Social Indicators Research Articles

Development of a Methodology for the Monitoring of Socio-Economic Indicators of Private Forest Owners towards Sustainable Forest Management: The Case of Lithuania

The development of a monitoring system for the socio-economic indicators of private forest owners includes the comprehensive collection of various socio-economic data. These data encompass general information about private forests owners, the need for monitoring, periodicity, and other relevant factors. This holistic approach allows for a detailed assessment of the social and economic conditions of private forest owners, as well as the economic efficiency of their operations, ultimately aiming to achieve sustainable forest management. This research builds upon previous studies by the authors that investigated the need for monitoring of the socio-economic indicators of private forests and involved interviews with forest experts. Based on the data obtained from these earlier efforts, this study aims to present a refined methodology for monitoring of the socio-economic indicators of Lithuanian private forest owners. Based on the findings of this research, it is highly recommended that monitoring be implemented at the state level across the entire territory of the Republic of Lithuania. The results of this research show that the monitoring of the economic and social indicators of private forest owners benefits not only the owners but also the state and society as a whole. Residence size, property size, and association membership emerged as the most significant factors influencing the need for forest monitoring, while knowledge in forestry, distance to the forest, and gender showed weaker but still notable effects. The research results suggest that monitoring can help to ensure the sustainable management of forests and the maintenance of ecosystem services, in addition to contributing to the region’s economic development. It is recommended that this monitoring be conducted every five years.

Aportes en la dimensión social y ambiental a la floricultura en el sector de hortensias bajo un enfoque de análisis de ciclo de vida

The Colombian flower industry has been growing and consolidating itself as one of the main economic activities in the country. This activity generates significant environmental and social impacts throughout its life cycle that must be resolved in order to consolidate itself as a sustainable economic activity, and for this reason the project "Environmental, economic and social life cycle assessment for hydrangea agro-industrial companies as a strategy for sustainable development in the Province of La Paz in eastern Antioquia, Colombia" is being developed for small and medium-sized producers' crops to trigger impacts and externalities in the production process. The methodology used in the project was based on the series of ISO 14040 and 14044 Life Cycle Assessment (LCA) and UNEP standards, which were evidenced in the production process of hydrangeas for export in a small farm. Some of the significant results of the research allowed identifying that the cultivation stage has grater influence on the categories of environmental impacts and social indicators evaluated, thus achieving the consolidation of relevant actions to improve the performance of the crops from a sustainability perspective.

Integrating the triple bottom line of sustainability, resilience strategies, and product perishability consideration to design a pharmaceutical supply chain network: A COVID-19 case study

This paper aims to design a resilient and sustainable pharmaceutical supply chain network under the perishability of medicine in which a multi-objective nonlinear mathematical model is formulated. To this end, four objective functions seek to minimize total cost, maximize the social indicators, minimize CO2 emission and minimize de-resilience measures. Moreover, the three main categories of resilience strategies are integrated to mitigate the severe impacts of disruption. In order to solve the model, lexicographic goal programming is applied for small-scale problems, and NSGA-II is utilized for large-scale problems. The applicability of the proposed model is demonstrated by implementing it in a real case study during the COVID-19 situation. Also, a set of sensitivity analyses is conducted to validate the model and show the behavior of the objective functions. The results reveal the superiority of the resilient model with integrated strategies. Eventually, the Pareto front solutions are provided to quantify the trade-offs in satisfying the conflicting objective functions.

Promoting inclusivity in the land market through legislative reforms in Ghana

Social inclusion in resource governance and enjoyment is critical towards attaining social cohesion, stability and shared prosperity. The paper examines how land law reforms in Ghana with the passage of the Land Act, 2020 promote social inclusion in the land market. The study used a descriptive research design and interviewed a total of 69 respondents – land experts and practitioners. The results revealed that six of the constructed social inclusion indicators significantly promote inclusiveness in the land market. The paper underscores the need for public education on the provisions of the law and the enactment of a legislative instrument to guide implementation.

Identifying priority populations for lung cancer screening intervention using neighborhood-level factors and cancer registry data.

To evaluate the association of neighborhood level economic, environmental, and social indicators with lung cancer (LC) incidence and mortality. Data for adult incident LC cases in Allegheny County, Pennsylvania, diagnosed between 2015-2019 were obtained from Pennsylvania cancer registry. Cases were summarized at census-tract level. Publicly available data on neighborhood deprivation index (NDI), built environment, and racial isolation at census-tracts were linked to cases. Poisson regression was used to compute relative risk (RR) for LC incidence and mortality, adjusting for covariates. A total of 3256 LC cases were included in the analyses. About 68% were ≥65 years, 54% female, 14% Black or African American, and 63% deceased. Results of the multivariable model found that increasing quintiles (Q) of NDI were significantly associated with increasing risk of LC incidence and mortality. The RRs (95% confidence interval) of LC incidence for Q2, Q3, Q4 and Q5 were 1.36 (1.21-1.52), 1.55 (1.40-1.72), 1.68 (1.51-1.87), 2.08 (1.82-2.38), respectively, compared with Q1 (P trend <0.01). The corresponding RRs for LC mortality were 1.46 (1.27-1.68), 1.63 (1.42-1.88), 1.74 (1.51-2.01), 2.04 (2.02-2.88) (P trend <0.01). Targeted interventions for LC prevention and early detection in high NDI neighborhoods may be more effective to reduce LC health disparities.

Spatio-Temporal Heterogeneity of the Urban Heat Effect and Its Socio-Ecological Drivers in Yangzhou City, China

Rapid urbanization and land-use changes may affect the intensity of urban heat islands (UHIs). However, research on the eastern Chinese city of Yangzhou is lacking. Using land cover data and the InVest Urban Cooling model, this study evaluated the spatiotemporal heterogeneity of the UHI effect from 1990 to 2020 and its socioecological drivers in Yangzhou City. Landscape pattern indices such as patch area (CA), percentage of landscape (PLAND), number of patches, patch density, and aggregation index were created using Fragstats 4.2 software. Several social indicators, such as gross domestic product (GDP), night-light index, and population density, were considered to explore their correlation with UHI indicators. During the past three decades, rapid urbanization in Yangzhou has intensified the UHI effect, with the cooling capacity (cc park) and heat mitigation index (HMI) decreasing by ~9.6%; however, the mixed air temperature (T air) has increased by 0.14 °C. The main heat island areas are concentrated in southern Yangzhou, including the Hanjiang and Guangling districts, and have expanded over time. T air was positively correlated with GDP, night-light index, and population density. Moreover, for the impervious land use type, cc park and HMI were negatively correlated with CA and PLAND (p &lt; 0.01). This study contributes to a deeper understanding of the dynamics of UHIs and provides valuable insights for policymakers, urban planners, and researchers striving to create sustainable and climate-resilient cities in Yangzhou.

Does change in area-level deprivation, change health outcomes? A latent class growth analysis of population data.

BackgroundWhile the link between deprivation and health is established, little is known about the association of persistent deprivation or deprivation trajectories over time with adverse health outcomes. AimTo examine latent class trajectories of area level-deprivation from 2010-2016 and their association with social distress indicators from 2017-2021. MethodAnalysis was based on linked administrative data (N=1,569,110) from NI GP Registrations Index, emergency department records (2017-21), enhanced prescribing data (2017-21) and biennial area-level deprivation (2010-2016). Latent class growth analysis (LCGA) identified deprivation trajectories between 2010 and 2016; and regression-based models, adjusted for age, sex and urbanicity, examined their association with indicators of individual level distress: occurrence of death, any accident and emergency (A&amp;E) visit, and any psychotropic medication between 2017 and 2021. ResultsBased on comparison of models and fit statistics, a non-linear LGCA model identified six trajectories: consistently deprived (21.2%); slight improvement (7.1%); substantial improvement (1.2%); consistently average deprivation (31.7%); slight worsening (18.5%); and consistently non-deprived (20.4%). Consistently living in a deprived area was associated with higher likelihood of death, A&amp;E visits and receipt of hypnotics, anxiolytics, and anti-depressants. Compared to consistent deprivation, slight improvement was associated with lower likelihood of death (OR=0.94, CI: 0.91-0.97) and all psychotropic medication in the follow-up period. ImplicationsFindings indicate that even a slight improvement in deprivation status can have a positive influence on health outcomes. Further population-wide analysis of deprivation trajectories, their determinants and associated health impact will inform targeted interventions that promote social mobility and improved health.

Genetic Predisposition of Different Social Status Indicators in Men and Women.

Although there is evidence that social status has a genetic basis, it is less known whether the genetic predisposition differs between men and women as well as among different status indicators and whether there are any intercorrelations among predispositions of status indicators. We therefore investigated the genetic predisposition for different indicators of social status separately for men and women, using polygenic scores obtained from the Wisconsin Longitudinal Study. We used multivariate polygenic regression of 7 different social status indicators on a total of 24 different polygenic scores. We find that in both men and women, wages and education show more associations with polygenic scores than the other status indicators. Also, the genetic predispositions for education and wages are correlated in both men and women, whereas in men more than in women, the genetic predispositions seem to cluster into wages and education on the one hand, and status indicators of position in the hierarchy, on the other hand, with being in a management position somewhere in between. These findings are consistent with an assumption of two different forms of selection pressure associated with either cognitive skill or dominance, which holds true particularly in men. We conclude that the genetic predisposition to higher social status may have changed even though the importance of the cultural trait of social status may have been very constant. Social status may thus be an example of a social trait of constant importance, but with a changing genetic predisposition.

Comprehensive Zoning Strategies for Flood Disasters in China

The frequency of global floods has increased, posing significant threats to economic development and human safety. Existing flood risk zoning studies in disaster prevention lack integration of the natural–economic–social chain and urban resilience factors. This study addresses this gap by constructing flood disaster risk and intensity indices using data from 31 provinces and 295 prefectural-level cities in China from 2011 to 2022. These indices incorporate natural (rainfall), economic (GDP), and social (population, built-up area) indicators to assess the flood likelihood and loss degree, providing comprehensive risk and intensity ratings. The study also examines the impact of resilience factors—environmental (green space), infrastructural (rainwater pipeline density), and natural resource (watershed areas)—on flood intensity. Findings reveal that high-risk regions are mainly in the Yangtze River Basin and southern regions, while high-intensity regions are primarily in the middle and lower Yangtze River and certain northwestern cities. Increasing rainwater pipeline density mitigates flood impacts in high-risk, high-intensity areas, while expanding green spaces and pipelines are effective in high-risk, low-intensity regions. This paper proposes a comprehensive flood hazard zoning mechanism integrating natural, economic, and social factors with urban resilience, offering insights and a scientific basis for urban flood management.

Measuring Social Sustainability in the Italian Agri-Food Sector: Proposed Key Performance Indicators.

The social dimension of sustainability in the agri-food sector is gaining more and more attention from both scholars and policymakers. In Europe, among different countries, Italy stood out for the active role played in including social conditionality in the Common Agricultural Policy. Despite such interest, there is still confusion concerning the concept of social sustainability, and tools aimed at measuring the social performance of farms are still lacking. The current study aims to identify indicators to measure the social sustainability of farm practices in the Italian agri-food system. The methodology included an analysis of the most relevant literature, legislation, and guidelines to identify five macro-areas of interest, which served as the foundation for developing theoretical social sustainability key performance indicators. The results of this study provide useful insights for both practitioners and policymakers to develop strategies and policies focused on social sustainability.

A hybrid machine learning solution for redesigning sustainable circular energy supply chains

Sustainability development goals require decision-makers to incorporate social and environmental indicators in their economic models using innovative solutions, such as a sustainable circular economy. This paper presents an innovative integrated production and logistic model for a circular economy using multi-objective optimization. Empirical data includes a renewable energy supply chain. We assess the sustainability performance of the proposed decision-making model by simultaneously considering production and logistics costs, carbon emissions, and the number of jobs created. The case study is optimized with an exact method, and a hybrid machine-learning algorithm solves large-scale numerical examples. The paper’s main contributions include movable manufacturers, uncertain parameters, a hybrid machine learning algorithm, and empirical data in the proposed decision-making model. The findings show that a moveable facility can substantially decrease total cost and carbon emissions. Sensitivity analysis shows that changes in moveable capacity and percent yield considerably impact the objectives. Findings show that decision-makers can achieve cost parity with fossil-based sources when employing circular supply chain management.

Effects of changing farming practices in African agriculture

Information on the effects of changing agricultural management on crop and livestock performance is critical for developing evidence-based policies, investments, and programs. Evidence for Resilient Agriculture (ERA) v1.0.1 presents a dataset that harmonizes and aggregates 112,859 observations from 2,011 agricultural studies taken place in Africa between 1934 and 2018. The dataset includes information on the effect of 364 combinations of management practices and technologies on 87 environmental, social, and economic indicators of outcomes. Observations are geolocated and temporally tagged and thus can be linked to other datasets such as historical weather, soil properties, and road networks. ERA offers a new resource for understanding the impacts of changing farming practices under diverse environmental contexts, providing data to support strategic interventions aimed to enhance productivity, resilience, and sustainability of African agriculture.

Global Health Management: Addressing Health Disparities And Inequalities

It is the state's responsibility to provide access to public health care management for the poor and vulnerable, as the cost of curative care is disproportionately higher among lower income groups, the majority of whom are Dalits. India's population health has significantly improved during the past 70 years. The disparity across social groupings is still rather large, though. Low health status is clearly associated with poverty, being a woman, living in a rural area, belonging to a tribal ethnic group, being a scheduled caste (SC), and belonging to particular minority groups. In order to guarantee health fairness, it is necessary to review the environment and policy implementation regime. The purpose of this article is to provide context for relevant healthcare concerns and challenges by examining a few key health, poverty, illness-related costs, and coping techniques across social groupings indicators. The conceptual foundation for the health effects of public health care management's globalisation is described in this study. An examination of the main social determinants influencing population health is known as the social determinant of health.

Diagnostic discrimination of social network indicators in alcohol use disorder: Initial examination using high-resolution and brief assessments.

Social network analysis (SNA) characterizes the structure and composition of a person's social relationships. Network features have been associated with alcohol consumption in observational studies, primarily of university undergraduates. No studies have investigated whether indicators from a person's social network can accurately identify the presence of alcohol use disorder (AUD), offering an indirect strategy for identifying AUD. Two cross-sectional case-control designs examined the clinical utility of social network indicators for identifying individuals with AUD (cases) versus demographically matched drinkers without AUD (controls). Study 1 (N = 174) used high-resolution egocentric SNA assessment, whereas Study 2 (N = 189) used a brief assessment. In Study 1, significant differences between AUD+ participants and controls were present for network alcohol severity (i.e., heavy drinking days; d = 1.23) and frequency (d = 0.35), but not network structural features. Network alcohol severity exhibited very good classification of AUD+ individuals versus controls (area under the curve [AUC] = 0.80), whereas network frequency did not (AUC = 0.61). In Study 2, significant differences were present for network alcohol severity (d = 1.02), quantity (d = 0.74), and frequency (d = 0.43), and severity exhibited good differentiation (AUC = 0.76). Social network indicators of alcohol involvement robustly differentiated AUD+ individuals from matched controls, and the brief assessment performed almost as well as the high-resolution assessment. These findings provide proof-of-concept for severity-related SNA indicators as promising novel clinical assessments for AUD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Spatial pattern of congenital toxoplasmosis incidence and its relationship with vulnerability and national health indicators in Brazil

There is a gap in evidence regarding spatial clusters of the congenital toxoplasmosis (CT) and its association with social and health indicators in the Brazilian territory. Thus, we aimed herein to identify CT risk areas in Brazil and its association with social vulnerability and health indicators. An ecological and population-based study was conducted. The CT incidence coefficient was calculated and smoothed using the Local Empirical Bayesian method. Global regression models and local spatial regression model were applied. High-incidence clusters of the disease were identified throughout the country. Additionally, a positive association was observed between the incidence of congenital toxoplasmosis and the Social Vulnerability Index, coverage of community health agents, and the percentage of prenatal consultations. This association was stronger the further south in the country. Herewith, the implementation and strengthening of public strategies, with focus on priority intersectoral actions for prevention, early diagnosis, and prompt treatment, is urgently required for the effective control of CT in Brazilian municipalities.

Is national economic growth associated with environmental social and governance performance of firms?

AbstractThis study delves into the effect of environmental, social and governance (ESG) indicators on economic growth trajectory of an emerging economy. A sample of firms listed on the ESG index of the National Stock Exchange (NSE) was examined. The findings reveal a positive and statistically significant relationship between ESG performance indicators and economic growth represented as gross domestic product (GDP) per capita. The sample is further segregated into energy and non‐energy sectors, where the aggregate ESG scores exhibited a statistically significant influence on economic growth in both sectors. However, upon a closer examination of the individual ESG pillars, the governance pillar is observed to exert a negative influence on economic performance in non‐energy firms. In contrast, the environment and social pillars show no significant influence. The analysis then employs a unique approach by applying a Difference‐in‐differences estimator to assess the impact of Business Responsibility and Sustainability Reporting (BRSR) regulations, which confirms a positive impact on economic growth after regulations but exclusively within the non‐energy sector. This study underscores the substantial impact of ESG aggregate and individual scores on GDP per capita, which translates to economic growth.

Research on the Impact of Digital Transformation on Corporate ESG - A Case Study of Jingdong Logistics

The purpose of this research is to analyze the impact that digital transformation has on the environmental, social, and governance (ESG) elements of businesses by using Jingdong Logistics as a case study. Jingdong Logistics' environmental, social, and governance (ESG) indicators have been impacted both directly and indirectly by the digital transformation that the company has undergone, as indicated by the study of data changes and measures taken both before and after the transition. This digital transition has led to huge reductions in greenhouse gas emissions, which is good news for the environment; but, it also creates challenges in terms of energy consumption requirements. Although there has been an increase in the number of training hours and a drop in the number of workplace injuries, there has been an increase in the number of full-time employees, while there has been an increase in employee turnover. Even though there was an increase in the number of vendors, anti-corruption incidents decreased. Regarding the governance side of things, improvements were made to data security and transparency. According to the findings of the inquiry, digital transformation had a positive impact on the environmental, social, and governance (ESG) of Jingdong Logistics; nevertheless, it also brought up new challenges that call for continued attention and growth.

The Information Disclosure of Environment, Social and Governance and Its Impact on the Financial Performance of Sinolink Securities

In the context of China's efforts to achieve "carbon peak", "carbon neutrality" and sustainable development, companies are transitioning to low-carbon business models by reporting environment, social and governance (ESG) indicators. This research aims to explore the practice of ESG-related information disclosure in the financial industry and analyze the impact on corporate performance. This research takes Sinolink Securities Co., Ltd. as an example, the disclosure of relevant information can be realized through corporate ESG reports, and then conduct comparisons from multiple aspects based on the relevant data from 2018 to 2022 to study the correlation between ESG and corporate performance. The research found that: 1. The company's ESG rating is generally at a leading level, and its specific performance in environmental, social, and corporate governance aspects is improving year by year. 2. There is an overall positive correlation between corporate performance and ESG practices. The improvement of ESG levels will help improve corporate performance and provide a solid foundation for the sustainable development of enterprises.

Метод оценки социально-экономической эффективности мероприятий целевых программ в области обеспечения ядерной и радиационной безопасности

The article considers approaches and methods for determining and evaluating the economic effectiveness of final stages of the life cycle of nuclear energy facilities, including nuclear legacy sites in the Arctic and on the continental part of Russia, taking into account social and environmental factors. The author proposes a relevant method based on estimates of the damage prevented, the facility disposal costs and related social indicators – the location of the facility with regard to the areas of population residence and specially protected natural sites, the availability of a credible operating organization and accessible open information support. Using the example of seven (7) disposed facilities of different types, the author evaluates economic efficiency in accordance with the proposed approaches, which allow clarifying the assessment of activities on eliminating nuclear legacy in the Arctic and the continental part in terms of their social significance and perception. The economic efficiency assessments obtained on the basis of the proposed method can be used when planning further steps to bring the nuclear legacy sites in the Arctic and continental Russia into an environmentally safe state.

제주도의 경제 성장과 지속 가능성 - GRDP의 한계와 GPI를 통한 지속 가능성 평가

This study aims to evaluate the comprehensive development level of Jeju Island by analyzing the Genuine Progress Indicator (GPI) across economic, environmental, and social dimensions. To achieve this, the GPI for Jeju Island was calculated for the years 2000 to 2021, and the trends in GRDP and GPI were comparatively analyzed. The results showed that while GRDP generally increased, GPI exhibited periods of decline or stagnation at certain points. Notably, since 2019, the COVID-19 pandemic led to a decrease in tourism revenue, resulting in a decline in GRDP, whereas GPI showed an upward trend. This trend can be attributed to the reduction in environmental pressures and the recovery of natural resources due to the decrease in tourist numbers, and such effects may have a long-term impact on GPI. This study suggests that GPI, as a complementary indicator to GRDP, can be effectively utilized as a policy tool for promoting sustainable development.