Search Results (1,719)

This study estimates the prevalence of co-use of alcohol and cannabis, assesses the sociodemographic risk factors of co-use, and examines the associations between mental health and heavy episodic drinking (HED) and alcohol–cannabis co-use in Canada during the early years of the COVID-19 pandemic. Nine successive cross-sectional surveys, held from May 2020 to January 2022, of adults (aged ≥18 years) living in Canada were pooled for 9011 participants. The prevalence of co-use was calculated across sociodemographic groups. Logistic regressions were used to assess associations. Alcohol–cannabis co-use was associated with a greater likelihood of engaging in HED and experiencing symptoms of anxiety, depression, and loneliness. The prevalence of co-use of alcohol was different across sociodemographic groups. The highest prevalence was among TGD people (35.5%), followed by individuals aged 18–39 years (14.5%). Additionally, being TGD (aOR = 3.61, 95% CI 2.09–6.25), separated/divorced/widowed (aOR = 1.60, 95% CI 1.23–2.07), living in an urban area (aOR = 1.26, 95% CI 1.07–1.56), and having a high household income (aOR = 1.41, 95% CI 1.09–1.82) increased the likelihood of reporting alcohol–cannabis co-use. These findings underscore the fact that developing public health and clinical interventions for preventing and treating excessive alcohol or cannabis use must consider both alcohol and cannabis use patterns and should be tailored to the highest-risk TGD and young adults. Full article

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

Urban flooding has significantly impacted the livelihoods of households and communities worldwide. It highlights the urgency of focusing on both flood preparedness and adaptation strategies to understand the community’s perception and adaptive capacity. This study investigates the levels of risk perception, flood preparedness, and adaptive capacity, while also exploring the inter-relationships among these factors within the context of urban flooding in Malaysia. A quantitative approach was employed, involving a structured questionnaire administered to residents in flood-prone urban areas across Greater Kuala Lumpur, Malaysia. A total of 212 responses were analysed using descriptive statistics, categorical index classification, and Spearman correlation analysis. The findings indicate that residents generally reported high levels of risk perception and preparedness, although adaptive capacity exhibited greater variability, with a mean score of 3.97 (SD = 0.64). Positive associations were found among risk perception, flood preparedness, and adaptive capacity. This study contributes to the existing knowledge by providing evidence on community resilience and highlighting key factors that can guide flood management policies and encourage adaptive planning at the community level. Full article

Background/Objectives: Dietary patterns have changed over time, characterising a process of nutritional transition that reflects socioeconomic and demographic inequalities among different populations. This study assessed changes in dietary consumption patterns and the associated social determinants, comparing two time periods in a sample of individuals from a state in the Northeast Region of Brazil. Methods: Data from the 2008–2009 and 2017–2018 Household Budget Survey for the state of Paraíba were analysed, totalling 951 and 1456 individuals, respectively. Foods were categorised according to the NOVA classification and compared based on sociodemographic and economic variables. To determine the factors that most strongly explain the contribution of each NOVA food group to the diet, beta regression analysis was conducted. Results: Differences were observed between the two periods regarding the dietary contribution of the NOVA food groups, with a decrease in consumption of unprocessed foods and an increase in ultra-processed foods. Living in urban areas, being an adolescent, and having an income above the minimum wage were associated with reduced intake of unprocessed foods in both periods. Additionally, being an adolescent and having more than eight years of schooling were associated with higher consumption of ultra-processed foods. Conclusions: The population under study showed changes in food consumption, reflecting a transition process that is occurring unevenly across socioeconomic and demographic groups, thereby reinforcing social inequalities. These findings can guide priorities in food and nutrition policies, highlighting the need for intervention studies to evaluate the effectiveness of such actions. Full article

The growth of rural residents’ disposable income is essential for narrowing the income gap between urban and rural areas and promoting integrated development. This study explores how China’s National Main Functional Zoning Plan influences rural household income through its regulatory impact on construction land expansion. Using data from county−level administrative units across China, the research identified the construction land regulation index as a key mediating variable linking zoning policy to changes in household income. By shifting the analytical perspective from a traditional urban–rural classification to a framework aligned with the National Main Functional Zoning Plan, the study reveals how spatial planning tools, particularly differentiated land quota allocations, influence household income. The empirical results confirm a structured causal chain in which zoning policy affects land development intensity, which in turn drives rural income growth. This relationship varies across different functional zones. In key development zones, strict land control limits income potential by constraining land supply. In main agricultural production zones, moderate regulatory control enhances land use efficiency and contributes to higher income levels. In key ecological function zones, ecological constraints require diverse approaches to value realization. The investigation contributes both theoretical and practical insights by elucidating the microeconomic effects of national spatial planning policies and offering actionable guidance for optimizing land use regulation to support income growth tailored to regional functions. Full article

Residential green space is an important component of urban green space and one of the major indicators for evaluating the quality of a residential community. Traditional indicators such as the green space ratio only consider the relationship between green space area and total area of the residential community while ignoring the difference in the amount of green space enjoyed by household residents in high-rise and low-rise buildings. Therefore, it is meaningful to estimate household green space and its spatial distribution in residential communities. However, there are frequent difficulties in obtaining specific green space area and household number through ground surveys or consulting with property management units. In this study, taking a composite residential community in Chongqing, China, as the study site, we first employed a five-lens drone to capture its oblique RGB images and generated the DOM (Digital Orthophoto Map). Subsequently, the green space area and distribution in the entire residential community were extracted from the DOM using VDVI (Visible Difference Vegetation Index). The YOLACT (You Only Look At Coefficients) instance segmentation model was used to recognize balconies from the facade images of high-rise buildings to determine their household numbers. Finally, the average green space per household in the entire residential community was calculated to be 67.82 m², and those in the high-rise and low-rise building zones were 51.28 m² and 300 m², respectively. Compared with the green space ratios of 65.5% and 50%, household green space more truly reflected the actual green space occupation in high- and low-rise building zones. Full article

This study investigates the factors influencing school trip mode choice among senior high school students in the Chiang Rai urban area, Chiang Rai, Thailand, under normal and adverse weather conditions. Utilizing data from 472 students across six extra-large urban schools, a Multinomial Logit (MNL) regression model was applied to examine the effects of socio-demographic attributes, household vehicle ownership, travel distance, and spatial variables on mode selection. The results revealed notable modal shifts during adverse weather, with motorcycle usage decreasing and private vehicle reliance increasing, while school bus usage remained stable, highlighting its role as a resilient transport option. Car ownership emerged as a strong enabler of modal flexibility, whereas students with limited access to private transport demonstrated reduced adaptability. Additionally, increased waiting and travel times during adverse conditions underscored infrastructure and service vulnerabilities, particularly for mid-distance travelers. The findings suggest an urgent need for transport policies that promote inclusive and climate-resilient mobility systems, particularly in the context of Chiang Rai, including expanded school bus services, improved first-mile connectivity, and enhanced pedestrian infrastructure. This study contributes to the literature by addressing environmental variability in school travel behavior and offers actionable insights for sustainable transport planning in secondary cities and border regions. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

Accurate forecasting of household waste generation is essential for sustainable urban planning and the development of data-driven environmental policies. Conventional statistical models, while simple and interpretable, often fail to capture the nonlinear and multidimensional relationships inherent in waste production patterns. This study proposes a machine learning-based regression framework utilizing Random Forest and XGBoost algorithms to predict annual household waste generation across four metropolitan regions in South Korea Seoul, Gyeonggi, Incheon, and Jeju over the period from 2000 to 2023. Independent variables include demographic indicators (total population, working-age population, elderly population), economic indicators (Gross Regional Domestic Product), and regional identifiers encoded using One-Hot Encoding. A derived feature, elderly ratio, was introduced to reflect population aging. Model performance was evaluated using R², RMSE, and MAE, with artificial noise added to simulate uncertainty. Random Forest demonstrated superior generalization and robustness to data irregularities, especially in data-scarce regions like Jeju. SHAP-based interpretability analysis revealed total population and GRDP as the most influential features. The findings underscore the importance of incorporating economic indicators in waste forecasting models, as demographic variables alone were insufficient for explaining waste dynamics. This approach provides valuable insights for policymakers and supports the development of adaptive, region-specific strategies for waste reduction and infrastructure investment. Full article

This study assesses the effects of the COVID-19 pandemic on catastrophic health expenditures and income inequality in Benin. A microsimulation was calibrated to estimate the impact of the pandemic under three different shock scenarios: low, moderate, and severe. The analysis relies on secondary data from household living condition surveys. The results indicate that the COVID-19 crisis would lead to a significant average income loss of up to 20% and income inequality, while the number of households with catastrophic health expenditures would increase by 4%. More importantly, the findings reveal heterogeneous impacts across households, with urban residents, younger individuals, more educated households, and male-headed households experiencing the greatest income decline. These findings underscore the need for targeted health coverage and employment policies to better protect vulnerable populations in Benin in the face of future shocks. Full article

This article examines the relationship between human capital accumulation, household income, and shared prosperity using 2005–2018 household surveys in Cameroon, Ethiopia, Kenya, Nigeria, and Uganda. Human capital is found to be positively and significantly correlated with household wellbeing in all five nations. Health’s indirect benefits in Cameroon, Ethiopia, and Kenya augment its direct benefits. Education has monotonic welfare benefits from primary to tertiary levels in all countries. Human capital and labour market participation are strongly associated with household wellbeing. The equalization of human capital endowments increases income for the 40% of the least well-off groups in three of the sample countries. All countries except Uganda record a decrease in human capital deprivation over the period studied. Redistribution is associated with a reduction in human capital deprivation, although less systematically than in the growth scenario. These results suggest that sizeable reductions in human capital deprivation are more likely to be accomplished by interventions that focus on boosting general human capital outcomes than those that redistribute the human capital formation inputs. In countries with declining human capital deprivation, the within-sector interventions seem to account for this success. Substantial heterogeneity in human capital poverty exists within and across countries and between rural and urban areas. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

The objective was to evaluate the quality of an instrument to measure the experience of household water insecurity (WI) and the factors associated with the prevalence of WI in an urban area in a municipality in the Western Brazilian Amazon. A cross-sectional, population-based study was conducted to investigate 983 urban households. The Household Water Insecurity Experiences (HWISE) scale was used to measure the psychometric properties of reliability and validity. An exploratory factor analysis was conducted, and the prevalence ratio (PR, 95% CI) was calculated, considering WI as the dependent variable and the other household variables as independent variables. WI affected 46.2% (95% CI: 43.0–49.4%) of the households, independently associated with: head of the family as parent/other and presence of a child in the household. The instrument exhibited unidimensionality in the factor analyses and was considered to be both reliable and valid, as indicated by a Cronbach’s α coefficient of 0.958. Household WI is a serious public health problem in the Amazon in correlation with both social vulnerability and a lack of public services. As a preliminary approach, the scale proved to be valid and reliable. However, considering the Amazonian context, misunderstandings about some issues by respondents were identified, and further validation studies are needed to improve the intelligibility of these questions. Full article

Africa’s rapid urbanization often exceeds the capacity of governments to provide essential services and infrastructure, exacerbating structural inequalities and exposing vulnerable populations to serious health risks. This paper examines the case of Douala, Cameroon, to demonstrate that health inequities in African cities are not simply the result of urban growth but are shaped by spatial inequities, historical legacies, and systemic exclusion. Disadvantaged neighborhoods are particularly impacted, becoming epicenters of health crises. Using a mixed-methods approach combining spatial analysis, household surveys and interviews, the study identifies three key findings: (1) Healthcare services in Douala are unevenly distributed and dominated by private providers, which limits access for low-income residents. (2) Inadequate infrastructure and environmental risks in informal settlements lead to a higher disease burden and an overflow of demand into better-equipped districts, which overwhelms public health centers across the city. (3) This structural mismatch fuels widespread reliance on informal and unregulated care practices. This study positions Douala as a microcosm of broader public health challenges in rapidly urbanizing African cities. It highlights the need for integrated urban planning and health system reforms that address spatial inequalities, strengthen public health infrastructure, and prioritize equity—key principles for achieving the third Sustainable Development Goal (ensuring good health and well-being for all residents) in sub-Saharan Africa. Full article

Analyses of student mobility are typically conducted in an urban environment and are informed by socio-demographic or trip attributes. The prevailing focus is on individual modes of transport, different groups of commuters travelling to campus, students’ behavioural perceptions, and the totality of student trips. This paper starts with the identification of the determinants of student mobility that have received insufficient research attention. Utilising surveys, the study captures the mobility patterns of a sample of 1014 students and calculates their carbon footprint (CF; in kg/academic year) to assess whether the factors neglected in previous studies influence differences in the actual environmental load of student commuting. A regression analysis is employed to ascertain the significance of these factors as predictors of sustainable student mobility. This study exclusively focuses on the group of student commuters to campus and analyses the trips associated with compulsory activities at a suburban campus that is distant from the university centre and student facilities, which changes the mobility context in terms of commuting options. The under-researched factors identified in this research have not yet been quantified as CF. The findings confirm that only some of the factors neglected in previous research are statistically significant predictors of the local environmental load of student mobility. Specifically, variables such as student employment, frequency of class attendance, and propensity for ride-sharing could be utilised to forecast and regulate students’ mobility towards more sustainable patterns. However, all of the under-researched factors (including household size, region of origin (i.e., past experiences), residing at term-time accommodation while studying, and the availability of a family car) have an influence on the differences in CF magnitude in the studied campus. Full article