International audience

PR | IFPRI3; ISI; CRP3.2; 4 Transforming Agricultural and Rural Economies | Development Strategies and Governance (DSG); Transformation Strategies | CGIAR Research Program on Maize (MAIZE)

Adipokines, cytokines secreted by adipose tissue, may contribute to obesity-related metabolic disease. The role of environmental phenols and parabens in racial difference in metabolic disease burden has been suggested, but there is limited evidence. We examined the cross-sectional associations of urinary phenols and parabens with adipokines and effect modification by race. Urinary concentrations of 6 phenols (bisphenol-A, bisphenol-F, 2,4-diclorophenol, 2,5-diclorophenol, triclosan, benzophenone-3) and 4 parabens (methyl-paraben, ethyl-paraben, propyl-paraben, butyl-paraben) were measured in 2002–2003 among 1200 women (mean age = 52.6) enrolled in the Study of Women's Health Across the Nation Multi-Pollutant Study. Serum adipokines included adiponectin, high molecular weight (HMW)-adiponectin, leptin, soluble leptin receptor (sOB-R). Linear regression models were used to estimate the adjusted percentage change in adipokines per inter-quantile range (IQR) increase in standardized and log-transformed levels of individual urinary phenols and parabens. Bayesian kernel machine regression (BKMR) was used to evaluate the joint effect of urinary phenols and parabens as mixtures. Participants included white (52.5%), black (19.3%), and Asian (28.1%) women. Urinary 2,4-dichlorophenol was associated with 6.02% (95% CI: 1.20%, 10.83%) higher HMW-adiponectin and urinary bisphenol-F was associated with 2.60% (0.48%, 4.71%) higher sOB-R. Urinary methyl-paraben was associated with lower leptin in all women but this association differed by race: 8.58% (−13.99%, −3.18%) lower leptin in white women but 11.68% (3.52%, 19.84%) higher leptin in black women (P interaction = 0.001). No significant associations were observed in Asian women. Additionally, we observed a significant positive overall effect of urinary phenols and parabens mixtures in relation to leptin levels in black, but not in white or Asian women. Urinary bisphenol-F, 2,4-dichlorophenol and methyl-paraben may be associated with favorable profiles of adipokines, but methyl-paraben, widely used in hair and personal care products, was associated with unfavorable leptin levels in black women. Future studies are needed to confirm this racial difference.

The present study aims to determine the associations of multiple plasma metal levels and plasma microRNAs (miRNAs) with diabetes risk, and further explore the mediating effects of plasma miRNAs on the associations of plasma metal with diabetes risk. We detected plasma levels of 23 metals by inductively coupled plasma mass spectrometry (ICP-MS) among 94 newly diagnosed and untreated diabetic cases and 94 healthy controls. The plasma miRNAs were examined by microRNA Array screening and Taqman real-time PCR validation among the same study population. The multivariate logistic regression models were employed to explore the associations of plasma metal and miRNAs levels with diabetes risk. Generalized linear regression models were utilized to investigate the relationships between plasma metal and plasma miRNAs, and mediation analysis was used to assess the mediating effects of plasma miRNAs on the relationships between plasma metals and diabetes risk. Plasma aluminum (Al), titanium (Ti), copper (Cu), zinc (Zn), selenium (Se), rubidium (Rb), strontium (Sr), barium (Ba), and Thallium (Tl) levels were correlated with elevated diabetic risk while molybdenum (Mo) with decreased diabetic risk (P < 0.05 after FDR multiple correction). MiR-122–5p and miR-3141 were positively associated with diabetes risk (all P < 0.05). Ti, Cu, and Zn were positively correlated with miR-122–5p (P = 0.001, 0.028 and 0.004 respectively). Ti, Cu, and Se were positively correlated with miR-3141 (P = 0.003, 0.015, and 0.031 respectively). In addition, Zn was positively correlated with miR-193b-3p (P = 0.002). Ti was negatively correlated with miR-26b-3p (P = 0.016), while Mo and miR-26b-3p were positively correlated (P = 0.042). In the mediation analysis, miR-122–5p mediated 48.0% of the association between Ti and diabetes risk. The biological mechanisms of the association are needed to be explored in further studies.

The potential effect of gestational exposure to phthalates on the lung function levels during childhood is unclear. Therefore, we examined this association at different ages (from 4 to 11 years) and over the whole childhood. Specifically, we measured 9 phthalate metabolites (MEP, MiBP, MnBP, MCMHP, MBzP, MEHHP, MEOHP, MECPP, MEHP) in the urine of 641 gestating women from the INMA study (Spain) and the forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁) and FEV₁/FVC in their offspring at ages 4, 7, 9 and 11. We used linear regression and mixed linear regression with a random intercept for subject to assess the association between phthalates and lung function at each study visit and for the overall childhood, respectively. We also assessed the phthalate metabolites mixture effect on lung function using a Weighted Quantile Sum (WQS) regression. We observed that the phthalate metabolites gestational levels were consistently associated with lower FVC and FEV₁ at all ages, both when assessed individually and jointly as a mixture, although most associations were not statistically significant. Of note, a 10% increase in MiBP was related to lower FVC (−0.02 (−0.04, 0)) and FEV₁ z-scores (−0.02 (−0.04, −0.01) at age 4. Similar significant reductions in FVC were observed at ages 4 and 7 associated with an increase in MEP and MnBP, respectively, and for FEV₁ at age 4 associated with an increase in MBzP. WQS regression consistently identified MBzP as an important contributor to the phthalate mixture effect. We can conclude that the gestational exposure to phthalates was associated with children's lower FVC and FEV₁, especially in early childhood, and in a statistically significant manner for MEP, MiBP, MBzP and MnBP. Given the ubiquity of phthalate exposure and its established endocrine disrupting effects in children, our findings support current regulations that limit phthalate exposure.

Currently, studies on the association between per-/polyfluoroalkyl substances (PFAS) concentrations and the renal function of residents, especially teenagers, living near fluorochemical industrial plants, are relatively rare, and not all these studies suggested associations. In this cross-sectional study, 775 local teenagers (11–15 years old) were included, and serum concentrations of 18 PFAS were measured. Perfluorooctanoic acid (PFOA) was found to be the dominant PFAS with a concentration of 22.3–3310 ng/mL (mean = 191 ng/mL), accounting for 71.5–99.1% of ΣPFAS. Statistical analyses demonstrated that internal exposure of perfluoroalkyl carboxylic acids (PFCA, C8–C10) was related to the plant. In addition, the prevalence rate of chronic kidney disease (CKD) (35.0%) in the participants was relatively high. A significantly positive association was observed between the increase in PFOA concentration and increasing risk of CKD (OR = 1.741; 95% CI: 1.004, 3.088; p = 0.048) by adjusting for gender, age, body mass index (BMI), and household income. Similar positive correlation was also observed in PFHpA with CKD (OR = 1.628, 95% CI: 1.031, 2.572; p = 0.037). However, no significant correlation was observed for concentrations of other PFAS and CKD (p > 0.05). Furthermore, linear regression analyses demonstrated that none of the PFAS concentrations were significantly correlated with estimated glomerular filtration rate (eGFR) or urine albumin/urine creatinine ratio (ACR) (p > 0.05). However, a significantly negative correlation was observed between PFOA concentration and abnormal ACR (β = −0.141, 95% CI: −0.283, 0.001; p = 0.048) after stratifying by CKD. Sensitivity analyses further confirmed these results. This cross-sectional study is the first, to our knowledge, to investigate the association between PFAS concentrations and renal function in teenagers living near a Chinese industrial plant. Further prospective and metabonomic studies are needed to interpret the results and clarify the biological mechanisms underlying this association.

In recent years, the naturally high background value region of Cd derived from the weathering of carbonate has received wide attention. Due to the significant difference in soil Cd content and bioavailability among different parent materials, the previous land classification scheme based on total soil Cd content as the classification standard, has certain shortcomings. This study aims to explore the factors influencing soil Cd bioavailability in typical karst areas of Guilin and to suggest a scientific and effective farmland use management plan based on the prediction model. A total of 9393 and 8883 topsoil samples were collected from karst and non-karst areas, respectively. Meanwhile, 149 and 145 rice samples were collected together with rhizosphere soil in karst and non-karst areas, respectively. The results showed that the higher CaO level in the karst area was a key factor leading to elevated soil pH value. Although Cd was highly enriched in karst soils, the higher pH value and adsorption of Mn oxidation inhibited Cd mobility in soils. Conversely, the Cd content in non-karst soils was lower, whereas the Cd level in rice grains was higher. To select the optimal prediction model based on the correlation between Cd bioaccumulation factors and geochemical parameters of soil, artificial neural network (ANN) and linear regression prediction models were established in this study. The ANN prediction model was more accurate than the traditional linear regression model according to the evaluation parameters of the test set. Furthermore, a new land classification scheme based on an ANN prediction model and soil Cd concentration is proposed in this study, making full use of the spatial resources of farmland to ensure safe rice consumption.

Many cities across the world face the challenge of severe fine particulate matter (PM₂.₅) pollution. Among the many factors that affect PM₂.₅ pollution, there is an increasing interest in the impacts of urban structure. However, quantifying these impacts in China has been difficult due to differences of study area and scale in existing research, as well as limited sample sizes. Here, we conducted a continental study focusing on 301 prefectural cities in mainland China to investigate the effects of urban structure, including urban size and urban compactness, on PM₂.₅ concentrations. Based on PM₂.₅ raster and land cover data, we used quantile regression and a general multilinear model to estimate the effects and relative contributions of urban size and urban compactness on urban PM₂.₅ pollution, with explicit consideration for pollution level, urban size and geographical location. We found: (1) nationwide, the larger and more compact that cities were, the heavier the PM₂.₅ pollution tended to be. Additionally, this relationship became stronger with increasing levels of pollution. (2) In general, urban size played a more important role than urban form, and there were no significant interactive effects between the two metrics on urban PM₂.₅ concentrations at the national scale. (3) The impacts of urban size and form varied by city size and geographical location. The impacts of urban size were only significant for small or medium-large cities but not for large cities. Among large cities, only urban form had a significantly positive effect on urban PM₂.₅ concentrations. The further north and west that cities were, the more dependent PM₂.₅ pollution was on urban form, whereas the further south and east that cities were, the greater the impact of urban size. These results provide insights into how urban design and planning can be used to alleviate air pollution.

Environmental heavy metal exposure has been considered to be the risk factor for neurodevelopmental disorders in children. However, the available data on the associations between multiple metals exposure and the risk of dyslexia in China are limited. The purpose of our study was to examine the associations between urinary metal concentrations and Chinese dyslexia risk. A total of 56 Chinese dyslexics and 60 typically developing children were recruited. The urinary concentration of 13 metals were measured by inductively coupled plasma-mass spectrometer (ICP-MS). Binary logistic regression and the Probit extension of Bayesian kernel machine regression (BKMR-P) were used to explore the associations between multiple metal exposure and the risk of Chinese dyslexia. Our results indicated that Co, Zn and Pb were significantly associated with Chinese dyslexia in the multiple-metal exposure model. After adjusting the covariates, a positive association was observed between Pb and the risk of Chinese dyslexia, with the odds ratio (OR) in the highest quartiles of 6.81 (95%CI: 1.07–43.19; p–trend = 0.024). Co and Zn were negatively associated with the risk of Chinese dyslexia. Compared to the lowest quartile, the ORs of Co and Zn in the highest quartile are 0.13 (95%CI: 0.02–0.72; p–trend = 0.026) and 0.18 (95%CI: 0.04–0.88; p–trend = 0.038), respectively. In addition, BKMR-P analysis indicated that with the cumulative level across Co, Zn and Pb increased, the risk of Chinese dyslexia gradually declined and then rebounded, albeit non-significantly, and Pb was the major contributor in this association. In general, the urinary concentrations of Co, Zn and Pb were significantly associated with Chinese dyslexia. More prospective studies are needed to confirm the health effects of multiple metals exposure in children with Chinese dyslexia.

Exposure to metals has been linked with the risk of hypertensive disorders of pregnancy (HDP), but little is known about the potential effects of exposure to metal mixtures. Thus, our study aimed to investigated the impact of a complex mixture of metals on HDP, especially the interactions among metal mixtures. We did a population-based nested case-control study from October 2013 to October 2016 in Wuhan, China, including 146 HDP cases and 292 controls. Plasma concentrations of Aluminum (Al), Barium (Ba), Cobalt (Co), Copper (Cu), Lead (Pb), Mercury (Hg), Molybdenum (Mo), Nickel (Ni), Selenium (Se), Strontium (Sr), Thallium (Tl), and Vanadium (V) were measured and collected between 10 and 16 gestational weeks. We employed quantile g-computation, conditional logistic regression models, and Bayesian Kernel Machine Regression (BKMR) to assess the association of individual metals and metal mixtures with HDP risk. In the quantile g-computation, the OR for a joint tertile increase in plasma concentrations was 3.67 (95% CI: 1.70, 7.91). Hg contributed the largest positive weights and followed by Al, Ni, and V. In conditional logistic regression models, concentrations of Hg, Al, Ni, and V were significantly associated with the risk of HDP (p-FDR < 0.05). Compared to the lowest tertiles, the ORs (95% CI) for the highest tertiles of these four metals were 2.67 (1.44, 4.95), 3.09 (1.70, 5.64), 5.31 (2.68, 10.53), and 4.52 (2.26, 9.01), respectively. In the BKMR analysis, we observed a linear positive association between Hg, Al, V, and HDP, and a nonlinear relationship between Ni and HDP. A potential interaction between Al and V was also identified. We found that exposure to metal mixtures in early pregnancy, both individually and as a mixture, was associated with the risk of HDP. Potential interaction effects of Al and V on the risk of HDP may exist.