Residential Density Research Articles

Urban and Rural Environments and Their Implications for Older Adults’ Adaptation to Heat Waves: A Systematic Review

The aim of this study is to synthesise the scientific evidence on the implications of urban and rural environments on older adults’ adaptation strategies to heatwaves. Methods: The methodology follows PRISMA guidelines, which involves a systematic search of the scientific literature in selected electronic databases, including Web of Science and Scopus, to assist in the selection, identification and retention of studies. Results: The search identified 4991 potentially eligible articles, of which 17 met the criteria, mainly from developed countries, emphasising a multidisciplinary approach and moderate to low quality. Urban and rural environments influence older adults’ adaptation strategies to heatwaves through the adequacy of the physical environment of the dwelling (design, materials, equipment) and the neighbourhood (green spaces, residential density, land use), the social environment (support network and type of assistance) and risk management (protective measures and heat warning systems). At the individual level, adaptation to heatwaves is determined by age, gender, health status, socio-economic status and social isolation. Discussion and conclusions: Differences in perceptions of heat adaptation were found according to location, typology and environmental characteristics, especially in developing countries. The findings contribute to promoting the adoption of protective measures, the design of heat warning systems, and the planning of friendly and resilient cities and rural communities to support the adaptation of an ageing society to the climate warming.

DEMOGRAPHIC DYNAMICS AND URBAN PROPERTY CRIME: A LINEAR REGRESSION ANALYSIS IN KUALA LUMPUR AND PUTRAJAYA (2015-2020)

In an era where urbanization is rapidly transforming the landscape of cities, this study provides a crucial overview of how demographic shifts influence property crime in metropolitan areas. The paper delves into the complex interplay between property crime rates and demographic characteristics in the urban settings of Kuala Lumpur and Putrajaya, Malaysia, over six years from 2015 to 2020. Employing linear regression analysis, the study meticulously examines the relationship between property crime and various demographic factors, including total population, male and female populations, and residential and household densities. The findings indicate a consistent positive correlation between total population and property crime, emphasizing urban density's role in crime propensity. Notably, the male population shows a stronger correlation with property crime than females. The study also highlights how residential and household densities influence property crime in these urban settings. These insights are invaluable for policymakers and urban planners, guiding targeted strategies to reduce property crime in growing cities.

Investigating the Nonlinear Effect of Land Use and Built Environment on Public Transportation Choice Using a Machine Learning Approach

Understanding the relationship between the demand for public transportation and land use is critical to promoting public-transportation-oriented urban development. Taking Beijing as an example, we took the Public Transportation Index (PTI) during the working day’s early peak hours as the dependent variable. And 15 land use and built environment variables were selected as the independent variables according to the “7D” built environment dimensions. According to the Modifiable Areal Unit Problem (MAUP), the size and shape of the spatial units will affect the aggregation results of the dependent variable and the independent variables. To find the ideal spatial unit division method, we assess how well the nonlinear model fits several spatial units. Extreme Gradient Boosting (XGBoost) was utilized to investigate the nonlinear effects of the built environment on PTI and threshold effects based on the ideal spatial unit. The results show that (1) the best spatial unit division method is based on traffic analysis zones (TAZs); (2) the top four explanatory variables affecting PTI are, in order: mean travel distance, residential density, subway station density, and public services density; (3) there are nonlinear relationships and significant threshold effects between the land use variables and PTI. The priority regeneration TAZs were identified according to the intersection analysis of the low PTI TAZs set and the PTI-sensitive TAZs set based on different land use variables. Prioritized urban regeneration TAZs require targeted strategies, and the results of the study may provide a scientific basis for proposing strategies to renew land use to increase PTI.

Estimation of Greenhouse Gas Emissions of Taxis and the Nonlinear Influence of Built Environment Considering Spatiotemporal Heterogeneity

The fuel consumption and greenhouse gas (GHG) emission patterns of taxis are in accordance with the urban structure and daily travel footprints of residents. With taxi trajectory data from the intelligent transportation system in Xi’an, China, this study excludes trajectories from electric taxis to accurately estimate GHG emissions of taxis. A gradient boosting decision tree (GBDT) model is employed to examine the nonlinear influence of the built environment (BE) on the GHG emissions of taxis on weekdays and weekends in various urban areas. The research findings indicate that the GHG emissions of taxis within the research area exhibit peak levels during the time intervals of 7:00–9:00, 12:00–14:00, and 23:00–0:00, with notably higher emission factors on weekends than on weekdays. Moreover, a clear nonlinear association exists between BE elements and GHG emissions, with a distinct impact threshold. In the different urban areas, the factors that influence emissions exhibit spatial and temporal heterogeneity. Metro/bus/taxi stops density, residential density, and road network density are the most influential BE elements impacting GHG emissions. Road network density has both positive and negative influences on the GHG emissions in various urban areas. Increasing the road network density in subcentral urban areas and increasing the mixed degree of urban functions in newly developed urban centers to 1.85 or higher can help reduce GHG emissions. These findings provide valuable insights for reducing emissions in urban transportation and promoting sustainable urban development by adjusting urban functional areas.

Examining social-demographic determinants of bike-sharing station capacity

This study applied Negative Binomial models to examine the social-demographic determinants of bike-sharing station capacity. It used social-demographic data from Smart Location Database and over 7,000 bike-sharing stations located in the United States. Results revealed that the station's city, households with no cars, the percentage of workers aged 18–64, gas prices, the Caucasian population, gross residential density on unprotected land, intersection density, and low to medium-earning workers are associated with the increase in station capacity. Contrarily, station capacity decreased with vehicle miles traveled and the number of high-earning workers. Findings are crucial to planners and operators in improving bike-sharing operations.

Prediction of bike-sharing station demand using explainable artificial intelligence

Bike-sharing systems have grown in popularity in metropolitan areas, providing a handy and environmentally friendly transportation choice for commuters and visitors alike. As demand for bike-sharing programs grows, efficient capacity planning becomes critical to ensuring good user experience and system sustainability in terms of demand. The random forest model was used in this study to predict bike-sharing station demand and is considered a strong ensemble learning approach that can successfully capture complicated nonlinear correlations and interactions between input variables. This study employed data from the Smart Location Database (SLD) to test the model accuracy in estimating station demand and used a form of explainable artificial intelligence (XAI) function to further understand machine learning (ML) prediction outcomes owing to the blackbox tendencies of ML models. Vehicle Miles of Travel (VMT) and Greenhouse Gas (GHG) emissions were the most important features in predicting docking station demand individually but not holistically based on the datasets. The percentage of zero-car households, gross residential density, road network density, aggregate frequency of transit service, and gross activity density were found to have a moderate influence on the prediction model. Further, there may be a better prediction model generating sensible results for every type of explanatory variable, but their contributions are minimum to the prediction outcome. By measuring each feature's contribution to demand prediction in feature engineering, bike-sharing operators can acquire a better understanding of the bike-sharing station capacity and forecast future demands during planning. At the same time, ML models will need further assessment before a holistic conclusion.

Joint associations of neighbourhood walkability and greenery with walking among middle-aged and older adults: Findings from diverse urban settings in Australia

There is evidence that neighbourhood walkability and greenery are associated with walking, but less is known about their joint associations. We investigated this using data from the AusDiab3 study (2011/12) with 3032 adults (mean age 60 years). Two-level logistic regression models were used with binary walking outcomes. There was an inverse relationship (r = −0.5) between walkability (a composite measure of residential, destinations and intersections densities) and greenery (the size of densely vegetated areas). However, both walkability and greenery were independently positively associated with odds of walking. Regarding joint associations, in low-walkability neighbourhoods, greenery was positively associated with walking. In high-walkability neighbourhoods, greenery was not associated with walking.

Factors Causing Peritoneal Tuberculosis in Children with A Family Nursing Approach: Case Report

The morbidity rate of children due to tuberculosis (TB) including peritoneal TB is still high. It is very important to know the factors that cause Peritoneal Tuberculosis in children, so that it can prevent and reduce morbidity rates by using a family nursing approach that not only involves children, but also involves families so as to support the health of children and families holistically. This study aims to determine what factors cause cases of Peritoneal Tuberculosis in children using a family nursing approach. The method used is case report. This study examined 9 factors causing Peritoneal Tuberculosis, namely nutritional status, age, gender, residential density, air circulation at home, home lighting, BCG immunization history, economic background, and parental knowledge related to Peritoneal Tuberculosis. The study was conducted for 6 home visits with a family nursing care approach, namely the Friedman framework assessment, intervention, implementation, and evaluation and online follow-up 3 times. Each visit lasted 30 to 45 minutes. Factors causing Peritoneal TB in children include nutritional status, age of the child, housing density, house lighting and air circulation at home, gender, BCG immunization history, economic background, and parental knowledge. The main factors that caused An.Z to develop Peritoneal Tuberculosis were nutritional status and environmental conditions in the house, such as occupancy density, lighting, and air circulation in the house.

The Relation between Flow Map Analysis and Residential Density Conditions in Sleman Regency, Special Region of Yogyakarta

The government of Sleman Regency has been seriously implementing the Smart Living concept under the Smart Regency idea. It is demonstrated by the achievements of the Transport Service Improvement Program in the form of developing type C terminal facilities, creating a transport licensing management information system, and data collection on public transport, types, number of modes, routes and route mapping. However, the affordability and availability of public transportation access in all government facilities (such as hospitals, schools and offices) as well as the integration of routes has not yet been fully realized. In order to support the identification of problems in the implementation of routes that should be integrated with residential areas, this research describe the relation between flow map analysis and residential density condition in Sleman Regency based on data respondent who has been living in Sleman Regency. The analysis was conducted by using quantitative method, especially using the ArcGIS as the analysis tool. Research data were collected through interviews, questionnaire distribution, observation which distribute all over the regency. The results showed that the current form of movement patterns originates from residential area that have high density (in terms of population), but not all of them are served by the existing transport public routes. The mapping results showed that although the majority of movement patterns are still operating in main service areas such as in the Yogyakarta Urban Area, however, there are still many areas that are not yet served, such as Kapanewon Moyudan, Minggir, Seyegan, Tempel, Turi, even Sleman as the administrative capital of Sleman Regency.

Priority Intervention Evaluation of Community Regeneration in Megacities Based on the Business Improvement District (BID) Model: A Case Study of Tianjin, China

This study aims to start from the macroscale of the megacity, explore a top-down operational technical path from the identification of community regeneration units as the evaluation objects to the BID priority intervention evaluation, and then propose differentiated community regeneration strategies based on the BID model. In the post-epidemic era, it is necessary for global megacities to take new measures in urban regeneration to respond to worldwide changes and challenges. As an innovative tool to promote central city revitalization, the BID model has played an important role in community transformation. In the context of the continuous decentralization of population and industry in China’s megacities, it is urgent to explore the technical path to apply the BID model to local community regeneration. Given the shortcomings of existing studies in the method to identify the scope of BID implementation and evaluate intervention priorities, this study takes Tianjin, a megacity in China, as an example and uses DBSCAN (density-based spatial clustering of applications with noise) and service area analysis to define the community regeneration units with commercial agglomeration characteristics as the objects. Then, the BID priority intervention evaluation system is constructed from the two measurement aspects of the intervention potential and the necessity of community regeneration to classify the BID intervention priorities of community regeneration units. The main conclusions are as follows: 1. When the DBSCAN analysis parameters take the minimum number of elements as 30 and the search distance as 120 m, the result is most suitable for identifying community units with commercial agglomeration of the study area; 2. Population vitality, especially working and residential population density, is the key factor affecting BID intervention potential, while road network density is an important indicator for determining the necessity of community regeneration; 3. Community regeneration units with high BID priority levels need to develop differentiated regeneration strategies combining their BID intervention potential, regeneration necessity characteristics, and location attributes. These conclusions can provide references for the governments of megacities to screen and establish BIDs.

Glyphosate and other plant protection products in size-segregated urban aerosol: Occurrence and dimensional trend

Plant protection products (PPPs) play a fundamental role in the maintenance of agricultural fields and private/public green areas, however they can contaminate zones nearby the application point due to wind drift, resuspension, and evaporation. Several studied have deepened the relationship between PPPs and living beings’ health, suggesting that these products might have a negative influence. Some PPPs belong to the class of Emergent Contaminants, which are compounds whose knowledge on the environmental distribution and influence is limited. These issues are even more stressed in urban aerosol, due to the high residential density that characterizes this area. Therefore, this study assessed the contamination caused by polar PPPs, such as herbicides (i.e., Glyphosate), fungicides (i.e., Fosetyl Aluminium), and growth regulators (i.e. Maleic Hydrazide), in size-segregated urban aerosol and evaluated their concentration variability with respect to atmospheric parameters (humidity, temperature, rain). Moreover, hypotheses on possible sources were formulated, exploiting also back-trajectories of air masses. A total of six PPPs were found in the samples: glyphosate was more present in the coarse fraction (2.5–10 μm), Fosetyl Aluminium, chlorate and perchlorate were more present in the coarse/fine fractions (10-1 μm), while cyanuric acid and phosphonic acid were mostly concentrated in the fine/ultrafine fractions (<1 μm). While for the first four we suspect of local sources, such as private gardening, the two latter might derive from the entire Po Valley, a highly polluted area in the North of Italy, and from degradation of other substances.

ANALISIS SANITASI LINGKUNGAN DAN KEBERADAAN VEKTOR TIKUS DI PANTI ASUHAN AL-ISTIKLAL

Environmental sanitation is an effort to monitor and control environmental elements such as clean water and waste, personal hygiene in public places, clean and healthy food processing, and the absence of hazardous substances in the air. This research aims to identify and analyze environmental conditions and the presence of rat vectors at the Al-Istiklal Orphanage, Pekanbaru City. This research uses an observation approach and in-depth interviews to examine current conditions. Five informants were research subjects. The research results show that the sanitary conditions at the Al-Istiklal orphanage are still poor, as shown by SPAL: many piles of rubbish smell bad and do not have lids; rubbish at the orphanage is not sorted before being thrown away and burned; some rooms in the orphanage were not sorted before being burned; and Some rooms have an outdoor and adjoining kitchen, and the windows do not open. Several mice were found in the orphanage. Orphanages must pay more attention to environmental sanitation issues, such as SPAL, food processing, waste processing, and residential density, as well as the presence of rat vectors.

Impact of Neighborhood Urban Morphologies on Walkability Using Spatial Multi-Criteria Analysis

With the increase in car domination, air pollution, traffic congestion, and urban sprawl, sustainable, livable, creative, and walkable cities are critical, now more than ever, for improving quality of life. The effect of neighborhood urban morphologies on walkability has received much attention in recent years. In this vein, the main research question is: how do different neighborhood urban morphologies impact the level of walkability in urban environments, and what are the essential elements impacting the walkability index? Thus, this research aims to determine the impact of urban morphology on walkability in the city of Alexandria, Egypt, as a case study by utilizing multi-spatial analysis. In particular, the study focused on assessing the walkability of four different study areas that vary according to their urban morphology: Kafr–Abdo, Smouha, Latin Quarter, and Roushdy areas. The analysis utilized GIS to calculate a number of indicators to reach the final walkability index for each study area. Results helped to identify the neighborhoods characterized by the lowest level of pedestrian walkability in relation to the area’s urban morphology in an attempt to help decision-makers suggest the appropriate interventions for those areas. The aggregated index results showed that the highest walkability index was that of the gridiron morphology, followed by the linear morphology, with the radial and organic morphologies coming in behind them, respectively. The composite walkability index values were 0.364, 0.247, 0.232 and 0.225, respectively. The reason for this is mainly the presence of the commercial density, intersection density, street density, services density, BCR, and residential density.

Counseling on Pulmonary TB Overcoming and Healthy House Sanitation for Pulmonary TB Patients

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis and spreads through the air when sufferers cough, sneeze or spit. TB is still a global health problem with 10 million cases in 2019 and 1.4 million deaths. Indonesia has a high TB incidence rate, with 316 per 100,000 population in 2018. Environmental factors such as ventilation, floor type and residential density greatly influence TB transmission. This research was conducted Community Health Center to measure the knowledge and sanitary conditions of TB patients' homes. The methods used include interviews, counseling and direct observation of house conditions. The results show an increase in knowledge about TB after the education, with 75% of houses not meeting ventilation requirements, 8.9% of houses not meeting floor type requirements, 7.1% of houses not meeting wall type requirements, and 39.3% of houses having low occupancy density. not eligible. Good knowledge of a healthy environment and behavior that supports TB prevention is very important to reduce the transmission of this disease.

Exploring heterogeneous relationships between multiscale built environment and overweight in urbanizing China

Overweight has emerged as a significant threat to people's health. Although a handful of studies have evaluated the neighborhood built environment (BE) and overweight connection, there is little knowledge about how urbanization moderates the connection. The present study seeks to assess whether there are differences in the BE and overweight connection between urban and rural settings, and how the connection varies across different urbanization rates. Based on a nationwide sample of 7883 individuals in China, we consider both scales of BE elements and examine their heterogeneous associations with overweight. The findings show that both scales of BE elements are essential determinants of overweight. Significant differences in the connection between urban and rural settings are observed. Most BE elements are shown to be significant contributors in urban settings, whereas only residential density, metro, and public transit supply play significant roles in rural settings. Additionally, the BE and overweight connection also varies across urbanization rates. The BE elements are more influential to overweight in more urbanized areas. Our findings indicate that planning efforts at both neighborhood and city scales are essential and targeted planning strategies should be made according to local contexts.

Analysis of Risk Factors for Dengue Hemorrhagic Fever in Children: An Observational Study in Batang Regency, Indonesia

Dengue hemorrhagic fever (DHF) is a significant public health problem in Indonesia, including in Batang Regency. This study aims to analyze the risk factors associated with the incidence of dengue fever in children in Batang Regency, Indonesia. A cross-sectional observational study was conducted on 258 child subjects in Batang Regency. Data was collected through structured interviews with parents or guardians, direct observation of the home environment, and laboratory tests to confirm the diagnosis of dengue fever. Data analysis included univariate, bivariate (Chi-square test), and multivariate (logistic regression) analyses to identify independent risk factors. Univariate analysis showed a relationship between the incidence of dengue fever and age, gender, parental education, parental occupation, residential density, presence of mosquito larvae in water reservoirs, habit of hanging clothes, history of mosquito bites, and nutritional status. Bivariate analysis identified several statistically significant risk factors, including high residential density (OR=2.87; 95% CI: 1.65-5.01), presence of mosquito larvae (OR=3.21; 95% CI: 1.89-5.45), habit of hanging clothes (OR=2.87; 95%CI:1.32-5.21), and history of mosquito bites (OR=2.54; 95%CI: 1.48 -4.36). Multivariate analysis confirmed that high residential density and the presence of mosquito larvae were independent predictors of dengue incidence. High residential density and the presence of mosquito larvae in the home environment are the main risk factors for the incidence of dengue fever in children in Batang Regency. Public health interventions that focus on vector control and improving environmental sanitation are critical to reducing the dengue burden in this area.

Do households value lower density: Theory, evidence, and implications from Washington, DC

A substantial literature demonstrates that zoning restrictions on building height or density lower supply and increase housing prices. However, negative externalities due to household preferences for lower neighborhood density could justify restrictions on private developers. Thus building density in a laissez-faire city may be above the welfare maximizing level. The potential external costs of height and density are tested here and found to be substantial. Increased building separation appears to mitigate the external cost of height. This implies that some level of density or floor regulation (FAR) may be welfare-enhancing, and that the gap between price and marginal construction cost may overstate the social cost of zoning because households value lower density. The analysis considers residential density and not employment density which can give rise to other types of externalities.

Association between density of food retailers and fitness centers and gestational diabetes mellitus in Eastern Massachusetts, USA: population-based study

Few studies have investigated the relationship between the food and physical activity environment and odds of gestational diabetes mellitus (GDM). This study quantifies the association between densities of several types of food establishments and fitness centers with the odds of having GDM. The density of supermarkets, fast-food restaurants, full-service restaurants, convenience stores and fitness centers at 500, 1000 and 1500m (m) buffers was counted at residential addresses of 68,779 pregnant individuals from Eastern Massachusetts during 2000-2016. The 'healthy food index' assessed the relative availability of healthy (supermarkets) vs unhealthy (fast-food restaurants, convenience stores) food retailers. Multivariable logistic regression quantified the cross-sectional association between exposure variables and the odds of having GDM, adjusting for individual and area-level characteristics. Effect modification by area-level socioeconomic status (SES) was assessed. In fully adjusted models, pregnant individuals living in the highest density tertile of fast-food restaurants had higher GDM odds compared to those living in the lowest density tertile (500m: odds ratio (OR):1.17 95% CI: [1.04, 1.31]; 1000m: 1.33 95% CI: [1.15, 1.53]); 1500m: 1.18 95% CI: [1.01, 1.38]). Greater residential density of supermarkets was associated with lower odds of GDM (1000m: 0.86 95% CI: [0.74, 0.99]; 1500m: 0.86 95% CI: [0.72, 1.01]). Similarly, living in the highest fitness center density tertile was associated with decreased GDM odds (500m:0.87 95% CI: [0.76, 0.99]; 1500m: 0.89 95% CI: [0.79, 1.01]). There was no evidence of effect modification by SES and no association found between the healthy food index and GDM odds. In Eastern Massachusetts, living near a greater density of fast-food establishments was associated with higher GDM odds. Greater residential access to supermarkets and fitness centers was associated with lower the odds of having GDM. NIH.

Risk and low-density dispersed urbanism

Settlements operate across a wide range of densities and do so for every socio- economic mode of life from those based on hunter-gatherer economies to those which are based on industrial production. Human beings also live across a range of residential densities from very high to very low. Why they do so is a function of many factors, especially differing socio-cultural ways of managing interaction and communication and the associated social and political practices of the communities. Settlement forms are seen as a derivative of many factors because they are. But they are not thereby an epiphenomenon - especially as they become larger, more durable, and bulkier. That gives them inertia and, as a consequence, they become an agency in their own right which produces outcomes with consequences for the communities, which inhabit them. They are not a neutral background. Instead, their materiality, their sizes, and their densities have an impact on the viability of social life. This paper considers the outcomes generated by the regional networks of low-density, urban settlements larger than 100 sq km in extent. The implications of what happened to agrarian-based low-density urban settlements, like Greater Angkor and the Classic Maya settlements, such as Caracol, are of consequence for the risk faced by the regional networks of present-day, low-density urban giants – the megalopoleis and desa-kota. A further perspective is provided by placing these great cities of the past and the present in the larger context of the trajectories and outcomes of smaller low-density settlements over the previous six millennia. The concern is the implications for the viability of low-density urbanism in contexts of the rapid, extreme climate change we are now beginning to experience. The implications are ominous, yet the past also indicates that social and cultural systems are robust, that human beings can survive, and that they retain and continue to remake their social traditions as they adjust to seriously changing circumstances.

Climatic Variations and Indoor Environmental Quality Performance of Houses in Selected Cities in Oyo State, Nigeria

Understanding how climatic variations influence Indoor Environmental Quality (IEQ) becomes crucial for designing sustainable and comfortable living spaces in this specific region. This study therefore investigates the effect of climatic variations on IEQ performance of houses in selected cities within Oyo State, Nigeria. The types of data collected for the study were numeric and ordinal. The numeric data of air temperature, relative humidity, air velocity and noise level, were gotten through objective measurements and IEQ through IEQ Calculator. The ordinal data were gotten through observation and questionnaire. Control Potential Zone technique on psychometric chat was used to analyze climate of Ibadan, Ogbomoso and Kisi. The physical measurements were conducted in the living, bedroom and kitchen spaces of the sampled houses in the low, medium and high residential density zones of the selected cities. A sample size of 581 houses from 3,490 were selected across each of the three residential density zones in the selected cities. The indoor temperature and relative humidity in the three cities were higher during the afternoon period with average thermal stress index of 39.40C, 36.90C and 38.40C respectively for Ibadan, Ogbomoso and Kisi respectively. None of the spaces satisfied the effective indoor ventilation comfort criteria of between 0.5m/s -1.5 m/s. All the spaces except the bedroom space in the compound impluvium house type satisfied the illumination range of between 50 – 60 lux. The maximum indoor noise level during the morning, afternoon and evening periods in study area were 58db, 59db and 58db respectively. Result from the IEQ calculator indicated that majority of the houses (83.6%) were star 2 in the IEQ performance. The implication was that these houses were below average in terms of IEQ performance.