Global Risk Index Research Articles

Predictability of GCC stock returns: The role of geopolitical risk and crude oil returns

Stock return predictability has always been one of the central themes of finance literature, given its crucial implications for investment decisions, risk management, and financial and monetary policymaking. This paper evaluates the in-sample and out-of-sample stock return predictive power of the global and Saudi geopolitical risk indices and crude oil returns in the context of six Gulf Cooperation Council (GCC) countries. Monthly data from February 2007 to December 2019 and the feasible generalized least square (FGLS) estimator for predictive modelling by Westerlund and Narayan (2012, 2015) are used. Global and Saudi GPR indices show weak evidence of in-sample predictability of excess stock returns. However, the out-of-sample forecasts show that only the global geopolitical risk index provides superior prediction in the context of Kuwaiti and Omani stock markets, compared to the historical average benchmark model. Crude oil prices are shown to be a better predictor in most cases, in both in-sample and out-of-sample forecast models The results imply that crude oil returns can be used for active prediction of GCC stock market returns, once econometric issues are accounted for. The findings remain mostly unaffected when excess risk adjusted returns are used.

Identification of the Chemical Forms of Heavy Metals in Municipal Sewage Sludge as a Critical Element of Ecological Risk Assessment in Terms of Its Agricultural or Natural Use.

The present study aimed to demonstrate that identification of the chemical forms of heavy metals in sewage sludge produced in municipal Wastewater Treatment Plants (WWTPs) is a critical element of ecological risk assessment, especially in terms of its agricultural or natural use. The concentrations of seven heavy metals (Cd, Cr, Cu, Ni, Pb, Zn and Hg) were determined using inductively coupled plasma optical spectrometry (ICP-OES) and cold vapor atomic absorption spectrometry (CV-AAS). The chemical forms of heavy metals were analyzed in accordance with the sequential extraction method proposed by the Community Bureau of Reference (BCR). Sludge samples were collected at the five municipal WWTPs located in the largest industrial area in the country, i.e., the Upper Silesian Industrial Region (southern Poland, central Europe). The ecological risk was assessed by calculating the Potential Ecological Risk Factor (ER), Risk Index (RI), Risk Assessment Code (RAC), Individual Contamination Factor (ICF), Global Risk Index (GRI) as well as the author’s indices, i.e., Individual Ecological Risk (IER) and Global Ecological Risk (GER). To demonstrate the differences between the level of ecological risk posed by the different heavy metals, sludge samples were collected at two specific points of the processing line. Considering the chemical forms of heavy metals, the highest ecological risk was posed by Zn, Cd and Ni, while in the case of their total concentrations, by Cd and Hg. The obtained results confirm that quantitative determination of the total content of heavy metals in sewage sludge is not a sufficient criterion in assessment of the ecological risk that these elements pose to the natural environment and living organisms. Moreover, multivariate statistical analysis revealed a significant correlation between the concentrations of heavy metals, which indicates that they plausibly originate from the same source of pollution.

Geospatial Assessment of Water-Migration Scenarios in the Context of Sustainable Development Goals (SDGs) 6, 11, and 16

Communities and countries around the world are gearing up efforts to implement the 2030 Agenda goals and targets. In this paper, the water and migration scenarios are explained with a focus on Sustainable Development Goals (SDGs) 6 (water-related), 11 (urbanization), and 16 (peace and political stability). The study has two phases. The first phase illustrates the application of geospatial data and tools to assess the water-migration interlinkages (nexus) by employing a case study approach. Three case studies, Lake Chad, the Aral Sea region, and the Nile Delta, representing various geographic and socio-political settings, were selected to perform the multitemporal analysis. For this analysis, a mixed toolset framework that combined algorithmic functions of digital image processing, the Landsat sensor data, and applied a geographic information system (GIS) platform was adopted. How water-related events directly or indirectly trigger human migration is described using spatial indicators such as water spread and the extent of urban sprawl. Additionally, the geospatial outputs were analyzed in tandem with the climate variables such as temperature, precipitation data, and socio-economic variables such as population trends and migration patterns. Overall, the three case studies examined how water and climate crisis scenarios influence migration at a local and regional scale. The second phase showcases global-scale analysis based on the Global Conflict Risk Index (GCRI). This indicator reflects on the risks and conflicts with environmental, social, and political aspects and comments on the connection of these dimensions with migration. Together, the two phases of this paper provide an understanding ofthe interplay of water-related events on migration by applying the geospatial assessment and a proxy global index. Additionally, the paper reiterates that such an understanding can serve to establish facts and create evidence to inform sustainable development planning and decision making, particularly with regard to SDGs 6, 11, and 16. Targets such as 6.4 (managing water stress), 6.5 (transboundary challenges) and, 11.B (adaptation and resilience planning) can benefit from the knowledge generated by this geospatial exercise. For example, the high GCRI values for the African region speak to SDG targets 11.B (integrated policies/plans) and 16.7 (decision support systems for peaceful societies). Two key highlights from the synthesis: (a) migration and urbanization are closely interconnected, and (b) the impact of water and climate crisis is comparatively high for rural-urban migration due to the considerable dependence of rural communities on nature-based livelihoods. In conclusion, geospatial analysis is an important tool to study the interlinkages between water and migration. The paper presents a novel perspective toward widening the scope of remote sensing data and GIS toward the implementation of the SDG Agenda.

10 Migrants caught in crises: Contexts, responses and innovation

10 Migrants caught in crises: Contexts, responses and innovation

The Global Conflict Risk Index: A quantitative tool for policy support on conflict prevention

In an effort to bridge the gap between academic and governmental initiatives on quantitative conflict modelling, this article presents, validates and discusses the Global Conflict Risk Index (GCRI), the quantitative starting point of the European Union Conflict Early Warning System. Based on open-source data of five risk areas representing the structural conditions characterising a given country (political, economic, social, environmental and security areas), it evaluates the risk of violent conflict in the next one to four years. Using logistic regression, the GCRI calculates the probability of national and subnational conflict risk. Several model design decisions, including definition of the dependent variable, predictor variable selection, data imputation, and probability threshold definition, are tested and discussed in light of the model's direct application in the EU policy support on conflict prevention. While the GCRI remains firmly rooted by its conception and development in the European conflict prevention policy agenda, it is validated as a scientifically robust and rigorous method for a baseline quantitative evaluation of armed conflict risk. Despite its standard, simple methodology, the model predicts better than six other published quantitative conflict early warning systems for ten out of twelve reported performance metrics. Thereby, this article aims to contribute to a cross-fertilisation of academic and governmental efforts in quantitative conflict risk modelling.

Vietnam Climate Change and Health Vulnerability and Adaptation Assessment, 2018

Background:The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030.Methods:The assessment followed the first 4 steps outlined in the World Health Organization’s Guidelines in conducting “Vulnerability and Adaptation Assessments.” A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events, (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5.Results:The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017, the level of “exposure” to climate change–related hazards of the health sector was “high” to “very high,” with an average score from 3.5 to 4.4 (out of 5.0). For “health sensitivity,” the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as “high.” For “adaptive capacity,” the scores were from 4.0 to 4.1, which meant adaptive capacity was “very low.” The overall V&A rating in 2013 was “very high risk” (score 4.1) and “high risk” with scores of 3.8 in 2014 and 3.7 in 2015 to 2017.Conclusions:Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.

Análisis postural del trabajador forestal en aserraderos de El Salto, Durango, México

El trabajo en la industria del aserrío es físicamente exigente porque se realiza bajo posturas corporales poco saludables que generan lesiones musculoesqueléticas y su estudio requiere de herramientas de evaluación de riesgos para identificarlas adecuadamente. En los aserraderos de El Salto, Durango, México se desconoce el nivel de riesgo de las posturas de trabajo en las personas, por lo que el objetivo de este estudio fue realizar un análisis postural en 15 puestos de trabajo. A partir de 7.5 h de video, que consideraron el trabajo efectivo en los puestos laborales, se obtuvieron 900 imágenes fijas a intervalos de 30 segundos para analizarlas mediante el método OWAS. Se estimó el índice global de riesgo postural y se elaboraron tablas de contingencia y pruebas de asociación entre variables categóricas de Chi-cuadrado. Los resultados mostraron una frecuencia de posturas de 48% con nivel de riesgo 2, 3 y 4, indicando realizar acciones de corrección postural para los riesgos 2 y 3 así como modificaciones inmediatas para el 4. El índice global de riesgo se estableció en 166 puntos catalogado como mínimo. Por puesto de trabajo, los topadores y volteadores son los más susceptibles de presentar lesiones musculoesqueléticas con índices globales de riesgo por encima de los 200 puntos. Por zona corporal, 43% de las posiciones de la espalda y 40% de las piernas se encuentran en un nivel de riesgo 2, considerado como poco dañino, y 100% de las posiciones de los brazos resultaron con un nivel de riesgo 1 que no requiere modificación alguna.

Data Mining for Integration and Verification of Socio-Geographical Trend Statements in the Context of Conflict Risk

Data mining enables an innovative, largely automatic meta-analysis of the relationship between political and economic geography analyses of crisis regions. As an example, the two approaches Global Conflict Risk Index (GCRI) and Fragile States Index (FSI) can be related to each other. The GCRI is a quantitative conflict risk assessment based on open source data and a statistical regression method developed by the Joint Research Centre of the European Commission. The FSI is based on a conflict assessment framework developed by The Fund for Peace in Washington, DC. In contrast to the quantitative GCRI, the FSI is essentially focused on qualitative data from systematic interviews with experts. Both approaches therefore have closely related objectives, but very different methodologies and data sources. It is therefore hoped that the two complementary approaches can be combined to form an even more meaningful meta-analysis, or that contradictions can be discovered, or that a validation of the approaches can be obtained if there are similarities. We propose an approach to automatic meta-analysis that makes use of machine learning (data mining). Such a procedure represents a novel approach in the meta-analysis of conflict risk analyses.

Data Mining for Integration and Verification of Socio-Geographical Trend Statements in the Context of Conflict Risk

Data mining enables an innovative, largely automatic meta-analysis of the relationship between political and economic geography analyses of crisis regions. As an example, the two approaches Global Conflict Risk Index (GCRI) and Fragile States Index (FSI) can be related to each other. The GCRI is a quantitative conflict risk assessment based on open source data and a statistical regression method developed by the Joint Research Centre of the European Commission. The FSI is based on a conflict assessment framework developed by The Fund for Peace in Washington, DC. In contrast to the quantitative GCRI, the FSI is essentially focused on qualitative data from systematic interviews with experts. Both approaches therefore have closely related objectives, but very different methodologies and data sources. It is therefore hoped that the two complementary approaches can be combined to form an even more meaningful meta-analysis, or that contradictions can be discovered, or that a validation of the approaches can be obtained if there are similarities. We propose an approach to automatic meta-analysis that makes use of machine learning (data mining). Such a procedure represents a novel approach in the meta-analysis of conflict risk analyses.

Environmental and administrative EVIAVE-based approach for landfill siting

Landfill site selection is a relevant and necessary issue for waste management. However, it is an extremely complex task since it must take into account different environmental, economic and socio-political criteria that need to comply with strict regulations and meet different opinions. Accordingly, in this paper we propose a multi-criteria EVIAVE-(Evaluación del impacto ambiental en vertederos) based approach to evaluate the suitability of a set of possible landfill locations and rationally provide an optimal location for a landfill. The approach requires a comprehensive analysis to identify the best feasible site(s) that minimize a Global Landfill Risk Index (GRI), focused on environmental, economic and administrative impacts, and simultaneously comply with governmental regulations and constraints. This GRI is based on the Environmental Landfill Index, Administrative Landfill Index, Environmental Risk Index, Environmental Value, Probability of Contamination and Contamination Risk Index. An innovative feature of this approach lies in incorporating a mathematical model that combines weighted environmental and administrative issues. The model not only provides an optimal landfill location but also establishes landfill location ranks according to indexes of interest. This methodology reveals flexibility and high adaptability, being a useful and effective tool in the decision-making process. The methodology presented was tested with data available from a preliminary study developed in the municipalities of Oporto Metropolitan Area, Portugal, for the implementation of a multi-municipal landfill, which considers nine different locations for analysis.

Growth in stress

We propose a new global risk index, Growth-in-Stress (GiS), that measures the expected fall in a country’s GDP as the global factors, which drive world growth, are subject to stressful conditions. Using the GDP growth rates of 87 countries, we find that, since the 2008 financial crisis, though mainly from 2011 on, the world overall has fallen in a state of complacency, with the cross-sectional average GiS falling quite dramatically; in 2015, the average worst outcome seems to be no growth at the 95% probability factor stress. However, the cross-sectional dispersion within groups is quite variable: it is the smallest among industrialized countries and the largest among emerging and developing countries. We also measure the factor stress on different quantiles of the GDP growth distribution of each country. We calculate an Armageddon-type event as we seek to find the GiS on the 5% quantile of growth under the extreme 95% probability events of the factors, and find that it can be as large as an annual 20% fall in GDP.

Comparing index-based vulnerability assessments in the Mississippi Delta: Implications of contrasting theories, indicators, and aggregation methodologies

There are many index-based approaches for assessing vulnerability to socio-natural hazards with differences in underlying theory, indicator selection and aggregation methodology. Spatially explicit output scores depend on these characteristics and contrasting approaches can therefore lead to very different policy implications. These discrepancies call for more critical reflection on index design and utility, a discussion that has not kept pace with the impetus for vulnerability assessments and respective index creation and application following the Hyogo Framework for Action 2005–2015. Comparing index outputs is an effective approach in this regard. Here, the Social Vulnerability Index (SoVI®) and the vulnerability component of the Global Delta Risk Index (GDRI) are applied at census tract level in the Mississippi Delta and visually and quantitatively compared. While the SoVI® is grounded in the hazard/risk research paradigm with primarily socio-economic indicators and an inductive principal component methodology, the GDRI incorporates advancements from sustainability science with ecosystem-based indicators and a modular hierarchical design. Maps, class rank changes, and correlations are used to assess the convergence and divergence of these indexes across the delta. Results show that while very different theoretical frameworks influence scores through indicator selection, methodology of index calculation has an even greater effect on output. Within aggregative methodology, the treatment of inter-indicator correlation is decisive. Implications include the need for an increased focus on index methodology and validation of results, transparency, and critical reflection regarding assessment limitations, as our results imply that contradictory risk reduction policies could be considered depending on the assessment methodology used.

Global Environmental Politics and Developing Nations' Climatic Vulnerability Nexus: A Systematic Review and Meta-Analysis

Climate change is arguably one of the most formidable environmental problems the world is facing nowadays and global environmental politics apprehends the complications further given its interdisciplinary nature and the scientific difficulties involved in climate change. Bangladesh has been recognized as one of the most vulnerable countries to climate change as per the Global Climate Risk Index (GCRI) 2018 at global stage emitting only 0.36 percent Greenhouse gas (carbon dioxide, methane, nitrous oxide, per-fluorocarbon, hydro-fluorocarbon, and sulfur hexafluoride) of total global GHG emission, which is lower than most of the countries. A paradox is felt across the globe is that the five major GHG emitting countries emit more than 60 percent of total global GHG emission but are not facing immediate climate risks. While on the contrary, countries like Bangladesh, Maldives, Lesotho or Tuvalu have little to do with GHG emissions but are most exposed to the long-term adverse impact of climate change. More to add, the most exposed countries to climate change are mostly developing or least developed and cannot fund their plans to fight out the climate change. In this global context, the countries at apex climatic risk despite demanding adequate financial support are not getting though. Being devoid of proper assistance from global community, they are getting more exposed to the climatic consequences and rushing to a possible extinction from the world map. This is being realized the most after a major GHG emitting country left Paris Agreement in 2017, believed to be influenced by international environmental politics, to pursue some short-term benefits leaving the long-term goals, and also has vowed to restructure the carbon regulations imposed by the previous administration. With the withdrawal of such a strong economic power from the agreement that pledged 3 billion dollars to the UN Green Climate Fund, at least two-thirds of the pledged amount is at Proceeding, International Conference on Climate Change (ICCC-2019), Dhaka, Bangladesh, 01-03 March, 2019 risk. Also, with the proposed restructuring of the carbon regulations, the global target to reduce carbon emission is expected to receive a major blow. This paper will explore the nexus between nature of global environmental politics and its implications on climate-vulnerable nation's as well as act as a future guideline toward the practitioners and nationwide policymakers in mainstreaming the inclusive resilience issues for the safeguard of the climatic hazard prone third world countries.

Hydrological Risk Analysis of Dams: The Influence of Initial Reservoir Level Conditions

In this paper, we present a method to assess the influence of the initial reservoir level in hydrological dam safety and risk analysis. Traditionally, in professional practice, the procedures applied are basically deterministic. Several physical processes are defined deterministically, according to the criteria of the designer (usually in the conservative side), although there is a high degree of uncertainty regarding these processes. A relevant variable is the reservoir level considered at the beginning of flood events. Hydrological dam safety assessment methods traditionally assume that the reservoir is initially full when it receives the design flood, thus, staying in the conservative side when designing a new dam. However, the distribution of reservoir levels at the beginning of flood episodes takes more importance for evaluating the real risk for the dams in operation. We analyzed three different scenarios—initial reservoir level equal to maximum normal level, equal to a maximum conservation level, and following the probability distribution from the historical records. To do so, we presented a method applied to a gated-spillway dam located in the Tagus river basin. A set of 100,000 inflow hydrographs was generated through a Monte Carlo procedure, by reproducing the statistics of the main observed hydrograph characteristics—peak flow, volume, and duration. The set of 100,000 hydrographs was routed through the reservoir applying the Volumetric Evaluation Method as a flood control strategy. In order to compare the three scenarios, we applied an economic global risk index. The index combines the hydrological risk for the dam, linked to the maximum water level reached in the reservoir, during the flood routing, and the flood risk in the downstream river reach, linked to the discharge releases from the dam. The results showed the importance of accounting for the fluctuation of initial reservoir levels, for assessing the risk related to hydrological dam safety. Furthermore, a procedure to quantify the uncertainty associated with the effects of initial reservoir level on hydrological dam safety, has been proposed.

The Correlation Between Life Expectancy and Disaster Risk

A healthy community is a community resilient to disaster. The Sendai Framework for Disaster Risk Reduction considers disaster impacts on health and encourages the implementation of disaster medicine and access to mental health services. Life expectancy (LE) is a basic statistic that indicates public health achievements and social development, including the health system, infrastructure, and accurate vital statistics. Thus, we hypothesized that LE corelates with disaster risk and strategies to achieve long LE can help achieving disaster risk reduction. We compared the disaster risk obtained from Index for Risk Management (INFORM) with the LE of both genders at birth to identify which component of INFORM risk correlates with LE. A correlation analysis revealed that overall INFORM risk negatively correlated with LE. The natural hazard category did not correlate with LE, but the human hazard category, vulnerability, and lack of coping capacity negatively correlated with LE. In the vulnerability dimension, indicators of socioeconomic vulnerability, health conditions, and children U5 negatively correlated with LE. In the lack of coping capacity dimension, indicators of communication, physical infrastructure, and access to health care negatively correlated with LE. Japan has achieved the longest LE and a low INFORM risk because of its lower vulnerability and reduced lack of coping capacity, including healthrelated indicators. In a cluster analysis of LE and INFORM categories of risk, we divided countries into four clusters and found categories that could be improved. Compared with another global disaster risk index, the Word Risk Index (WRI), the INFORM risk index seems to represent the overall disaster risk better, though they have different aspects of risk evaluation. The WRI is also negatively correlated with LE, supporting our hypothesis. In conclusion, LE is an important indicator of disaster risk and strategies to achieve long LE can be effective and important strategies in disaster risk reduction.

Valoración funcional básica del judoka: un estudio piloto

El objetivo del presente estudio fue describir el Perfil Funcional Básico (VAFB) de un grupo de 13 judokas competidores a nivel nacional. Se utilizó la batería Valoración Funcional Básica propuesta por Gil-López (2018). Los datos obtenidos indican un Índice Global de Riesgo de Lesión (IGRL) de 45,74±2,01%. Las compensaciones que más se han dado entre todos los judokas fueron rotación externa del pie derecho/izquierdo, pronación pie derecho/izquierdo, pérdida de disociación lumbo-pélvica, movimiento del tórax, escápulas aladas y protacción cervical. En cuanto, a los años de práctica se muestran diferencias en el test de la articulación del hombro (SM), donde aparece mayor número de compensaciones en los sujetos que llevan menos de diez años practicando judo. El grupo de judokas analizado no muestra un alto riesgo de lesión, pero se recomienda incluir un trabajo correctivo para la mejora de los déficits registrados.

The impact of climate risk on firm performance and financing choices: An international comparison

Increasingly adverse climatic conditions have created greater systematic risk for companies throughout the global economy. Few studies have directly examined the consequences of climate-related risk on financing choices by publicly listed firms across the globe. We attempt to do so using the Global Climate Risk Index compiled and published by Germanwatch (Kreft & Eckstein, 2014), which captures at the country level the extent of losses from extreme weather events. As expected, we find the likelihood of loss from major storms, flooding, heat waves, etc. to be associated with lower and more volatile earnings and cash flows. Consistent with policies that attempt to moderate such effects, we show that firms located in countries characterized by more severe weather are likelier to hold more cash so as to build financial slack and thereby organizational resilience to climatic threats. Those firms also tend to have less short-term debt but more long-term debt, and to be less likely to distribute cash dividends. In addition, we find that certain industries are less vulnerable to extreme weather and so face less climate-related risk. Our results are robust to using an instrumental variable approach, a propensity-score-matched sample, and path analysis, and remain unchanged when we consider an alternative measure of climate risk. Finally, our conclusions are invariant to the timing of financial crises that can affect different countries at different times.

A global risk approach to assessing groundwater vulnerability

This research provides a new approach to assess groundwater vulnerability to contamination from anthropogenic activities and sea water intrusion. The DRASTIC and GALDIT parametric methods were then linked to a novel land use index to create a more robust “global risk index”, useful for assessing aquifer vulnerability to pollution and seawater intrusion risk.In addition, sensitivity analysis was used to evaluate the effect of each individual parameter on the final models.The vulnerability to pollution and the seawater intrusion contamination maps show three classes of water resources degradation: low, moderate and high, relating to the intrinsic properties. In addition, the global risk map shows three risk classes': low (25%), moderate (64%) and high (11%) depending on the hydrogeological characteristics, land use, distance from the coast and human impacts in most of the study area. The modified models were statistically compared with the nitrate concentration and the water resistivity values for validation.These maps are considered indispensable for sustainable land use planning and groundwater management of the shallow aquifer.

Validity of nutrition risk index as a malnutrition screening tool compared with subjective global assessment in end-stage renal disease patients on peritoneal dialysis.

We undertook this study to compare subjective global assessment (SGA) and nutrition risk index (NRI) as malnutrition screening tools in peritoneal dialysis (PD) patients. Nutrition status of the patients was categorized into low, moderate and high risk of malnutrition based on both NRI and SGA. The sensitivity, specificity and predictive values of NRI were compared with SGA, an already validated tool of nutrition status assessment in PD patients. Two hundred and eighty-three end-stage renal disease patients (age 50.02 ± 13.76 years; 204 males, 150 diabetic) were included. Based on SGA, 71/283 (25.08%) had normal nutrition, 192/283 (67.84%) mild–moderate and 20/283 (7.07%) severe malnutrition. Based on NRI, 38/283 (13.43%) patients had normal nutritional status, 193/283 (68.20%) mild-moderate and 52/283 (18.37%) severe malnutrition. Twenty-three of 283 (8.1%) were correctly classified as normal by NRI (true negative) and 197/283 (69.6%) as malnourished (true positive), 15/283 (5.3%) as false negative, 48/283 (16.96%) were misclassified as malnourished (false positive). NRI has sensitivity of 92.9% and specificity of 32.39%. Positive predictive value and Negative predictive values (NPVs) of NRI are 80.41% and 60.53%, respectively. Accuracy of the test is 78%. The receiver operating characteristic curve of NRI is 0.63. To conclude, NRI carries high sensitivity but low specificity as compared to SGA. It can be used as screening tool but not as a diagnostic tool for assessment of nutritional status in PD patients because of its low specificity and NPV.

Institutional structures underpinning flood management in Vietnam

The Germanwatch global climate risk index ([10]) ranked Vietnam the 6th country most affected by extreme weather events between 1992 and 2011. Similarly, the [35] estimated that 59 percent of Vietnam's total land area and 71 percent of its population were living with the risk of being exposed to extreme storm events and flooding. Like other countries that are prone to natural disasters, the government of Vietnam has developed extensive legislation to improving resilience to and minimise the risks posed by natural disasters.In this study, the existing legal systems regarding flood management are reviewed and opportunities to strengthen them are identified. The legislation was reviewed in consultation with flood management specialists and government officials at the central, provincial and district levels. Local community members were also interviewed to gain insights as to how they are affected by floods and impacted by flood mitigation measures.Whilst there are a large number of legal documents pertaining to natural disaster management, they are fragmented, overlapping and repetitive. In addition, lack of training and insufficient technical and financial support at local levels exacerbates the problems. Recommendations are made to strengthen institutional support to economic sectors and individuals who are victims of extreme flood events. These include: a shift from the current ‘top-down’ approach to include a ‘bottom-up’ approach; encouragement of transparency and accountability; decentralisation of the allocation of both technical and financial resources to improve training, particularly at the local levels and; to investigate the merits of introducing insurance schemes.