Validation of the automated neuropsychological assessment metrics for assessing cognitive impairment in systemic lupus erythematosus

Objective We previously demonstrated the utility of the Automated Neuropsychological Assessment Metrics (ANAM) for screening cognitive impairment (CI) in patients with systemic lupus erythematosus (SLE) and developed composite indices for interpreting ANAM results. Our objectives here were to provide further support for the ANAM’s concurrent criterion validity against the American College of Rheumatology neuropsychological battery (ACR-NB), identify the most discriminatory subtests and scores of the ANAM for predicting CI, and provide a new approach to interpret ANAM results using Classification and Regression Tree (CART) analysis. Methods 300 adult SLE patients completed an adapted ACR-NB and ANAM on the same day. As per objectives, six models were built using combinations of ANAM subtests and scores and submitted to CART analysis. Area under the curve (AUC) was calculated to evaluate the ANAM’s criterion validity compared to the adapted ACR-NB; the most discriminatory ANAM subtests and scores in each model were selected, and performance of models with the highest AUCs were compared to our previous composite indices; decision trees were generated for models with the highest AUCs. Results Two models had excellent AUCs of 86 and 89%. Eight most discriminatory ANAM subtests and scores were identified. Both models demonstrated higher AUCs against our previous composite indices. An adapted decision tree was created to simplify the interpretation of ANAM results. Conclusion We provide further validity evidence for the ANAM as a valid CI screening tool in SLE. The decision tree improves interpretation of ANAM results, enhancing clinical utility.

National Forest Inventory Data to Evaluate Climate-Smart Forestry

National Forest Inventory (NFI) data are the main source of information on forest resources at country and subcountry levels. This chapter explores the strengths and limitations of NFI-derived indicators to assess forest development with respect to adaptation to and mitigation of climate change, that is, the criteria of Climate-Smart Forestry (CSF). We reflect on harmonizing NFI-based indicators across Europe, use literature to scrutinize available indicators to evaluate CSF, and apply them in 1) Switzerland, where CSF is evaluated for NFI records and simulation model projections with four management scenarios; 2) 43 selected European countries, for which the indicators for Sustainable Forest Management (SFM) are used. The indicators were aggregated to composite indices for adaptation and mitigation and to an overall CSF rating. The Swiss NFI records showed increased CSF ratings in mountainous regions, where growing stocks increased. Simulations under business-as-usual management led to a positive CSF rating, whereas scenarios of increased harvesting decreased either only adaptation or both mitigation and adaptation. European-level results showed increases in CSF ratings for most countries. Negative adaptation ratings were mostly due to forest damages. We discuss the limitations of the indicator approach, consider the broader context of international greenhouse gas reporting, and conclude with policy recommendations.

Urban-rural differences in the associated factors of severe under-5 child undernutrition based on the composite index of severe anthropometric failure (CISAF) in Bangladesh

Introduction Severe undernutrition among under-5 children is usually assessed using single or conventional indicators (i.e., severe stunting, severe wasting, and/or severe underweight). But these conventional indicators partly overlap, thus not providing a comprehensive estimate of the proportion of malnourished children in the population. Incorporating all these conventional nutritional indicators, the Composite Index of Severe Anthropometric Failure (CSIAF) provides six different undernutrition measurements and estimates the overall burden of severe undernutrition with a more comprehensive view. This study applied the CISAF indicators to investigate the prevalence of severe under-5 child undernutrition in Bangladesh and its associated socioeconomic factors in the rural-urban context. Methods This study extracted the children dataset from the 2017–18 Bangladesh Demographic Health Survey (BDHS), and the data of 7661 children aged under-5 were used for further analyses. CISAF was used to define severe undernutrition by aggregating conventional nutritional indicators. Bivariate analysis was applied to examine the proportional differences of variables between non-severe undernutrition and severe undernutrition group. The potential associated socioeconomic factors for severe undernutrition were identified using the adjusted model of logistic regression analysis. Results The overall prevalence of severe undernutrition measured by CISAF among the children under-5 was 11.0% in Bangladesh (rural 11.5% vs urban 9.6%). The significant associated socioeconomic factors of severe undernutrition in rural areas were children born with small birth weight (AOR: 2.84), children from poorest households (AOR: 2.44), and children aged < 36 months, and children of uneducated mothers (AOR: 2.15). Similarly, in urban areas, factors like- children with small birth weight (AOR: 3.99), children of uneducated parents (AOR: 2.34), poorest households (APR: 2.40), underweight mothers (AOR: 1.58), mothers without postnatal care (AOR: 2.13), and children’s birth order ≥4 (AOR: 1.75), showed positive and significant association with severe under-5 undernutrition. Conclusion Severe undernutrition among the under-5 children dominates in Bangladesh, especially in rural areas and the poorest urban families. More research should be conducted using such composite indices (like- CISAF) to depict the comprehensive scenario of severe undernutrition among the under-5 children and to address multi-sectoral intervening programs for eradicating severe child undernutrition.

Index method for assessing the quality of the urban environment: international and Russian experience

В современных условиях высокого уровня урбанизации качество городской среды как неотъемлемый компонент качества жизни населения выступает одним из приоритетных направлений государственной политики, отраженных в национальных проектах России. Целью статьи является критический анализ зарубежных и отечественных методик оценки качества городской среды, основанных на индексном подходе. Рассматривается методический опыт крупнейших научно-исследовательских и консалтинговых организаций, проводящих сравнительные исследования городов на регулярной основе с использованием композитных индексов. Выделяются основные направления оценки качества городской среды, охватывающие экономические, социальные, культурные, экологические, политико-правовые аспекты жизнедеятельности населения. Показываются преимущества композитных индексов как универсальных инструментов агрегирования большого массива данных в целях осуществления комплексной оценки качества городской среды. Делается вывод о том, что существующие системы оценки ориентированы на измерение «средней городской температуры» с преимущественным использованием доступных статистических данных, позволяющих единовременно обеспечить массовый охват городов в целях их сравнительного анализа. На основе проведенного анализа формулируется перспективная научно-методическая задача - разработка композитных индексов, позволяющих оценивать внутригородские территориальные дисбалансы среды жизнедеятельности. Реализация указанной задачи имеет высокую практическую значимость для управления развитием сверхкрупных городов (мегаполисов), включая разработку дифференцированных программ совершенствования городской среды на уровне внутригородских территорий - районов, микрорайонов. In modern conditions of high urbanization, the quality of the urban environment as an integral component of the quality of life of the population is one of the priority areas of state policy, reflected in national projects of Russia. The purpose of the paper is a critical analysis of foreign and domestic methods for assessing the quality of the urban environment, based on an index approach. The publication considers the methodological experience of major research and consulting organizations conducting comparative studies of cities on a regular basis using composite indices. The main directions of assessment of the quality of the urban environment, covering economic, social, cultural, environmental, political and legal, are identified. The author shows the advantages of composite indexes as universal tools for aggregating a large array of data in order to carry out an integrated assessment of the quality of the urban environment. It is concluded that existing assessment systems focus on the measurement of "average urban temperature," preferring the use of available statistics that allow for a one-time mass coverage of cities for comparative analysis. Based on the analysis, a promising scientific and methodological task is formulated, namely: the development of composite indices that allow assessing the intracity territorial imbalances of the life environment. The implementation of this task is of high practical importance for the management of the development of super-large cities (megacities), including the development of differentiated programs for improving the urban environment at the level of inner-city territories - districts, microdistricts.

BASIC INSTITUTIONS AND ECONOMIC DEVELOPMENT IN CENTRAL- AND EASTERN-EUROPEAN POST-COMMUNIST COUNTRIES

Contrasting outcomes of economic reforms conducted by the post-communist countries in Central and Eastern Europe over the last thirty years seem to be directly associated with the peculiarities of their formal and informal institutions. The rapid pace and flexible adjustment of institutional changes, along with mindful heed towards existing institutional frameworks, have become the key to the success of more than a dozen of countries, which eventually and ultimately joined the European Union. In order to analyze the impact of institutions’ quality on economic development in post-socialist countries, the authors substantiate the approach, which outlines five basic groups of institutions: property, power, competition, innovations, and values. A number of indicators collected or calculated by international organizations such as the World Bank, Transparency International, The Heritage Foundation, among others, have been used to describe and quantify the impact of these institutions. In addition, they have been applied to construct and calculate composite indices for each of the five basic groups of institutions, as well as to generalize an integrated institutional index. The authors have chosen the World Bank data on gross domestic products per capita to illustrate the level of economic development of the studied countries. Subsequently, a list of simple linear and multiple regression models has been created, which facilitated identifying a statistically significant impact of an ample number of selected institutions on the level of well-being in post-socialist countries. In particular, the influence of power, innovation, and competition institutions is especially noticeable, also confirmed for the composite indices for these groups of institutions. Furthermore, in multiple regression models, a combination of one of the indicators of power or the corresponding composite index with the R&D expenditures’ share indicator and the Human development index seems a common pattern. In overall, different versions of the models built contain parameters that attribute to four of the five basic institutions. The absence of property-related indicators in these models could probably be explained via the nature of chosen indices and possibilities of the significant indirect impact of property institutions through the indicators of power institutions. Keywords: institutions, economic development, Central and Eastern European countries, institutional changes, basic institutions, regression analysis. JEL Classification B52, O17, O43, P30 Formulas: 0; fig.: 0; tabl.: 4; bibl.: 24.

Application of AHP for the Weighting of Sustainable Development Indicators at the Subnational Level

This article presents an indicator weighting method for constructing composite indices to assess sustainable development at the subnational level. The study uses an analytic hierarchy process (AHP), which is considered relevant, since it establishes links between the indicators that make up the different sustainable development goals (SDG). For this purpose, 28 indicators defined by experts constitute the base to evaluate the progress towards sustainable development of the Aburrá Valley region, located in Antioquia, Colombia. The results show that health, employment, and education indicators obtained higher weights, while environmental indicators received the most reduced weights. Likewise, the model proves to be consistent using a consistency ratio, which generates the possibility of replicating this model at different subnational levels.

Executive Function and Self-Regulation: Bi-Directional Longitudinal Associations and Prediction of Early Academic Skills

Despite a tendency to study executive function (EF) and self-regulation (SR) separately, parallel lines of research suggest considerable overlap between the two abilities. Specifically, both show similar developmental trajectories (i.e., develop rapidly in the early years), predict a broad range of overlapping outcomes across the lifespan (e.g., academic success, mental and physical health, and social competence), and have overlapping neural substrates (e.g., prefrontal cortex). While theoretical frameworks diverge in how they reconcile EF and SR – ranging from treating the two as functionally synonymous, to viewing them as related yet distinct abilities – there is no consensus and limited empirical evidence on the nature of their relationship and how this extends developmentally. The current study examined bi-directional longitudinal associations between early EF and SR, and their longitudinal associations with subsequent early academic skills, in a sample of 199 3- to 5-year-old pre-school children. The adopted measures permitted EF and SR to be modelled as composite indices for these analyses, thereby decreasing task-specific components of these associations. Early academic skills were captured by a standardized direct assessment. Bi-directional associations between EF and SR were found, with both accounting for unique variance in early academic skills 7 and 19months later. The current results provide important evidence to distinguish between EF and SR abilities, yet also for their reciprocal influence in situ and across early development.

CIRCULAR ECONOMY AND INNOVATIVE ENTREPRENEURSHIP, PREREQUISITES FOR SOCIAL PROGRESS

Quality of life and social welfare are objectives of the social policy of any state. The study aims to identify the influence of factors such as the circular economy, digital innovation, sustainable entrepreneurship on social progress and completes the current approach identified in the literature by assessing the dependencies between the phenomena represented by them. The quantification of the influences of the enumerated factors on social progress was achieved by identifying some synthetic indicators, such as composite indices, which would surprise the complexity of the analyzed phenomena. To measure the progress of the transition to the circular economy – using multivariate analysis methods – a composite indicator has been proposed and determined that allows the ranking of EU states according to its orientation, as a premise of social progress, and can substantiate the adjustment national policies. The integration of the proposed indicator in the regression models used, with similar indices, is done to highlight the impact of the circular economy, innovation and sustainable entrepreneurship on social progress. Thus, the adaptation of digital technologies in current business models, the development of sustainable innovative entrepreneurship support the transition from the linear economy to a circular economy and offer new study opportunities.