Springer Science and Business Media LLC

In the European Union (EU), the safety assessment of plant protection products relies to a large extent on toxicity studies commissioned by the companies producing them. By law, all performed studies must be included in the dossier submitted to authorities when applying for approval or renewal of the active substance. For one type of toxicity, i.e. developmental neurotoxicity (DNT), we evaluated if studies submitted to the U.S. Environmental Protection Agency (EPA) had also been disclosed to EU authorities. We identified 35 DNT studies submitted to the U.S. EPA and with the corresponding EU dossiers available. Of these, 9 DNT studies (26%) were not disclosed by the pesticide company to EU authorities. For 7 of these studies, we have identified an actual or potential regulatory impact. We conclude that (1) non-disclosure of DNT studies to EU authorities, in spite of clear legal requirements, seems to be a recurring phenomenon, (2) the non-disclosure may introduce a bias in the regulatory risk assessment, and (3) without full access to all performed toxicity studies, there can be no reliable safety evaluation of pesticides by EU authorities. We suggest that EU authorities should cross-check their data sets with their counterparts in other jurisdictions. In addition, applications for pesticide approval should be cross-checked against lists of studies performed at test facilities operating under Good Laboratory Practice (GLP), to ensure that all studies have been submitted to authorities. Furthermore, rules should be amended so that future studies should be commissioned by authorities rather than companies. This ensures the authorities’ knowledge of existing studies and prevents the economic interest of the company from influencing the design, performance, reporting and dissemination of studies. The rules or practices should also be revised to ensure that non-disclosure of toxicity studies carries a significant legal risk for pesticide companies.

We discuss the translocation of inhaled asbestos fibers based on pulmonary and pleuro-pulmonary interstitial fluid dynamics. Fibers can pass the alveolar barrier and reach the lung interstitium via the paracellular route down a mass water flow due to combined osmotic (active Na+ absorption) and hydraulic (interstitial pressure is subatmospheric) pressure gradient. Fibers can be dragged from the lung interstitium by pulmonary lymph flow (primary translocation) wherefrom they can reach the blood stream and subsequently distribute to the whole body (secondary translocation). Primary translocation across the visceral pleura and towards pulmonary capillaries may also occur if the asbestos-induced lung inflammation increases pulmonary interstitial pressure so as to reverse the trans-mesothelial and trans-endothelial pressure gradients. Secondary translocation to the pleural space may occur via the physiological route of pleural fluid formation across the parietal pleura; fibers accumulation in parietal pleura stomata (black spots) reflects the role of parietal lymphatics in draining pleural fluid. Asbestos fibers are found in all organs of subjects either occupationally exposed or not exposed to asbestos. Fibers concentration correlates with specific conditions of interstitial fluid dynamics, in line with the notion that in all organs microvascular filtration occurs from capillaries to the extravascular spaces. Concentration is high in the kidney (reflecting high perfusion pressure and flow) and in the liver (reflecting high microvascular permeability) while it is relatively low in the brain (due to low permeability of blood-brain barrier). Ultrafine fibers (length < 5 μm, diameter < 0.25 μm) can travel larger distances due to low steric hindrance (in mesothelioma about 90% of fibers are ultrafine). Fibers translocation is a slow process developing over decades of life: it is aided by high biopersistence, by inflammation-induced increase in permeability, by low steric hindrance and by fibers motion pattern at low Reynolds numbers; it is hindered by fibrosis that increases interstitial flow resistances.

Abstract Background The Democratic National Convention (DNC) in Boston, Massachusetts in 2004 provided an opportunity to evaluate the impacts of a localized and short-term but potentially significant change in traffic patterns on air quality, and to determine the optimal monitoring approach to address events of this nature. It was anticipated that the road closures associated with the DNC would both influence the overall air pollution level and the distribution of concentrations across the city, through shifts in traffic patterns. Methods To capture these effects, we placed passive nitrogen dioxide badges at 40 sites around metropolitan Boston before, during, and after the DNC, with the goal of capturing the array of hypothesized impacts. In addition, we continuously measured elemental carbon at three sites, and gathered continuous air pollution data from US EPA fixed-site monitors and traffic count data from the Massachusetts Highway Department. Results There were significant reductions in traffic volume on the highway with closures north of Boston, with relatively little change along other highways, indicating a more isolated traffic reduction rather than an across-the-board decrease. For our nitrogen dioxide samples, while there was a relatively small change in mean concentrations, there was significant heterogeneity across sites, which corresponded with our a priori classifications of road segments. The median ratio of nitrogen dioxide concentrations during the DNC relative to non-DNC sampling periods was 0.58 at sites with hypothesized traffic reductions, versus 0.88 for sites with no changes hypothesized and 1.15 for sites with hypothesized traffic increases. Continuous monitors measured slightly lower concentrations of elemental carbon and nitrogen dioxide during road closure periods at monitors proximate to closed highway segments, but not for PM2.5 or further from major highways. Conclusion We conclude that there was a small but measurable influence of DNC-related road closures on air quality patterns in the Boston area, and that a low-cost monitoring study combining passive badges for spatial heterogeneity and continuous monitors for temporal heterogeneity can provide useful insight for community air quality assessments.

Few studies have assessed air pollution exposure association with birthweight during both preconception and gestational periods. Leveraging a preconception cohort consisting of 14220 pregnant women and newborn children in Shanghai, China during 2016–2018, we aim to assess associations of NO2 and PM2.5 exposure, derived from high-resolution spatial-temporal models, during preconception and gestational periods with outcomes including term birthweight, birthweight Z-score, small-for-gestational age (SGA) and large-for-gestational age (LGA). Linear and logistic regressions were used to estimate 3-month preconception and trimester-averaged air pollution exposure associations; and distributed lag models (DLM) were used to identify critical exposure windows at the weekly resolution from preconception to delivery. Two-pollutant models and children’s sex-specific associations were explored. After controlling for covariates, one standard deviation (SD) (11.5 μg/m3, equivalent to 6.1 ppb) increase in NO2 exposure during the second and the third trimester was associated with 13% (95% confidence interval: 2 – 26%) and 14% (95% CI: 1 – 29%) increase in SGA, respectively; and one SD (9.6 μg/m3) increase in PM2.5 exposure during the third trimester was associated with 15% (95% CI: 1 – 31%) increase in SGA. No association have been found for outcomes of birthweight, birthweight Z-score and LGA. DLM found that gestational weeks 22–32 were a critical window, when NO2 exposure had strongest associations with SGA. The associations of air pollution exposure tended to be stronger in female newborns than in male newborns. However, no significant associations of air pollution exposure during preconception period on birthweight outcomes were found. Consistent with previous studies, we found that air pollution exposure during mid-to-late pregnancy was associated with adverse birthweight outcomes.

The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed. We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA) using extensive data on covariates and residential history from two case-control studies for 1983–1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation. Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of breast cancer on upper Cape Cod. The analysis suggests further investigation of the potential association between breast cancer and pollution plumes based on detailed exposure modeling.

Household air pollution (HAP) from cooking with solid fuels has become a leading cause of death and disability in many developing countries including Bangladesh. We assess the association between HAP and risk of selected adverse birth and maternal health outcomes. Data for this study were extracted from Bangladesh Demographic and Health Survey conducted during 2007–2014. Selected adverse birth outcomes were acute respiratory infection (ARI) among children, stillbirth, low birth weight (LBW), under-five mortality, neonatal mortality and infant mortality. Maternal pregnancy complications and cesarean delivery were considered as the adverse maternal health outcomes. Place of cooking, use of solid fuel within the house boundary and in living room were the exposure variables. To examine the association between exposure and outcome variables, we used a series of multiple logistic regression models accounted for complex survey design. Around 90% of the respondents used solid fuel within the house boundary, 11% of them used solid fuel within the living room. Results of multiple regression indicated that cooking inside the house increased the risk of neonatal mortality (aOR,1.25; 95% CI, 1.02–1.52), infant mortality (aOR, 1.18; 95% CI, 1.00–1.40), ARI (aOR, 1.18; 95% CI, 1.08–1.33), LBW (aOR, 1.25; 95% CI, 1.10–1.43), and cesarean delivery (aOR,1.18; 95% CI, 1.01–1.29). Use of solid fuel, irrespective of cooking places, increased the risk of pregnancy complications (aOR, 1.36; 95% CI, 1.19–1.55). Compared to participants who reported cooking outside the house, the risk of ARI, LBW were significantly high among those who performed cooking within the house, irrespective of type of cooking fuel. Indoor cooking and use of solid fuel in household increase the risk of ARI, LBW, cesarean delivery, and pregnancy complication. These relationships need further investigation using more direct measures of smoke exposure and clinical measures of health outcomes. The use of clean fuels and structural improvement in household design such as provision of stove ventilation should be encouraged to reduce such adverse health consequences. Data related to health were collected by following the guidelines of ICF international and Bangladesh Medical Research Council. The registration number of data collection was 132,989.0.000, and the data-request was registered on March 11, 2015.

We previously found additive effects of long- and short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) on all-cause mortality rate using a generalized propensity score (GPS) adjustment approach. The study addressed an important question of how many early deaths were caused by each exposure. However, the study was computationally expensive, did not capture possible interactions and high-order nonlinearities, and omitted potential confounders. We proposed two new methods and reconducted the analysis using the same cohort of Medicare beneficiaries in Massachusetts during 2000–2012, which consisted of 1.5 million individuals with 3.8 billion person-days of follow-up. The first method, weighted least squares (WLS), leveraged large volume of data by aggregating person-days, which gave equivalent results to the linear probability model (LPM) method in the previous analysis but significantly reduced computational burden. The second method, m-out-of-n random forests (moonRF), implemented scaling random forests that captured all possible interactions and nonlinearities in the GPS model. To minimize confounding bias, we additionally controlled relative humidity and health care utilizations that were not included previously. Further, we performed low-level analysis by restricting to person-days with exposure levels below increasingly stringent thresholds. We found consistent results between LPM/WLS and moonRF: all exposures were positively associated with mortality rate, even at low levels. For long-term PM2.5 and O3, the effect estimates became larger at lower levels. Long-term exposure to PM2.5 posed the highest risk: 1 μg/m3 increase in long-term PM2.5 was associated with 1053 (95% confidence interval [CI]: 984, 1122; based on LPM/WLS methods) or 1058 (95% CI: 988, 1127; based on moonRF method) early deaths each year among the Medicare population in Massachusetts. This study provides more rigorous causal evidence between PM2.5, O3, and NO2 exposures and mortality, even at low levels. The largest effect estimate for long-term PM2.5 suggests that reducing PM2.5 could gain the most substantial benefits. The consistency between LPM/WLS and moonRF suggests that there were not many interactions and high-order nonlinearities. In the big data context, the proposed methods will be useful for future scientific work in estimating causality on an additive scale.

Although recent research evidence suggests an association between household air pollution from solid fuel use, such as coal or biomass, and cardiovascular events such as hypertension, little epidemiologic data are available concerning such exposure effects on cardiovascular endpoints other than hypertension. We explored the association between in-home solid fuel use and self-reported diagnoses of cardiovascular endpoints, such as hypertension, coronary heart disease (CHD), stroke, and diabetes. We analyzed 14,068 Chinese adults, aged 18 years and older. Odds ratios (OR) and the corresponding 95% confidence intervals (CI) were estimated using logistic regression models for the risk of each outcome after adjusting for potential confounders. The use of solid fuel in home was significantly associated with an increased risk for hypertension (OR 1.70, 95% CI 1.40 to 2.07), CHD (OR 2.58, 95% CI 1.53 to 4.32), and diabetes (OR 2.48, 95% CI 1.59 to 3.86), after adjusting for potential confounders. Compared with individuals in the lowest tertile of the duration of solid fuel exposure, those in the highest tertile of the duration of solid fuel exposure had an increased odds of hypertension (OR 1.73, 95% CI 1.45 to 2.06), stroke (OR 1.87, 95% CI 1.03 to 3.38), and diabetes (OR 3.18, 95% CI 2.11 to 4.78). Our data suggest that in-home solid fuel exposure maybe associated with increased risk for hypertension, CHD, stroke, and diabetes in the Chinese adult population. Further large-scale longitudinal studies are warranted to confirm these findings.

Studies of effects of hurricanes on perinatal outcomes often rely on approximate measures of exposure. This study aims to use observed damage from aerial imagery to refine residential building damage estimates, evaluate the population changes post landfall, and assess the associations between the extent of residential building damage and adverse perinatal outcomes and access to prenatal care (PNC) services.  Vital statistics data from the Florida Department of Health’s Office of Vital Statistics were used to align maternal geocoded address data to high-resolution imagery (0.5-foot resolution, true color with red, blue, and green bands) aerial photographs. Machine learning (support vector machines) classified residential roof damage across the study area. Perinatal outcomes were compared with the presence or absence of damage to the mother’s home. Log-binomial regression models were used to compare the populations living in and outside of high-risk/damage areas, to assess the population changes after Hurricane Michael, and to estimate the associations between damage after Hurricane Michael and adverse perinatal outcomes/access to PNC services. A semi-parametric linear model was used to model time of first PNC visit and increase in damage. We included 8,965 women in analysis. Women with lower education and/or of Black or other non-White race/ethnicity were more likely to live in areas that would see high damage than other groups. Moreover, there was a greater proportion of births delivered by women living in the high-risk/damage area (> 25% damaged parcels after Michael) in the year before Michael than the year after Michael. Lastly, living in the area with relatively high damage increased the risk of having intermediate or inadequate PNC (adjusted Risk Ratio = 1.21, 95% CI: 1.03, 1.43), but not other adverse perinatal outcomes. Aerially observed damage data enable us to evaluate the impact of natural disasters on perinatal outcomes and access to PNC services based on residential building damage immediately surrounding a household. The association between the extent of damage and adverse perinatal outcomes should be further investigated in future studies.