95% CI: 0.33-1.76) and DBP by 1.13 mmHg (95% CI: 0.47-1.78).

CONCLUSIONS

Our study highlights the effectiveness of combining traditional and novel models as an analytical strategy to quantify the health effects of PM2.5 constituent mixtures.

Associations Between Individual and Combined Metal Exposures in Whole Blood and Kidney Function in U.S. Adults Aged 40 Years and Older

The effects of metal exposure on kidney function have been reported in previous literature. There is limited and inconsistent information on the associations between individual and combined exposures to metals and kidney function among the middle-aged and older population. The aim of this study was to clarify the associations of exposure to individual metals with kidney function while accounting for potential coexposure to metal mixtures and to evaluate the joint and interactive associations of blood metals with kidney function. A total of 1669 adults aged 40 years and older were enrolled in the present cross-sectional study using the 2015-2016 National Health and Nutrition Examination Survey (NHANES). Single-metal and multimetal multivariable logistic regression models, quantile G-computation, and Bayesian kernel machine regression models (BKMR) were fitted to explore the individual and joint associations of whole blood metals [lead (Pb), cadmium (Cd), mercury (Hg), cobalt (Co), manganese (Mn), and selenium (Se)] with the odds of decreased estimated glomerular filtration rate (eGFR) and albuminuria. A decreased eGFR was defined as an eGFR ≤ 60 mL/min per 1.73 m2, and albuminuria was categorized as a urinary albumin-creatinine ratio (UACR) of ≥ 30.0 mg/g. The results from quantile G-computation and BKMR indicated positive associations between exposure to the metal mixture and the prevalence of decreased eGFR and albuminuria (all P values < 0.05). These positive associations were mainly driven by blood Co, Cd, and Pb. Furthermore, blood Mn was identified as an influential element contributing to an inverse correlation with kidney dysfunction within metal mixtures. Increasing blood Se levels were negatively associated with the prevalence of decreased eGFR and positively associated with albuminuria. In addition, a potential pairwise interaction between Mn-Co on decreased eGFR was identified by BKMR analysis. Findings from our study suggested a positive association between exposure to the whole blood metal mixture and decreased kidney function, with blood Co, Pb, and Cd being the main contributors to this association, while Mn demonstrated an inverse relationship with renal dysfunction. However, as our study was cross-sectional in nature, further prospective studies are warranted to better understand the individual and combined effects of metals on kidney function.

Associations between metal(loid) exposure with overweight and obesity and abdominal obesity in the general population: A cross-sectional study in China

Previous studies have revealed links between metal(loid)s and health problems; however, the link between metal(loid)s and obesity remains controversial. We evaluated the cross-sectional association between metal(loid) exposure in whole blood and obesity among the general population. Vanadium (V), chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), molybdenum (Mo), cadmium (Cd), antimony (Sb), thallium (T1), and lead (Pb) were measured in 3029 subjects in Guangdong Province (China) using ICP-MS. The prevalence of overweight and obesity (OWO) and abdominal obesity (AOB) was calculated according to body mass index (BMI) and waist circumference (WC), respectively. Multivariate analysis showed that elevated blood Cu, Cd, and Pb levels were inversely associated with the risk of OWO, and these associations were confirmed by a linear dose-response relationship. Elevated blood Co concentration was associated with a decreased risk of AOB. A quantile g-computation approach showed a significantly negative mixture-effect of 13 metal(loid)s on OWO (OR: 0.96; 95% CI: 0.92, 0.99). Two metals-Ni and Mo-were inversely associated with the risk of OWO but positively associated with AOB. We cross-grouped the two obesity measurement types and found that the extremes of metal content were present in people with AOB only. In conclusion, blood Cu, Mo, Ni, Cd, and Pb were inversely associated with the risk of OWO. The presence of blood Co may be protective, while Ni and Mo exposure might increase the risk of AOB. The association between metal(loid) exposure and obesity warrants further investigation in longitudinal cohort studies.

Associations between plasma metal/metalloid mixtures and the risk of central obesity: A prospective cohort study of Chinese adults

Central obesity has increased rapidly over the past decade and posed a substantial disease burden worldwide. Exposure to metals/metalloids has been acknowledged to be involved in the development of central obesity through regulation of cortisol, insulin resistance, and glucocorticoid receptor reduction. Despite the importance, it is lack of prospective study which comprehensively evaluate the relations between multiple metals exposure and central obesity. We explored the prospective associations of plasma metal concentrations with central obesity in a prospective study of the Dongfeng-Tongji cohort. The present study included 2127 participants with a 6.87-year mean follow-up duration. We measured 23 plasma metal/metalloid concentrations at baseline. The associations between metals and incident central obesity were examined utilizing the Cox proportional hazard regression in single and multiple metals models. Additionally, we applied elastic net (ENET), Bayesian kernel machine regression (BKMR), plasma metal score (PMS), and quantile-based g-computation (Qgcomp) models to explore the joint associations of metal mixtures with central obesity. After adjusting potential confounders, we found significant associations of plasma manganese (Mn) and thallium (Tl) concentrations with a higher risk of central obesity, whereas plasma rubidium (Rb) concentration was associated with a lower risk of central obesity both in single and multiple metals models (all FDR <0.05). The ENET and Qqcomp models verified similar metals (Mn, Rb, and Tl) as important predictors for central obesity. The results of both BKMR model and PMS suggested cumulative exposure to metal mixtures was associated with a higher risk of central obesity. Our findings suggested that co-exposure to metals was associated with a higher risk of central obesity. This study expands our knowledge that the management of metals/metalloids exposure may be beneficial for the prevention of new-onset central obesity, which may subsequently alleviate the disease burden of late-life health outcomes.

Vanadium, cobalt, zinc, and rubidium are associated with markers of inflammation and oxidative stress in a Greek population with obesity

Introduction

The prevalence of obesity is rising globally, with negative effects on the socioeconomic system. As a result of its drivers which include low-grade chronic inflammation, oxidative stress, and fatty acid metabolism, this phenotype develops metabolic anomalies that exacerbate its pathogenesis. It has been discovered that metals and metalloids have substantial effects on both the immune system and metabolism and are influenced by factors connected to obesity. Although there is a known connection between metals, obesity, and related metabolic disorders, it is still under research.

Methods

We determined the plasma levels of 16 metals and metalloids in 76 individuals with obesity and investigated the relationships with inflammatory and oxidative stress biomarkers in order to clarify the processes by which metals/metalloids exhibit their effects.

Results

After adjusting for age, gender, BMI, physical activity level, smoking, the existence of metabolic abnormalities, and dietary intake of the corresponding metal, regression analysis revealed the following statistically significant associations; vanadium was negatively associated with oxLDL (Beta ± SE= -0.014 ± 0.005, p=0.007), zinc was negatively associated with leptin (Beta ± SE= -12.390 ± 5.226, p=0.025), cobalt was associated negatively with adiponectin (Beta ± SE= -0.030 ± 0.012, p=0.001) and positively with MPO (Beta ± SE= 0.002 ± 0.001, p=0.023), and rubidium was negatively associated with oxLDL (Beta ± SE= -1.139 ± 0.411, p=0.008) and positively with MPO (Beta ± SE= 0.324 ± 0.102, p=0.003).

Discussion

The aforementioned associations highlight the need for further research, demonstrating the importance of inflammation and oxidative stress in the association between metals/metalloids and obesity-related metabolic abnormalities.

Why Do People Gain Belly Fat in Rural Areas? A Study of Urinary Metal(loid)s and Abdominal Obesity in China

Obesity is prevalent in rural areas of China, and there are inconsistent findings regarding the association between metal(loid) exposure and the risk of obesity. Abdominal obesity (AOB), which reflects visceral fat abnormity, is a crucial factor in studying obesity-related diseases. We conducted a study measuring 20 urinary metal(loid)s, 13 health indicators, and the waist circumference (WC) in 1849 participants from 10 rural areas of China to investigate their relationships. In the single exposure models, we found that urinary chromium (Cr) was significantly associated with the odds of having AOB [adjusted odds ratio (OR) = 1.81 (95% confidence interval (CI): 1.24, 2.60)]. In the mixture exposure models, urinary Cr consistently emerged as the top contributor to AOB, while the overall effect of mixed metal(loid)s was positive toward the odds of having AOB [adjusted OR: 1.33 (95% CI: 1.00, 1.77)], as revealed from the quantile g-computation model. After adjusting for the effects of other metal(loid)s, we found that the elevation of apolipoprotein B and systolic blood pressure significantly mediated the association between urinary Cr and the odds of having AOB by 9.7 and 19.4%, respectively. Our results suggest that exposure to metal(loid)s is a key factor contributing to the prevalence of AOB and WC gain in rural areas of China.

Association of genetic polymorphisms in detoxifying systems and urinary metal(loid) levels with excess body weight among Spanish children: A proof-of-concept study

Exposure to metal(loid)s during critical developmental windows could result in permanent damage to the target organ system, increasing susceptibility to disease later in life. In view of the fact that metals(loid)s have been shown to work as obesogens, the aim of the present case-control study was to evaluate the modification effect of exposure to metal(loid)s on the association between SNPs in genes involved in metal(loid) detoxification and excess body weight among children. A total of 134 Spanish children aged 6-12 years old were included (88 controls and 46 cases). Seven SNPs (GSTP1 rs1695 and rs1138272; GCLM rs3789453, ATP7B rs1061472, rs732774 and rs1801243; and ABCC2 rs1885301) were genotyped on GSA microchips, and ten metal(loid)s were analysed in urine samples through Inductively coupled plasma mass spectrometry (ICP-MS). Multivariable logistic regressions were conducted to assess the genetic and metal exposures' main association and interaction effects. GSTP1 rs1695 and ATP7B rs1061472 showed significant effects on excess weight increase in those children carrying two copies of the risk G allele and being highly exposed to chromium (ORa = 5.38, p = 0.042, p interaction = 0.028 for rs1695; and ORa = 4.20, p = 0.035, p interaction = 0.012 for rs1061472) and lead (ORa = 7.18, p = 0.027, p interaction = 0.031 for rs1695, and ORa = 3.42, p = 0.062, p interaction = 0.010 for rs1061472). Conversely, GCLM rs3789453 and ATP7B rs1801243 appeared to play a protective role against excess weight in those exposed to copper (ORa = 0.20, p = 0.025, p interaction = 0.074 for rs3789453) and lead (ORa = 0.22, p = 0.092, p interaction = 0.089 for rs1801243). Our findings provide the first proof that interaction effects could exist between genetic variants within GSH and metal transporting systems and exposure to metal(loid)s, on excess body weight among Spanish children.

Association Between Essential and Non-essential Metals, Body Composition, and Metabolic Syndrome in Adults

Growing evidence indicates that metal exposure is associated with metabolic syndrome (MetS); however, mixed results have been reported. The aim of this study was to clarify associations of exposure to essential and non-essential metals with body composition and risks of obesity and MetS. Anthropometry and blood biochemistry of metabolic parameters were obtained from 150 middle-aged Taiwanese adults. Plasma metals were assessed using inductively coupled plasma mass spectrometry, and body compositions were measured by a bioelectrical impedance analysis (BIA). The essential metals of copper (Cu), manganese (Mn), and chromium (Cr) were positively correlated with the body fat mass but inversely correlated with the skeletal muscle mass (all p < 0.05). An adjusted logistic regression showed that Mn [odds ratio (OR) = 1.624 (95% confidence interval 1.072, 2.462), p = 0.02] and, to a lesser extent, Cu [OR = 1.501 (0.985, 2.292), p = 0.059] predicted abdominal obesity, while plasma Cu [OR = 2.211 (1.146, 4.266), p = 0.02] and zinc (Zn) [OR = 2.228 (1.048, 4.736) p = 0.04] predicted MetS. Significant correlations between dyslipidemia and lithium [OR = 1.716 (1.080, 2.726)], Cu [OR = 2.210 (1.415, 3.454)], Mn [OR = 2.200 (1.320, 3.666)], molybdenum [OR = 1.853 (1.160, 2.958)], and Zn [OR = 1.993 (1.186, 3.349)], and between boron [OR = 2.583 (1.137, 5.868)] and hyperglycemia were observed (all p < 0.05). Exposure to essential metals may affect the body composition and metabolic profiles, exacerbating the risk of MetS.

Exposure to Metal Mixtures and Overweight or Obesity Among Chinese Adults

Previous research has investigated the association between individual metal exposure and overweight/obesity (OW/OB). However, there is limited data about metal mixture exposure and OW/OB. This study aimed to explore the individual and joint effects of 21 metals on OW/OB and its metabolic phenotypes. A total of 4042 participants were enrolled in our study, and 51.0% of them were overweight/obese. We quantified 21 metal levels in the urine sample. OW/OB was defined as BMI ≥ 24 kg/m², while the metabolic phenotypes, including metabolic unhealthy overweight/obesity (MUOW/OB) and metabolic health overweight/obesity (MHOW/OB), were determined by BMI and metabolic state. We used logistic regression to analyze the effect of individual metal exposure on OW/OB and its metabolic phenotypes. Quantile g-computation was applied to evaluate the joint effect of metal exposure on OW/OB and its metabolic phenotypes. In logistic regression, zinc (Zn) was positively associated with OW/OB, with the odds ratio (OR) in the highest quartiles of 2.19 (95% confidence interval (CI), 1.74, 2.77; P trend < 0.001), while arsenic (As) and cadmium (Cd) were negatively associated with OW/OB (OR = 0.70 (0.56, 0.87) and 0.61 (0.48, 0.78), respectively). After adjustment for age, gender, education, cigarette smoking, alcohol drinking, physical activity, meat intake, and vegetable intake, Zn was positively associated with MUOW/OB, while As, Cd, nickel (Ni), and strontium (Sr) were negatively associated with MUOW/OB (all P trend < 0.05). Quantile g-computation showed a significantly negative association between metal mixture exposure and MUOW/OB. Our study suggested that metal mixture exposure might be negatively associated with OW/OB, particularly with MUOW/OB. Zn, As and Cd contributed most to the effect of the mixture. More prospective studies are warranted to confirm these findings and reveal the underlying mechanisms.

Interaction of biomass fuels use and metals exposure on hypertension: A prospective cohort study in rural areas along the Yangtze River, China

Humans maybe simultaneously exposed to multiple-metals and indoor air pollution in daily life. However, limited prospective studies have assessed the interaction between multiple metals exposure and biomass fuels use on hypertension in China. The prospective cohort study in rural areas along the Yangtze River included 2625 adults in 2014-2015, and they were followed up till 2019. Among 1248 rural residents who were without hypertension at baseline, 377 hypertension events (30.21%) were observed after 4.5 years of average follow-up time. First-morning urine samples of residents were collected at baseline, the association between urinary metals level and hypertension were assessed using quantile g-computation. Additionally, we also examined the effect of biomass fuels use, fuels switching, and cookstove ventilation on the association of metals exposure with hypertension. Quantile g-computation analyses showed a positive joint effect of 17 metals on hypertension, with the odds ratio (OR) of 1.68 (95% CI: 0.89, 3.14) when increasing all seventeen metals by one quartile, and cadmium, lithium, copper contributed the largest positive weights. Biomass fuels use can interact with cadmium exposure on hypertension with OR for interaction of 1.28 (95%CI: 1.00, 1.73), and increase the association between copper, manganese and zinc exposure and systolic blood pressure, lithium exposure and diastolic blood pressure at the follow-up visit. Moreover, switching from biomass fuels to clean fuels during follow up, cookstove ventilation can alleviate the risk of higher blood pressure from metals exposure. In rural areas along the Yangtze River, China, biomass fuels use for cooking can interact with multiple-metals exposure on hypertension. Residents who switched from biomass fuels to clean fuels and who used ventilation had a lower risk of hypertension. Further cohort studies are needed to clarify the mechanism of combined effects of metals exposure and biomass fuels use on the human health.

Multiple environmental exposures and obesity in eastern China: An individual exposure evaluation model

Obesity has caused a huge burden of disease. Few studies have explored individuals' environmental exposure level and the impact of multiple environmental exposures on obesity. The aim of this study was to explore individual air pollution exposure evaluation, and the association between and multiple environmental factors and obesity among adult residents in rural areas of China. In this study, 8400 residents of 14 districts and counties in eastern of China were selected by multistage stratified cluster sampling, and a total of 8377 residents were included in the final analysis. We adopted BMI (Body Mass Index) > 28 kg/m² as the definition of obesity. First, an individual air pollution evaluation model was established based on the monitoring data of air pollution stations closest to residential address, different demographic characteristics of residents and daily living habits using generalized linear model and random forest model. Then, we used Bayesian Kernel Machine Regression (BKMR) and Quantile g-Computation (QgC) models to explore multiple environmental exposures on obesity. The results showed that six air pollutants were significantly positively associated with obesity, and green space had a significant protective effect on obesity. The BKMR model showed that the effects of different air pollutants on obesity were significantly enhanced by each other, while green space significantly reduced the positive effect of air pollution on obesity. The QgC model showed a significant positive association with obesity when all environmental factors were exposed as a whole, especially in males, higher household incomes and young people. It suggested that relevant authorities should improve regional air quality and green space to reduce the burden of disease caused by obesity.

The association between essential trace element mixture and cognitive function in Chinese community-dwelling older adults

BACKGROUND

The evidence about the effect of essential trace element (ETE) mixture on cognitive function amongst older adults is limited. This study aims to evaluate the associations of single ETEs and ETE mixture with cognitive function using a representative sample of community-dwelling older adults in China.

METHODS

A total of 3814 older adults were included in the study. Urinary concentrations of selenium (Se), vanadium (V), cobalt (Co), strontium (Sr), and molybdenum (Mo) were detected by inductively coupled plasma mass spectrometry. Cognitive function in older adults was assessed using the Chinese version of the Mini-Mental State Examination (MMSE). Linear regression and Bayesian kernel machine regression (BKMR) were performed to explore the associations of single ETEs and ETE mixture with cognitive function, respectively.

RESULTS

Linear regression showed that urinary levels of Se and V were positively associated with MMSE scores in the adjusted single-element models. BKMR also showed marginally positive associations of Se and V with MMSE scores. Moreover, higher urinary levels of ETE mixture were significantly associated with increased MMSE scores in a dose-response pattern, and Se was the most important contributor within the mixture. Both Se and V demonstrated positive additive effects on the associations of other ETEs with MMSE scores, whereas Co had a negative additive effect.

CONCLUSIONS

V and Se are positively associated with cognitive function, individually and as a mixture. ETE mixture exhibits a linear dose-response association with improved cognitive function, with Se being the most important component within the mixture. Mixture analyses rather than single ETE analyses may provide a real-world perspective on the relationship between ETE mixture and cognitive function. Further cohort studies are needed to clarify the association of multiple ETEs with cognitive function.

Life-Time Environmental Chemical Exposure and Obesity: Review of Epidemiological Studies Using Human Biomonitoring Methods

The exponential global increase in the incidence of obesity may be partly attributable to environmental chemical (EC) exposure. Humans are constantly exposed to ECs, primarily through environmental components. This review compiled human epidemiological study findings of associations between blood and/or urinary exposure levels of ECs and anthropometric overweight and obesity indices. The findings reveal research gaps that should be addressed. We searched MEDLINE (PubMed) for full text English articles published in 2006-2020 using the keywords "environmental exposure" and "obesity". A total of 821 articles were retrieved; 102 reported relationships between environmental exposure and obesity indices. ECs were the predominantly studied environmental exposure compounds. The ECs were grouped into phenols, phthalates, and persistent organic pollutants (POPs) to evaluate obesogenic roles. In total, 106 articles meeting the inclusion criteria were summarized after an additional search by each group of EC combined with obesity in the PubMed and Scopus databases. Dose-dependent positive associations between bisphenol A (BPA) and various obesity indices were revealed. Both individual and summed di(2-ethylhexyl) phthalate (DEHP) and non-DEHP metabolites showed inconsistent associations with overweight and obesity indices, although mono-butyl phthalate (MBP), mono-ethyl phthalate (MEP), and mono-benzyl phthalate (MBzP) seem to have obesogenic roles in adolescents, adults, and the elderly. Maternal exposure levels of individual POP metabolites or congeners showed inconsistent associations, whereas dichlorodiphenyldichloroethylene (DDE) and perfluorooctanoic acid (PFOA) were positively associated with obesity indices. There was insufficient evidence of associations between early childhood EC exposure and the subsequent development of overweight and obesity in late childhood. Overall, human evidence explicitly reveals the consistent obesogenic roles of BPA, DDE, and PFOA, but inconsistent roles of phthalate metabolites and other POPs. Further prospective studies may yield deeper insights into the overall scenario.