Socioeconomic Outcomes Research Articles

A predictive approach for myocardial infarction risk assessment using machine learning and big clinical data

Myocardial infarction is one of the most common cardiovascular diseases in emergency departments. Early prevention of this dangerous condition significantly impacts public health and considerable socioeconomic outcomes. The emergence of electronic health records (EHR) and the availability of real-world clinical data have provided opportunities to improve the quality and efficiency of healthcare by using artificial intelligence tools. In this study, we focus on the early recognition of risk factors, which can provide valuable information for early prediction of myocardial infarction and promoting a healthy life. Based on a big clinical dataset, we develop a predictive analytics approach for myocardial infarction. A vital step in efficient prediction is assessing the significance of input features, their relationships and their contributions to the disease. Therefore, we adopted statistical techniques, principal component analysis (PCA) and feature engineering. To reveal patterns and insights on our dataset, we implemented machine learning (ML) models varying from classical to more sophisticated: decision trees (DT), random forests (RF), gradient boosting algorithms (GBoost, LightGBM, CatBoost, and XGBoost) and deep neural networks (DNN). The imbalance-data issue is tackled by employing random under-sampling technique. The light gradient boosting model (LightGBM) with feature engineering on the balanced dataset is the best prediction performance achieved in this study.

ENHANCING WAQF GOVERNANCE FOR SUSTAINABLE DEVELOPMENT: A CRITICAL REVIEW

This research study aims to critically examine the governance of waqf, a significant aspect of Islamic social finance that has historically played a crucial role in advancing societal welfare and development. The study identifies several critical challenges in waqf governance, including the need for published documents and bibliometric analyses, ambiguity in waqf property information, non-uniform management practices, and quality issues in waqf reporting. It emphasises the significance of transparency, accountability, and standardised practices in managing waqf properties to maximise their positive impact on society. The methodology employed in this study involves a comprehensive review of existing literature on waqf governance challenges and improvements in Malaysia. The study highlights the need for rigorous empirical research to inform decision-making and policy formulation in waqf governance. Future research directions include investigating the intersection of waqf governance with sustainable development goals and exploring innovative approaches to enhance socio-economic outcomes through effective waqf governance practices. By proposing solutions to address these challenges and suggesting avenues for future research, the paper contributes to the ongoing discourse on optimising waqf governance for sustainable development and the well-being of communities.

TARGETING ECO-INNOVATION PERFORMANCE AMONG EU COUNTRIES: CLUSTER OUTCOME

An indispensable tool for enhancing economic growth and protecting the environment is eco-innovation, which integrates innovation and sustainable development. By utilizing innovation to address social, economic, and environmental issues, eco-innovation is essential to achieving sustainable development goals. One significant strategy for addressing environmental issues and promoting economic expansion is eco-innovation. Optimizing resource use and promoting efficiency across various sectors, eco-innovation holds significant importance in modern conditions. Eco-innovation represents a proactive approach and leads to positive environmental outcomes. The performance of eco-innovation is a key determinant of its effectiveness in achieving sustainable development goals. Undoubtedly, the European Union’s (EU) policy plan of the past few decades strongly emphasizes eco-innovation. Through initiatives such as the Eco-Innovation Scoreboard, which provides a comprehensive evaluation of eco-innovation performances across EU member states, the EU has been at the forefront of fostering eco-innovation. Eco-Innovation Scoreboards consist of indicators designed to measure various aspects of eco-innovation, used to assess the overall eco-innovation performance of EU member states and to track progress over time. This study examines the average value of eco-innovation performances across EU member states using data from the Eco-innovation Scoreboard. It also presents a comparative analysis of eco-innovation performances across EU member states over two different periods, 2013-2017 and 2018-2022, using indicators including eco-innovation input, eco-innovation activities, eco-innovation output, resource efficiency outcomes, and socio-economic outcomes. Cluster analysis groups EU member states based on their eco-innovation performances, allowing for a comparative assessment of different clusters. The examination evaluates the effectiveness of EU member states in combining innovative practices with sustainable development by focusing on cluster outcomes. The results of the analysis show dynamic changes in eco-innovation performance among EU countries, indicating migration between clusters over time. The observed trends suggest an evolution of priorities and strategies in eco-innovation, which requires adaptive policy responses. Policymakers are advised to adopt flexible and adaptive strategies that take into account the changing performance landscape of eco-innovation and that capitalize on the strengths recognized within each cluster while overcoming identified weaknesses.

Community-science reveals delayed fall migration of waterfowl and spatiotemporal effects of a changing climate.

Climate change has well-documented, yet variable, influences on the annual movements of migratory birds. The effects of climate change on fall migration remains understudied compared with spring but appears to be less consistent among species, regions and years. Changes in the pattern and timing of waterfowl migration in particular may result in cascading effects on ecosystem function, and socio-economic and cultural outcomes. We investigated changes in the migration of 15 waterfowl species along a major flyway corridor of continental importance in northeastern North America using 43 years of community-science data. We built spatially- and temporally explicit hierarchical generative additive models for each species and demonstrated that climate, specifically the interaction between minimum temperature and precipitation, significantly influences migration phenology for most species. Certain species' migratory movements responded to specific temperature thresholds (climate migrants) and others reacted more to the interaction of temperature and precipitation (extreme event migrants). There are already significant changes in the fall migration phenology of common waterfowl species with high ecological and economic importance, which may simply increase in the context of a changing climate. If not addressed, climate change could induce mismatches in management, regulations and population surveys which would negatively impact the hunting industry. Our findings highlight the importance of considering species-specific spatiotemporal scales of effect on climate on migration and our methods can be widely adapted to quantify and forecast climate-driven changes in wildlife migration.

Clinical practice guideline: Interventions for Developmental Language Delay and Disorders.

Approximately 9.9 % of children present with difficulties in language development (DLD), 7.6 % without serious additional impairments and 2.3 % associated with languagerelevant comorbidities, e.g., hearing loss. Notably, in a consensus statement by experts in German-speaking countries, in the guideline presented here, and further in this article, all of these disorders are referred to as "developmental language disorders" (DLD), whereas the international consortium CATALISE only refers to those without comorbidities as DLD. DLDs are among the most commonly treated childhood disorders and, if persistent, often reduce educational and socio-economic outcome. Children in their third year of life with developmental language delay (late talkers, LT) are at risk of a later DLD. This German interdisciplinary clinical practice guideline reflects current knowledge regarding evidence-based interventions for developmental language delay and disorders. A systematic literature review was conducted on the effectiveness of interventions for DLD. The guideline recommends parent training (Hedges g = 0.38 to 0.82) for LTs with expressive language delay, language therapy (Cohen's d = -0.20 to 0.90) for LTs with additional receptive language delay or further DLD risk factors, phonological or integrated phonological treatment methods (Cohen's d = 0.89 to 1.04) for phonological speech sound disorders (SSDs), a motor approach for isolated phonetic SSDs (non-DLD), and for lexical-semantic and morpho-syntactic impairments combinations of implicit and explicit intervention approaches (including input enrichment, modeling techniques, elicitation methods, creation of production opportunities, metalinguistic- approaches, visualizations; Cohen's d = 0.89-1.04). Recom mendations were also made for DLD associated with pragmatic-communicative impairment, bi-/ multilingualism, hearing loss, intellectual disability, autism-spectrum disorders, selective mutism, language- relevant syndromes or multiple disabilities, and for intensive inpatient language rehabilitation. Early parent- and child-centered speech and language intervention implementing evidence-based intervention approaches, frequency, and settings, combined with educational language support, can improve the effectiveness of management of developmental language delay and disorders.

Predictors of birth weight in pregnant women with malaria: a prospective cohort facility-based study in Webuye-Kenya

In sub-Saharan Africa, malaria, which remains a major public health burden, has a prevalence of 9 to 28% and malaria in pregnancy is associated with severe adverse outcomes for the mother and her baby. Here, we sought to determine the predictors of birth weight in a cohort of 140 women with malaria in pregnancy, who were recruited at the Webuye County hospital in Western Kenya. All study participants underwent malaria diagnosis through microscopic examination of blood smear samples and were grouped into the malaria-positive and malaria-negative groups. Both groups were followed up beginning at the first antenatal visit (March 2022) until delivery (December 2022) and various data, including demographic, parity, gravidity, socioeconomic, maternal and fetal outcomes were collected. Data analyses were done using SPSS version 27. Chi-square and Fisher’s Exact tests were used for bivariate and relative risk analyses at a p-value of ≤0.05 (95%) confidence level. Most of the participants were aged 18–25 years, were primigravidas and married, had secondary school-level education, earned 20–30 thousand Kenya shillings, resided in rural areas, and were in the second trimester. There were 6 (4.6%) cases of low birth weight, 3 (4.5%) in the malaria-negative group and 3 (4.7%) in the malaria-positive group. During pregnancy, 41 (31.5%) were anaemic, 5 (3.8%) were HIV-positive, 5 (3.8%) had preeclampsia, and 2 (1.5%) had gestational diabetes. Our analyses show that confounding factors like anaemia, HIV, pre-eclampsia and gestational diabetes did not influence birthweight (p ≥ 0.923). The malaria-positive and malaria-negative groups did not differ significantly with regard to the low birth weight (relative risk: 0.999, 95% confidence interval: 0.926–1.077). Marital status, gestational age, and area of residence were associated with malaria p ≤ 0.001, ≤ 0.001 and 0.028 respectively. In both groups, 124 of the 140 deliveries had normal birth weights and of these 63 (95.4%, n = 70) were in the malaria-negative group, whereas 61 (95.3%, n = 70) belonged to the malaria-positive group.

Abstract IA010: Neighborhood socioeconomic status and outcomes of patients with endometrial cancer

Abstract Cancer disparities manifest a particularly intricate interplay between incompletely understood genomic risks, biologic susceptibility, and access to quality care. Disparate access to quality cancer care is often a reflection of a complex relationship between social, historical, and environmental factors that influence a patient’s surroundings, however large observational studies rarely quantify these contextual elements beyond individual or area-level income and education. The well-established racial and socioeconomic inequities in uterine cancer outcomes remain one of the widest amongst all cancer types, with an approximate 20% difference in 5-year survival between Black and White patients, which remains unchanged over the past 15 years. Racial disparities persist even when controlling for more advanced stage at presentation, the occurrence of more aggressive tumor subtypes and quality of treatment. When controlling for age, time period of diagnosis, region of the country, urban or rural setting, treating facility type, socioeconomic status, education, insurance, comorbidity index, pathologic stage, histology, lymphadenectomy and adjuvant treatment, African American patients still have lower overall survival than White patients (HR 1.21, 95% CI 1.16-1.26). There continues to be a concerted call for further explanation of the socioeconomic factors that contribute to these racial disparities. To date, few epidemiologic studies of uterine cancer have utilized markers that are more representative of the complex interplay of various social and environmental factors that influence health outcomes. Some studies have examined area level poverty and uterine cancer treatment and outcomes, finding that living in more vulnerable neighborhoods was associated with poor survival, delays in care, and inadequate treatment. However, these studies do not take into account the interplay of neighborhood poverty and how race, or experience of racism, may affect this relationship. Given the complex and insidious nature of racism in the United States, we have further explored how neighborhood poverty may affect uterine cancer outcomes taking into account the race of patients studied. Preliminary data from New York state suggests that neighborhood socioeconomic vulnerability is associated with worse treatment and survival for patients with uterine cancer, and this was best seen in White patients living outside of major metropolitan areas. The greatest Black/White survival disparities are seen in the wealthiest neighborhoods in New York City. Black women with advanced stage endometrial cancer living in affluent areas have no significant survival advantage over those living in vulnerable neighborhoods. Citation Format: Charlotte Gamble. Neighborhood socioeconomic status and outcomes of patients with endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr IA010.

Mapping Health Disparities:: Leveraging Area-Based Deprivation Indices for Targeted Chronic Disease Intervention.

This article addresses the critical link between socioeconomic status and health outcomes in chronic disease patients, emphasizing the need for system-level outcome measurement stratified by socioeconomic status. Despite the acknowledged influence of social determinants, there is a lack of published studies analyzing chronic disease outcomes neighborhood by neighborhood. The importance of mapping as a public health tool, and the significance of analyzing outcomes at the neighborhood level is emphasized. The U.S. Census Bureau's hierarchy of space definitions is presented, particularly focusing on census tracts as a unique opportunity for analyzing chronic disease outcomes. Two Area-Based Deprivation Indices (ABDIs) - the Area Deprivation Index (ADI) and the Social Vulnerability Index (SVI) - as tools to measure socioeconomic disadvantage and vulnerability to environmental stressors, respectively are described. A brief survey of the weaknesses of ABDIs and limitations in addressing individual-level factors is addressed followed by a discussion of the challenges in translating patient address data into census block data. The evolving conversation around equity analysis and its impact on chronic disease management is presented. It highlights the willingness of public payers to tie payments to ABDIs, signaling a shift towards a more equitable healthcare system. Private insurers and health systems are urged to invest in geocoding strategies to understand and improve outcomes for the diverse neighborhoods they serve, acknowledging that the path forward involves addressing health disparities at the population level.

Forecasting the Future: The Interplay of Artificial Intelligence, Innovation, and Competitiveness and its Effect on the Global Economy

The study investigates the profound impact of Artificial Intelligence (AI) on various facets of the global economic landscape. Against a backdrop of rapid technological advancements, the study draws on the context of the pivotal IMF report highlighting the transformative potential of AI. The report suggests that AI could modify, replace, or transform about 60% of jobs in advanced economies and a significant proportion in emerging and low-income countries, reflecting a global paradigm shift in employment and economic structures. The core objective of this study is to thoroughly examine the role of AI-driven innovation in organizational competitiveness, its impact on community development and socioeconomic dynamics, and its implications on national economic policies and global economic trends. A quantitative research methodology was employed, involving a structured survey targeting a diverse group of professionals in various industries. The survey was meticulously designed to capture insights into participants' experiences and perceptions regarding AI implementation and its impacts. A total of 642 valid responses from consultants, technology enthusiasts, industry experts, and policymakers provided a robust dataset for analyzing the study's four hypotheses. The research findings reveal that AI integration significantly bolsters organizational competitiveness, echoing the insights from contemporary literature. Higher levels of AI adoption in communities are linked to improved socioeconomic outcomes, albeit with the risk of intensifying existing inequalities. On a national scale, strategies focusing on AI and innovation correlate with enhanced global economic competitiveness. Furthermore, the integration of AI in business processes markedly influences workforce dynamics, necessitating shifts in skill requirements and job roles. In light of these findings, the paper recommends strategic AI integration within businesses, equitable policy frameworks for AI deployment, a focus on AI in national economic strategies, substantial investment in workforce training, and international collaboration in AI development and ethics are imperative for maximizingAI's benefits while mitigating potential risks.

Family learning environments in Scandinavia: dimensions, types and socioeconomic profiles

In this paper, we use data from 44 Danish families to develop a new conceptual framework for analysing family learning environments and how they shape children’s opportunities in the Scandinavian context. We use data from qualitative interviews and a new smartphone app to outline six key dimensions of family learning environments that intersect in four types, which we label Expansive curators, Recreational home dwellers, Casual pragmatists and Disempowered strugglers. The dimensions and types of family learning environments provide a conceptual framework for (1) identifying a set of mechanisms that might explain intergenerational associations in socioeconomic outcomes; (2) linking dimensions of family learning environments often studied in isolation (e.g. family activities and networks); (3) incorporating dimensions of learning environments rarely considered (e.g. day care and children’s use of digital devices); and (4) distinguishing socioeconomic gradients in family learning environments.

Breast cancer learning health system: Patient information from a data and analytics platform characterizes care provided.

In a learning health system (LHS), data gathered from clinical practice informs care and scientific investigation. To demonstrate how a novel data and analytics platform can enable an LHS at a regional cancer center by characterizing the care provided to breast cancer patients. Socioeconomic information, tumor characteristics, treatments and outcomes were extracted from the platform and combined to characterize the patient population and their clinical course. Oncologists were asked to identify examples where clinical practice guidelines (CPGs) or policy changes had varying impacts on practice. These constructs were evaluated by extracting the corresponding data. Breast cancer patients (5768) seen at the Juravinski Cancer Centre between January 2014 and June 2022 were included. The average age was 62.5 years. The commonest histology was invasive ductal carcinoma (74.6%); 77% were estrogen receptor-positive and 15.5% were HER2 Neu positive. Breast-conserving surgery (BCS) occurred in 56%. For the 4294 patients who received systemic therapy, the initial indications were adjuvant (3096), neoadjuvant (828) and palliative (370). Metastases occurred in 531 patients and 495 patients died. Lowest-income patients had a higher mortality rate. For the adoption of CPGs, the uptake for adjuvant bisphosphonate was very low, 8% as predicted, compared to 64% for pertuzumab, a HER2 targeted agent and 40.2% for CD4/6 inhibitors in metastases. During COVID-19, the provincial cancer agency issued a policy to shorten the duration of radiation after BCS. There was a significant reduction in the average number of fractions to the breast by five fractions. Our platform characterized care and the clinical course of breast cancer patients. Practice changes in response to regulatory developments and policy changes were measured. Establishing a data platform is important for an LHS. The next step is for the data to feedback and change practice, that is, close the loop.

Engaging men in women’s empowerment: impact of a complex gender transformative intervention on household socio-economic and health outcomes in the eastern democratic republic of the Congo using a longitudinal survey

BackgroundIn the Democratic Republic of the Congo, women in (peri-)urban areas are commonly engaged in small trade, which allows them to meet the basic needs of their families. Microsaving approaches are a low-risk option to obtain financing for economic activities. A project combining men’s sensitization on gender equity and women’s empowerment through village savings and loan associations were implemented in North and South Kivu to raise the household economic level.ObjectiveThis study assessed how involving men in gender equity affects women’s health and socio-economic outcomes, including food security.MethodsA cohort study was conducted with 1812 women at the baseline; out of them 1055 were retrieved at the follow-up. Baseline data collection took place from May to December 2017 and the follow-up from July 2018 to January 2019. To identify socio-economic changes and changes of gender relations, linear and logistic regressions were run.ResultsResults showed that the household income improved with intervention (coefficient = 0.327; p = 0.002), while the capacity to pay high bills without contracting debts decreased (coefficient = 0.927; p = 0.001). We did not find enough statistically significant evidence of the influence of the intervention on skilled birth attendance (coefficient = 0.943; p = 0.135), or family planning use (coefficient = 0.216; p = 0.435) nor women’s participation in the decision-making (coefficient = 0.033; p = 0.227) nor on couple’s cohesion (coefficient = 0.024; p = 0.431). Food insecurity levels decreased over time regardless of being in the intervention or control area.ConclusionEmpowering women while sensitizing men on gender aspects improves financial well-being (income). Time, security, and strong politics of government recognizing and framing the approach are still needed to maximize the benefit of such projects on social factors such as women’s participation in decision-making and social cohesion.

The Relationship Between Childhood Abuse and Unintended Pregnancy Among Married Women of Reproductive Age in Bangladesh

ABSTRACT Childhood abuse has been associated with adverse medical, psychological, behavioral, and socioeconomic outcomes in adulthood. Despite this, limited research explores the connection between childhood abuse and unintended pregnancy during adulthood. Notably, existing studies have predominantly focused on high-income countries, leaving a significant gap regarding low- and middle-income nations. This study aims to investigate the impact of childhood physical, sexual, and psychological abuse on the prevalence of unintended pregnancies and explore the interaction effects of childhood abuse on unintended pregnancy occurrences. The cross-sectional survey study was conducted between October 2015 and January 2016 in the Chandpur District of Bangladesh. Data were collected from 426 married women aged 15–49 years who had at least one child of six months or younger. The assessment of child abuse pertains to the mother’s own experiences of childhood abuse and not abuse inflicted on her child. The prevalence of childhood physical, psychological, and sexual abuse was 37%, 26%, and 15%, respectively. About 25.1% of their most recent pregnancies were unintended. Notably, women with a history of childhood sexual abuse were twice as likely to experience unintended pregnancy compared to those without such a history. Furthermore, a dose-response connection was observed between the combined exposure of all categories of childhood abuse and a higher risk of unintended pregnancy. These findings highlight the need for targeted interventions, such as comprehensive sex education, accessible mental health support, and improved child protection frameworks, to address the potential repercussions of maternal childhood abuse and reduce the incidence of unintended pregnancies.

Group‐based and citizen science on‐farm variety selection approaches for bean growers in Central America

AbstractParticipatory approaches for crop variety testing can help breeding teams to incorporate traditional knowledge and consider site‐specific sociocultural complexities. However, traditional participatory approaches have drawbacks and are seldom streamlined or scaled. Decentralized on‐farm testing supported by citizen science addresses some of these challenges. In this study, we compare a citizen science on‐farm testing approach — triadic comparisons of technology options (tricot‐PVS) — with the benchmark state‐of‐the‐art group‐based participatory variety testing approach (group‐PVS) over a set of socioeconomic outcomes. We focus on on‐farm testing of common bean (Phaseolus vulgaris L.) in the Trifinio area of Central America. We measure the impact of these two approaches on bean growers in terms of on‐farm diversification and food security. We use data from 1978 smallholder farmers from 140 villages, which were randomly assigned to tricot‐PVS, group‐PVS or control. Utilizing a difference‐in‐difference model with inverse probability weighting and an instrumental variable approach, we observe that farmers involved in group‐PVS, and tricot‐PVS had comparable levels of on‐farm varietal diversification with respect to control farmers. Nonetheless, group‐PVS appears to be significantly more effective in boosting household food security, which can be attributed to improved agronomic management of the crops. This study contributes to the next generation of innovations in exploring trait preferences to produce more inclusive, demand‐driven varietal design that democratize participatory varietal selection programs.

Social inequalities in health within the City of Milan (Lombardy Region, Northern Italy): An ecological assessment.

to document existing geographical inequalities in health in the city of Milan (Lombardy Region, Northern Italy), examining the association between area socioeconomic disadvantage and health outcomes, with the aim to suggest policy action to tackle them. the analysis used an ecological framework; multiple health indicators were considered in the analysis; socioeconomic disadvantage was measured through indicators such as low education, unemployment, immigration status, and housing crowding. For each municipal statistical area, Bayesian Relative Risks of the outcomes (using the Besag-Yorkand-Mollié model) were plotted on the city map. To evaluate the association between social determinants and health outcomes, Spearman correlation coefficients were estimated. residents in the City of Milan aged between 30 and 75 years who were residing in Milan as of 01.01.2019, grouped in 88 statistical areas. all-cause mortality, type-2 diabetes mellitus, hypertension, neoplasms, respiratory diseases, metabolic syndrome, antidepressants use, polypharmacy, and multimorbidity. the results consistently demonstrated a significant association between socioeconomic disadvantage and various health outcomes, with low education exhibiting the strongest correlations. Neoplasms displayed an inverse social gradient, while the relationship with antidepressant use varied. these findings provide valuable insights into the distribution of health inequalities in Milan and contribute to the existing literature on the social determinants of health. The study highlights the need for targeted interventions to address disparities and promote equitable health outcomes. The results can serve to inform the development of effective public health strategies and policies aimed at reducing health inequalities in the city.

Associations of current and childhood socioeconomic status and health outcomes amongst patients with knee or hip osteoarthritis in a Mexico City family-practice setting

ObjectivesTo examine the association of current and childhood socioeconomic status (SES) with patient-reported functional status, quality of life and disability in patients with knee or hip osteoarthritis (OA).MethodsCross-sectional study amongst individuals seeking care for any medical reason in a primary care family-practice clinic in Mexico City. We included individuals with self-reported doctor-diagnosed arthritis, recruited through waiting-room posters and invitations by treating family physicians. We administered a survey using validated Spanish language versions of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the Osteoarthritis of Lower Limbs and Quality of Life (AMICAL), and the Stanford Health Assessment Questionnaire-Disability Index (HAQ-DI). To estimate current and childhood SES, we collected data on education level and occupation type for both the patient and their parents, as well as using a validated tool to estimate income quintile.ResultsWe recruited 154 patients and excluded 8 patients. There was a high correlation between outcome scores. Estimated income and education levels were correlated with WOMAC, AMICAL and HAQ-DI scores, and significant differences were found in all scores by occupation type. The associations for current SES variables and outcome scores remained significant independently of age, sex, BMI, and presence of diabetes or hypertension, and were largely explained by current income in mutually adjusted models. Childhood SES – in particular as measured through maternal education – was best correlated with AMICAL scores, though its effect seemed largely mediated by its association with current SES.ConclusionsCurrent Socioeconomic Status impacts functional status, quality of life and disability amongst OA patients in Mexico City. The WOMAC, AMICAL and HAQ-DI scores correlate with each other and are all potentially useful markers of disease severity. More research is needed to elucidate the relationships between childhood SES and OA outcomes. Awareness of life-course SES may be useful in identifying patients at risk for worse outcomes.

Indonesia’s Just Energy Transition: The Societal Implications of Policy and Legislation on Renewable Energy

Abstract The global shift to decarbonization and a sustainable economic development underscores the importance of a just energy transition. In 2019, Indonesia’s energy sector accounted for 34.5 per cent of its total emissions (lulucf included). While transitioning to green energy is paramount, it is laden with interwoven challenges encompassing technological innovation, infrastructure expansion, financing, and harmonizing socio-economic and environmental outcomes. At the heart of a just energy transition is the commitment to counteract potential setbacks, such as unemployment, ecological degradation, and ensuring equitable prospects within the transformative phase. This article delves into Indonesia’s legislative and policy framework regarding energy transition, spotlighting the obstacles and potentialities of implementing current strategies as well as contemplating the formulation of future policies that champion justice in the energy metamorphosis. Our research methodology includes a literature review with extensive interviews with pivotal stakeholders. The goal is to gauge the ramifications of Indonesia’s energy policies in their social, economic, and environmental dimensions. While Indonesia has an impressive potential in renewable energy resources, a distinct challenge remains – the absence of transparency in orchestrating a just energy transition. Forthcoming legislation and strategies should focus on community needs, particularly of marginalized people, ensuring that they benefit from a just energy transition. Incorporating stakeholders in policy deliberations is vital to shape comprehensive, inclusive strategies.

The long shadow of childhood mental health problems

The long shadow of childhood mental health problems Dr Niamh Dooley and Professor Mary Cannon explore what young adult life looks like for individuals who had mental health problems as children. People who suffer with their mental health in childhood are at greater risk of poor mental health in adulthood. What is less well known is that they are also at greater risk of other poor outcomes such as substance misuse, physical health problems, loneliness, and unemployment. In 2011, a classic study by Alissa Goodman and colleagues showed that poor childhood mental health was linked much more strongly to poor socioeconomic outcomes in adulthood than poor childhood physical health. (1) The past ten years of research broadly support those findings. (2-4)

Monetary Policy and the Gender and Racial Employment Dynamics in Brazil

ABSTRACT Monetary policy has been historically concerned with controlling inflation, using the interest rate as its main tool. However, such policies are not gender- or race-neutral. This paper explores econometrically the effect of changes in the interest rate for female and black employment creation in Brazil. We conducted a fixed effects analysis for 13 states between 2012 and 2021 to estimate the effects of changes in interest rates on unemployment, separating it by gender and race. Our results show that the increase in the real interest rate has a positive effect on the relative unemployment of black men to white men, no effect on the relative unemployment of black women to white men, and a negative effect on the relative unemployment of white women to white men. These effects are intensified in regions where the black share of the population is lower. This paper contributes to understanding the challenges to closing gender and racial gaps, particularly in developing economies. We conclude that social stratification, if not considered, can lead to misleading policies that perpetuate unequal socioeconomic outcomes.

The Nexus between Citizen Participation and Engagement in Elections and Development in Ghana: Empirical Evidence from Voters in Four Electorally-Swing Constituencies in Ghana

The Nexus between Citizen Participation and Engagement in Elections and Development in Ghana: Empirical Evidence from Voters in Four Electorally-Swing Constituencies in Ghana
 *Gbensuglo Alidu Bukari 
 Department of Political Science
 University for Development Studies, Tamale-Ghana
 E-mail: gbukari@uds.edu.gh
 
 Eliasu Mumuni
 Department of Communication, Innovation and Technology
 University for Development Studies, Tamale-Ghana
 Email: meliasu@uds.edu.gh
 
 Adam Osman Oscar
 Department of Logistics and Procurement Management
 Tamale Technical University, Tamale-Ghana
 oadamosman@tatu.edu.gh
 
 Abstract
 This paper establishes the relationship between individual citizens' voting participation in national elections and their felt socio-economic outcomes in Ghana. The paper adopts a micro-level approach and utilises data from a random sample of 600 respondents in four electorally-swing constituencies. The aim is to ascertain their views on a range of socio-economic issues related to elections and felt individual and community outcomes. The analysis of the results was conducted using standard multi-regression. The results of the analysis established that the relationship between individual and household economic welfare related to personal income, employment opportunities, personal and household educational opportunities and personal and household health status and voting participation is varied. The conclusion is that the unique circumstances of voter participation and choice in an election in the electorally-swing constituencies in the country are contingent on superior socio-economic policies of an incumbent government or political parties in electoral competition with the aspiration to win political power and dominance in a future electoral contest in Ghana. Therefore, based on the results, the enhancement of democracy through active participation in the political and electoral processes should place a premium on inclusive access of citizens to income, health, education and employment opportunities.
 Keywords: elections, democracy, participation, engagement, development, voting behaviour, Ghana