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)

The antimicrobial agent triclosan (TCS) has attracted much attention worldwide because of its pervasive existence in the human body and environment. TCS exposure has been reported to be associated with decreased male reproductive function. However, few studies have investigated these associations in humans. To examine the relationship between TCS in urine and male semen quality. A total of 406 men from a reproductive clinic were enrolled in this study. Urinary TCS concentrations were determined by ultra-high performance liquid chromatography–electrospray ionization tandem mass spectrometry. Sixteen semen parameters were assessed according to the guidelines of World Health Organization (WHO), including parameters for volume, count, motility, and motion. We used multivariate linear regression models and restricted cubic splines to estimate the linear and non-linear associations between TCS exposure and semen parameters, respectively. Logistical regression models were further applied to explore the associations with abnormal semen quality. TCS was detected in 74.6% of urine specimens. The monotonous trend of TCS tertiles and continuous TCS levels with all semen quality parameters were not observed in multivariate linear regression models (p > 0.05). However, compared with those in the lowest tertile, subjects in the second tertile showed significantly higher linearity and wobble (p < 0.05), indicating potential effects on sperm motion. In the models using restricted cubic splines with 3–5 knots, there were no significant non-linear associations between TCS exposure and any semen quality parameter. In addition, TCS tertiles were not associated with the risk of abnormal semen quality (i.e., count and motility) in the logistical regression models. Our results revealed that low-level TCS exposure may have limited (none or modest) effects on male semen quality, potentially inducing some fluctuations. Further mechanistic studies on low levels of exposure are needed.

Sea fish contain omega-3 polyunsaturated fatty acids (omega-3 PUFAs) which have been found to reduce triglyceride (TG) levels. However, sea fish may contain pollutants such as mercury which cause oxidative stress and increase TG levels. Therefore, the relationship between sea fish and TG remains unclear. We aimed to explore whether blood mercury (BHg) can affect the effect of sea fish consumption frequency on TG level among Chinese adults. A total of 10,780 participants were included in this study. BHg levels were measured using inductively coupled plasma mass spectrometry (ICP-MS). The associations of sea fish consumption frequency with BHg and TG levels as well as the association of BHg with TG levels were evaluated using multiple linear regression. Causal mediation analysis was used to evaluate the mediation effect of BHg levels on the association of sea fish consumption frequency with TG levels. The frequency of sea fish consumption showed a negative association with TG level. Compared with the participants who never ate sea fish, the TG level decreased by 0.193 mmol/L in those who ate sea fish once a week or more [β (95%CI): −0.193 (−0.370, −0.015)]. Significant positive associations were observed of BHg with TG levels. With one unit increase of log2-transformed BHg, the change of TG level was 0.030 mmol/L [0.030 (0.009, 0.051)]. The association between sea fish consumption and TG was mediated by log2-transformed BHg [total effect = −0.037 (−0.074, −0.001); indirect effect = 0.009 (0.004, 0.015)], and the proportion mediated by log2-transformed BHg was 24.25%. BHg may reduce the beneficial effect of sea fish consumption frequency on TG levels among Chinese adults. Overall, sea fish consumption has more benefits than harms to TG.

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.

Bisphenol A (BPA) is a representative endocrine disrupting compound used in a vast array of consumer products, and are being frequently substituted by its analogues, bisphenol S (BPS) and bisphenol F (BPF). We aimed to examine the association between urinary bisphenol levels with obesity and lipid profiles in the general population to comprehensively evaluate its potential of metabolic disturbance. A representative sample of 1046 US adults from the National Health and Nutrition Examination Survey (2013–2016) and 3268 Korean adults from the Korean National Environmental Health Survey (2015–2017) was analyzed. We examined the exposure levels of bisphenols and determined their associations with obesity, high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) levels, and hypercholesterolemia prevalence through multiple linear, and binary/ordinal logistic regression models. In both populations, high BPA levels (lowest tertile vs. 2nd, 3rd tertiles) showed corresponding associations with lipid profile and obesity. BPA levels were associated with decreased HDL-C levels (Q3: β = −0.053, p = 0.08 (US); Q2: β = −0.030, p-0.03), increased TG levels (Q3: β = 0.121, p = 0.029 (US); Q3: β = 0.089, p = 0.021, and higher odds for obesity (Q3: OR = 1.58, 95% CI: 1.06, 2.35 (US); Q3: OR = 1.41, 95% CI: 1.11, 1.78). Higher BPS levels were positively associated with obesity status, especially in US men (Q2: OR = 1.84, 95% CI: 1.15, 2.96) and Korean women (Q3: OR = 1.27, 95% CI: 0.99, 1.64). A significant decrease in HDL-C (Q3: β = −0.088, p = 0.01) and elevated odds for obesity at higher BPF levels (Q3: OR = 1.60, 95% CI: 1.00, 2.56) was observed in US women. The findings of our study indicate that BPA and its analogues, BPS and BPF, are associated with lipid metabolism disorders in addition to obesity in adults. Given the increase in exposure to BPA alternatives, continuous biomonitoring, and further investigation of their health effects through prospective cohort studies are warranted.

Air pollution is a leading public health concern around the world. Assessing the public's knowledge about air quality is critical to calibrate public health interventions. However, previous efforts to measure knowledge about air quality (AQIQ) have not relied on consistent and validated measures, thus precluding cross-country comparisons. We aimed to develop a robust scale to assess AQIQ and tested it in multiple countries. To evaluate the psychometric properties and select the best performing items out of 10 AQIQ questions, we used methods from classical test theory and item response theory. We evaluated the scales using several scalability measures, including the Kuder-Richardson Formula 20 (KR-20), Loevinger's H, as well as trace lines. Volunteers from the United States (US, n = 400), India (n = 403), and China (n = 443) were recruited to validate the scale. Multiple linear regression was used to estimate the association between demographic factors and AQIQ. We found that participants from India had the highest AQIQ. In addition, not all questions performed well in each country. The scale was pruned and shorter subscales were validated. In the US, we obtained a 4-item scale (KR20 = 0.53, Loevinger's H = 0.34). In India, we obtained a 6-item scale (KR20 = 0.56; Loevinger's H = 0.48 for just 2 items). In China, we obtained a 5-item scale (KR20 = 0.39; Loevinger's H = 0.41 for just 2 items). Compared to the 10-item scale, the pruned scales showed stronger associations between measures of socioeconomic status and AQIQ. The results were robust to the scale used. Overall, general knowledge questions measured AQIQ more effectively in the US and India whereas knowledge of the air quality index better measured AQIQ in China. The findings suggest that careful measurement and validation are essential to develop knowledge scales for use in public health and environmental research.

This study aims to investigate the effect of transportation infrastructure on the decrease of NO₂ air pollution during three COVID-19-induced lockdowns in a vast region of France. For this purpose, using Sentinel-5P satellite data, the relative change in tropospheric NO₂ air pollution during the three lockdowns was calculated. The estimation of regional infrastructure intensity was performed using Kernel Density Estimation, being the predictor variable. By performing hotspot–coldspot analysis on the relative change in NO₂ air pollution, significant spatial clusters of decreased air pollution during the three lockdowns were identified. Based on the clusters, a novel spatial index, the Clustering Index (CI) was developed using its Coldspot Clustering Index (CCI) variant as a predicted variable in the regression model between infrastructure intensity and NO₂ air pollution decline. The analysis revealed that during the three lockdowns there was a strong and statistically significant relationship between the transportation infrastructure and the decline index, CCI (r = 0.899, R² = 0.808). The results showed that the largest decrease in NO₂ air pollution was recorded during the first lockdown, and in this case, there was the strongest inverse correlation with transportation infrastructure (r = −0.904, R² = 0.818). Economic and population predictors also explained with good fit the decrease in NO₂ air pollution during the first lockdown: GDP (R² = 0.511), employees (R² = 0.513), population density (R² = 0.837). It is concluded that not only economic-population variables determined the reduction of near-surface air pollution but also the transportation infrastructure. Further studies are recommended to investigate other pollutant gases as predicted variables.

The association between polycyclic aromatic hydrocarbons (PAHs) exposure and hearing loss is rarely assessed. We aimed to evaluate the relationship of polycyclic aromatic hydrocarbons (PAHs) exposure and hearing loss among US adults and adolescents, and to explore the mediating role of systemic inflammation in the associations. Participants from the National health and Nutrition Examination Surveys (NHANES, 2001–2016) were included. Multiple logistic regression models were used to explore the associations between PAH metabolites and hearing loss. A total of 4200 adults and 1337 adolescents were included in the present analysis. For adults, we found positive association between urinary PAH metabolites and hearing loss, including total, speech-frequency and high-frequency hearing loss. The odds ratios (ORs) and 95% confidence intervals (CIs) for each one-unit increase in the log-transformed level of 3-Hydroxyfluorene (3-OHFlu), 2-Hydroxyfluorene (2-OHFlu) and 2 & 3-Hydroxyphenanthrene (2&3-OHPh) with total hearing loss were 1.17 (1.04–1.31), 1.24 (1.07–1.43), and 1.18 (1.03–1.37), respectively. For adolescents, urinary PAH metabolites were positively associated with total and speech-frequency hearing loss, not with high-frequency. The ORs and 95% CIs for each one-unit increase in the log-transformed level of 3-OHFlu, 2-OHFlu and total urinary PAH metabolites with total hearing loss were 1.34 (1.06–1.68), 1.48 (1.13–1.93), and 1.33 (1.04–1.72), respectively. Each one-unit increase in the log-transformed level 2-OHFlu (β = 0.112, 95%CI = 0.018–0.206) and 2&3-OHPh (β = 0.145, 95%CI = 0.037–0.253) were positively associated with C-reactive protein (CRP) among adolescents, but not among adults. No mediating effect for CRP on the association of urinary PAH metabolites with hearing loss was found (all P > 0.05). 3-OHFlu and 2-OHFlu are associated with increased prevalence of hearing loss among adults and adolescents. Systemic inflammation does not mediate the associations. Further studies should be conducted to verify the results.

From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutional neural network and Shapely additive explanation (SHAP) to examine the complex underlying nonlinearity between variations of surface ozone and meteorological factors. Results of the models showed that between 2000 and 2019, specific humidity (38% and 27%) and temperature (28% and 37%) contributed the most to ozone formation over the Houston and Dallas metropolitan areas, respectively. On the other hand, the results show that solar radiation (50%) strongly impacted ozone variation over West Texas during this time. Using a combination of the Kolmogorov-Zurbenko (KZ) filter and multiple linear regression, we also evaluated the influence of meteorology on ozone and quantified the contributions of meteorological parameters to trends in surface ozone formation. Our findings showed that in Houston and Dallas, meteorology influenced ozone variations to a large extent. The impacts of meteorology on West Texas, however, showed meteorological factors had fewer influences on ozone variabilities from 2000 to 2019. This study showed that SHAP analysis and the KZ approach can investigate the contributions of the meteorological factors on ozone concentrations and help policymakers enact effective ozone mitigation policies.