The potential of implementing superblocks for multifunctional street use in cities
Ontology highlight
ABSTRACT:
SUBMITTER: Eggimann S
PROVIDER: S-EPMC7612763 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Street food makes a significant contribution to the diet of many dwellers in low- and middle-income countries and its trade is a well-developed activity in the central Asian region. However, data on its purchase and nutritional value is still scarce. This study aimed to describe street food purchasing patterns in central Asia, according to time and place of purchase. A multicentre cross-sectional study was conducted in 2016/2017 in the main urban areas of four central Asian countries: Dushanbe (Tajikistan), Bishkek (Kyrgyzstan), Ashgabat (Turkmenistan) and Almaty (Kazakhstan). Street food markets (n = 34) and vending sites (n = 390) were selected by random and systematic sampling procedures. Data on the purchased foods and beverages were collected by direct observation. Time and geographic location of the purchases was registered, and their nutritional composition was estimated. A total of 714 customers, who bought 852 foods, were observed. Customers' influx, buying rate and purchase of industrial food were higher in city centers compared to the outskirts (median: 4.0 vs. 2.0 customers/10 min, p < 0.001; 5.0 vs. 2.0 food items/10 min, p < 0.001; 36.2 vs. 28.7%, p = 0.004). Tea, coffee, bread and savory pastries were most frequently purchased in the early morning, bread, main dishes and savory pastries during lunchtime, and industrial products in the mid-morning and mid-afternoon periods. Energy and macronutrient density was highest at 11:00-12:00 and lowest at 09:00-10:00. Purchases were smaller but more energy-dense in city centers, and higher in saturated and trans-fat in the peripheries. This work provides an overview of the street food buying habits in these cities, which in turn reflect local food culture. These findings from the main urban areas of four low- and middle-income countries which are currently under nutrition transition can be useful when designing public health interventions customized to the specificities of these food environments and their customers.
| S-EPMC9263728 | biostudies-literature
Project description:Virtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (- 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.
| S-EPMC7392983 | biostudies-literature
Project description:Understanding seasonal breeding dynamics is essential for maximizing efficiency and welfare in the application of street dog management programs. Humane Society International (HSI) has conducted many animal birth control programmes concerning the street dog populations in urban India. This paper analyses the data on reproductive indicators-oestrus, pregnancy, and pups-collected by HSI sterilization clinics in the cities of Jamshedpur, Dehradun, and Vadodara over a period of 3, 5, and 4 years, respectively. We found a consistent reproductive seasonality dynamic in all three cities, with peak oestrus and pregnancies occurring in the late/post-monsoon season. Pup proportions peaked soon after. Both these findings are consistent with previous studies of free-roaming domestic dog populations both in India and worldwide. Additionally, we identified minor inter-city differences in the temporal breeding dynamic, which we propose are the result of localized seasonal climatic and human factors. Finally, we examine and assert the relevance of breeding seasonality in the implementation of efficient and welfare-sensitive birth control programmes.
| S-EPMC9247615 | biostudies-literature
Project description:BackgroundCities are shifting toward providing more efficient services and the Internet of Things (IoT) becoming the future of things. The shift toward using eco-friendlier LED lights in lighting cities is another genuine game-changer in the future of Light Fidelity technology (Li-Fi). Li-Fi is a visible light communication (VLC) technology that uses Light Emitting Diodes (LED) bulbs for communication. The utilisation of thousands of light sources around a city acting as wireless access points and delivering location-based content will shift cities towards being smart sustainable cities. Recently, this technology got huge attention from the research community and different research has been conducted to improve this filed. However, there is a noticeable need to develop real-world systems that utilise Li-Fi technology.MethodsThis article aims to contribute to developing a Geo-Li-Fi system that uses LED lights to provide the services for collecting contextual data and delivering location-based services (LBS) in different areas of the city. The system is described along with details of its design, implementation and development. Moreover, the overall set-up of the testbed that used to evaluate the proposed system is presented. In addition, an experiment is conducted using a real-world scenario to test the functionality of the system and report the outputs.ResultsThe effect of the system is discussed according to different aspects of sustainability which include economic, social and environmental aspects. The system was tested in indoor and outdoor environments, and it can be seen that the sunlight does not affect the ability of LEDs to deliver the content during the daytime. Regarding the transmission range of the LED lamp, it can be seen that it is affected by different factors. It depends mainly on the power of lamp, so it will be increased significantly when the power of LED is increased. Also, an increase in the beam angle will result in wider coverage area which affected by the intensity.
| S-EPMC9454865 | biostudies-literature
Project description:New 'big data' streams such as street-level imagery are offering unprecedented possibilities for developing health-relevant data on the urban environment. Urban environmental features derived from street-level imagery have been used to assess pedestrian-friendly neighbourhood design and to predict active commuting, but few such studies have been conducted in Canada. Using 1.15 million Google Street View (GSV) images in seven Canadian cities, we applied image segmentation and object detection computer vision methods to extract data on persons, bicycles, buildings, sidewalks, open sky (without trees or buildings), and vegetation at postal codes. The associations between urban features and walk-to-work rates obtained from the Canadian Census were assessed. We also assessed how GSV-derived urban features perform in predicting walk-to-work rates relative to more widely used walkability measures. Results showed that features derived from street-level images are better able to predict the percent of people walking to work as their primary mode of transportation compared to data derived from traditional walkability metrics. Given the increasing coverage of street-level imagery around the world, there is considerable potential for machine learning and computer vision to help researchers study patterns of active transportation and other health-related behaviours and exposures.
| S-EPMC9626470 | biostudies-literature
Project description:Increasing prescription numbers of cannabis-based medicines raise the question of whether uptake of these medicines can be distinguished from recreational cannabis use. In this pilot study, serum cannabinoid profiles after use of cannabis-based medicines were investigated, in order to identify potential distinguishing markers. Serum samples after use of Sativex®, Dronabinol or medical cannabis were collected and analyzed for 18 different cannabinoids, using a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Analytes included delta-9-tetrahydrocannabinol, 11-hydroxy-tetrahydrocannabinol, 11-nor-9-carboxy-tetrahydrocannabinol, cannabidiol, cannabinol, cannabigerol, cannabichromene, cannabicyclol, tetrahydrocannabivarin, cannabidivarin, tetrahydocannabinolic acid A, cannabidiolic acid, cannabinolic acid, cannabigerolic acid, cannabichromenic acid, cannabicyclolic acid, tetrahydrocannabivarinic acid and cannabidivarinic acid. Cannabinoid profiles of study samples were compared to profiles of street cannabis user samples via principal component analysis and Kruskal-Wallis test. Potential distinguishing markers for Dronabinol and Sativex® intake were identified, including 11-hydroxy-tetrahydrocannabinol/delta-9-tetrahydrocannabinol ratios ≥1 and increased concentrations of 11-nor-9-carboxy-tetrahydrocannabinol, cannabidiol or cannabichromene. Larger quantities of minor cannabinoids suggested use of cannabis. Use of medical and street cannabis could not be distinguished, except for use of a cannabidiol-rich strain with higher cannabidiol/delta-9-tetrahydrocannabinol and cannabichromene/delta-9-tetrahydrocannabinol ratios. Findings of the study were used to classify forensic serum samples with self-reported use of cannabis-based medicines.
| S-EPMC8153355 | biostudies-literature
Project description:The success or failure of the street network depends on its reliability. In this article, using resilience analysis, the author studies how the shape and appearance of street networks in self-organised and top-down planned cities influences urban transport. Considering London and Beijing as proxies for self-organised and top-down planned cities, the structural properties of London and Beijing networks first are investigated based on their primal and dual representations of planar graphs. The robustness of street networks then is evaluated in primal space and dual space by deactivating road links under random and intentional attack scenarios. The results show that the reliability of London street network differs from that of Beijing, which seems to rely more on its architecture and connectivity. It is found that top-down planned Beijing with its higher average degree in the dual space and assortativity in the primal space is more robust than self-organised London using the measures of maximum and second largest cluster size and network efficiency. The article offers an insight, from a network perspective, into the reliability of street patterns in self-organised and top-down planned city systems.
| S-EPMC4686176 | biostudies-literature
Project description:According to the biophilia hypothesis, humans have evolved to prefer natural environments that are essential to their thriving. With urbanization occurring at an unprecedented rate globally, urban greenspace has gained increased attention due to its environmental, health, and socioeconomic benefits. To unlock its full potential, an increased understanding of greenspace metrics is urgently required. In this first-of-a-kind study, we quantified street-level greenspace using 751 644 Google Street View images and computer vision methods for 125 274 locations in Ireland's major cities. We quantified population-weighted exposure to greenspace and investigated the impact of greenspace on health and socioeconomic determinants. To investigate the association between greenspace and self-reported health, a negative binomial regression analysis was applied. While controlling for other factors, an interquartile range increase in street-level greenspace was associated with a 2.78% increase in self-reported "good or very good" health [95% confidence interval: 2.25-3.31]. Additionally, we observed that populations in upper quartiles of greenspace exposure had higher levels of income and education than those in lower quartiles. This study provides groundbreaking insights into how urban greenspace can be quantified in unprecedented resolution, accuracy, and scale while also having important implications for urban planning and environmental health research and policy.
| S-EPMC8277136 | biostudies-literature
Project description:Background: According to the latest Guidelines from the World Health Organization, there is an increasing need for patient-centered tuberculosis disease management given the socio-economic factors influencing the tuberculosis epidemic. In the present study, we aimed to study TB in Barcelona city from an anthropological point of view and to devise a series of specific proposals to implement a patient-centered approach in our setting. Methods: We carried out a qualitative study using an anthropological approach in Barcelona in the period between November 2017 and November 2018 and proposed specific interventions based on our observations. Results: In practice, in our environment (a low-incidence European country where tuberculosis tends to present in patients with multiple social problems), and despite the goodwill of the care teams, there are no established and stable circuits, or specific tools to ensure that this is done routinely. Based on our observations, we have devised a series of specific proposals to implement a patient-centered approach. With these interventions we aim to (a) directly ameliorate TB patients well-being in any diagnostic/healthcare management center and (b) at more general level, to increase TB detection and treatment adherence. Conclusions: The patient-centered TB management recommended by the WHO might be essential for patients' well-being, but there is a lack of circuits or working protocols that ensure its implementation in a regulated manner. In the present manuscript we explain the various concrete measures that we propose in our region and which could be put into practice in other cities or geographic regions with similar epidemiological characteristics.
| S-EPMC6901950 | biostudies-literature
Project description:Unprecedented levels of urbanization have escalated urban environmental health issues, including increased air pollution in cities globally. Strategies for mitigating air pollution, including green urban planning, are essential for sustainable and healthy cities. State-of-the-art research investigating urban greenspace and pollution metrics has accelerated through the use of vast digital data sets and new analytical tools. In this study, we examined associations between Google Street View-derived urban greenspace levels and Google Air View-derived air quality, where both have been resolved in extremely high resolution, accuracy, and scale along the entire road network of Dublin City. Particulate matter of size fraction less than 2.5 μm (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and carbon dioxide were quantified using 5,030,143 Google Air View measurements, and greenspace was quantified using 403,409 Google Street View images. Significant (p < 0.001) negative associations between urban greenspace and pollution were observed. For example, an interquartile range increase in the Green View Index was associated with a 7.4% [95% confidence interval: -13.1%, -1.3%] decrease in NO2 at the point location spatial resolution. We provide insights into how large-scale digital data can be harnessed to elucidate urban environmental interactions that will have important planning and policy implications for sustainable future cities.
| S-EPMC10702516 | biostudies-literature