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Aims: Blood biochemistry may provide information on associations between road traffic noise, air pollution, and cardiovascular disease risk. We evaluated this in two large European cohorts (HUNT3, Lifelines)., Methods and Results: Road traffic noise exposure was modelled for 2009 using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU). Annual ambient air pollution (PM10, NO2) at residence was estimated for 2007 using a Land Use Regression model. The statistical platform DataSHIELD was used to pool data from 144 082 participants aged ≥20 years to enable individual-level analysis. Generalized linear models were fitted to assess cross-sectional associations between pollutants and high-sensitivity C-reactive protein (hsCRP), blood lipids and for (Lifelines only) fasting blood glucose, for samples taken during recruitment in 2006-2013. Pooling both cohorts, an inter-quartile range (IQR) higher day-time noise (5.1 dB(A)) was associated with 1.1% [95% confidence interval (95% CI: 0.02-2.2%)] higher hsCRP, 0.7% (95% CI: 0.3-1.1%) higher triglycerides, and 0.5% (95% CI: 0.3-0.7%) higher high-density lipoprotein (HDL); only the association with HDL was robust to adjustment for air pollution. An IQR higher PM10 (2.0 µg/m3) or NO2 (7.4 µg/m3) was associated with higher triglycerides (1.9%, 95% CI: 1.5-2.4% and 2.2%, 95% CI: 1.6-2.7%), independent of adjustment for noise. Additionally for NO2, a significant association with hsCRP (1.9%, 95% CI: 0.5-3.3%) was seen. In Lifelines, an IQR higher noise (4.2 dB(A)) and PM10 (2.4 µg/m3) was associated with 0.2% (95% CI: 0.1-0.3%) and 0.6% (95% CI: 0.4-0.7%) higher fasting glucose respectively, with both remaining robust to adjustment for air/noise pollution., Conclusion: Long-term exposures to road traffic noise and ambient air pollution were associated with blood biochemistry, providing a possible link between road traffic noise/air pollution and cardio-metabolic disease risk., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.)

The forest-steppe ecotone in southern Siberia is highly sensitive to climate change; global warming is expected to push the ecotone northwards, at the same time resulting in degradation of the underlying permafrost. To gain a deeper understanding of long-term forest-steppe carbon dynamics, we use a highly resolved, multiproxy, palaeolimnological approach, based on sediment records from Lake Baikal. We reconstruct proxies that are relevant to understanding carbon dynamics including carbon mass accumulation rates (CMAR; g C m -2  yr -1 ) and isotope composition of organic matter (δ 13 C TOC ). Forest-steppe dynamics were reconstructed using pollen, and diatom records provided measures of primary production from near- and off-shore communities. We used a generalized additive model (GAM) to identify significant change points in temporal series, and by applying generalized linear least-squares regression modelling to components of the multiproxy data, we address (1) What factors influence carbon dynamics during early Holocene warming and late Holocene cooling? (2) How did carbon dynamics respond to abrupt sub-Milankovitch scale events? and (3) What is the Holocene carbon storage budget for Lake Baikal. CMAR values range between 2.8 and 12.5 g C m -2  yr -1 . Peak burial rates (and greatest variability) occurred during the early Holocene, associated with melting permafrost and retreating glaciers, while lowest burial rates occurred during the neoglacial. Significant shifts in carbon dynamics at 10.3, 4.1 and 2.8 kyr bp provide compelling evidence for the sensitivity of the region to sub-Milankovitch drivers of climate change. We estimate that 1.03 Pg C was buried in Lake Baikal sediments during the Holocene, almost one-quarter of which was buried during the early Holocene alone. Combined, our results highlight the importance of understanding the close linkages between carbon cycling and hydrological processes, not just temperatures, in southern Siberian environments., (© 2016 John Wiley & Sons Ltd.)

We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006-2013 (HUNT3, Lifelines and UK Biobank).Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM 10 ) and nitrogen dioxide (NO 2 )) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a "compute to the data" approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence.PM 10 or NO 2 higher by 10 µg·m -3 was associated with 12.8% (95% CI 9.5-16.3%) and 1.9% (95% CI 1.1-2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence.This study suggests that long-term ambient PM 10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation., (Copyright ©ERS 2017.)

Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman's rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Lifelines is a prospective population-based cohort study investigating the biological, behavioral and environmental determinants of healthy ageing among 167,729 participants from the North East region of the Netherlands. The collection and geocoding of (history of) home and work addresses allows linkage of individual-level health data to detailed exposure data. We describe the reasons for choosing particular assessments of environmental exposures in LifeLines and consider the implications for future investigations., Methods: Exposure to ambient air pollution and road traffic noise was estimated using harmonized models. Data on noise annoyance, perceived exposure to electromagnetic fields, perceived living environment, and neighborhood characteristics were collected with questionnaires. A comprehensive medical assessment and questionnaires were completed in order to assess determinants of health and well-being. Blood and urine samples were collected from all participants and genome wide association data are available for a subsample of 15,638 participants., Results: Mean age was 45 years (standard deviation (SD) 13 years), and 59 % were female. Median levels of NO2 and PM10 were 15.7 (interquartile range (IQR) 4.9) μg/m(3) and 24.0 (IQR 0.6) μg/m(3) respectively. Median levels of daytime road traffic noise were 54.0 (IQR 4.2) dB(A)., Conclusions: The combination of harmonized environmental exposures and extensive assessment of health outcomes in LifeLines offers great opportunities for environmental epidemiology. LifeLines aims to be a resource for the international scientific community.

The EU-FP7-funded BioSHaRE project is using individual-level data pooled from several national cohort studies in Europe to investigate the relationship of road traffic noise and health. The detailed input data (land cover and traffic characteristics) required for noise exposure modelling are not always available over whole countries while data that are comparable in spatial resolution between different countries is needed for harmonised exposure assessment. Here, we assess the feasibility using the CNOSSOS-EU road traffic noise prediction model with coarser input data in terms of model performance. Starting with a model using the highest resolution datasets, we progressively introduced lower resolution data over five further model runs and compared noise level estimates to measurements. We conclude that a low resolution noise model should provide adequate performance for exposure ranking (Spearman's rank = 0.75; p < 0.001), but with relatively large errors in predicted noise levels (RMSE = 4.46 dB(A))., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Objectives: We investigated the role of a stress-sensitive personality on relations between noise, noise annoyance and somatic symptom reporting. First, we investigated the cross-sectional association of road traffic noise exposure and somatic symptoms, and its modification by hostility and vulnerability to stress. Second, we investigated the cross-sectional association of noise annoyance from eight sources (e.g. road traffic, aircraft, neighbours) and somatic symptoms, and it's confounding by hostility and vulnerability to stress., Methods: Data were obtained from LifeLines, a general population cohort from the Netherlands. Road traffic noise was estimated using the Common Noise Assessment Methods in Europe (CNOSSOS-EU) noise model. Noise annoyance, hostility, vulnerability to stress, and somatic symptoms were assessed with validated questionnaires., Results: Poisson regression models adjusted for demographic and socioeconomic variables indicated no association of noise exposure and somatic symptoms (incidence rate ratio (IRR) 1.001; 95% confidence interval (CI) 1.000-1.001; n=56,937). Interactions of noise exposure and hostility and vulnerability to stress were not statistically significant. Small positive associations were found for noise annoyance from each of the eight sources and somatic symptoms, when adjusted for demographic and socioeconomic variables (e.g. for road traffic noise annoyance IRR 1.014, 95% CI 1.011-1.018; n=6177). Additional adjustment for hostility and vulnerability to stress resulted in small decreases of the IRRs for noise annoyance from each of the eight sources, but the associations remained statistically significant., Conclusions: Personality facets hostility and vulnerability to stress did not modify the relation between road traffic noise exposure and somatic symptom reporting, or confound relations between noise annoyance and symptoms., (Copyright © 2015 Elsevier GmbH. All rights reserved.)

Background: Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI., Methods: In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa., Results: This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found., Conclusions: These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality., (© The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Uncooked corn-starch (UCCS) has been the mainstay of therapy for the hepatic glycogen storage diseases (GSD) but is not always effective. A new starch (WMHMS) has demonstrated a more favourable short-term metabolic profile., Objective: To determine efficacy and safety of a new uncooked starch (WMHMS) compared to UCCS over 16 weeks treatment with each., Method: A double-blind cross-over study of 10 adults (aged 16 - 38 years, six male) with GSD Ia and Ib. After an individualised fast, subjects were randomised to take a 50 g starch-load of either WMHMS or UCCS. Starch-loads terminated when blood glucose was < 3.0 mmol/L or the subject felt subjectively hypoglycaemic. Anonymous biochemical profiles were assessed by 2 investigators and a starch administration schedule recommended. Each starch was delivered in coded sachets and intake was monitored for the following 16 weeks. After a washout period, the protocol was repeated with the alternative product., Results: 4 subjects failed to establish therapy on the cross-over limb. Data from 7 paired starch load showed: longer median fasting duration with WMHMS (7.5 versus 5 hours; p = 0.023), slower decrease in the glucose curve (0.357 versus 0.632 mmol/hr p = 0.028) and less area under insulin curves for the first 4 hours (p = 0.03). Two of six subjects took 50% or less WMHMS compared to UCCS and one took more. Plasma triglycerides, cholesterol and uric acid were unchanged after each study phase., Conclusion: WMHMS leads to significant reduction in insulin release and reduced starch use in some GSD patients.

Objectives: In the context of public health, risk governance (or risk analysis) is a framework for the assessment and subsequent management and/or control of the danger posed by an identified disease threat. Generic frameworks in which to carry out risk assessment have been developed by various agencies. These include monitoring, data collection, statistical analysis and dissemination. Due to the inherent complexity of disease systems, however, the generic approach must be modified for individual, disease-specific risk assessment frameworks., Study Design: The analysis was based on the review of the current risk assessments of vector-borne diseases adopted by the main Public Health organisations (OIE, WHO, ECDC, FAO, CDC etc…)., Methods: Literature, legislation and statistical assessment of the risk analysis frameworks., Results: This review outlines the need for the development of a general public health risk assessment method for vector-borne diseases, in order to guarantee that sufficient information is gathered to apply robust models of risk assessment. Stochastic (especially spatial) methods, often in Bayesian frameworks are now gaining prominence in standard risk assessment procedures because of their ability to assess accurately model uncertainties., Conclusions: Risk assessment needs to be addressed quantitatively wherever possible, and submitted with its quality assessment in order to enable successful public health measures to be adopted. In terms of current practice, often a series of different models and analyses are applied to the same problem, with results and outcomes that are difficult to compare because of the unknown model and data uncertainties. Therefore, the risk assessment areas in need of further research are identified in this article., (Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.)

Background: Developmental delay in the offspring of women with phenylketonuria (PKU) can be prevented by maintaining maternal blood phenylalanine (Phe) within a target range (100-250 micromol/L)., Objective: We aimed to analyze outcomes in the offspring of women with PKU during pregnancy and to identify prognostic factors., Design: Occipitofrontal circumference at birth (OFC-B); developmental scores [developmental quotient (DQ) and intelligence quotient (IQ)]at 1, 4, 8, and 14 y; and the time of starting a Phe-restricted diet (before or after conception) were collected. The influence of maternal Phe concentrations during pregnancy on offspring outcomes also was assessed., Results: The study included 105 children born to 67 mothers with PKU. Mean (+/-SD) OFC-B z scores did not differ between the preconception and postconception diet groups (0.42 +/- 1.24 and -0.96 +/- 1.19, respectively). DQ at 1 y and IQ at 8 y were higher in offspring from the preconception diet group than in offspring from the postconception diet group [DQ: 107 +/- 13.8 and 99.3 +/- 13.3, respectively (P = 0.014); IQ: 110.6 +/- 14.8 and 91.2 +/- 23.9, respectively (P = 0.005)]. Maternal Phe concentrations correlated negatively with DQ and IQ scores, and variations (SD) in all maternal blood Phe correlated negatively with 4-, 8-, and 14-y IQ scores (r = -0.385, -0.433, and -0.712; P = 0.002, 0.008, and 0.031, respectively), even when concentrations were consistently within the target range., Conclusions: The study suggests that women with PKU should start a Phe-restricted diet before conception. Maintenance of maternal blood Phe within the target range predicts good offspring outcomes, but variations even within that range should be avoided.

Objective: To determine whether a new starch offers better short-term metabolic control than uncooked cornstarch in patients with glycogen storage diseases (GSDs)., Study Design: A short-term double-blind cross-over pilot study comparing uncooked physically modified cornstarch (WMHM20) with uncooked cornstarch in patients with GSD types Ia, Ib and III. Twenty-one patients (ages 3-47, 9 female) were given 2 g/kg cornstarch or WMHM20 mixed in water. Blood glucose, lactate and insulin, and breath hydrogen and (13)CO2 enrichment were measured, at baseline and after each load. The hourly biochemical evaluations terminated when blood glucose was < or = 3.0 mmol/L, when the study period had lasted 10 h or when the patient wished to end the test. The alternative starch was administered under similar trial conditions a median of 10 days later., Results: The median starch load duration was 9 h for WMHM20 versus 7 h for cornstarch. Glucose decreased more slowly (p = 0.05) and lactate was suppressed faster (p = 0.17) for WMHM20 compared with cornstarch. Peak hydrogen excretion was increased (p = 0.05) when cornstarch was taken., Conclusion: These data indicate longer duration of euglycaemia and better short-term metabolic control in the majority of GSD patients with WMHM20 compared to cornstarch.