Accounting for Big City Growth in Low Paid Occupations: Immigration and/or Service Class Consumption

Growth of 'global cities' in the 1980s was supposed to have involved an occupational polarisation, including growth of low paid service jobs. Though held to be untrue for European cities, at the time, some such growth did emerge in London a decade later than first reported for New York. The question is whether there was simply a delay before London conformed to the global city model, or whether another distinct cause was at work in both cases. This paper proposes that the critical factor in both cases was actually an upsurge of immigration from poor countries providing an elastic supply of cheap labour. This hypothesis and its counterpart based on growth in elite jobs are tested econometrically for the British case with regional data spanning 1975-2008, finding some support for both effects, but with immigration from poor countries as the crucial influence in late 1990s London. Keywords: regional labour markets; wages; employment; international migration; consumer demand JEL Codes: J21, J23, F22, R12

Model-based appraisal of minimum unit pricing for alcohol in Northern Ireland

In 2009, the Sheffield Alcohol Research Group (SARG) at Sheffield University developed the Sheffield Alcohol Policy Model version 2.0 (SAPM) to appraise the potential impact of alcohol policies, including different levels of MUP, for the population of England. In 2013, SARG were commissioned by the DHSSPS and the Department for Social Development to adapt the Sheffield Model to NI in order to appraise the potential impact of a range of alcohol pricing policies. The present report represents the results of this work. Estimates from the Northern Ireland (NI) adaptation of the Sheffield Alcohol Policy Model - version 3 - (SAPM3) suggest: 1. Minimum Unit Pricing (MUP) policies would be effective in reducing alcohol consumption, alcohol related harms (including alcohol-related deaths, hospitalisations, crimes and workplace absences) and the costs associated with those harms. 2. A ban on below-cost selling (implemented as a ban on selling alcohol for below the cost of duty plus the VAT payable on that duty) would have a negligible impact on alcohol consumption or related harms. 3. A ban on price-based promotions in the off-trade, either alone or in tandem with an MUP policy would be effective in reducing alcohol consumption, related harms and associated costs. 4. MUP and promotion ban policies would only have a small impact on moderate drinkers at all levels of income. Somewhat larger impacts would be experienced by increasing risk drinkers, with the most substantial effects being experienced by high risk drinkers. 5. MUP and promotion ban policies would have larger impacts on those in poverty, particularly high risk drinkers, than those not in poverty. However, those in poverty also experience larger relative gains in health and are estimated to marginally reduce their spending due to their reduced drinking under the majority of policies åÊ

El Cercle de l'Anell : anàlisi del consum d'un producte cultural segons el model del Circuit de la Cultura : tolkiendili i ringers. El cas de l'Smial de Lórien.

Anàlisi del fenomen cultural creat al voltant de J.R.R. Tolkien, l'autor d'El Senyor dels Anells, tot emprant el model del Circuit de la Cultura (Du Gay et als). La recerca se centra en el Consum: els fans i les fans de Tolkien i de la trilogia cinematogràfica 'The Lord of the Rings': tolkiendili i ringers.

Missing value imputation in longitudinal measures of alcohol consumption

Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003-2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, "real" observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered. Copyright (C) 2011 John Wiley & Sons, Ltd.

Predicting outcome after acute basilar artery occlusion based on admission characteristics.

OBJECTIVE: To develop a simple prognostic model to predict outcome at 1 month after acute basilar artery occlusion (BAO) with readily available predictors. METHODS: The Basilar Artery International Cooperation Study (BASICS) is a prospective, observational, international registry of consecutive patients who presented with an acute symptomatic and radiologically confirmed BAO. We considered predictors available at hospital admission in multivariable logistic regression models to predict poor outcome (modified Rankin Scale [mRS] score 4-5 or death) at 1 month. We used receiver operator characteristic curves to assess the discriminatory performance of the models. RESULTS: Of the 619 patients, 429 (69%) had a poor outcome at 1 month: 74 (12%) had a mRS score of 4, 115 (19%) had a mRS score of 5, and 240 (39%) had died. The main predictors of poor outcome were older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIH Stroke Scale (NIHSS) score, and longer time to treatment. A prognostic model that combined demographic data and stroke risk factors had an area under the receiver operating characteristic curve (AUC) of 0.64. This performance improved by including findings from the neurologic examination (AUC 0.79) and CT imaging (AUC 0.80). A risk chart showed predictions of poor outcome at 1 month varying from 25 to 96%. CONCLUSION: Poor outcome after BAO can be reliably predicted by a simple model that includes older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIHSS score, and longer time to treatment.

Experimentation and Stages of Acquisition for Tobacco Consumption in Spanish Adolescents

One area which has been largely neglected when studying the acquisition of addiction to smoking with thetranstheoretical model is whether the individual had previously experimented with smoking. The importance of includingthe experimentation variable was supported by this research

Regional consumption of antibiotics : a demand system approach

Through this paper. we have attempted to model the demand for different classes of antibiotics used for respiratory infections in outpatient care in Switzerland using a spatial version of the linear approximate Almost Ideal Demand System (AIDS) model. This model takes spatial dependency into account by means of spatial lags of antibiotic budget shares. We control for the health status of patients and the potential harmful effects of antibiotic use in terms of bacterial resistance. Elasticities to socioeconomic determinants of consumption and own- and cross-price elasticities between different groups of antibiotic have also been computed in this paper. Significant cross-price elasticities are found between newer or more expensive generations and older or less expensive generations of antibiotics. (C) 2009 Elsevier B.V. All rights reserved.

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Consumption heterogenity over the business cycle

We study consumption heterogeneity over the business cycle. Using household panel data from 1984 to 2010 in the US we find that the welfare cost of the business cycle is non-negligible, once agents heterogeneity is taken into account, and sums to about 1% of yearly consumption. This is due to the structure of comovements between the different parts of the consumption distribution, in particular the tails are highly volatile and negatively related to each other. We also find that business cycle fluctuations originating from exogenous financial shocks only hit the top end of the consumption distribution and therefore reduce consumption inequality.

A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

CO2 emissions embodied in international trade: A multiregional Inputoutput model for Spain

As a result of globalization and free trade agreements, international trade is enormously growing and inevitably putting more pressure on the environment over the last few decades. This has drawn the attention of both environmentalist and economist in response to the ever growing concerns of climate change and urgent need of international action for its mitigation. In this work we aim at analyzing the implication of international trade in terms of CO2 between Spain and its important partners using a multi-regional input-output (MRIO) model. A fully integrated 13 regions MRIO model is constructed to examine the pollution responsibility of Spain both from production and consumption perspectives. The empirical results show that Spain is a net importer of CO2 emissions which is equivalent to 29% of its emission due to production. Even though the leading partner with regard to import values are countries such as Germany, France, Italy and Great Britain, the CO2 embodied due to trade with China takes the largest share. This is mainly due to the importation of energy intensive products from China coupled with Chinese poor energy mix which is dominated by coal-power plant. The largest portion (67%) of the global imported CO2 emissions is due to intermediate demand requirements by production sectors. Products such as Motor vehicles, chemicals, a variety of machineries and equipments, textile and leather products, construction materials are the key imports that drive the emissions due to their production in the respective exporting countries. Being at its peak in 2005, the Construction sector is the most responsible activity behind both domestic and imported emissions.

Selective neurodegeneration induced in rotation-mediated aggregate cell cultures by a transient switch to stationary culture conditions: a potential model to study ischemia-related pathogenic mechanisms.

Aggregating brain cell cultures at an advanced maturational stage (20-21 days in vitro) were subjected for 1-3 h to anaerobic (hypoxic) and/or stationary (ischemic) conditions. After restoration of the normal culture conditions, cell loss was estimated by measuring the release of lactate dehydrogenase as well as the irreversible decrease of cell type-specific enzyme activities, total protein and DNA content. Ischemia for 2 h induced significant neuronal cell death. Hypoxia combined with ischemia affected both neuronal and glial cells to different degrees (GABAergic neurons>cholinergic neurons>astrocytes). Hypoxic and ischemic conditions greatly stimulated the uptake of 2-deoxy-D-glucose, indicating increased glucose consumption. Furthermore, glucose restriction (5.5 mM instead of 25 mM) dramatically increased the susceptibility of neuronal and glial cells to hypoxic and ischemic conditions. Glucose media concentrations below 2 mM caused selective neuronal cell death in otherwise normal culture conditions. GABAergic neurons showed a particularly high sensitivity to glucose restriction, hypoxia, and ischemia. The pattern of ischemia-induced changes in vitro showed many similarities to in vivo findings, suggesting that aggregating brain cell cultures provide a useful in vitro model to study pathogenic mechanisms related to brain ischemia.

Predicting global change impacts on plant species' distributions: Future challenges

Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species' range shifts, changes in phenology and species' extinctions, accurate projections of species' responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species' responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species' distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the "trailing edge" of shifting populations, species' interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes A occurring on the leading and trailing edge of the species' distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species' migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species' distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. (c) 2007 Rubel Foundation, ETH Zurich. Published by Elsevier GrnbH. All rights reserved.

Propagation velocity kinetics and repolarization alternans in a free-behaving sheep model of pacing-induced atrial fibrillation.

AIMS: Experimental models have reported conflicting results regarding the role of dispersion of repolarization in promoting atrial fibrillation (AF). Repolarization alternans, a beat-to-beat alternation in action potential duration, enhances dispersion of repolarization when propagation velocity is involved. METHODS AND RESULTS: In this work, original electrophysiological parameters were analysed to study AF susceptibility in a chronic sheep model of pacing-induced AF. Two pacemakers were implanted, each with a single right atrial lead. Right atrial depolarization and repolarization waves were documented at 2-week intervals. A significant and gradual decrease in the propagation velocity at all pacing rates and in the right atrial effective refractory period (ERP) was observed during the weeks of burst pacing before sustained AF developed when compared with baseline conditions. Right atrial repolarization alternans was observed, but because of the development of 2/1 atrioventricular block with far-field ventricular interference, its threshold could not be precisely measured. Non-sustained AF was not observed at baseline, but appeared during the electrical remodelling in association with a decrease in both ERP and propagation velocity. CONCLUSION: We report here on the feasibility of measuring ERP, atrial repolarization alternans, and propagation velocity kinetics and their potential in predicting susceptibility to AF in a free-behaving model of pacing-induced AF using the standard pacemaker technology.