Search Results (131)

How to promote sustainable development and deal with the actual development demands in economic transformation through land-use planning is crucial for local governments. The urban sustainable development mainly relies on creativity and talents in the digital era, and talents are increasingly attracted by local people-oriented land use. However, the current planning ideology remains at meeting corporate and people’s basic needs rather than specific needs of talents, especially the increasingly emerging digital creatives. To promote the talent agglomeration and sustainable development through land planning, this paper uses micro-celebrities on Bilibili, an influential creative content creation platform among young people in China, as an example to study the geographical distribution of digital creative talents and its relationship with urban amenities by constructing an index system of urban amenities, comprising natural, leisure, infrastructure, and social and institutional amenities. The concept of borrowed amenities is introduced to examine the effects of amenities of surrounding cities. This study demonstrates that micro-celebrities show a stronger preference for amenities compared with other skilled talents. Meanwhile, social and institutional amenities are most crucial. Furthermore, urban leisure represented by green spaces and consumption spaces is also attractive. At the regional scale, with prefecture-level cities as units, the local talents agglomeration is also influenced by the borrowed amenities in the context of regional integration. It indicates that the local land use should consider the characteristics of the surrounding cities. This study provides strategic inspiration that a happy and sustainable city should first be people-oriented and provide sufficient space for consumption, entertainment, and interaction. Full article

Background/Objectives: Although eating disorders (EDs) affect a large portion of the population and have a significant impact on health and productivity, they are understudied in the workplace. We assessed the frequency of EDs and studied the relationship between EDs and occupational and individual factors. Methods: All workers undergoing health surveillance were invited to fill in the Eating Disorder Examination Questionnaire, short form (EDE-QS) and, before their routine medical examination that included metabolic tests, measure their level of health literacy, stress, quality of sleep, anxiety, depression, and happiness. Out of a total of 2085 workers, 1912 (91.7%) participated. Results: Suspected EDs affected 4.9% (CI95% 3.9; 5.9) of workers, with no notable difference in gender (5.3% CI95% 4.1; 6.7 in female workers vs. 4.2%, CI95% 2.9; 5.9 in male). Cases were significantly associated with trauma and emotional factors (anxiety, depression, unhappiness), but also with work-related stress and poor sleep quality, and negatively associated with health literacy. Using a hierarchical logistic regression model, suspected cases of EDs were significantly predicted in Model II by life trauma (OR 2.21 CI95% 1.40; 3.48, p < 0.001) and health literacy (OR 0.94 CI95% 0.90; 0.98, p < 0.001), in Model III also by work-related stress (OR 2.57 CI95% 1.68; 3.94, p < 0.001), and in Model IV by depression (OR 1.19 CI95% 1.02; 1.38, p < 0.05) and happiness (OR 0.88 CI95% 0.78; 0.99, p < 0.05). An association was also found between EDs and overweight, obesity, increased abdominal circumference, hypercholesterolemia, hypertriglyceridemia, hyperglycemia, arterial hypertension, atherogenic index of plasma, and metabolic syndrome. Conclusions: The workplace is an ideal setting for the prevention of EDs and their consequences. Occupational health intervention should promote health literacy, improve sleep quality, and reduce work-related stress. Full article

Happiness is defined as well-being and contentment with life. The growing imperative to evaluate well-being beyond economic growth alone has led to the formulation of holistic indices that better reflect quality of life and sustainable development goals. This has resulted in the emergence of the Happiness Score (HS), which adopts a more holistic and human-centred perspective on development and well-being. The present study takes the Happiness Score as a basis for the identification of some of the main determinants of happiness in an empirical and data-driven perspective. To this end, data from 145 countries was analysed, using statistical methodologies such as Generalised Linear Models (GLM), Principal Component Analysis (PCA), fuzzy set Qualitative Comparison Analysis (fsQCA) and the decision tree machine learning approach. A range of indices were considered to translate the reality of countries in different socio-economic dimensions, the level of development of each country, and the continent to which it belongs. The African continent demonstrates substantial disparities across virtually all variables and is frequently associated with the most unfavourable values for each index. The indicators that exerted the most profound influence on happiness were identified as the freedom to make life choices, literacy rate, and Gross Domestic Product (GDP) per capita. These results inform policy strategies aligned with sustainable development, emphasising that enhancing happiness requires multidimensional action beyond economic indicators—particularly in low- and middle-income countries. Full article

The relationship between income and subjective well-being (SWB) has been widely studied. While previous research has shown that the correlation between income and SWB is not always strong, there is limited research examining how the choice of SWB index influences this relationship. Drawing on survey data collected from 32 countries between 2015 and 2017, this study explores how the income–SWB relationship varies across different SWB indices. The dataset encompasses both developed and developing nations. We analyzed six types of SWB indices documented in the literature—covering a broader range than is typically included—and conducted comparative analyses. To account for the possibility of a nonlinear relationship between income and these SWB measures, we used a semiparametric approach by applying generalized additive models. Our findings show that these six indices can be categorized into three groups: (1) mental health and affect balance, (2) subjective happiness and eudaimonia, and (3) life satisfaction and the Cantril Ladder. These results underscore the significant impact that the selected SWB index can have on the income–SWB relationship. While economic development is often assumed to enhance SWB, our analysis reveals that this relationship does not hold consistently across all SWB indicators. In particular, certain indicators show little or no improvement in well-being despite increasing income levels, suggesting the presence of excessive or inefficient consumption that fails to contribute to genuine human flourishing. These findings challenge the conventional growth-centric paradigm and call for a deeper societal and academic inquiry into what constitutes “true prosperity.” From a sustainability perspective, aligning economic progress with authentic improvements in well-being is essential. This requires not only more careful selection and interpretation of SWB metrics, but also a broader re-evaluation of consumption patterns and policy goals to ensure that future development contributes meaningfully to human and ecological well-being. Full article

This article presents an innovative methodology for enhancing statistical databases as reliable sources of information. The study leverages data from “Big Data of the Modern Global Economy: A Digital Platform for Data Mining—2020”, which serves as a digital tool designed to predict economic development at both global and national levels, particularly in the context of the COVID-19 crisis and its aftermath. Utilizing a dataset focused on the G7 and BRICS nations as a case study, we assemble forecasts for several key indicators: the Digital Competitiveness Index, Global Innovation Index, Human Development Index, Gross Domestic Product (GDP), Economic Growth Rate, GDP per Capita, Quality of Life Index, Happiness Index, and Sustainable Development Index for 2021. Additionally, we conducted a plan-fact analysis. The accuracy of the post-pandemic economic recovery forecast is validated through comparison with actual data. Furthermore, this research provides statistical analyses and forecasts to minimize uncertainty during crises, considering the interconnected nature of climate change and financial factors inherent in these crises. Full article

Welfare quality is usually a stochastic outcome, as attempts at improving social welfare cannot be predicted in advance. The advances in stock market participation conclude that equity market performance is able to reflect investors’ mass reactions and therefore can fairly reflect the empiricism of welfare quality. In this paper, the pillars of the Happy Planet Index (hereinafter HPI) are used as proxies for countries’ welfare quality. The data cover 57 countries where equity markets exist over the annual period of 2006–2020. The results indicate that (a) the three pillars of HPIs have historical positive impacts on market capitalization and stock turnover; (b) stochastically, life satisfaction has an expected positive impact on market capitalization and stock turnover; (c) firms located in high (low) HPIs, life satisfaction, and life expectancy have significant (insignificant) stochastic impacts on market capitalization; and (d) the historical ecological footprints have positive impacts on market capitalization and stock turnover, whereas stochastic impacts are statistically insignificant. Full article

This study aims to compare the accuracy performances of different machine learning algorithms (Logistic Regression, Decision Tree, Support Vector Machines (SVMs), Random Forest, Artificial Neural Network, and XGBoost) using World Happiness Index data. The study is based on the 2024 World Happiness Report data and employs indicators such as Ladder Score, GDP Per Capita, Social Support, Healthy Life Expectancy, Freedom to Determine Life Choices, Generosity, and Perception of Corruption. Initially, the K-Means clustering algorithm is applied to group countries into four main clusters representing distinct happiness levels based on their socioeconomic profiles. Subsequently, classification algorithms are used to predict the cluster membership and the accuracy scores obtained serve as an indirect measure of the clustering quality. As a result of the analysis, Logistic Regression, Decision Tree, SVM, and Neural Network achieve high accuracy rates of 86.2%, whereas XGBoost exhibits the lowest performance at 79.3%. Furthermore, the practical implications of these findings are significant, as they provide policymakers with actionable insights to develop targeted strategies for enhancing national happiness and improving socioeconomic well-being. In conclusion, this study offers valuable information for more effective classification and analysis of World Happiness Index data by comparing the performance of various machine learning algorithms. Full article

Taking Yunyu New Village in Nanyang City, a typical newly built resettlement area of the South-to-North Water Diversion Project of China, as an example, this paper tries to construct a health environment evaluation index system for the resettlement area and determines the priority and content of residential environment renovation in the resettlement area through residents’ health satisfaction evaluation and IPA analysis. The results revealed that six factors, namely, winter insulation, summer heat insulation, quality of domestic drinking water, indoor natural light environment, humanized design, and architectural plane function design, need to be renovated first. For the indoor environment, which is the focus of renovation, the light and heat environments were evaluated via field measurements and simulation experiments. The results show that the indoor comfort, daylighting, and energy savings of the surveyed buildings all fail to meet Chinese building design standards. Corresponding optimization strategies for indoor ventilation, thermal insulation performance of the envelope structure, and window wall ratio are proposed and verified via relevant software simulations and immigrants’ wishes. For the outdoor environment, we investigate the living habits and renovation needs of immigrants from the aspects of public space and courtyard space in the resettlement area and propose corresponding optimization strategies. The results of this research can help enhance the sense of gain and happiness of immigrants in the resettlement and provide a reference for improving the living environment of the same type of immigrant resettlement area. Full article

Objective: The objective of this study is to gain insights into the influence of income on the body mass index (BMI) locus in the elderly population. Methods: The Chinese Longitudinal Healthy Longevity and Happy Family Study (CLHLS-HF) was included at baseline (2008) for participants aged 65 years and older. The total number of participants analyzed in this study was 7555. A population-based trajectory model (GBTM) was used. The economic income level was an independent variable and adjusted for age, gender, ethnicity, education, marriage, and physical activity (Model 1), and the baseline BMI value was added in Model 2, with a quadratic of the income added in Model 3. A sensitivity analysis was adopted. Results: Three BMI trajectory groups were identified using GBTM and were labeled as “overweight”, “normal”, and “obesity”. After adjusting for covariates (Model 1), with the increase in economic income, the risk of the elderly transitioning into the overweight trajectory group and the obesity trajectory group was relatively increased. When the baseline BMI values were adjusted for Model 2, the effect of economic income on the overweight and obesity trajectories was enhanced. A sensitivity analysis was performed, and it was found that the result of the positive impact of economic income on the BMI trajectory group was robust. Conclusions: The higher the income, the greater the risk of Chinese elderly individuals developing the overweight or obesity trajectory. It is suggested that elderly individuals with higher economic income especially need interventions and nutrition education to help them acquire nutrition knowledge for a healthy lifestyle. The positive impact of economic income on the BMI trajectories of the elderly provides further directions for preventing and controlling obesity in the elderly. Full article

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication. While many studies suggest that individuals with ASD struggle with emotion processing, the association between emotion processing and autistic traits in non-clinical populations is still unclear. We examine whether neurotypical adults’ facial emotion recognition and expression imitation are associated with autistic traits. We recruited 32 neurotypical adults; each received two computerized tasks, the Dynamic Emotion Recognition and Expression Imitation, and two standardized measures: the Chinese version AQ and the Twenty-Item Prosopagnosia Index (PI-20). Results for the dynamic emotion recognition showed that happiness has the highest mean accuracy, followed by surprise, sadness, anger, fear, and disgust. For expression imitation, it was easiest to imitate surprise and happiness, followed by disgust, while the accuracy of imitating sadness, anger, and fear was much lower. Importantly, individual AQ scores negatively correlated with emotion recognition accuracy and positively correlated with PI-20. The AQ imagination, communication sub-scores, and PI-20 positively correlated with the expression imitation of surprise. In summary, we found a significant link between recognizing emotional expressions and the level of autistic traits in non-clinical populations, supporting the concept of broader autism phenotype. Full article

This study examines the intricate relationship between national happiness and sustainability by analyzing data from the 2024 World Happiness Report (WHR) and the Sustainable Development Goal (SDG) Index across 74 countries. Employing multidimensional scaling (MDS) and K-means clustering, we investigate the interplay of economic, social, and environmental factors that contribute to subjective well-being. Our results indicate that high-income countries, particularly those characterized by secular–rational values, tend to achieve elevated scores in both happiness and sustainability. In contrast, lower-income nations exhibit diverse cultural value systems that significantly influence their happiness and sustainability outcomes. This analysis identifies distinct clusters of countries with unique governance and cultural profiles, underscoring the inadequacies of traditional economic indicators in measuring societal well-being. By integrating sustainability metrics into happiness assessments, we propose a comprehensive framework for understanding and promoting human happiness. These findings offer critical insights for policymakers aiming to address pressing global challenges, including inequality and health disparities. Full article

This study examines the balance between technical and social focus in artificial intelligence, blockchain, cybersecurity, and privacy publications in Web of Science across countries, exploring the social factors that influence these research priorities. We use regression analysis to identify predictors of research focus and cluster analysis to reveal patterns across countries, combining these methods to provide a broader view of global research priorities. Our findings reveal that liberal democracy index, life expectancy, and happiness are significant predictors of research focus, while traditional indicators like education and income show weaker relationships. This unexpected result challenges conventional assumptions about the drivers of research priorities in digital technologies. The study identifies distinct clusters of countries with similar patterns of research focus across the four technologies, revealing previously unrecognized global typologies. Notably, more democratic societies tend to emphasize social implications of technologies, while some rapidly developing countries focus more on technical aspects. These findings suggest that political and social factors may play a larger role in shaping research agendas than previously thought, necessitating a re-evaluation of how we understand and predict research focus in rapidly evolving technological fields. The study provides valuable information for policymakers and researchers, informing strategies for technological development and international collaboration in an increasingly digital world. Full article

Oasis cities are central to the economic and social development as well as ecological sustainability in the arid region in Northwest China. This study aims to explore the balance between river health and human well-being of local residents in the Hexi River oasis, while also enhancing the effectiveness of water resource management within the basin. Utilizing the SMI-P method, we construct a ‘Happy River’ evaluation system that integrates goals, criteria, and indicators. We analyze the evaluation index system for ‘Happy River’ construction in the study area, specifically the Zhangye City section of the Heihe River Basin, and derive a comprehensive evaluation value for the ‘Happy River’ initiative. Additionally, we assess the fit attribute of the evaluation system using the coupled coordination degree model and harmony degree theory, thereby enhancing the rationality of the evaluation method and ensuring a more thorough examination process. The results indicate that from 2017 to 2021, the urban wastewater treatment rate and the degree of water quality excellence in the Zhangye City section of the Black River Basin represent the highest and lowest weights, respectively, within the evaluation system. This suggests that improving the quality of the urban water environment has emerged as the primary factor influencing the assessment of the Happy River during the construction of the Happy River and Happy Lake. Moreover, ecological health is identified as the most significant criterion in the evaluation system, serving as the main factor affecting residents’ perceptions of happiness related to rivers and lakes. Over the five-year period, the happiness level in the study area improved from “relatively happy” to “very happy”, while the coupling coordination degree increased from 0.605 to 0.687, indicating a gradual progression toward coordinated development. Simultaneously, the harmony degree rose from 0.527 to 0.601, suggesting a tendency towards a condition of basic harmony. Additionally, the happiness index increased from 76.71 to 81.97, transitioning from a state of happiness to one of very high happiness. The composite index also improved, rising from 0.459 to 0.526, which demonstrates the preliminary success of the ‘Happy River’ construction efforts in the study area. The evaluation system and model of the ‘Happy River’, along with the final results of this study, can serve as theoretical references for the development of similar initiatives in typical characteristic rivers within the arid region of Northwest China. Full article

Abundant and accessible food, energy, and water are essential to the functioning of human societies and individual health and happiness. However, growing populations, intensifying climate change, and violent instability undermine resource security. We used data from the recently updated Pardee RAND Food–Energy–Water (FEW) Index and the INFORM risk model to assess global and regional trends in resource security and relationships with the Human Development Index (HDI), internal conflict risk, and population growth. Our analysis finds that resource security has modestly improved with an average global FEW Index improvement of 2.61%, but this figure masks significant regional disparities, with several countries in Sub-Saharan Africa and South Asia regressing in terms of food and water security. We observe continued high correlations between HDI and the FEW Index (0.8664) and also find the FEW Index to be highly correlated with national income per capita (0.6547). We also find that at a global level, there is a significant negative association between trends in the FEW Index and population growth (−0.4724) during the study period, suggesting that a growing proportion of the global population is experiencing resource insecurity. Finally, our analysis suggests that several resource-insecure countries are also conflict-prone and these nations tended to do worse over the study period than similarly resource-insecure states that were internally stable. Full article

The urban living environment is a crucial determinant of the well-being and survival of city residents in modern society. Accurately evaluating the Quality of Human Settlements (QHS) and identifying its influencing factors are essential for advancing sustainable urban development. This study develops an assessment system for the Quality of Human Settlements Index (QHSI) by integrating three dimensions and 29 sub-indicators. The AHP and VIKOR methods are employed to conduct a comprehensive evaluation of the QHS while proposing a factor system of QHS-influencing indicators based on four dimensions and 29 sub-indicators. Additionally, a novel hybrid RBFNN and GARSON method is introduced to identify the importance of QHS-influencing factors. Using Wuhan, China, as a case study, the results reveal that (1) RBFNN-GARSON demonstrates robustness and generalization ability under optimal parameters, effectively revealing the inherent relationships between QHS-influencing indicators and evaluation indicators; and (2) the overall QHSI for Wuhan City is 0.724, with the importance of cultural facilities, historic district preservation, and street cleanliness identified as 0.060, 0.057, and 0.056, respectively, denoting them as the most critical factors influencing the QHS. This method is expected to provide city managers with a deeper understanding of the QHS, enabling them to formulate policies more efficiently, ultimately promoting social progress and enhancing residents’ sense of achievement and happiness. This study contributes to the advancement of sustainable urban development and residents’ well-being. Full article