Selective Migration in New Towns: Influence on Regional Accountability in Early School Leaving

In an attempt to stop the rampant suburbanization, which countries experienced after World War II, a 'new town' policy was enrolled. As a major objective, and related to its origins, new towns were effective in attracting low and medium income households. Nowadays, cities and municipalities experience an increased accountability in which incentives are provided by 'naming and shaming'. This paper focuses on an issue where both historical and local policy come together: early school leaving. Using an iterative matching analysis, it suggests how to account for differences in population and regional characteristics. In other words, how to compare and interpret early school leaving in new towns in a more `fair' way. The results point out that (statistically) mitigating historical differences is necessary, even though this does not necessarily means that 'naming' is replaced by 'shaming'.Urban Economics; New Town; Early School Leaving; Naming and Shaming; Iterative Matching, Urban Planning

Impact of foods with health logo on ssaturated fat, sodium and sugar intake of young Dutch adults

Objective Health logos are introduced to distinguish foods with ‘healthier’ nutrient composition from regular foods. In the present study, we evaluated the effects of changed food compositions according to health logo criteria on the intake of saturated fat, sugar and sodium in a Dutch population of young adults. Design Foods in the Dutch food composition table were evaluated against nutrient criteria for logo eligibility. Three replacement scenarios were compared with the nutrient intake ‘as measured’ in the Dutch consumption survey. The foods not complying with health logo criteria were replaced either by ‘virtual’ foods exactly complying with the health logo criteria, with real 2007 market shares (scenario I) and 100 % market shares (scenario II), or by existing similar foods with a composition that already complied with the health logo criteria (scenario III). Results The percentage reduction in nutrient intake with the current 2007 market shares of ‘health logo foods’ was -2·5 % for SFA, 0 % for sodium and -1 % for sugar. With a 100 % market share these reductions would be -10 % for SFA, -4 % for sodium and -6 % for sugar. This may lead to a reduction of -40 % for SFA, -23 % for sodium and -36 % for sugar in the most optimal replacement scenario. Conclusions With ‘health logo foods’, available in 2007 and current consumption patterns, small reductions can be achieved for SFA and sugar. For additional reductions, lowering the fat/sodium content of meat (products) towards health logo criteria and drinks without sugar towards limits far below health logo criteria would be the most effective reformulation strategy

Inname aan zware metalen en nitraat door jonge kinderen

Innameberekeningen zijn uitgevoerd voor zware metalen, nitraat en zout op basis van metingen uit een duplicaat voedingsstudie bij baby's en deze zijn vergeleken met innameberekeningen op basis van monitoringsdata uit de KAP-databank. Voor de duplicaat voedingen is gebruik gemaakt van data verzameld in de EUBABY-studie van baby’s van 8 tot 12 maande

Intake of nitrate and nitrite and the risk of gastric cancer: a prospective cohort study.

The association between the intake of nitrate or nitrite and gastric cancer risk was investigated in a prospective cohort study started in 1986 in the Netherlands, of 120,852 men and women aged 55-69 years. At baseline, data on dietary intake, smoking habits and other covariates were collected by means of a self-administered questionnaire. For data analysis, a case-cohort approach was used, in which the person-years at risk were estimated from a randomly selected subcohort (1688 men and 1812 women). After 6.3 years of follow-up, 282 microscopically confirmed incident cases of stomach cancer were detected: 219 men and 63 women. We did not find a higher risk of gastric cancer among people with a higher nitrate intake from food [rate ratio (RR) highest/lowest quintile = 0.80, 95% CI 0.47-1.37, trend-P = 0.18], a higher nitrate intake from drinking water (RR highest/lowest quintile = 0.88, 95% CI 0.59-1.32, trend-P = 0.39) or a higher intake of nitrite (RR highest/lowest quintile = 1.44, 95% CI 0.95-2.18, trend-P = 0.24). Rate ratios for gastric cancer were also computed for each tertile of nitrate intake from foods within tertiles of vitamin C intake and intake of beta-carotene, but no consistent pattern was found. Therefore, our study does not support a positive association between the intake of nitrate or nitrite and gastric cancer risk

Automated mobile virtual reality cognitive behavior therapy for aviophobia in a natural setting: a randomized controlled trial

Background: Access to evidence-based psychological treatment is a challenge worldwide. We assessed the effectiveness of a fully automated aviophobia smartphone app treatment delivered in combination with a $5 virtual reality (VR) viewer.Methods: In total, 153 participants from the Dutch general population with aviophobia symptoms and smartphone access were randomized in a single-blind randomized controlled trial to either an automated VR cognitive behavior therapy (VR-CBT) app treatment condition (n = 77) or a wait-list control condition (n = 76). The VR-CBT app was delivered over a 6-week period in the participants' natural environment. Online self-report assessments were completed at baseline, post-treatment, at 3-month and at 12-month follow-up. The primary outcome measure was the Flight Anxiety Situations Questionnaire (FAS). Analyses were based on intent-to-treat.Results: A significant reduction of aviophobia symptoms at post-test for the VR-CBT app compared with the control condition [p Conclusions: This study is the first to show that fully automated mobile VR-CBT therapy delivered in a natural setting can maintain long-term effectiveness in reducing aviophobia symptoms. In doing so, it offers an accessible and scalable evidence-based treatment solution that can be applied globally at a fraction of the cost of current treatment alternatives

Dynamic vehicle routing with time windows in theory and practice

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon’s benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment

Distribution of emphysema in heavy smokers: Impact on pulmonary function

SummaryPurposeTo investigate impact of distribution of computed tomography (CT) emphysema on severity of airflow limitation and gas exchange impairment in current and former heavy smokers participating in a lung cancer screening trial.Materials and MethodsIn total 875 current and former heavy smokers underwent baseline low-dose CT (30mAs) in our center and spirometry and diffusion capacity testing on the same day as part of the Dutch–Belgian Lung Cancer Screening Trial (NELSON). Emphysema was quantified for 872 subjects as the number of voxels with an apparent lowered X-ray attenuation coefficient. Voxels attenuated <−950HU were categorized as representing severe emphysema (ES950), while voxels attenuated between −910HU and −950HU represented moderate emphysema (ES910). Impact of distribution on severity of pulmonary function impairment was investigated with logistic regression, adjusted for total amount of emphysema.ResultsFor ES910 an apical distribution was associated with more airflow obstruction and gas exchange impairment than a basal distribution (both p<0.01). The FEV1/FVC ratio was 1.6% (95% CI 0.42% to 2.8%) lower for apical predominance than for basal predominance, for Tlco/VA the difference was 0.12% (95% CI 0.076–0.15%). Distribution of ES950 had no impact on FEV1/FVC ratio, while an apical distribution was associated with a 0.076% (95% CI 0.038–0.11%) lower Tlco/VA (p<0.001).ConclusionIn a heavy smoking population, an apical distribution is associated with more severe gas exchange impairment than a basal distribution; for moderate emphysema it is also associated with a lower FEV1/FVC ratio. However, differences are small, and likely clinically irrelevant

Deliverable 6.1 - Demonstration prototype of the EuroMix model toolbox

This document describes in short the new features in a demonstration prototype of the EuroMix toolbox, developed as MCRA 8.2. An important aim of the EuroMix project is to develop and implement a web-based platform (the EuroMix toolbox) including data and models accessible to all key-actors in risk assessment and risk management. In the EuroMix project the development of a mixture selection module based on exposure was prioritised, because the choice of chemicals for the experiments depended on this. A mixture selection module was therefore developed, based on a method called sparse non-negative matrix under-approximation (SNMU). The mixture selection module was then applied to French and Dutch data, leading to a list of suggested chemicals for each adverse outcome pathway in the project