Life expectancy is often considered the most effective measure for evaluating a nation's health status. In light of this, the study investigates the impact of carbon dioxide emissions on life expectancy in the Gulf Cooperation Council countries, controlling for economic growth (GDPpc), energy consumption, and urbanization between 1990 and 2020. To ensure the validity and reliability of the findings, the study employs a robust methodology, including Unit Root, cross-sectional dependence tests, and the novel method of moments quantile regression. The findings were further validated through additional models such as Fully Modified Ordinary Least Square, Panel-Corrected Standard Error, and Feasible Generalized Least Square, which ensure the robustness of the results. The estimation results consistently reveal an inverse relationship between CO2 emissions and life expectancy, underscoring the negative health impacts of environmental degradation. In contrast, GDP per capita, urbanization, and energy consumption contribute positively to life expectancy. The study also identifies energy consumption as a mediator that exacerbates the negative effects of CO2 emissions on health outcomes in the GCC. Overall, the study's conclusions are sound and based on comprehensive statistical tests, indicating high validity and reliability. However, the study's completeness is somewhat limited as it excludes potential health determinants such as healthcare quality and lifestyle factors, which could introduce omitted variable bias. Nonetheless, the results offer compelling insights for GCC policymakers, recommending immediate actions to reduce CO2 emissions and prioritize clean energy to improve health outcomes in alignment with Sustainable Development Goal 3.
{"title":"Impact of CO2 emissions, income, and urbanization on health status in GCC countries: A moderating role of energy consumption","authors":"Hatem Hatef Abdulkadhim Altaee , Fakher Rahim , Kenesh Dzhusupov , Karlygash Toguzbaeva","doi":"10.1016/j.glt.2025.04.005","DOIUrl":"10.1016/j.glt.2025.04.005","url":null,"abstract":"<div><div>Life expectancy is often considered the most effective measure for evaluating a nation's health status. In light of this, the study investigates the impact of carbon dioxide emissions on life expectancy in the Gulf Cooperation Council countries, controlling for economic growth (GDPpc), energy consumption, and urbanization between 1990 and 2020. To ensure the validity and reliability of the findings, the study employs a robust methodology, including Unit Root, cross-sectional dependence tests, and the novel method of moments quantile regression. The findings were further validated through additional models such as Fully Modified Ordinary Least Square, Panel-Corrected Standard Error, and Feasible Generalized Least Square, which ensure the robustness of the results. The estimation results consistently reveal an inverse relationship between CO<sub>2</sub> emissions and life expectancy, underscoring the negative health impacts of environmental degradation. In contrast, GDP per capita, urbanization, and energy consumption contribute positively to life expectancy. The study also identifies energy consumption as a mediator that exacerbates the negative effects of CO<sub>2</sub> emissions on health outcomes in the GCC. Overall, the study's conclusions are sound and based on comprehensive statistical tests, indicating high validity and reliability. However, the study's completeness is somewhat limited as it excludes potential health determinants such as healthcare quality and lifestyle factors, which could introduce omitted variable bias. Nonetheless, the results offer compelling insights for GCC policymakers, recommending immediate actions to reduce CO<sub>2</sub> emissions and prioritize clean energy to improve health outcomes in alignment with Sustainable Development Goal 3.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 211-222"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-04-07DOI: 10.1016/j.glt.2025.04.001
Alexis Rojas Ospina , Alexander Zúñiga Collazos
This study develops and validates a structural model to assess the relationship between agricultural activity (AA) and Environmental Sustainability Performance (ESP). The model was empirically tested in plantain crops in Valle del Cauca, Colombia, using structural equation modeling (SEM) to examine causal relationships among key sustainability factors. Data were collected through a structured 28-item instrument applied to 600 administrators, managers, and owners of Agricultural Production Units (APUs). The analysis, conducted using partial least squares SEM (PLS-SEM) in SmartPLS 4.0, reveals that Business Associativity (BA), Agricultural Management (AM), Citizen Participation (CP), and Information and Communication Technologies (ICTs) have a direct and positive effect on ESP. Moreover, significant indirect effects are observed between ICTs and AM, ICTs and CP, and AM and BA, highlighting their interconnected influence on ESP. These findings emphasize the strategic role of associativity, management practices, digital transformation, and civic engagement in enhancing sustainability outcomes. The study provides actionable insights for policymakers and stakeholders, advocating for targeted interventions and data-driven policies to foster sustainable agricultural practices.
{"title":"Model for assessing environmental sustainability performance in the agricultural sector: A case study on plantain cultivation","authors":"Alexis Rojas Ospina , Alexander Zúñiga Collazos","doi":"10.1016/j.glt.2025.04.001","DOIUrl":"10.1016/j.glt.2025.04.001","url":null,"abstract":"<div><div>This study develops and validates a structural model to assess the relationship between agricultural activity (AA) and Environmental Sustainability Performance (ESP). The model was empirically tested in plantain crops in Valle del Cauca, Colombia, using structural equation modeling (SEM) to examine causal relationships among key sustainability factors. Data were collected through a structured 28-item instrument applied to 600 administrators, managers, and owners of Agricultural Production Units (APUs). The analysis, conducted using partial least squares SEM (PLS-SEM) in SmartPLS 4.0, reveals that Business Associativity (BA), Agricultural Management (AM), Citizen Participation (CP), and Information and Communication Technologies (ICTs) have a direct and positive effect on ESP. Moreover, significant indirect effects are observed between ICTs and AM, ICTs and CP, and AM and BA, highlighting their interconnected influence on ESP. These findings emphasize the strategic role of associativity, management practices, digital transformation, and civic engagement in enhancing sustainability outcomes. The study provides actionable insights for policymakers and stakeholders, advocating for targeted interventions and data-driven policies to foster sustainable agricultural practices.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 175-188"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2024-12-30DOI: 10.1016/j.glt.2024.12.002
Aura Girlovan, Cristiana Tudor, Gabriel Robert Saiu, Daniel Dumitru Guse
This paper investigates the determinants of environmental sustainability by analyzing the impact of various economic, fiscal, and energy-related variables on greenhouse gas (GHG) emissions and energy intensity (EI) across 27 European Union member states from 2005 to 2022. Using dynamic panel data analysis through the system Generalized Method of Moments (GMM) estimator, we explore how key factors such as GDP per capita growth, foreign direct investment (FDI), portfolio investments (PI), trade openness (TO), and stock market performance (SMP) influence environmental outcomes. Additionally, the analysis examines the role of fiscal policies, represented by government deficit/surplus (GDT), and energy-related factors, such as renewable energy consumption (REC) and research and development expenditure (ERD), in shaping sustainability. The findings reveal that while GDP growth correlates positively with increased GHG emissions, it negatively impacts energy intensity, suggesting that economic expansion may drive emissions upward while concurrently promoting greater energy efficiency. Trade openness significantly mitigates GHG emissions, indicating that enhanced international trade facilitates access to cleaner technologies. The effects of FDI and PI present a more ambivalent picture, often associated with elevated GHG emissions in the absence of stringent regulatory frameworks. Notably, renewable energy adoption emerges as a critical driver of sustainability, effectively mitigating the environmental impacts of globalization. This study provides valuable insights into the complex interplay between economic globalization and environmental sustainability, offering actionable policy recommendations to align economic growth with the EU's long-term environmental objectives.
{"title":"Exploring the impact of globalization and economic-energy dynamics on environmental sustainability in the EU","authors":"Aura Girlovan, Cristiana Tudor, Gabriel Robert Saiu, Daniel Dumitru Guse","doi":"10.1016/j.glt.2024.12.002","DOIUrl":"10.1016/j.glt.2024.12.002","url":null,"abstract":"<div><div>This paper investigates the determinants of environmental sustainability by analyzing the impact of various economic, fiscal, and energy-related variables on greenhouse gas (GHG) emissions and energy intensity (EI) across 27 European Union member states from 2005 to 2022. Using dynamic panel data analysis through the system Generalized Method of Moments (GMM) estimator, we explore how key factors such as GDP per capita growth, foreign direct investment (FDI), portfolio investments (PI), trade openness (TO), and stock market performance (SMP) influence environmental outcomes. Additionally, the analysis examines the role of fiscal policies, represented by government deficit/surplus (GDT), and energy-related factors, such as renewable energy consumption (REC) and research and development expenditure (ERD), in shaping sustainability. The findings reveal that while GDP growth correlates positively with increased GHG emissions, it negatively impacts energy intensity, suggesting that economic expansion may drive emissions upward while concurrently promoting greater energy efficiency. Trade openness significantly mitigates GHG emissions, indicating that enhanced international trade facilitates access to cleaner technologies. The effects of FDI and PI present a more ambivalent picture, often associated with elevated GHG emissions in the absence of stringent regulatory frameworks. Notably, renewable energy adoption emerges as a critical driver of sustainability, effectively mitigating the environmental impacts of globalization. This study provides valuable insights into the complex interplay between economic globalization and environmental sustainability, offering actionable policy recommendations to align economic growth with the EU's long-term environmental objectives.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 41-55"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-07-09DOI: 10.1016/j.glt.2025.07.002
Fatima Azdagaz , Omar Zirari , Mariem Liouaeddine
This study examines climate change impacts on agricultural productivity and human health across 20 developing countries (2000–2020) using Panel Autoregressive Distributed Lag (Panel-ARDL) methodology. Our systems approach models dynamic relationships between climate variables, food production, and nutritional outcomes, addressing multicollinearity through variance inflation tests and alternative specifications. National carbon dioxide (CO2) emissions serve as proxies for multiple climate pathways including temperature variations and economic development patterns affecting food systems. Results reveal strong negative long-run relationships between CO2 emissions and food production, with positive associations with child stunting. The Pooled Mean Group estimator demonstrates homogeneous long-run coefficients while allowing heterogeneous short-term dynamics across countries. The paradoxical positive CO2-food insecurity relationship reflects greater climate stresses and inequitable benefit distribution in higher-emission countries. Health impacts exhibit greater persistence than production shocks, emphasizing comprehensive monitoring needs. Findings suggest integrated policies combining climate mitigation, productivity enhancement, and health system strengthening for resilient food systems.
{"title":"Navigating climate change impacts on agricultural productivity, food and human health security in developing countries","authors":"Fatima Azdagaz , Omar Zirari , Mariem Liouaeddine","doi":"10.1016/j.glt.2025.07.002","DOIUrl":"10.1016/j.glt.2025.07.002","url":null,"abstract":"<div><div>This study examines climate change impacts on agricultural productivity and human health across 20 developing countries (2000–2020) using Panel Autoregressive Distributed Lag (Panel-ARDL) methodology. Our systems approach models dynamic relationships between climate variables, food production, and nutritional outcomes, addressing multicollinearity through variance inflation tests and alternative specifications. National carbon dioxide (CO<sub>2</sub>) emissions serve as proxies for multiple climate pathways including temperature variations and economic development patterns affecting food systems. Results reveal strong negative long-run relationships between CO<sub>2</sub> emissions and food production, with positive associations with child stunting. The Pooled Mean Group estimator demonstrates homogeneous long-run coefficients while allowing heterogeneous short-term dynamics across countries. The paradoxical positive CO<sub>2</sub>-food insecurity relationship reflects greater climate stresses and inequitable benefit distribution in higher-emission countries. Health impacts exhibit greater persistence than production shocks, emphasizing comprehensive monitoring needs. Findings suggest integrated policies combining climate mitigation, productivity enhancement, and health system strengthening for resilient food systems.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 430-440"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-03-13DOI: 10.1016/j.glt.2025.03.001
Abroon Qazi , Linda C. Angell , Mecit Can Emre Simsekler , Abdelkader Daghfous , M.K.S. Al-Mhdawi
This study examines the impact of failing to achieve Sustainable Development Goals (SDGs) on disaster and pandemic vulnerabilities, providing a country-level perspective to inform resilience planning. The study introduces the concept of SDG-related risk, defined as the probability of not achieving the desired SDG, and classifies these risks into three categories: high, medium, and low. Using a Bayesian Belief Network (BBN) framework, two probabilistic models are developed to evaluate the influence of SDG performance on disaster risk and COVID-19 vulnerability across 165 countries. The results highlight that shortcomings in SDGs such as ‘quality education’, ‘sustainable cities and communities’, ‘no poverty’, and ‘affordable and clean energy’ significantly increase disaster and pandemic risks. Conversely, strong performance in ‘peace, justice and strong institutions’ and ‘life on land’ enhances systemic resilience. Countries with very high disaster risk are particularly exposed to deficiencies in SDGs related to ‘peace, justice and strong institutions’, ‘sustainable cities and communities’, and ‘good health and well-being’. For COVID-19 risk, ‘affordable and clean energy’ emerges as the most critical SDG influencing high-risk exposure, whereas ‘climate action’ is pivotal in predicting low-risk states. These findings demonstrate the cascading risks posed by failing to achieve critical SDGs and emphasize the need for targeted interventions to mitigate vulnerabilities to disasters and pandemics, providing actionable insights for sustainable resilience strategies.
{"title":"Assessing the impact of sustainability risks on disaster and pandemic vulnerabilities: A global perspective","authors":"Abroon Qazi , Linda C. Angell , Mecit Can Emre Simsekler , Abdelkader Daghfous , M.K.S. Al-Mhdawi","doi":"10.1016/j.glt.2025.03.001","DOIUrl":"10.1016/j.glt.2025.03.001","url":null,"abstract":"<div><div>This study examines the impact of failing to achieve Sustainable Development Goals (SDGs) on disaster and pandemic vulnerabilities, providing a country-level perspective to inform resilience planning. The study introduces the concept of SDG-related risk, defined as the probability of not achieving the desired SDG, and classifies these risks into three categories: high, medium, and low. Using a Bayesian Belief Network (BBN) framework, two probabilistic models are developed to evaluate the influence of SDG performance on disaster risk and COVID-19 vulnerability across 165 countries. The results highlight that shortcomings in SDGs such as ‘quality education’, ‘sustainable cities and communities’, ‘no poverty’, and ‘affordable and clean energy’ significantly increase disaster and pandemic risks. Conversely, strong performance in ‘peace, justice and strong institutions’ and ‘life on land’ enhances systemic resilience. Countries with very high disaster risk are particularly exposed to deficiencies in SDGs related to ‘peace, justice and strong institutions’, ‘sustainable cities and communities’, and ‘good health and well-being’. For COVID-19 risk, ‘affordable and clean energy’ emerges as the most critical SDG influencing high-risk exposure, whereas ‘climate action’ is pivotal in predicting low-risk states. These findings demonstrate the cascading risks posed by failing to achieve critical SDGs and emphasize the need for targeted interventions to mitigate vulnerabilities to disasters and pandemics, providing actionable insights for sustainable resilience strategies.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 159-174"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-06-12DOI: 10.1016/j.glt.2025.06.001
Wanqi Wen , Wenxuan Zhao , Dashan Zheng , Jianheng Chen , Biao Kan , Haijian Zhou , Bo Pang , Hualiang Lin
Introduction
The United Nations Sustainable Development Goals (UN SDG) include targets for safe drinking water, sanitation, and hygiene (WASH), which are critical in preventing cholera, a persistent health threat in low- and middle-income countries (LMICs). We aimed to assess the attributable burden of WASH on cholera under the UN SDG framework to inform global control efforts.
Methods
We extracted cholera-related information along with socioeconomic, geographical, and climate data across 89 LMICs from 2000 to 2017. Genome data from Enterobase and World Health Organization (WHO) weekly reports, were utilized to identify cholera occurrence. A modified Poisson generalized additive mixed model (GAMM) was employed to investigate the impact of WASH access on cholera, and the attributable burden and prevention fraction were further estimated.
Results
Statistically significant protective effects against cholera were observed for improved WASH facilities (e.g., piped water: prevalence ratio, PR = 0.88, 95 % CI: 0.85–0.91), while harmful effects were noted for unimproved facilities (e.g., open defecation: PR = 1.09, 95 % CI: 1.06–1.12). Regional disparities in WASH access further contributed to unequal cholera burden. In Sub-Saharan Africa, 25.77 % of cholera occurrences were attributed to the high proportion of unimproved drinking water, much higher than 9.09 % in Northern Africa and Western Asia. Achieving universal access to improved sanitation could reduce cholera risk by 32.98 % in Sub-Saharan Africa, compared to 7.47 % in Central and Southern Asia.
Conclusion
Our findings highlight the need for maintaining and increasing access to safe WASH in cholera-affected countries, and offer comprehensive information for implementing targeted, local-level control approaches to end cholera globally.
{"title":"Water and sanitation access shapes cholera burden in low- and middle-income countries","authors":"Wanqi Wen , Wenxuan Zhao , Dashan Zheng , Jianheng Chen , Biao Kan , Haijian Zhou , Bo Pang , Hualiang Lin","doi":"10.1016/j.glt.2025.06.001","DOIUrl":"10.1016/j.glt.2025.06.001","url":null,"abstract":"<div><h3>Introduction</h3><div>The United Nations Sustainable Development Goals (UN SDG) include targets for safe drinking water, sanitation, and hygiene (WASH), which are critical in preventing cholera, a persistent health threat in low- and middle-income countries (LMICs). We aimed to assess the attributable burden of WASH on cholera under the UN SDG framework to inform global control efforts.</div></div><div><h3>Methods</h3><div>We extracted cholera-related information along with socioeconomic, geographical, and climate data across 89 LMICs from 2000 to 2017. Genome data from Enterobase and World Health Organization (WHO) weekly reports, were utilized to identify cholera occurrence. A modified Poisson generalized additive mixed model (GAMM) was employed to investigate the impact of WASH access on cholera, and the attributable burden and prevention fraction were further estimated.</div></div><div><h3>Results</h3><div>Statistically significant protective effects against cholera were observed for improved WASH facilities (e.g., piped water: prevalence ratio, PR = 0.88, 95 % CI: 0.85–0.91), while harmful effects were noted for unimproved facilities (e.g., open defecation: PR = 1.09, 95 % CI: 1.06–1.12). Regional disparities in WASH access further contributed to unequal cholera burden. In Sub-Saharan Africa, 25.77 % of cholera occurrences were attributed to the high proportion of unimproved drinking water, much higher than 9.09 % in Northern Africa and Western Asia. Achieving universal access to improved sanitation could reduce cholera risk by 32.98 % in Sub-Saharan Africa, compared to 7.47 % in Central and Southern Asia.</div></div><div><h3>Conclusion</h3><div>Our findings highlight the need for maintaining and increasing access to safe WASH in cholera-affected countries, and offer comprehensive information for implementing targeted, local-level control approaches to end cholera globally.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 333-341"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Early sexual activity can have a substantial negative impact on adolescents and youths. Biological, psychological, socio-cultural, and economic factors put youths at high risk of initiating sexual intercourse at an early age. This study aimed to assess the level of early sexual initiation and associated factors among school youth in the Benishangul Gumuz region.
Methods
School-based cross-sectional study was conducted from February 4–15, 2022. A pretested and self-administered questionnaire was used to collect the data. Bivariable and multivariable binary logistic regression model was used to determine the presence of a significant association between sexual initiation and independent variables.
Results
Out of 424 study subjects, 178 (43 %) had ever initiated sexual intercourse, of which 143 (80.3 %) had initiated before 18 years of age. Students who were in the age category of 15–19 years (AOR = 6.29; 95 % CI: 2.53, 15.63) and those who had multiple sexual partners (AOR = 5.08, 95 % CI = 2.00, 12.87) had higher odds of having early sexual initiation as compared with their counterpart. Similarly, students who consumed alcohol (AOR = 2.91, 95 % CI = 1.03, 8.17) and who had never used a condom during sexual intercourse (AOR = 3.09, 95 % CI = 1.22, 7.81) had a higher odd of initiating sexual intercourse at an early age as compared with their counterpart.
Conclusions
This study revealed that there was high magnitude of early sexual intercourse in the region. Predictors were having multiple sexual partners, never used a condom, and drunk alcohol. Delaying age at sexual initiation is a strategy that needs to be incorporated into the curriculums of primary and secondary schools. Parents have also a moral duty and responsibility to educate their children on the impact and consequence of early sexual initiation.
背景：严重的性行为会对青少年产生严重的负面影响。生理、心理、社会文化和经济因素使青少年过早开始性行为的风险很高。本研究旨在评估Benishangul Gumuz地区学校青少年的早期性行为水平及其相关因素。方法以学校为基础的横断面研究于2022年2月4日至15日进行。使用预先测试和自我管理的问卷来收集数据。使用双变量和多变量二元逻辑回归模型来确定性起始和自变量之间是否存在显著关联。结果424名调查对象中，178人（43%）曾有性行为，其中143人（80.3%）在18岁前有性行为。15 ~ 19岁学生(AOR = 6.29；95% CI: 2.53, 15.63)和那些有多个性伴侣的人（AOR = 5.08, 95% CI = 2.00, 12.87）与他们的同伴相比，有更高的几率过早开始性行为。同样，饮酒的学生（AOR = 2.91, 95% CI = 1.03, 8.17）和在性交过程中从未使用安全套的学生（AOR = 3.09, 95% CI = 1.22, 7.81）与同龄学生相比，在早期开始性交的几率更高。结论本研究显示该地区存在较高的早期性行为发生率。预测因素包括有多个性伴侣、从未使用安全套和酗酒。推迟开始性行为的年龄是一项需要纳入中小学课程的策略。父母也有道德上的义务和责任教育他们的孩子关于过早开始性行为的影响和后果。
{"title":"Early sexual initiation among school youths in Metekel Zone, Benishangul Gumuz Region, Northwestern Ethiopia: Cross sectional study","authors":"Mulatu Agajie , Tesfu Zewdu , Muluwas Amentie Zelka","doi":"10.1016/j.glt.2025.02.001","DOIUrl":"10.1016/j.glt.2025.02.001","url":null,"abstract":"<div><h3>Background</h3><div>Early sexual activity can have a substantial negative impact on adolescents and youths. Biological, psychological, socio-cultural, and economic factors put youths at high risk of initiating sexual intercourse at an early age. This study aimed to assess the level of early sexual initiation and associated factors among school youth in the Benishangul Gumuz region.</div></div><div><h3>Methods</h3><div>School-based cross-sectional study was conducted from February 4–15, 2022. A pretested and self-administered questionnaire was used to collect the data. Bivariable and multivariable binary logistic regression model was used to determine the presence of a significant association between sexual initiation and independent variables.</div></div><div><h3>Results</h3><div>Out of 424 study subjects, 178 (43 %) had ever initiated sexual intercourse, of which 143 (80.3 %) had initiated before 18 years of age. Students who were in the age category of 15–19 years (AOR = 6.29; 95 % CI: 2.53, 15.63) and those who had multiple sexual partners (AOR = 5.08, 95 % CI = 2.00, 12.87) had higher odds of having early sexual initiation as compared with their counterpart. Similarly, students who consumed alcohol (AOR = 2.91, 95 % CI = 1.03, 8.17) and who had never used a condom during sexual intercourse (AOR = 3.09, 95 % CI = 1.22, 7.81) had a higher odd of initiating sexual intercourse at an early age as compared with their counterpart.</div></div><div><h3>Conclusions</h3><div>This study revealed that there was high magnitude of early sexual intercourse in the region. Predictors were having multiple sexual partners, never used a condom, and drunk alcohol. Delaying age at sexual initiation is a strategy that needs to be incorporated into the curriculums of primary and secondary schools. Parents have also a moral duty and responsibility to educate their children on the impact and consequence of early sexual initiation.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 81-86"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-02-27DOI: 10.1016/j.glt.2025.02.003
Mona Gamal Mohamed , Taliaa Mohsen Al-Yafeai , Shukri Adam , Md Moyazzem Hossain , Ramya Kundayi Ravi , Fatima Mohamed Jalo , Aamna Eltayeb Osman
Background
Emotional intelligence and resilience empower students in the academic settings to face and overcome the challenges that comes with demanding academic tasks and social pressure.
Objective
This study aimed to examine the role of emotional intelligence in managing academic stress, fostering resilience, and supporting the transition experience among Northern Emirati students in health sciences. Additionally, it sought to assess whether factors such as GPA are related to EI, stress, and resilience levels.
Methods
A cross-sectional, descriptive survey design was used, with data collected from 230 second -year students at RAK Medical and Health Sciences University. The questionnaire included sections on sociodemographic data, the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), the Brief Resilience Scale (BRS), and the Student Stress Inventory - Stress Manifestations (SSISM). Data analysis involved descriptive statistics in SPSS version 29, Structural Equation Modeling (SEM) for relational insights, and regression analysis in R to evaluate the predictive influence of EI on stress and resilience.
Results
Regression analysis indicated that EI significantly predicted resilience and stress levels, with GPA showing an additional positive relationship to EI and resilience. Regression analysis indicated that EI significantly predicted resilience (β = 0.52, p < 0.001) and stress levels (β = −0.33, p < 0.001). GPA exhibited a positive relationship with resilience (r = 0.29, p < 0.05) and well-being (r = 0.45, p < 0.001). Structural Equation Modeling (SEM) confirmed a well-fitting model (Chi-Square/DF = 2.879, RMSEA = 0.108, CFI = 0.785, TLI = 0.846). The path coefficients demonstrated that well-being had the strongest influence on GPA (β = 0.452, p < 0.001), while stress had a minimal but non-significant impact (β = 0.087, p = 0.107).
Conclusions
The findings suggest that emotional intelligence is a significant factor in helping health sciences students manage academic stress and foster resilience. These results highlight the potential benefit of EI development programs to support students during key academic transitions. However, the study's cross-sectional design and reliance on self-reported data suggest that further longitudinal research is needed to confirm these findings.
情商和适应力使学生在学术环境中能够面对和克服艰巨的学术任务和社会压力带来的挑战。目的本研究旨在探讨情绪智力在管理学业压力、培养韧性和支持阿联酋北部健康科学学生的过渡体验方面的作用。此外，它还试图评估GPA等因素是否与情商、压力和恢复能力水平有关。方法采用横断面描述性调查设计，收集来自RAK医学与健康科学大学230名二年级学生的数据。问卷内容包括社会人口统计数据、特质情商短表（TEIQue-SF）、简短弹性量表（BRS）和学生压力量表-压力表现（SSISM）。数据分析使用SPSS version 29进行描述性统计，使用结构方程模型（SEM）进行关系分析，使用R进行回归分析，评估EI对应力和恢复力的预测影响。结果回归分析表明，EI对心理弹性和压力水平有显著的预测作用，GPA与EI和心理弹性呈显著正相关。回归分析表明，EI显著预测心理弹性(β = 0.52, p <；0.001)和应力水平(β = - 0.33, p <；0.001)。GPA与弹性呈正相关(r = 0.29, p <；0.05)和幸福感(r = 0.45, p <；0.001)。结构方程模型（SEM）证实模型拟合良好（Chi-Square/DF = 2.879, RMSEA = 0.108, CFI = 0.785, TLI = 0.846）。通径系数显示，幸福感对GPA的影响最大(β = 0.452, p <；0.001)，而压力的影响最小但不显著（β = 0.087, p = 0.107）。研究结果表明，情商是帮助健康科学专业学生管理学业压力和培养适应力的重要因素。这些结果强调了情商发展项目在关键的学业过渡期间支持学生的潜在好处。然而，该研究的横断面设计和对自我报告数据的依赖表明，需要进一步的纵向研究来证实这些发现。
{"title":"The significance of emotional intelligence in academic stress, resilience, and safe transition from high school to university: An SEM analysis among Northern Emirati university students","authors":"Mona Gamal Mohamed , Taliaa Mohsen Al-Yafeai , Shukri Adam , Md Moyazzem Hossain , Ramya Kundayi Ravi , Fatima Mohamed Jalo , Aamna Eltayeb Osman","doi":"10.1016/j.glt.2025.02.003","DOIUrl":"10.1016/j.glt.2025.02.003","url":null,"abstract":"<div><h3>Background</h3><div>Emotional intelligence and resilience empower students in the academic settings to face and overcome the challenges that comes with demanding academic tasks and social pressure.</div></div><div><h3>Objective</h3><div>This study aimed to examine the role of emotional intelligence in managing academic stress, fostering resilience, and supporting the transition experience among Northern Emirati students in health sciences. Additionally, it sought to assess whether factors such as GPA are related to EI, stress, and resilience levels.</div></div><div><h3>Methods</h3><div>A cross-sectional, descriptive survey design was used, with data collected from 230 second -year students at RAK Medical and Health Sciences University. The questionnaire included sections on sociodemographic data, the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), the Brief Resilience Scale (BRS), and the Student Stress Inventory - Stress Manifestations (SSISM). Data analysis involved descriptive statistics in SPSS version 29, Structural Equation Modeling (SEM) for relational insights, and regression analysis in R to evaluate the predictive influence of EI on stress and resilience.</div></div><div><h3>Results</h3><div>Regression analysis indicated that EI significantly predicted resilience and stress levels, with GPA showing an additional positive relationship to EI and resilience. Regression analysis indicated that EI significantly predicted resilience (β = 0.52, p < 0.001) and stress levels (β = −0.33, p < 0.001). GPA exhibited a positive relationship with resilience (r = 0.29, p < 0.05) and well-being (r = 0.45, p < 0.001). Structural Equation Modeling (SEM) confirmed a well-fitting model (Chi-Square/DF = 2.879, RMSEA = 0.108, CFI = 0.785, TLI = 0.846). The path coefficients demonstrated that well-being had the strongest influence on GPA (β = 0.452, p < 0.001), while stress had a minimal but non-significant impact (β = 0.087, p = 0.107).</div></div><div><h3>Conclusions</h3><div>The findings suggest that emotional intelligence is a significant factor in helping health sciences students manage academic stress and foster resilience. These results highlight the potential benefit of EI development programs to support students during key academic transitions. However, the study's cross-sectional design and reliance on self-reported data suggest that further longitudinal research is needed to confirm these findings.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 109-117"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To develop an artificial intelligence (AI)-assisted chest x-ray diagnostic system for the detection, differential diagnosis, and follow-up of tuberculosis (TB), and prove its usefulness.
Methods
This is a retrospective study. In-house developed AI-assisted chest x-ray diagnostic system was used to identify and diagnose lung abnormalities in participants' chest x-rays and to compare imaging findings from two x-rays. First, 100 chest radiographs were reviewed including TB cases (N = 43) with positive sputum test confirmation and non-TB cases (N = 57) for initial diagnosis and differential diagnosis. Next, 45 pairs of TB cases from the identical patients were reviewed for follow-up. The AI system diagnosed TB and graded the comparison images into three categories (improved, stable, or worsening). The performance was evaluated by four expert radiologists or pulmonary medicine specialists.
Results
The AI system demonstrated an exceptional sensitivity of 100 %, successfully identifying all 43 TB cases. Nevertheless, it is also susceptible to misclassify other diseases as TB, resulting in low specificity score of 66.7 %. The comparison function determined that expert physicians and AI-assisted chest x-ray diagnostic system were 58 % in exact agreement and 100 % in within one grade agreement.
Conclusions
The AI system successfully detected all TB patients identified in this study and demonstrated a reasonable comparison function. Therefore, our AI assisted chest x-ray diagnostic system is feasible and practical for TB screening.
{"title":"Development and evaluation of an artificial intelligence (AI) -assisted chest x-ray diagnostic system for detecting, diagnosing, and monitoring tuberculosis","authors":"Lalita Kaewwilai , Hiroshi Yoshioka , Antoine Choppin , Thepasit Prueksaritanond , Thitisant Palakawong Na Ayuthaya , Chantapat Brukesawan , Somruetai Matupumanon , Sho Kawabe , Yuki Shimahara , Arthit Phosri , Orawan Kaewboonchoo","doi":"10.1016/j.glt.2025.02.005","DOIUrl":"10.1016/j.glt.2025.02.005","url":null,"abstract":"<div><h3>Objectives</h3><div>To develop an artificial intelligence (AI)-assisted chest x-ray diagnostic system for the detection, differential diagnosis, and follow-up of tuberculosis (TB), and prove its usefulness.</div></div><div><h3>Methods</h3><div>This is a retrospective study. In-house developed AI-assisted chest x-ray diagnostic system was used to identify and diagnose lung abnormalities in participants' chest x-rays and to compare imaging findings from two x-rays. First, 100 chest radiographs were reviewed including TB cases (N = 43) with positive sputum test confirmation and non-TB cases (N = 57) for initial diagnosis and differential diagnosis. Next, 45 pairs of TB cases from the identical patients were reviewed for follow-up. The AI system diagnosed TB and graded the comparison images into three categories (improved, stable, or worsening). The performance was evaluated by four expert radiologists or pulmonary medicine specialists.</div></div><div><h3>Results</h3><div>The AI system demonstrated an exceptional sensitivity of 100 %, successfully identifying all 43 TB cases. Nevertheless, it is also susceptible to misclassify other diseases as TB, resulting in low specificity score of 66.7 %. The comparison function determined that expert physicians and AI-assisted chest x-ray diagnostic system were <strong>58</strong> % in exact agreement and 100 % in within one grade agreement.</div></div><div><h3>Conclusions</h3><div>The AI system successfully detected all TB patients identified in this study and demonstrated a reasonable comparison function. Therefore, our AI assisted chest x-ray diagnostic system is feasible and practical for TB screening.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 87-93"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01Epub Date: 2025-06-24DOI: 10.1016/j.glt.2025.06.005
Elsayed Farrag Elsaid Mohamad Elsayed , Yasmeen Fekery Yaseen Elkhodary , Mousa Gowfal Selmey , Abdalqader Ahmed Baker Al Bakery AL Masabi
Purposes
This study aims to develop and establish a concept referred to as Multidimensional Sustainable Inclusive Growth (MSIG), by examining inclusive growth from a micro-level perspective. Unlike previous studies that focus on the macro level, this approach seeks to offer a more realistic and precise definition and measure of inclusive growth on micro level, especially for developing countries.
Methods
The MSIG framework is constructed based on three key components.
A multidimensional participation component (measuring participation in production, adjusted by the ratio of wages to GDP), A multidimensional poverty component, and A multidimensional inequality component.
This approach introduces a comprehensive and in-depth measure of inclusive growth by integrating these dimensions into a single conceptual framework.
Findings
The results show notable variation in definitions, dimensions, and measurements of inclusive growth among existing literature. The newly developed MSIG shows: Positive growth in the years 2012, 2015, and 2019, and A decline in 2017.
The MSIGR (Multidimensional Sustainable Inclusive Growth Rate) was positive in 2012, 2015, and 2019—indicating a deterioration in inclusive growth—and negative in 2017, indicating an improvement in MSIGR.
When compared with Dudley Seers' method, both MSIGR and Seers’ inclusive growth rates display a similar trend, further validating the findings.
Conclusions
The study recommends that in developing country contexts, inclusive growth strategies should aim to be deep and multidimensional. Using comprehensive measures—such as poverty, inequality, and production participation (adjusted by wage-to-GDP ratios)—provides policymakers with nuanced insights into each component. This enables more informed decision-making and facilitates the adoption of strategies that foster sustainable and inclusive growth.
{"title":"Developing a multidimensional sustainable framework for measuring inclusive Growth: Evidence from Egypt","authors":"Elsayed Farrag Elsaid Mohamad Elsayed , Yasmeen Fekery Yaseen Elkhodary , Mousa Gowfal Selmey , Abdalqader Ahmed Baker Al Bakery AL Masabi","doi":"10.1016/j.glt.2025.06.005","DOIUrl":"10.1016/j.glt.2025.06.005","url":null,"abstract":"<div><h3>Purposes</h3><div>This study aims to develop and establish a concept referred to as Multidimensional Sustainable Inclusive Growth (MSIG), by examining inclusive growth from a micro-level perspective. Unlike previous studies that focus on the macro level, this approach seeks to offer a more realistic and precise definition and measure of inclusive growth on micro level, especially for developing countries.</div></div><div><h3>Methods</h3><div>The MSIG framework is constructed based on three key components.</div><div>A multidimensional participation component (measuring participation in production, adjusted by the ratio of wages to GDP), A multidimensional poverty component, and A multidimensional inequality component.</div><div>This approach introduces a comprehensive and in-depth measure of inclusive growth by integrating these dimensions into a single conceptual framework.</div></div><div><h3>Findings</h3><div>The results show notable variation in definitions, dimensions, and measurements of inclusive growth among existing literature. The newly developed MSIG shows: Positive growth in the years 2012, 2015, and 2019, and A decline in 2017.</div><div>The MSIGR (Multidimensional Sustainable Inclusive Growth Rate) was positive in 2012, 2015, and 2019—indicating a deterioration in inclusive growth—and negative in 2017, indicating an improvement in MSIGR.</div><div>When compared with Dudley Seers' method, both MSIGR and Seers’ inclusive growth rates display a similar trend, further validating the findings.</div></div><div><h3>Conclusions</h3><div>The study recommends that in developing country contexts, inclusive growth strategies should aim to be deep and multidimensional. Using comprehensive measures—such as poverty, inequality, and production participation (adjusted by wage-to-GDP ratios)—provides policymakers with nuanced insights into each component. This enables more informed decision-making and facilitates the adoption of strategies that foster sustainable and inclusive growth.</div></div>","PeriodicalId":33615,"journal":{"name":"Global Transitions","volume":"7 ","pages":"Pages 420-429"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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