Level Of Economic Activity Research Articles

Interaction between alcohol intake and employment status changes on mortality among young workers

Abstract Background To investigate the impact of changes in employment status and their interaction with alcohol consumption on health outcomes among young workers. This study aims to explore how employment fluctuations, periodic unemployment, and economic activity levels influence the health of economically active individuals, focusing particularly on the synergistic effects that these employment changes may have when combined with alcohol consumption. Methods We conducted a retrospective cohort study using data from the Korean National Health Insurance Service database. The study included individuals aged 25-44 years who underwent health check-ups between 2009 and 2010. We categorized changes in employment status into three groups: continuously employed, economically active with employment fluctuations, and periodically unemployed. We estimated adjusted hazard ratios and 95% confidence intervals using multivariable Cox proportional hazard models to assess the impact of changes in employment status on the risk of all-cause mortality. The relative excess risk due to interaction, a widely accepted indicator of additive interaction, was used to assess the interaction between alcohol consumption and changes in employment status. Results Changes in employment status significantly increased the risk of all-cause mortality in both men and women in the economically active with employment fluctuations and periodically unemployed groups compared with the continuously employed group. The synergistic effect of alcohol consumption and changes in employment status on the risk of all-cause mortality was significant only among men. Conclusions The findings of this study indicate that changes in employment status, particularly when combined with alcohol consumption, significantly affect all-cause mortality among young workers. Key messages • Employment status fluctuations combined with alcohol consumption significantly increase all-cause mortality risks among young workers, especially men. • This study emphasizes the urgent need for targeted interventions that address the combined impact of employment and lifestyle factors on public health.

The Integration of Machine Learning in Central Banks: Implications and Innovations

The effectiveness of using artificial intelligence (AI) techniques to lessen the negative effects of economic cycles is examined in this study article. Economic cycles, which are defined by variations in the level of economic activity, present important difficulties for decision-makers in government, business, and society at large. This research investigates many approaches to reducing economic cycles, such as forecasting, policy creation, and adaptive decision-making, by utilizing AI, namely machine learning algorithms. The first section of the paper reviews the body of research on economic cycles and how artificial intelligence might be used to address them. After that, it explores certain AI methods including neural networks, time series analysis, and natural language processing, explaining how they might be used for risk management and economic forecasting. Additionally, the study investigates AI-driven policy interventions, examining how machine learning algorithms might be used to optimize monetary and fiscal policies in order to sustain growth and prevent economic downturns. The study also addresses the difficulties and constraints that come with using AI technologies in economic management, such as problems with algorithmic biases, data quality, and legal considerations. It highlights how crucial interdisciplinary cooperation and openness are to creating AI-driven solutions that are reliable, moral, and socially conscious. This research paper offers insights into the possible advantages and disadvantages of employing AI tools for damping economic cycles through empirical analysis and case studies. In order to fully realize AI's promise in fostering resilience and stability in the economy, it ends by presenting future research areas and policy suggestions. Keywords: artificial intelligence, trend, economic cycles, resilience

THE STATE AND PROSPECTS OF THE DEVELOPMENT OF THE TOURISM INDUSTRY IN UKRAINE IN THE CONDITIONS OF GLOBAL CHALLENGES

The article examines the state and prospects of international tourism development in Ukraine amid global crises, particularly the COVID-19 pandemic and the Russian-Ukrainian war. A comprehensive analysis of key factors affecting the tourism industry is conducted, including international travel restrictions, geopolitical instability, economic difficulties, and changes in consumer behavior. It demonstrates how global crises, such as COVID-19 and the Russian-Ukrainian war, have led to a significant reduction in international tourist flows, decreased foreign exchange earnings from tourism activities, and created additional risks for tourism infrastructure. In such conditions, the recovery of the industry and its integration into the country's economic development require a comprehensive approach that includes not only investments but also the digitalization of tourism services. The research highlights key changes in tourist flows, the level of economic activity in the sector, and the impact of internal and external challenges on tourism infrastructure. It was found that after a significant decline in 2022 due to the war, a gradual recovery began in 2023 thanks to the development of domestic tourism and the opening of new safe routes. Digitalization has become a key factor in the development of the modern tourism industry, affecting all stages of the tourist experience. The implementation of digital technologies, such as online booking, mobile applications, virtual and augmented reality, allows companies to enhance their service and improve competitiveness. The article emphasizes the importance of strengthening tourism infrastructure and supporting entrepreneurship in times of instability. Directions for further research are proposed, including the development of domestic tourism, the assessment of the resilience of tourism entities to crises, and the analysis of the long-term effects of the war on international tourist flows. The study underscores the significance of the tourism industry for Ukraine's economic recovery and its potential for integration into the global tourism market.

Dynamic Impact of Digital Inclusive Finance and Financial Market Development on Forests and Timber in China: Economic and Social Perspective

This study investigates how digital inclusive finance, financial development, and technology influenced forest and timber outputs across 31 provinces in China from 2011 to 2021. The findings, derived from panel quantile regression analysis, indicate that digital inclusive finance significantly enhances forest economic output, particularly in regions with lower economic activity, by improving access to critical financial resources such as credit and investment. However, the positive effects diminish at higher levels of economic activity, suggesting potential diminishing returns. Through the marketization of credit distribution and diverse financial instruments, financial development is essential for promoting sustainable forestry practices and adopting new technologies. Based on the findings, the study suggests expanding digital financial services in areas with low forest activity to help people access credit and investments, boosting forest productivity. It also recommends improving financial markets and investing in new forestry technologies to support better forest management and timber production.

City and Countryside in Byzantine Anatolia: Amorium

Amorium is a key site for the period AD 700-900 owing to its historical importance as the capital of the Anatolic Theme. The well preserved remains provide an exceptional opportunity to study the layout and function of the Byzantine city and its excavation sheds light on the transition, modification, and continuity of the settlement between the Late Roman and Byzantine periods. The evidence from twenty years of excavation points to the existence of a large and prosperous city during Early and Middle Byzantine times, where various trades and crafts were practised and which served as the centre of a vibrant rural community engaged in agriculture as well as animal husbandry. The destruction layers from the capture of Amorium by the Arabs in 838 create a fixed horizon and reference point for the entire archaeology and material culture of early to mid-ninth century Anatolia. Pottery and coin finds in particular provide good indicators of the level and nature of economic activity. In this study some conclusions are drawn from that material, and discussion of it is set in the context of other sites and the interpretation of finds there. The evidence from Amorium presents new insights that appear at odds with accepted views of the Byzantine world in the Early Middle Ages.

Geographical distribution of the COVID‐19 pandemic and key determinants: Evolution across waves in Spain

AbstractAmidst the COVID‐19 pandemic, most research has examined specific temporal snapshots. This study diverges by offering a comprehensive analysis of COVID‐19 incidence across the Spanish provinces throughout six distinct waves of the pandemic. Using spatial exploratory techniques, we find no single pandemic; rather, there have been waves. Significant differences in the spatial distribution of cases and deaths across six waves show that each has unique characteristics. Homogeneous conclusions cannot be drawn at the national level. Notable regional differences in the pandemic’s spatial distribution suggest a need for subnational responses, reflecting variations in climate, economic dynamism, sectoral specialisation, and socio‐health resources. Spatial regression models show that the main determinants of COVID‐19 incidence depend on stage. Traditional factors commonly associated with epidemiological studies, such as temperature, exerted significant influence during the pandemic’s onset. However, as mobility restrictions were enforced and vaccination campaigns were rolled out, economic conditions, and especially levels of economic activity, emerged as increasingly significant determinants.

Modelling Bank Lending in Cameroon Using Two Steps Cointegration Technique

This paper has as objective to model the key determinants of bank lending in Cameroon using time series data collected mainly from the World Bank database for the period spanning from 1979 to 2019. After exploring related theoretical and empirical literature, Engle and Granger two steps cointegration testing procedure was employed together with the necessary pretesting (unit root tests) and post estimation testing. Results of stationarity tests indicate that variable were a mixture of stationary and first difference. The lagged residual term possess unit root at level indicating that the variables are actually cointegarted and that ECM is relevant. The estimated cointegration regression model and the corresponding ECM were globally significant at one percent and the models were equally adequate with explanatory power of over 73 and 52 percent respectively. The results of the two models revealed that the effect of economic growth on bank lending was positive and highly significant, the effect of interest rate is negative and equally significant, then the effect of Gross Investment rate was also positive but not very significant in the short run. Based on the major findings, bank lending can be encouraged by stimulating the level of economic activities, by reducing interest rate on loans and by encouraging more investment projects.

Exploring the pathways accounting: Foreign direct investment as a catalyst for idiosyncratic risk, sectoral GDP, economic activity, and economic growth

This study examines the interaction between foreign direct investment (FDI), idiosyncratic risk, sectoral GDP, economic activity, and economic growth in ASEAN countries using structural equation modeling (SEM) performed using AMOS software. The analysis uses data from the ASEAN Statistics Database 2023 to distinguish the significant direct and indirect impacts of FDI on idiosyncratic risks, sectoral GDP, economic activity and aggregate economic growth can. ASEAN, which includes ten Southeast Asian countries, has experienced rapid economic growth and increasing integration in recent decades, making it an interesting area to study these relationships. The study covers a comprehensive period to capture trends and differences among ASEAN member states. Applying SEM with AMOS allows a detailed examination of complex relationships between important economic variables. The results show a clear link between FDI inflows, idiosyncratic risks, industry GDP performance, economic activity, and overall economic growth. More specifically, FDI inflows have a notable direct influence on idiosyncratic risks, which then impact GDP growth by sector, and the level of economic activity and ultimately contribute to economic growth trends. economy more broadly in ASEAN countries. These findings highlight the importance of understanding and effectively managing the dynamics between FDI and various economic indicators to promote sustainable economic development across ASEAN. This information can inform policymakers, investors, and stakeholders in developing targeted strategies and policies that maximize the benefits of FDI while minimizing related risks to promote strong and inclusive economic growth in the region. This study highlights the multifaceted relationships in the ASEAN economic context, emphasizing the need for strategic interventions and policy frameworks to exploit the potential of foreign investment directed at ASEAN, to the Sustainable Development Goals and long-term economic prosperity in the region.

Characteristics of the labor market in Croatia and contemporary external migration

The paper analyzes the characteristics of the labor market in Croatia, the changes in the demographic potential of the working-age population, and the structural determinants of the labor system. The movement of the number of able-bodied, active and inactive population from 2013 until today, points to a trend of decreasing the able-bodied contingent, economic activity and unemployment of the population, and an increase in employment. The analysis showed that the structural problems on the labor market in Croatia are an insufficiency of educational staff, structural unemployment, youth unemployment, and the mismatch between the supply and demand of jobs. Such characteristics of the work system influenced the movement of the determinants of external migration in Croatia, especially after 2013. Simultaneously with the strengthening of emigration, the number of immigrated persons also increases, so that from 2013 to 2022, their number amounted to about 195 thousand of mostly foreign citizens. We can establish that we are talking about free economic migrations and an increased inflow of labor, mostly unskilled workers, which makes up for the lack of domicile workforce.Structural-selective unemployment in Croatia can be analyzed on a general level according to age groups and according to education, and on a specific level, through indicators of the skills mismatch on the labor market. The total unemployment rate in Croatia has experienced a significant decline since 2013, and current unemployment is the lowest in the youngest working age, and the highest in the age over 40. Compared to 2013, the share of unemployed persons with primary and lower secondary education in Croatia is continuously decreasing, the share of unemployed persons with upper secondary and post-secondary non-tertiary education levels is slightly falling (with frequent oscillations), while the share of unemployed persons with tertiary education is increasing. Problems on the labor market in Croatia have been noticeable after the global economic crisis of 2008 and its high unemployment, and in the last ten years also in the areas with a low level of economic activity of the population and a lack of domestic labor for the functionality of certain sectors of activity.On the other hand, the structure of the emigrant contingent, in which the young and able-bodied population predominates, points to the outflow of labor force of medium and high qualification levels. The review of research on recent emigration confirms the complex conditionality of leaving Croatia, and among the main factors a group of economic ones arising from the macroeconomic situation and structural deficiencies in the labor market stands out. In addition to economic factors, other types of factors are strengthening, which is why the continuation of the emigration of the Croatian population and the immigration of the foreign population are likely to be expected. The isolated and presented indicators and trends point to the complexity of the relationship between economic and labor factors, contemporary migration patterns and demographic characteristics of the resident population, in accordance with previous theoretical and empirical knowledge.

Colombia's economic relations with China: The role of economics and politics in trade, investment, and economic agreements

AbstractOver the past two decades, many Latin America and Caribbean (LAC) countries have deepened their economic relationship with China by accepting large amounts of Chinese investments and signing up for China's Belt and Road Initiative (BRI). However, Colombia has not followed such a path. Using cross‐border data on trade, investment, and economic agreements, this article demonstrates that Colombia's under‐engagement with China is driven by Colombia's lower competitiveness in the commodities sectors, where Chinese demand for LAC products is highest. Colombia's limited competitiveness has led to lower exports to China and lower amounts of Chinese investment. The low level of bilateral economic activities has resulted in a lack of incentives for Colombia to sign economic agreements with China, as well as general public skepticism toward China and more favorable attitudes toward the United States even though this trend has been on the decline since 2016. Colombia can benefit from strengthening ties with China, without distancing itself from the United States, on issues pertaining to energy transition and the development of rural infrastructure, which will help reduce inequality and broaden export diversification in the medium to long term.

Investigating the Effect of Property Investment and Inflation on Economic Growth in Indonesia

Sustained economic growth is essential to sustainable development and overall societal prosperity. This phenomenon denotes the continuous enhancement of a nation's economic conditions over time, characterised by elevated levels of economic activity compared to preceding periods. Economic growth is typically correlated with improved societal welfare, which is a key indicator of successful economic development. However, it is imperative to consider additional factors such as income distribution to comprehensively assess the impact of growth on well-being. Establishing economic growth is fundamental to sustainable economic development and prosperity. The primary objective of this study is to investigate the short- and long-run effects of Property Investment and Inflation on economic growth in Indonesia and examine the equilibrium relationship between Property Investment and Inflation on economic growth from the short run to the long run. To achieve this objective, this study employs the autoregressive distributed lag (ARDL) Panel Model and a cointegration test to establish short- and long-run relationships. The results indicate a short-to long-run equilibrium among the variables. An additional finding is that property investment has a positive effect on economic growth in the long run but no effect in the short run. The inflation variable demonstrates a positive effect on economic growth in the long run but no effect in the short run.

Decoupling dynamics: Evaluating the relationship between ship emissions and socioeconomic progress in the Yangtze River Basin from 2007 to 2022

To investigate the decoupling relationship between inland ship emissions and regional socioeconomic development in the Yangtze River Basin, this study constructed an emissions inventory for inland ships from 2007 to 2022, based on inland shipping freight statistics and ship carbon pollution emission intensity. Additionally, the Petri-Tapio decoupling model was employed to analyze the relationship between ship carbon pollution emissions and per capita GDP. The study concluded that CO2 emissions from inland ships in the Yangtze River Basin increased from 2.418 million tons in 2007 to 10.801 million tons in 2022. In 2021, the emissions of NOx and SOx from inland ships in the Yangtze River Basin accounted for 2.27% and 0.0021%, respectively, of China's anthropogenic emissions. Despite a year-on-year increasing trend in ship emissions within the basin, significant reductions in PM and SO2 emissions were observed post-2018 due to the implementation of emission reduction policies. Furthermore, we found that economically developed areas such as Shanghai, Jiangsu, and Zhejiang had higher emissions compared to other regions, with regional ship emissions positively correlating with the level of economic activity. Decoupling analysis results indicated that most provinces in the Yangtze River Basin have not effectively decoupled ship carbon pollution emissions from GDP growth. The findings of this study provide support for the Chinese government to formulate stricter ship emission control policies while promoting the growth of the Yangtze River shipping economy.

Can toll prices changes affect the housing market? The case of the Severn crossing toll removal

PurposeSince 1966, the Severn crossing has been connecting England and Wales. In January 2018, its ownership returned to the UK Government, and this marked the start of a toll-free journey across the two countries and made commuting between the regions more affordable. In this paper, we examine the impact of the toll removal on the property market.Design/methodology/approachWe employ property-level data from the Land Registry and a difference-in-differences (DiD) empirical model for the periods 2016–2018 and 2019–2021 to capture the pre- and post-toll removal dynamics. The DiD estimation allows us to examine the causal relationship between policy changes and property prices.FindingsOur findings suggest that property prices in Newport and Monmouthshire (South East Wales) are positively affected by the policy, which results in a statistically significant increase of 5.8% more than those located in the South West England (Bristol and South Gloucestershire) region in the period 2019–2021. The impact can reach up to 13.1% for properties located in a 10 km radius of the bridge. The results indicate that the toll removal enables the ripple effect across the two markets by reducing commuting costs.Originality/valueThis is the first paper that examines the Severn Crossing case study. Its contribution is significant since we provide empirical evidence on how reduced transportation costs increase property prices in the lowest income region and have the opposite effect on the area with higher incomes and economic activity levels.

Registration shutdown of tax invoices / calculations of adjustments: prerequisites and consequences

This article covers the prerequisites and consequences of introducing a mechanism for the registration shutdown of tax invoices / calculations of adjustments. In fact, any innovations related to the administration of taxes and fees in the future have both negative and positive consequences for the state and business. That is why timely identification of negative consequences and shortcomings helps in the operational research and improvement of tax administration mechanisms, in order to increase the level of revenues to the state budget, reduce the level and risk of corruption and tax evasion, increase the level of business activity of businesses, as well as in order to prevent future scaling and generate concomitant negative consequences for the economy and budget of the country as a whole. We have studied current publications and articles of modern scientists and practitioners related to the administration of value-added tax. An assessment of the effectiveness of the current mechanism for the registration shutdown of tax invoices / calculations of adjustments is given. The main problems and incomplete development of the current procedure for the registration shutdown of tax invoices / calculations of adjustments, administrative and judicial appeals against decisions of regulatory authorities are highlighted. The consequences of introducing a mechanism for the registration shutdown of tax invoices / calculating adjustments on the level of economic activity of businesses, the judicial system of Ukraine and the tax system as a whole are studied. Based on the conducted research, we provided recommendations on ways to improve the existing system of value-added tax administration in the context of the mechanism for the registration shutdown of tax invoices / calculations of adjustments. In addition, options were proposed for combining electronic document management systems, tax audit, as additional monitoring tools for the electronic value-added tax administration service.

Demand and distribution in a dynamic spatial panel model for the United States: Evidence from state‐level data

AbstractWe estimate a modified demand‐and‐distribution system for the 48 contiguous US states and the District of Columbia (DC) employing dynamic spatial panel data for 1980–2019. We allow for endogenous regressors, test for the presence, significance, and magnitude of spatial spillovers, and estimate immediate and cumulative effects on our endogenous variables of interest. Without testing for spatial dependence and spillovers, we estimate that output growth and capacity utilization in the sample US states and DC rise in response to an increase in their own wage share. When we test for spatial dependence and spillovers as required by the state‐level nature of the data, and consider that the functional distribution of income and the level of economic activity are jointly determined, we estimate that a higher state wage share raises output growth in the own state and the neighboring states. Yet the effect of a change in the state wage share on capacity utilization in the own state and the neighboring states is not statistically significant. Meanwhile, a higher state output growth raises the wage share in the own state, but its impact on the wage share in the neighboring states is not statistically significant. A higher state capacity utilization raises the wage share in the own state, yet it reduces the wage share in the neighboring states.

Carbon Monitor Power-Simulators (CMP-SIM v1.0) across countries: a data-driven approach to simulate daily power generation

Abstract. The impact of climate change on power demand and power generation has become increasingly significant. Changes in temperature, relative humidity, and other climate variables affect cooling and heating demand for households and industries and, therefore, power generation. Accurately predicting power generation is crucial for energy system planning and management. It is also crucial to understand the evolution of power generation to estimate the amount of CO2 emissions released into the atmosphere, allowing stakeholders to make informed plans to reduce emissions and to adapt to the impacts of climate change. Artificial intelligence techniques have been used to investigate energy-demand-side responses to external factors at various scales in recent years. However, few have explored the impact of climate and weather variability on power demand. This study proposes a data-driven approach to model daily power demand provided by the Carbon Monitor Power project by combining climate variables and human activity indices as predictive features. Our investigation spans the years 2020 to 2022 and focuses on eight countries or groups of countries selected to represent different climates and economies, accounting for over 70 % of global power consumption. These countries include Australia, Brazil, China, the European Union (EU), India, Russia, South Africa, and the United States. We assessed various machine-learning regressors to simulate daily power demand at the national scale. For countries within the EU, we extended the analysis to one group of countries. We evaluated the models based on key evaluating metrics: coefficient of determination (R2), mean absolute error (MAE), root mean squared error (RMSE), and median absolute error (MedAE). We also used the models to identify the most influential variables that impact power demand and determine their relationship with it. Our findings provide insight into variations in important predictive features among countries, along with the role played by distinct climate variables and indicators of the level of economic activity, such as weekends and working days, vacations and holidays, and the influence of COVID-19.

An Analysis of the Relationship between Business Confidence and Macroeconomic Factors: Türkiye Case

Investor sentiment plays an important role in the all level of economic activities. Confidence as an indicator of investor sentiment has become an important and interesting concept in recent years. Confidence indicators are a way in assessing economic developments in the short term. The aim of this study is to analyze the long and short term relationship between the Real Sector Confidence Index and macroeconomic/financial variables for the period of January 2007 – December 2021. The Johansen Cointegration Test results prove a long-term cointegration relationship. Vector Error Correction Models for both macroeconomic and financial variables are statistically significant at the 5% level. In the short run, Manufacturing Capacity Utilization Ratio, Official Reserves, Domestic Debt Stocks, Real Exchance Rate, US Dollar/TRL Buying Rate, Non-Residents’ Stock Portfolio and Volatility Index have a statistically significant effect on the changes in Real Sector Confidence Index. Thus, this study informs investors to predict the effects of changes in the confidence index on financial instruments bilaterally and contribute to their investment decision.

Brazilian Fiscal Policy and Its Procyclical Nature: A Long-Term Analysis

Fiscal policy should be contractionary during economic expansion and expansionary during recessions. The objective of this article is to investigate the nature of long-term discretionary fiscal policy in Brazil in relation to the level of economic activity and the terms of trade. A fiscal policy variable without cyclical effects was chosen, and the results of the cointegration analysis indicate that long-term fiscal policy is destabilizing; this findings parallels those in the literature. However, in regard to trade cycles, this policy prevents their amplification.

Социальные риски достижения устойчивого развития Арктического региона

The sustainable development of circumpolar countries is of great importance for the whole world, because the Arctic Region is currently experiencing an unprecedented level of economic activity. From the perspective of the concept of sustainable development, the intensification of industrial activity in the Arctic region makes the issues of achieving long-term environmental and social sustainability for local communities relevant. Despite the fact that the Arctic countries, especially the countries of Northern Eu-rope, are leaders in achieving the UN Sustainable Development Goals, additional attention is needed to coordinate efforts to achieve them at all levels of administrative-territorial management. The relevance of our study is determined by the need to overcome the challenges and threats to the sustainable development of the Arctic territories of circumpolar countries. The aim of the study was to analyze the social risks of achieving sustainable development of the Arctic region. The methodological basis of the study was the system approach, methods of structural-historical and comparative-geographical analysis. It was substantiated that social risks in achieving sustainable development in the Arctic region are limited access to educational services; social tension in the labor markets, produced by professional and qualification imbalances of labor demand and supply and problems of youth employment; child poverty and poverty of the indigenous population. The scientific novelty of the research is in substantiating the social risks that pose a threat to the sustainable development of the Arctic region. The prospects for further research are conditioned by the need to solve urgent socio-economic and managerial problems associated with the sustainable development of the Arctic region.

골관절염 여성노인의 건강관련 삶의 질 영향요인

This research investigates factors impacting the health-related quality of life in elderly women with osteoarthritis. The study surveyed 1,855 participants using National Health and Nutrition Examination Survey data from 2016 to 2020. Statistical analyses, conducted with SPSS/WIN 25, employed T-tests, analysis of variance (ANOVA), cross-analysis, and general linear analysis for descriptive statistics, along with Bonferroni post-hoc tests. Correlations between variables and the quality of life in elderly women with osteoarthritis were determined through correlation coefficients. Additionally, factors influencing the quality of life were analyzed using multiple regression analysis with general linear models. The study revealed significant differences in the quality of life based on demographic such as age, residence, marital status, education level, economic activity, depression, subjective health status, activity limitation, stress perception, smoking, body mass index, exercise, and aerobic activity. Similarly, there were statistically significant differences in the quality of life based on health-related characteristics, including age, residence, marital status, education level, economic activity, depression, subjective health status, activity limitation, stress perception, smoking, body mass index, exercise, and aerobic activity. The average quality of life score for participants was 0.82±0.18, with notable correlations found with age, subjective health status, and stress perception. Factors influencing health-related quality of life included having a spouse, higher household income, engagement in economic activity, lower age, and lower stress levels, as well as higher subjective health status. The model's explanatory power was 36.5%. Based on these findings, the study underscores the necessity for comprehensive and individualized nursing intervention programs.