Economic vulnerability, multidimensional deprivation and social cohesion in an enlarged European community

In this article we have sought to combine regional and social exclusion perspectives on economic exclusion in the enlarged European Community. Our analysis, based on the European Quality of Life Survey, confirms that while the economically vulnerable, identified through latent class analysis, constitute substantially larger groups in the poorer economic clusters, they are much more sharply differentiated from others in the richer clusters. While the economically vulnerable are also disadvantaged in relation to measures of multidimensional deprivation and social cohesion, between economic clusters differences on these dimensions cannot be accounted for by corresponding variations in levels and intensity of economic vulnerability. In fact, the impact of such vulnerability on social cohesion is greater in the more affluent clusters. Copyright © 2005 SAGE Publications.

The impact of body mass index on maternal and neonatal outcomes: a retrospective study in a UK obstetric population, 2004-2011

Objective: To assess the prevalence of overweight and obesity, and the impact of body mass index (BMI) on maternal and neonatal outcomes, in a UK obstetric population.
Design: Retrospective study.
Setting: A tertiary referral unit in Northern Ireland.
Population: A total of 30 298 singleton pregnancies over an 8-year period, 2004–2011.
Methods: Women were categorised according to World Health Organization classification: underweight (BMI < 18.50 kg/m2); normal weight (BMI 18.50–24.99 kg/m2; reference group); overweight (BMI 25.00–29.99 kg/m2); obese class I (BMI 30.00–34.99 kg/m2); obese class II (BMI 35–39.99 kg/m2); and obese class III (BMI = 40 kg/m2). Maternal and neonatal outcomes were examined using logistic regression, adjusted for confounding variables.
Main outcome measures: Maternal and neonatal outcomes.
Results: Compared with women of normal weight, women who were overweight or obese class I were at significantly increased risk of hypertensive disorders of pregnancy (OR 1.9, 99% CI 1.7–2.3; OR 3.5, 99% CI 2.9–4.2); gestational diabetes mellitus (OR 1.7, 99% CI 1.3–2.3; OR 3.7, 99% CI 2.8–5.0); induction of labour (OR 1.2, 99% CI 1.1–1.3; OR 1.3, 99% CI 1.2–1.5); caesarean section (OR 1.4, 99% CI 1.3–1.5; OR 1.8, 99% CI 1.6–2.0); postpartum haemorrhage (OR 1.4, 99% CI 1.3–1.5; OR 1.8, 1.6–2.0); and macrosomia (OR 1.5, 99% CI 1.3–1.6; OR 1.9, 99% CI 1.6–2.2), with the risks increasing for obese classes II and III. Women in obese class III were at increased risk of preterm delivery (OR 1.6, 99% CI 1.1–2.5), stillbirth (OR 3.0, 99% CI 1.0–9.3), postnatal stay > 5 days (OR 2.1, 99% CI 1.5–3.1), and infant requiring admission to a neonatal unit (OR 1.6, 99% CI 1.0–2.6).
Conclusions: By categorising women into overweight and obesity subclassifications (classes I –III), this study clearly demonstrates an increasing risk of adverse outcomes across BMI categories, with women who are overweight also at significant risk.
Keywords Body mass index, maternal and neonatal outcomes,obesity, pregnancy

Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

THE CUE-RESPONSIVITY PHENOMENON IN DEPENDENT DRINKERS - PERSONALITY VULNERABILITY AND ANXIETY AS INTERVENING VARIABLES

The cue-responsivity phenomenon to alcohol-associated stimuli in dependent drinkers was examined. In accordance with previous research, significant differences on both physiological and subjective cue-responsivity variables, between dependent and non-dependent drinkers were found. The unique contribution of this paper is two-fold. Firstly, evidence is presented which suggests that the Eysenckian personality traits of introversion and neuroticism are more predictive of cue-responsivity variance in the dependent drinkers than either severity of dependence or number of years' drinking. Secondly, within this dependent group, the relationship between cue-responsivity and 'craving' was seen to be less straightforward than traditionally thought. Specifically, it suggested that it was the extent to which autonomic cue-responsivity elicited increases in self-reported anxiety, which predicted most of the variance on the 'craving' variable. Taken together, these results raise the interesting possibility that a personality disposition akin to trait anxiety, and the degree to which cue exposure elicits state anxiety, mediated the relationship between cue-responsivity and 'craving' in dependent drinkers.

Economic globalization, inequality and body mass index:a cross-national analysis of 127 countries

This article investigates to what extent the worldwide increase in body mass index (BMI) has been affected by economic globalization and inequality. We used time-series and longitudinal cross-national analysis of 127 countries from 1980 to 2008. Data on mean adult BMI were obtained from the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. Globalization was measured using the Swiss Economic Institute (KOF) index of economic globalization. Economic inequality between countries was measured with the mean difference in gross domestic product per capita purchasing power parity in international dollars. Economic inequality within countries was measured using the Gini index from the Standardized World Income Inequality Database. Other covariates including poverty, population size, urban population, openness to trade and foreign direct investment were taken from the World Development Indicators (WDI) database. Time-series regression analyses showed that the global increase in BMI is positively associated with both the index of economic globalization and inequality between countries, after adjustment for covariates. Longitudinal panel data analyses showed that the association between economic globalization and BMI is robust after controlling for all covariates and using different estimators. The association between economic inequality within countries and BMI, however, was significant only among high-income nations. More research is needed to study the pathways between economic globalization and BMI. These findings, however, contribute to explaining how contemporary globalization can be reformed to promote better health and control the global obesity epidemic. © 2013 Copyright Taylor and Francis Group, LLC.

Nonparametric Estimation of Data Dimensionality Prior to Data Compression: the case of the Human Development Index

In many applications in applied statistics researchers reduce the complexity of a data set by combining a group of variables into a single measure using factor analysis or an index number. We argue that such compression loses information if the data actually has high dimensionality. We advocate the use of a non-parametric estimator, commonly used in physics (the Takens estimator), to estimate the correlation dimension of the data prior to compression. The advantage of this approach over traditional linear data compression approaches is that the data does not have to be linearized. Applying our ideas to the United Nations Human Development Index we find that the four variables that are used in its construction have dimension three and the index loses information.

Effect of cataract extraction on the Glaucoma Progression Index (GPI) in glaucoma patients

PURPOSE: To determine the effect of cataract extraction on the glaucoma progression index (GPI) in glaucoma patients with coexisting cataract.

PATIENTS AND METHODS: This is a retrospective noncomparative study. Consecutive eligible patients with glaucoma who underwent phacoemulsification alone or in combination with augmented trabeculectomy were included. All patients had Swedish Interactive Threshold Algorithm-standard 24-2 visual fields within 10 months of surgery. Exclusion criteria included other ocular morbidity, intraoperative complications, and perimetric reliability indices greater than 33%. Comparison was made between the immediate visual fields before and after surgery. The main outcome measure was the change in GPI. Changes in the pattern standard deviation (PSD) and mean deviation (MD) were also assessed. Comparison of means was performed with the paired t test.

RESULTS: Thirty-three eyes of 33 patients (all Whites) were analyzed. The mean age at surgery was 77.0+/-8.7 years. Visual field tests were performed 3.3+/-3.0 months SD before surgery and 5.4+/-2.6 months after surgery. There was a statistically significant increase in the GPI after cataract surgery (from 71.5+/-18.5% to 74.6+/-17.1%; P=0.02). The improvement in MD was also statistically significant (from -11.8+/-5.3 to -10.2+/-5.3 dB; P <0.01), but the change in PSD did not reach statistical significance.

CONCLUSIONS: Uncomplicated cataract extraction resulted in a statistically significant improvement in the 24-2 Swedish Interactive Threshold Algorithm-standard GPI and MD, but not in PSD. Both the MD and the GPI may be influenced by lens opacities, which could make detection of glaucoma visual field progression more difficult for clinicians in glaucoma patients with concurrent cataract.

Perimetric progression in open angle glaucoma and the Visual Field Index (VFI)

PURPOSE: To evaluate the changes in the Visual Field Index (VFI) in eyes with perimetric glaucomatous progression, and to compare these against stable glaucoma patients.

PATIENTS AND METHODS: Consecutive patients with open angle glaucoma with a minimum of 6 reliable visual fields and 2 years of follow-up were identified. Perimetric progression was assessed by 4 masked glaucoma experts from different units, and classified into 3 categories: "definite progression," "suspected progression," or "no progression." This was compared with the Glaucoma Progression Analysis (GPA) II and VFI linear regression analysis, where progression was defined as a negative slope with significance of <5%.

RESULTS: Three hundred ninety-seven visual fields from 51 eyes of 39 patients were assessed. The mean number of visual fields was 7.8 (SD 1.1) per eye, and the mean follow-up duration was 63.7 (SD 13.4) months. The mean VFI linear regression slope showed an overall statistically significant difference (P<0.001, analysis of variance) for each category of progression. Using expert consensus opinion as the reference standard, both VFI analysis and GPA II had high specificity (0.93 and 0.90, respectively), but relatively low sensitivity (0.45 and 0.41, respectively).

CONCLUSIONS: The mean VFI regression slope in our cohort of eyes without perimetric progression showed a statistically significant difference compared with those with suspected and definite progression. VFI analysis and GPA II both had similarly high specificity but low sensitivity when compared with expert consensus opinion.