Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.

Importance: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality. Objective: To investigate the association between image-based built environment and the prevalence of cardiometabolic disease in urban cities. Design, Setting, and Participants: This cross-sectional study used features extracted from Google satellite images (GSI) to measure the built environment and link them with prevalence of cardiometabolic disease. Convolutional neural networks, light gradient-boosting machines, and activation maps were used to assess the association with health outcomes and identify feature associations with coronary heart disease (CHD), stroke, and chronic kidney disease (CKD). The study obtained aerial images from GSI covering census tracts in 7 cities (Cleveland, Ohio; Fremont, California; Kansas City, Missouri; Detroit, Michigan; Bellevue, Washington; Brownsville, Texas; and Denver, Colorado). The study used census tract-level data from the US Centers for Disease Control and Prevention's 500 Cities project. The data were originally collected from the Behavioral Risk Factor Surveillance System that surveyed people 18 years and older across the country. Analyses were conducted from February to December 2022. Exposures: GSI images of built environment and cardiometabolic disease prevalence. Main Outcomes and Measures: Census tract-level estimated prevalence of CHD, stroke, and CKD based on image-based built environment features. Results: The study obtained 31 786 aerial images from GSI covering 789 census tracts. Built environment features extracted from GSI using machine learning were associated with prevalence of CHD (R2 = 0.60), stroke (R2 = 0.65), and CKD (R2 = 0.64). The model performed better at distinguishing differences between cardiometabolic prevalence between cities than within cities (eg, highest within-city R2 = 0.39 vs between-city R2 = 0.64 for CKD). Addition of GSI features both outperformed and improved the model that only included age, sex, race, income, education, and composite indices for social determinants of health (R2 = 0.83 vs R2 = 0.76 for CHD; P <.001). Activation maps from the features revealed certain health-related built environment such as roads, highways, and railroads and recreational facilities such as amusement parks, arenas, and baseball parks. Conclusions and Relevance: In this cross-sectional study, a significant portion of cardiometabolic disease prevalence was associated with GSI-based built environment using convolutional neural networks.

Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.

BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the association between machine vision-based built environment and prevalence of cardiometabolic disease in US cities. METHODS: This cross-sectional study used features extracted from Google Street View (GSV) images to measure the built environment and link them with prevalence of coronary heart disease (CHD). Convolutional neural networks, linear mixed-effects models, and activation maps were utilized to predict health outcomes and identify feature associations with CHD at the census tract level. The study obtained 0.53 million GSV images covering 789 census tracts in seven US cities (Cleveland, OH; Fremont, CA; Kansas City, MO; Detroit, MI; Bellevue, WA; Brownsville, TX; and Denver, CO). RESULTS: Built environment features extracted from GSV using deep learning predicted 63% of the census tract variation in CHD prevalence. The addition of GSV features improved a model that only included census tract-level age, sex, race, income, and education or composite indices of social determinant of health. Activation maps from the features revealed a set of neighbourhood features represented by buildings and roads associated with CHD prevalence. CONCLUSIONS: In this cross-sectional study, the prevalence of CHD was associated with built environment factors derived from GSV through deep learning analysis, independent of census tract demographics. Machine vision-enabled assessment of the built environment could potentially offer a more precise approach to identify at-risk neighbourhoods, thereby providing an efficient avenue to address and reduce cardiovascular health disparities in urban environments.

Numerical thermal assessment and theoretical analysis of horizontal-hole interlock composite insulation blocks.

In this paper, the thermal performance of 54 horizontal-hole interlocking composite insulation blocks was numerically analyzed based on the steady-state heat transfer model, the regulations were found, and prediction models for the thermal parameters of the blocks were established based on the parallel network thermal resistance model. The influence of block types and block materials on the thermal performance was studied, and it was found that the thermal performance of H-shaped interlocking insulation blocks was better than that of crossed-shaped ones, and the lower the thermal conductivity of block materials, the better the thermal performance of blocks, among which the reduction of thermal conductivity of concrete materials improved the thermal performance of blocks the most. The simulated values of thermal conductivity of H-shaped interlocking insulation blocks and thermal conductivity under the parallel network thermal resistance model were highly linearly correlated with correlation coefficients as high as 0.998 and 0.999. This finding enables the prediction models of thermal parameters of H-shaped interlocking insulation blocks to be established with high accuracy and provides an effective guide for the energy-saving design of interlocking insulation blocks wall.

Medical financial hardship between young adult cancer survivors and matched individuals without cancer in the United States.

BACKGROUND: Young adult cancer survivors face medical financial hardships that may lead to delaying or forgoing medical care. This study describes the medical financial difficulties young adult cancer survivors in the United States experience in the post-Patient Protection and Affordable Care Act period. METHOD: We identified 1009 cancer survivors aged 18 to 39 years from the National Health Interview Survey (2015-2022) and matched 963 (95%) cancer survivors to 2733 control individuals using nearest-neighbor matching. We used conditional logistic regression to examine the association between cancer history and medical financial hardship and to assess whether this association varied by age, sex, race and ethnicity, and region of residence. RESULTS: Compared with those who did not have a history of cancer, young adult cancer survivors were more likely to report material financial hardship (22.8% vs 15.2%; odds ratio = 1.65, 95% confidence interval = 1.50 to 1.81) and behavior-related financial hardship (34.3% vs 24.4%; odds ratio = 1.62, 95% confidence interval = 1.49 to 1.76) but not psychological financial hardship (52.6% vs 50.9%; odds ratio = 1.07, 95% confidence interval = 0.99 to 1.16). Young adult cancer survivors who were Hispanic or lived in the Midwest and South were more likely to report psychological financial hardship than their counterparts. CONCLUSIONS: We found that young adult cancer survivors were more likely to experience material and behavior-related financial hardship than young adults without a history of cancer. We also identified specific subgroups of young adult cancer survivors that may benefit from targeted policies and interventions to alleviate medical financial hardship.

Profound regional disparities shaping the ecological risk in surface waters: A case study on cadmium across China.

The scientific advancement of water quality criteria (WQC) stands as one of the paramount challenges in ensuring the security of aquatic ecosystem. The region-dependent species distribution and water quality characteristics would impact the toxicity of pollutant, which would further affect the derivation of WQC across regions. Presently, however, numerous countries adhere to singular WQC values. The "One-size-fits-all" WQC value for a given pollutant may lead to either "over-protection" or "under-protection" of organisms in specific region. In this study, we used cadmium(Cd) pollution in surface waters of China as a case study to shed light on this issue. This study evaluated critical water quality parameters and species distribution characteristics to modify WQC for Cd across distinct regions, thus unveiling the geographical variations in ecological risk for Cd throughout China. Notably, regional disparities in ecological risk emerged a substantial correlation with water hardness, while species-related distinctions magnified these regional variations. After considering the aforementioned factors, the variation in long-term WQC among different areas reached 84-fold, while the divergence in risk quotient extended to 280-fold. This study delineated zones of both heightened and diminished ecological susceptibility of Cd, thereby establishing a foundation for regionally differentiated management strategies.

Sex-specific heart failure burden across the United States: Global burden of disease 1990-2019.

BACKGROUND: Heart failure (HF) has unique aspects that vary by biological sex. Thus, understanding sex-specific trends of HF in the US population is crucial to develop targeted interventions. We aimed to analyze the burden of HF in female and male patients across the US, from 1990 to 2019. METHODS: Using the Global Burden of Disease (GBD) study data from 2019, we performed an analysis of the burden of HF from 1990-2019, across US states and regions. The GBD defined HF through studies that used symptom-based criteria and expressed the burden of HF as the age-adjusted prevalence and years lived with disability (YLDs) rates per 100,000 individuals. RESULTS: The age-adjusted prevalence of HF for the US in 2019 was 926.2 (95% UI [799.6, 1,079.0]) for females and 1,291.2 (95% UI [1,104.1, 1,496.8]) for males. Notably, our findings also highlight cyclic fluctuations in HF prevalence over time, with peaks occurring in the mid-1990s and around 2010, while reaching their lowest points in around 2000 and 2018. Among individuals >70 years of age, the absolute number of individuals with HF was higher in females, and this age group doubled the absolute count between 1990 and 2019. Comparing 1990-1994 to 2015-2019, 10 states had increased female HF prevalence, while only 4 states increased male prevalence. Overall, Western states had the greatest relative decline in HF burden, in both sexes. CONCLUSION: The burden of HF in the US is high, although the magnitude of this burden varies according to age, sex, state, and region. There is a significant increase in the absolute number of individuals with HF, especially among women >70 years, expected to continue due to the aging population.

Spatiotemporal variability of PAHs and their derivatives in sediments of the Laizhou Bay in the eastern China: Occurrence, source, and ecological risk assessment.

To understand the pollution status and risk levels in the Laizhou Bay, the spatiotemporal distribution, source, and ecological risk of 16 polycyclic aromatic hydrocarbons (PAHs) and 20 substituted PAHs (SPAHs) were studied in surface sediments in 2022. The findings indicated significant seasonal differences in the concentrations of PAHs and SPAHs under the influences of precipitation, temperature, light, and human activities, with higher storage levels in summer than in spring, and there was also a spatial distribution trend of estuary > coast > offshore. 2-Nitrofluorene (2-NF) and 2-methylnaphthalene (2-MN) were the most abundant components of SPAHs in both spring and summer, with levels of 21.44 ng/g and 17.89 ng/g in spring, 43.22 ng/g and 25.51 ng/g in summer, respectively. The results of the diagnostic ratio and principal component analysis - multiple linear regression identified sources of PAHs and SPAHs as combustion sources, including petroleum, coal, and biomass. The risk level of PAHs was low-to-moderate according to the toxicity equivalent quotient (TEQ) and risk quotient. A novel calculation method based on TEQ was proposed to assess the ecological risk of SPAHs, and the results indicated that the risk level of SPAHs was moderate-to-high.

Water quality variation and driving factors quantitatively evaluation of urban lakes during quick socioeconomic development.

Rapid urbanisation has caused a significant impact on the ecological environment of urban lakes in the world. To maintain the harmonious development of urban progress and water quality, it is essential to evaluate water quality variation and explore the driving factors quantitatively. A comprehensive evaluation method with cluster analysis and Kriging interpolation was used to explore the spatiotemporal variation in a typical urban lake in China, Chaohu Lake, from 2011 to 2020. The correlation between water quality and socioeconomic factors was evaluated by Pearson correlation analysis. Results indicated that: total phosphorus (TP) and total nitrogen (TN) were the key pollution parameters of Chaohu Lake. The pollution situation was gradually improving, however, and the improvement in chemical oxygen demand (COD) is more evident due to anthropogenic control. The spatial heterogeneity of water quality in Chaohu Lake is remarkable, and the water quality is poor in the west but better in the east. Natural attributes of lakes and external load were the main reasons for the spatial heterogeneity. The western residential areas of Chaohu Lake Basin (CLB) are concentrated, and a large amount of industrial and domestic sewage exacerbates water pollution in the west of tributaries. In contrast, the implementation of water environmental governance policies in recent years has alleviated water pollution. From 2011 to 2020, water quality has improved by 23%-35% in the west and 7%-14% in the east. This study provided a framework for quantitatively assessing water quality variation and its driving forces in urban lakes.

Experience of Racial Discrimination was Associated with Psychological Distress and Worsening Sex Life Among Adult Americans During COVID-19.

The recent escalation of racism in the U.S. during the COVID-19 pandemic points to the importance of examining the association between experienced racism and sexual health. Based on data from a nationally representative survey conducted in the U.S. in October 2020 (n = 1,915), Chi-square tests and multivariable logistic regressions were estimated to examine the association between experience of racism and changes in sex life during the pandemic. We further performed a causal mediation analysis using the bootstrap technique to assess the mediating role of psychological distress in the observed association between the experience of racism and changes in sex life. Among the respondents, the proportions reporting better, worse, or no change in sex life were, respectively, 15%, 21%, and 64%. Experiencing racial discrimination during COVID-19 was significantly associated with worsening sex life (adjusted odd ratio [AOR] = 1.53; 95% confidence interval [CI] = 1.04, 2.25). Respondents with experienced racism were also more likely to report psychological distress (AOR = 1.68; 95% CI = 1.09, 2.59). About one-third (32.66%) of the observed association between experienced racism and worsening sex life was mediated through psychological distress. Addressing racism and its association with psychological distress has the potential to improve sexual health and reduce related racial and ethnic disparities.

Bio-Inspired Low-Cost Fabrication of Stretchable, Adhesive, Transparent, and Multi-Functionalized Joint Wound Dressings.

Ideal joint wound dressings should not only promote wound healing and have good mechanical properties including stretchability and adhesion but also possess functions such as sterilization or motion monitoring. The multiple characteristic requirements have greatly limited the material's alternative, resulting in research on functional joint wound dressings falling far short of market demand. Therefore, low-cost, comprehensive designs need to be developed. Herein, inspired by the spiral arteries in the endometrium, alginate-based helical fibers were introduced into polyacrylamide/gelatin (PAM-Gel) to obtain composite polymer membranes, realizing a combination of both mechanical and functional properties. Large scale (100 m) and high-throughput (10 times higher than literature) fabrication of helical microfibers were first achieved, ensuring the low cost of fiber preparation. The composite film had adequate stretchability (>300% strain), adhesion strength (14 kPa), high transparency, and good biocompatibility. The helical fibers could be easily functionalized without affecting the mechanical properties of the dressings, thus broadening the range of materials available for joint dressings. After different treatments of the helical fibers, controlled drug release and joint motion monitoring were realized. Therefore, this helical microfiber composite membrane design achieved low-cost preparation, good mechanical properties, and functionalities including healing promotion, drug release, and motion monitoring ability, demonstrating application potential.

The Health and Economic Impact of Expanding Home Blood Pressure Monitoring.

INTRODUCTION: Home blood pressure monitoring is more convenient and effective than clinic-based monitoring in diagnosing and managing hypertension. Despite its effectiveness, there is limited evidence of the economic impact of home blood pressure monitoring. This study aims to fill this research gap by assessing the health and economic impact of adopting home blood pressure monitoring among adults with hypertension in the U.S. METHODS: A previously developed microsimulation model of cardiovascular disease was used to estimate the long-term impact of adopting home blood pressure monitoring versus usual care on myocardial infarction, stroke, and healthcare costs. Data from the 2019 Behavioral Risk Factor Surveillance System and the published literature were used to estimate model parameters. The averted cases of myocardial infarction and stroke and healthcare cost savings were estimated among the U.S. adult population with hypertension and in subpopulations defined by sex, race, ethnicity, and rural/urban area. The simulation analyses were conducted between February and August 2022. RESULTS: Compared with usual care, adopting home blood pressure monitoring was estimated to reduce myocardial infarction cases by 4.9% and stroke cases by 3.8% as well as saving an average of $7,794 in healthcare costs per person over 20 years. Non-Hispanic Blacks, women, and rural residents had more averted cardiovascular events and greater cost savings related to adopting home blood pressure monitoring compared with non-Hispanic Whites, men, and urban residents. CONCLUSIONS: Home blood pressure monitoring could substantially reduce the burden of cardiovascular disease and save healthcare costs in the long term, and the benefits could be more pronounced in racial and ethnic minority groups and those living in rural areas. These findings have important implications in expanding home blood pressure monitoring for improving population health and reducing health disparities.

Disparities in Successful Discharge to the Community Following Use of Medicare Home Health by Level of Neighborhood Socioeconomic Disadvantage.

Considering the importance of social and structural support and resources in recovering health, where people reside could lead to differences in health outcome in Medicare home health care. We used the 2019 Outcome and Assessment Information Set and Area Deprivation Index to examine the association between neighborhood context and successful discharge to community among older Medicare home health care users. Based on the multivariable logistic regression (OR: 0.84; 95% CI, 0.83-0.85) and conditional logistic regression models stratified by home health agency (OR: 0.95; 95% CI, 0.94-0.95), patients living in the most disadvantaged neighborhoods were less likely to experience successful discharge to community than others. Furthermore, the predicted probability of successful discharge to community decreased as the percentage of patients from the most disadvantaged neighborhoods within a home health agency increased. Policymakers should consider using area-level interventions and supports to reduce disparities in Medicare home health care.

An Order Reduction Design Framework for Higher-Order Binary Markov Random Fields.

The order reduction method is an important approach to optimize higher-order binary Markov random fields (HoMRFs), which are widely used in information theory, machine learning and image analysis. It transforms an HoMRF into an equivalent and easier reduced first-order binary Markov random field (RMRF) by elaborately setting the coefficients and auxiliary variables of RMRF. However, designing order reduction methods is difficult, and no previous study has investigated this design issue. In this paper, we propose an order reduction design framework to study this problem for the first time. Through study, we find that the design difficulty mainly lies in that the coefficients and variables of RMRF must be set simultaneously. Therefore, the proposed framework decomposes the design difficulty into two processes, and each process mainly considers the coefficients or auxiliary variables of RMRF. Some valuable properties are also proven. Based on our framework, a new family of 14 order reduction methods is provided. Experiments, such as synthetic data and image denoising, demonstrate the superiority of our method.

Breast Cancer Screening Should Embrace Precision Medicine: Evidence by Reviewing Economic Evaluations in China.

The cost-effectiveness of conventional population-based breast cancer screening strategies (e.g. mammography) has been found controversial, while evidence shows that genetic testing for early detection of pathogenic variants is cost-effective. We aimed to review the economic evaluations of breast cancer screening in China to provide an information summary for future research on this topic. We searched the literature to identify the economic evaluations that examined breast cancer screening and testing in China, supplemented by hand-searching the reference lists of the included studies. We finally included five studies satisfying our inclusion criteria. Four articles examined mammography while the rest investigated multigene testing. The existing breast cancer screening programmes were found to be cost-effective among urban Chinese women, but one study concluded that they might cause harm to women in rural areas. Contextual factors, such as data absence, urban-rural disparity, willingness-to-pay threshold, and model design, imposed barriers to cost-effectiveness analysis. Multigene testing was found to be cost-effective and has a promising population impact among all women with breast cancer in China. Future research should investigate the cost-effectiveness of screening and identifying breast cancer through precision medicine technologies, including genetic testing, genome sequencing, cascade testing, and the return of secondary findings.

Activity Assay of Amylase and Xylanase Is Available for Quantitative Assessment of Strain Aging in Cultivated Culinary-Medicinal Morchella Mushrooms (Ascomycotina).

Strain aging has been mainly contributing to the "uncertainty" of Morchella farming. The situation calls for urgent quantitative assessment of strain aging in cultivated Morchella mushrooms. In this paper, systemic senescence of the productive strains of M. eximia, M. importuna, and M. sextelata was achieved through successive subculturing to provide subcultures with different degree of aging for further studies. Then the quantitative assessment of morel strain aging was conducted by activity assay of amylase and xylanase using dinitrosalicylic acid (DNS) method. The results suggested that both activity of amylase and xylanase decreased along with the rise of subculture times. Meanwhile, the correlation between xylanase activity and time of subculturing in the tested morel strains was higher than that of amylase assay. Consequently, assay of amylase and xylanase activity by DNS method can be used in the quantitative assessment of morel strain aging, and assay of xylanase activity is the better alternative. The work will improve the settlement of "uncertainty" in the morel industry and thus be beneficial for stable development of morel farming.

Social Determinants of Cardiovascular Health: A Longitudinal Analysis of Cardiovascular Disease Mortality in US Counties From 2009 to 2018.

Background Disparities in cardiovascular disease (CVD) outcomes persist across the United States. Social determinants of health play an important role in driving these disparities. The current study aims to identify the most important social determinants associated with CVD mortality over time in US counties. Methods and Results The authors used the Agency for Healthcare Research and Quality's database on social determinants of health and linked it with CVD mortality data at the county level from 2009 to 2018. The age-standardized CVD mortality rate was measured as the number of deaths per 100 000 people. Penalized generalized estimating equations were used to select social determinants associated with county-level CVD mortality. The analytic sample included 3142 counties. The penalized generalized estimating equation identified 17 key social determinants of health including rural-urban status, county's racial composition, income, food, and housing status. Over the 10-year period, CVD mortality declined at an annual rate of 1.08 (95% CI, 0.74-1.42) deaths per 100 000 people. Rural counties and counties with a higher percentage of Black residents had a consistently higher CVD mortality rate than urban counties and counties with a lower percentage of Black residents. The rural-urban CVD mortality gap did not change significantly over the past decade, whereas the association between the percentage of Black residents and CVD mortality showed a significant diminishing trend over time. Conclusions County-level CVD mortality declined from 2009 through 2018. However, rural counties and counties with a higher percentage of Black residents continued to experience higher CVD mortality. Median income, food, and housing status consistently predicted higher CVD mortality.

Understanding Relationships between Cultivated Land Pressure and Economic Development Level across Spatiotemporal Characteristics: Implications for Supporting Land-Use Management Decisions.

Food security is crucial to world peace. Economic development has posed a great threat to the protection of cultivated land. Considering 20 cities in the lower Yellow River (AALYR) as the study area, this study explored the spatial evolution of cultivated land pressure (CLP) and economic development from 1998 to 2018, revealing the spatiotemporal coupling characteristics of the CLP index and economic development. The main results are as follows: we discerned that CLP and economic development have an obvious spatiotemporal consistency during 1998-2018. The CLP showed a spatial pattern of overall stability, as well as local changes. Most prefecture-level cities experienced decreased significantly in CLP and improvements in food security. Overall, there were regional differences in the coupling relationships between CLP and economic development in the study area. The explanatory power of the proportion of secondary and tertiary industries were significantly higher than other driving factors. Therefore, while developing the economy rapidly, we should also protect cultivated land resources and improve the coordination level between them, which is essential to guarantee food security and a steady economic development.

Identifying pathways to religious service attendance among older adults: A lagged exposure-wide analysis.

We used prospective data (spanning 8 years) from a national sample of older U.S. adults aged > 50 years (the Health and Retirement Study, N = 13,771) to evaluate potential factors that lead to subsequent religious service attendance. We applied a lagged exposure-wide epidemiologic design and evaluated 60 candidate predictors of regular subsequent religious service attendance. Candidate predictors were drawn from the following domains: health behaviors, physical health, psychological well-being, psychological distress, social factors, and work. After rigorous adjustment for a rich set of potential confounders, we observed modest evidence that changes in some indices of physical health, psychological well-being, psychological distress, and social functioning predicted regular religious service attendance four years later. Our findings suggest that there may be opportunities to support more regular religious service attendance among older adults who positively self-identify with a religious/spiritual tradition (e.g., aid services for those with functional limitations, psychological interventions to increase hope), which could have downstream benefits for various dimensions of well-being in the later years of life.

Combination with Continual Learning Update Scheme for Power System Transient Stability Assessment.

In recent years, the power system transient stability assessment (TSA) based on a data-driven method has been widely studied. However, the topology and modes of operation of power systems may change frequently due to the complex time-varying characteristics of power systems. which makes it difficult for prediction models trained on stationary distributed data to meet the requirements of online applications. When a new working situation scenario causes the prediction model accuracy not to meet the requirements, the model needs to be updated in real-time. With limited storage space, model capacity, and infinite new scenarios to be updated for learning, the model updates must be sustainable and scalable. Therefore, to address this problem, this paper introduces the continual learning Sliced Cramér Preservation (SCP) algorithm to perform update operations on the model. A deep residual shrinkage network (DRSN) is selected as a classifier to construct the TSA model of SCP-DRSN at the same time. With the SCP, the model can be extended and updated just by using the new scenarios data. The updated prediction model not only complements the prediction capability for new scenarios but also retains the prediction ability under old scenarios, which can avoid frequent updates of the model. The test results on a modified New England 10-machine 39-bus system and an IEEE 118-bus system show that the proposed method in this paper can effectively update and extend the prediction model under the condition of using only new scenarios data. The coverage of the updated model for new scenarios is improving.

Housing Security and Settlement Intentions of Migrants in Urban China.

A huge gap remains in the urbanization rate between China and developed countries, although China has experienced a rapid growth in urbanization rate over the last decade. Critical to the future growth of urbanization is how to increase the settlement intentions of migrants. This study uses land supply for security housing as an exogeneous shock to the supply of security housing in the near future to explore how housing security is associated with intentions to settle down in destination cities of the migrant population. We found that increased land supply for security housing promotes the settlement intentions of migrants. Moreover, housing security is positively associated with permanent settlement intentions, while its relation to temporary settlement intentions is not significant. Lastly, the effect of housing security is larger for households with more housing expenditure. Our results have important theoretical and practical significance for the research on urban development and social welfare.