Search Results (282)

The National Adaptation Plan of Bangladesh identifies eleven climate-stressed zones, placing nearly 100 million people at high risk of climate-related hazards. Vulnerable groups such as the poor, floating populations, daily laborers, and slum dwellers are particularly affected. However, there is a lack of data on climate-sensitive diseases and related hospital visits in these areas. This study explored the prevalence of such diseases using the Delphi method through focus group discussions with 493 healthcare professionals from 153 hospitals in 156 upazilas across 21 districts and ten zones. Participants were selected by district Civil Surgeons. Key climate-sensitive diseases identified included malnutrition, diarrhea, pneumonia, respiratory infections, typhoid, skin diseases, hypertension, cholera, mental health disorders, hepatitis, heat stroke, and dengue. Seasonal surges in hospital visits were noted, influenced by factors like extreme heat, air pollution, floods, water contamination, poor sanitation, salinity, and disease vectors. Some diseases were zone-specific, while others were widespread. Regions with fewer hospital visits often had higher disease burdens, indicating under-reporting or lack of access. The findings highlight the need for area-specific adaptation strategies and updates to the Health National Adaptation Plan. Strengthening resilience through targeted investment and preventive measures is crucial to reducing health risks from climate change. Full article

In pursuit of the Sustainable Development Goals (SDGs)’s objective of eliminating slum cities, the government of Indonesia has initiated a survey-based slum mapping program. Unfortunately, recent observations have highlighted considerable inconsistencies in the mapping process. These inconsistencies can be attributed to various factors, including variations in the expertise of surveyors and the intricacies of the indicators employed to characterize slum conditions. Consequently, reliable data is lacking, which poses a significant barrier to effective monitoring of slum upgrading programs. Remote sensing (RS)-based approaches, particularly those employing deep learning (DL) techniques, have emerged as a highly effective and accurate method for identifying slum areas. However, the reliance on RS alone is likely to encounter challenges in complex urban environments. A substantial body of research has previously identified the merits of integrating land surface data with RS. Therefore, this study seeks to combine remote sensing imagery (RSI) with street view imagery (SVI) for the purpose of slum mapping and compare its accuracy with a field survey conducted in 2024. The city of Bandung is a pertinent case study, as it is facing a considerable increase in population density. These slums collectively encompass approximately one-tenth of Bandung City’s population as of 2020. The present investigation evaluates the mapping results obtained from four distinct deep learning (DL) networks: The first category comprises FCN, which utilizes RSI exclusively, and FCN-DK, which also employs RSI as its sole input. The second category consists of two networks that integrate RSI and SVI, namely FCN and FCN-DK. The findings indicate that the integration of RSI and SVI enhances the precision of slum mapping in Bandung City, particularly when employing the FCN-DK network, achieving an accuracy of 86.25%. The results of the mapping process employing a combination of the FCN-DK network, which utilizes the RSI and SVI, indicate the presence of 2294 light slum points and 29 medium slum points. It should be noted that the outcomes are contingent upon the methodological approach employed, the accessibility of the dataset, and the training data that mirrors the distribution of slums in 2020 and the specific degree of its integration within the FCN network. The FCN-DK model, which integrates RSI and SVI, demonstrates enhanced performance in comparison to the other models examined in this study. Full article

The efficient and precise identification of urban slums is a significant challenge for urban planning and sustainable development, as their morphological diversity and complex spatial distribution make it difficult to use traditional remote sensing inversion methods. Current deep learning (DL) methods mainly face challenges such as limited receptive fields and insufficient sensitivity to spatial locations when integrating multi-source remote sensing data, and high-quality datasets that integrate multi-spectral and geoscientific indicators to support them are scarce. In response to these issues, this study proposes a DL model (coordinate-attentive U²-DeepLab network [CAU²DNet]) that integrates multi-source remote sensing data. The model integrates the multi-scale feature extraction capability of U²-Net with the global receptive field advantage of DeepLabV3+ through a dual-branch architecture. Thereafter, the spatial semantic perception capability is enhanced by introducing the CoordAttention mechanism, and ConvNextV2 is adopted to optimize the backbone network of the DeepLabV3+ branch, thereby improving the modeling capability of low-resolution geoscientific features. The two branches adopt a decision-level fusion mechanism for feature fusion, which means that the results of each are weighted and summed using learnable weights to obtain the final output feature map. Furthermore, this study constructs the São Paulo slums dataset for model training due to the lack of a multi-spectral slum dataset. This dataset covers 7978 samples of 512 × 512 pixels, integrating high-resolution RGB images, Normalized Difference Vegetation Index (NDVI)/Modified Normalized Difference Water Index (MNDWI) geoscientific indicators, and POI infrastructure data, which can significantly enrich multi-source slum remote sensing data. Experiments have shown that CAU²DNet achieves an intersection over union (IoU) of 0.6372 and an F1 score of 77.97% on the São Paulo slums dataset, indicating a significant improvement in accuracy over the baseline model. The ablation experiments verify that the improvements made in this study have resulted in a 16.12% increase in precision. Moreover, CAU²DNet also achieved the best results in all metrics during the cross-domain testing on the WHU building dataset, further confirming the model’s generalizability. Full article

Background—Against childhood lead poisoning, removing lead exposure is the main measure, but how to do it effectively has not been fully established. Our objective was to determine the impact of several interventions (education, housing remediation, and relocation) on children’s blood lead levels. Methods—A historical cohort of childhood lead poisoning was drawn in Marseille, France, from 2011 to 2018. A generalized mixed model was developed to study the kinetics of blood lead levels. Results—We included 151 children, with 56% living in legal substandard housing and others living in slums. Medical follow-up (median: 612 days) included 492 blood samples. In legal substandard housing, blood lead level decrease was significantly associated with every intervention. In slums, blood lead level decrease was significantly associated with housing relocation and education, although to a lesser extent. Conclusions—Every intervention contributed to reducing blood lead levels in substandard housing. Educational intervention is rapidly implemented. Housing remediation follows a long-lasting but effective legal procedure. Some families get housing relocation, depending on their financial resources or whether they are eligible for social housing. In slums, access to legal housing is the most effective against environmental exposure and education has a wider impact on health literacy. Full article

Objective: Malnutrition remains a global challenge to child development, with urban slums in India experiencing high rates of protein deficiency. This study aimed to evaluate the effectiveness of a low-cost, fish bycatch-derived protein supplement in supporting catch-up growth among malnourished children. Methods: Using the Sustainable Community Partnership and Empowerment (SCOPE) model, we implemented a 90-day intervention with daily 10 g of Advanced Protein Powder (APP), produced from underutilized fish bycatch. Forty-six malnourished children (aged 3–6) from Bengaluru slums were randomized into a Control group receiving caloric support or an APP supplement group. Growth indicators, cognition, and caregiver perspectives were assessed. Results: Children receiving the APP supplement showed a significant increase in the weight-for-age percentile (underweight), rising by 7.59%, compared to 0.59% in the Control group (p = 0.02185). Muscle growth, measured by mid-upper arm circumference, also improved significantly in the APP Group (p < 0.05). In the first month, APP supplementation led to a significant height gain of 1.86 cm (p < 0.001), whereas the Control group showed no change (p > 0.05). Additionally, APP supplementation enhanced cognitive function, visual processing, short-term memory, and planning ability, with sustained effects at six months (p < 0.05). Caregivers reported noticeable improvements in children’s vitality, appetite, focus, and engagement in social and learning activities. Conclusions: Bycatch-derived protein supplementation, implemented through the SCOPE model, enhanced physical growth, behavior, and cognition in malnourished children in urban slums. Future studies should investigate the long-term effects, scalability, and adaptability of this sustainable solution for addressing child malnutrition. Full article

Morro do Banco, a slum in Rio de Janeiro, Brazil, is home to a community composed mainly of Brazilian and Venezuelan nationals, where littering is a persistent issue. This study investigates the causes of littering and examines the differences in perceptions and littering behaviours between residents, addressing a research gap in multicultural slums. A face-to-face survey was conducted with 150 residents, complemented by interviews with community members and professionals from urban cleaning and waste management services. Visual observations were also made. The results indicate that littering is primarily linked to a lack of containers for waste disposal and collection, as well as residents’ failure to dispose of waste at the designated times. There is a notable absence of awareness campaigns aimed at addressing the problem. While both communities recognise the littering issue, Venezuelan residents are less aware of public services and report observing lower levels of littering than Brazilian residents. Furthermore, Brazilians tend to place more responsibility on local authorities, while Venezuelans attribute responsibility to the central government. Venezuelans also express less support for oversight actions involving penalties compared to Brazilians. These findings highlight the need for targeted awareness campaigns and inclusive policies to effectively tackle littering in multicultural slums. Full article

Rodent-borne diseases threaten global public health, impacting the urban poor. Despite widespread application of rodenticide in rodent/rodent-borne disease control programs, empirical evidence demonstrating their effectiveness is lacking. This review proposed guidelines for designing and implementing empirical studies on rodenticides as public health measures. The recommendations include: (i) the importance of the type of quasi-experimental design adopted, and how it creates robust evidence; (ii) how urban slums present both challenges for control and ideal settings for studies; (iii) partnering with pest control authorities and community engagement for long-term viability; (iv) leveraging zoonotic systems with direct/environmental transmission, reliable diagnosis, and high prevalence for effectivity assessment; (v) pairing human cohort studies to observe epidemiological links; (vi) systematic data collection and management protocols; (vii) short- and long-term goals for critical evaluation and course-correction; (viii) focus on mechanistic approach; (ix) the need for standardized reporting of the findings. Full article

Rapid urbanization has led to significant demographic shifts and environmental challenges worldwide, with a growing portion of the urban population living in slums. This study investigates the impact of an urban slum upgrading program on pro-environmental behaviors and health-oriented mindsets among residents in Surakarta City, Indonesia. Specifically, it aims to reveal how pro-environmental behaviors, house satisfaction, health-oriented behaviors, and sustainability beliefs manifest within this unique socio-cultural setting. A representative survey was conducted among 327 residents of newly renovated urban slum housing. Additionally, cluster analysis with the Silhouette method was performed to identify distinct demographic and social ‘personalities’ characterized by pro-environmental and health-oriented mindsets within the heterogeneous population across three observed districts. The findings show that while strong beliefs in sustainability are common, there is a gap in translating these beliefs into action, as evidenced by low engagement with recycling and waste-burning avoidance. Furthermore, four clusters with unique profiles emerged: (1) residents dissatisfied with housing but proactive in sustainability (23.3%); (2) health-focused residents satisfied with housing but less engaged in sustainability (5.8%); (3) residents content with housing but low on health awareness and moderate in sustainability beliefs (46.8%); and (4) residents with strong sustainability beliefs but minimal pro-environmental actions (24.1%). This study offers valuable insights for policymakers to guide urban slum upgrading programs with targeted interventions addressing the unique characteristics among the residents. These findings are vital for creating a sustainable urban environment and preventing upgraded areas from reverting to slum conditions. Full article

Refugee camps are typically designed as temporary sustainable settlements, prioritizing logistics over cultural considerations, which can lead to environments being misaligned with the lived experiences of displaced populations. This study addresses the challenge of traditional humanitarian camp designs that prioritize logistical efficiency over cultural and socio-cultural needs, leading to environments that do not align with the lived experiences of displaced populations. Focusing on the Zaatari Syrian Refugee Camp in Jordan, the research employs a structured questionnaire distributed among 102 households to investigate how refugees have reconfigured the camp’s original grid layout into more cohesive clustered patterns, informed by the principles of defensible space theory. Key findings reveal that refugees actively transform public courtyards into semi-private spaces, driven by cultural imperatives and safety needs. Statistical analyses confirm significant correlations between clustering behaviors and the attributes of defensible space, particularly the zones of influence and boundary demarcation, enhancing community resilience and accessibility. However, the study finds a limited predictive power overall, indicating that while these adaptations are significant, factors such as natural surveillance and territorial behavior do not exhibit strong influences on clustering dynamics. These findings have important implications for humanitarian planning and design. They highlight the necessity for more culturally sensitive and flexible approaches that prioritize refugee agencies and communal identity in camp layouts. This research advocates for a hybrid planning approach that integrates socio-cultural values, promoting resilience and quality of life among refugees. By aligning spatial designs with the social and cultural realities of refugee communities, humanitarian actors can enhance the effectiveness of their interventions, ultimately contributing to more sustainable and inclusive urban environments as part of broader goals related to urban planning and development. Future research is encouraged to explore these practices in diverse refugee contexts, providing further validation of these findings and enhancing the applicability of these design principles in global humanitarian efforts. Full article

The informal city, also known as the clandestine city and usually associated with the phenomenon of urban self-organisation, is a reality that cuts across all societies today and occurs in the most diverse regions of the globe, which raises the following question: Why do such different cultures, in such different geographies, adopt a common idea of an ‘informal city’ to live in? Despite the dramatic human condition that characterises slums and informal settlements, it is challenging to understand how these settlements can be adopted as a living space for so many and such diverse populations, admitting the interpretation that it is a utopia and an urban idealisation. Informal urbanisation processes occur outside the system and on the fringes of the practice of ‘institutional urban planning’, as a necessary and immediate response to the absence of public land policies, housing market failures or situations arising from social and economic crises. The object of this study is to find out to what extent the configuration of space, the territorialisation model and the morphology of the informal city, characterised by an entropic urbanism, correspond to an urban organisational structure that occurs when it is up to society to provide its own habitat and urban environment. Full article

Objective: With rapid urbanization in countries like India, understanding the nutritional status and needs of urban populations, particularly among underprivileged groups such as people living in slums, is crucial. This study investigates the prevalence, characteristics, and determinants of child malnutrition in the urban slums of the Kolkata Municipal Corporation (KMC) and Siliguri Municipal Corporation (SMC) in West Bengal, India. Methods: A cross-sectional study was conducted among 736 children aged 6–59 months. Data were collected using structured interviews to gather socioeconomic, demographic, and dietary information, alongside anthropometric measurements. The analysis employed the Composite Index of Anthropometric Failure (CIAF), and multiple linear regression (MLR) models to identify key factors influencing malnutrition. Results: The findings revealed a high prevalence of stunting (24.1%), underweight (22.3%), and wasting (15.4%) among children aged 6–59 months, with significant variations observed between the two study sites. Key predictors of anthropometric malnutrition include low household income, incidence of recent illness, low maternal nutrition, and delayed initiation of breastfeeding. Conclusions: Addressing child malnutrition in urban slums requires integrated strategies encompassing income-generation opportunities, health-sensitive urban planning, and focused maternal and child health interventions. Full article

In this study, the aim was to comparatively examine the perception of risk for developing severe illness or complications due to COVID-19 among the general population and socially vulnerable populations in Brazil, focusing on uncovering the associated factors that disproportionately impacted people experiencing homelessness and slum dwellers. This study is part of the project “Social Thermometer—COVID-19 in Brazil”, which employed a hybrid approach, combining a national online survey with field research in state capitals and the Federal District. Data collection took place from August 2020 to October 2023, and the data were analyzed using descriptive statistics and logistic regression. A total of 5094 participants were included in this study, with 2363 from the general population and 2731 from the socially vulnerable population. Among the general population, the majority of participants were women, white individuals, those with higher incomes, formal employment, and higher education levels. Concerning the vulnerable population, most were men, Black individuals, those with lower incomes, unemployment, and lower education levels. It was observed that 87% of the general population perceived a risk of severe COVID-19, compared to 74% of the vulnerable population. Slum dwellers who received emergency aid (OR_a = 1.39; 95% CI: 1.02–1.91), adhered to mask-wearing practices (OR_a = 1.93; 95% CI: 1.39–2.66), used COVID-19-related medications (ORa = 2.13; 95% CI: 1.31–3. 64), and those with pre-existing conditions, such as high blood pressure (OR_a = 1.86; 95% CI: 1.20–2.98), demonstrated a heightened perception of risk for severe COVID-19 complications. Among the homeless population, individuals who wore masks (OR_a = 1.67; 95% CI: 1.26–2.20 and had been vaccinated (OR_a = 1.44; 95% CI: 1.04–1.98) were also more likely to perceive a high risk. In conclusion, in this study, significant disparities are revealed in the perception of COVID-19 risk between the general and socially vulnerable populations in Brazil. Factors such as receiving emergency aid, adherence to mask-wearing, use of COVID-19-related medications, and pre-existing health conditions were associated with increased risk perception. Despite facing greater socioeconomic challenges, vulnerable groups, particularly those experiencing homelessness and slum dwellers, showed a lower perception of the risk for severe COVID-19 complications. Full article

An increasing body of literature has investigated the implications of housing quality on health, confirming the negative consequences of poor housing quality on physical and mental health. Despite this increased focus on the salutogenic impacts of housing, the relationship between housing quality and cognitive health remains understudied. This study examined how the housing quality in urban informal settlements, where living conditions are often substandard, affects women’s cognitive functioning, with a specific focus on executive function (EF) skills. EF is a decision-making system that enables us to make decisions using working memory and attentional control. This study addressed two key questions: (1) Is housing quality associated with EF skills? (2) Does perceived housing stress experienced by women mediate the housing–EF relationship? A standardized observer-based tool assessed housing quality, psychometric instruments measured EF skills, and a 12-item questionnaire evaluated perceived housing stress. Results indicated that better housing quality is positively associated with higher EF skills, with housing stress acting as a mediating factor in this relationship. These findings have important implications for both health and housing policies. Investments in improving housing conditions can yield cognitive health benefits for women, and addressing stress-inducing housing factors could further enhance cognitive outcomes. Full article

Introduction: Food insecurity is a vital issue, especially in places such as Kinshasa. Additionally, food insecurity has been worsened by the COVID-19 pandemic, particularly in low- and middle-income countries. Thus, this study examined food insecurity in Kinshasa after the peak of the pandemic to understand the impact of post-pandemic recovery efforts as well as the heterogeneity of this problem according to the residence of respondent (slum vs. non-slum areas). Methods: Grounded in the four key dimensions of food security (availability, access, vulnerability, and utilization), this cross-sectional study was conducted in Kinshasa with a representative sample of 2170 households selected from 62 enumeration areas. We used a questionnaire to interview participants about their food situations. Interviews were conducted with the head of each household or their designated representative by 150 master’s students using tablets powered by the SurveyCTO application. Household food security status was evaluated using the Household Food Insecurity Access Scale. A logistic regression model was developed to assess household risk factors associated with food insecurity. Results: Most people we talked to were over 40 years old, and many lived in households with fewer than six people. About a third of the households were overcrowded. The prevalence of food insecurity was 76.5% (95%CI: 74.6–78.3). Factors associated with food insecurity included being a household head aged over 50 years, insufficient living space, lower socioeconomic status, and residing in slum areas (AOR: 1.38; 95% CI: 1.06–1.79). Conclusions: Vulnerable groups, such as slum residents, older adults, and informal workers are more likely to be affected by food insecurity. Addressing these challenges requires the government to develop targeted strategies that bolster resilience and mitigate household vulnerability during crises. Full article

Since proclaiming independence in 1960, Senegal has faced economic and demographic imbalances across its regions. To address these disparities, the government launched decentralization policies in three major phases, aiming to stimulate socio-economic growth at the local level. This study examines the impact of these policies on urban–rural development using socio-economic data between 2000 and 2020, and a multiple linear regression model in the entirety of Senegal. The findings reveal significant correlations between rural population growth, access to electricity, fertilizer availability, and per capita cultivated land, all positively associated with agricultural productivity. Additionally, rapid urbanization (47.3%) and weak land tenure (88.6%) adversely affect ecological systems and contribute to the proliferation of slums. A notable lack of health facilities per capita highlights a severe gap in healthcare accessibility. The study suggests increasing agricultural income, creating jobs, and promoting policies that support rural collective entrepreneurship as critical steps. It also recommends adopting a “one ecological zone, one economic activity” strategy to reduce economic disparities and encourage sustainable development in rural Senegal. Full article