No abstract

Older adults living in high-deprivation areas walk less than those living in low-deprivation areas. Previous research has shown that older adults’ outdoor walking levels are related to the neighbourhood built environment. This study examines inequalities in perceived built environment attributes (i.e., safety, pedestrian infrastructure and aesthetics) and their possible influences on disparities in older adults’ outdoor walking levels in low- and high-deprivation areas of Birmingham, United Kingdom. It applied a mixed-method approach, included 173 participants (65 years and over), used GPS technology to measure outdoor walking levels, used questionnaires (for all participants) and conducted walking interviews (with a sub-sample) to collect data on perceived neighbourhood built environment attributes. The results show inequalities in perceived neighbourhood safety, pedestrian infrastructure and aesthetics in high- versus low-deprivation areas and demonstrate that they may influence disparities in participants’ outdoor walking levels. Improvements of perceived neighbourhood safety, pedestrian infrastructure and aesthetic in high-deprivation areas are encouraged.

Older residents of high-deprivation areas walk less than those of low-deprivation areas. Previous research has shown that neighborhood built environment may support and encourage outdoor walking. The extent to which the built environment supports and encourages walking is called “walkability”. This study examines inequalities in neighborhood walkability in high- versus low-deprivation areas and their possible influences on disparities in older adults’ outdoor walking levels. For this purpose, it focuses on specific neighborhood built environment attributes (residential density, land-use mix and intensity, street connectivity, and retail density) relevant to neighborhood walkability. It applied a mixed-method approach, included 173 participants (≥65 years), and used a Geographic Information System (GIS) and walking interviews (with a sub-sample) to objectively and subjectively measure neighborhood built environment attributes. Outdoor walking levels were measured by using the Geographic Positioning System (GPS) technology. Data on personal characteristics was collected by completing a questionnaire. The results show that inequalities in certain land-use intensity (i.e., green spaces, recreation centers, schools and industries) in high- versus low-deprivation areas may influence disparities in older adults’ outdoor walking levels. Modifying neighborhood land use intensity may help to encourage outdoor walking in high-deprivation areas.

Abstract:The transformation of cities towards healthy urban living environments for all is a challenge that needs to be addressed through collaboration of all relevant sectors in a transdisciplinary research processes. This paper reports on the design and showcase implementation of a methodological approach, named Interactive Spatial Understanding Support System (ISUSS), that is intended to support interactive knowledge co-production and integration among practitioners and researcher in a specific local context. The approach involves the combined use of interactive maps on a MapTable and a rich picture. The goal is to stimulate, articulate and map stakeholders' knowledge on environmental health issues to come to a shared problem understanding. Drawing on the rich seam of data gathered over the reflexive engagement with the participants in Dortmund, Germany, we explored incidences of a transdisciplinary process. Findings suggest that the approach has the potential to encourage communication and social learning geared towards a shared understanding of the holistic problem situation. Whilst locally embedded spatial knowledge was shared using interactive maps on the MapTable, the rich picture elicited issues linked to wider geographical scale as well as non-spatial drivers. The paper concludes discussing research needs to further explore the approach among various other groups, including citizens.

No abstract

Differential exposure to multiple environmental burdens and benefits and their distribution across a population with varying vulnerability can contribute heavily to health inequalities. Particularly relevant are areas with high cumulative burdens and high social vulnerability termed as “hotspots”. This paper develops an index-based approach to assess these multiple burdens and benefits in combination with vulnerability factors at detailed intra-urban level. The method is applied to the city of Dortmund, Germany. Using non-spatial and spatial methods we assessed inequalities and identified “hotspot” areas in the city. We found modest inequalities burdening higher vulnerable groups in Dortmund (CI = −0.020 at p < 0.05). At the detailed intra-urban level, however, inequalities showed strong geographical patterns. Large numbers of “hotspots” exist in the northern part of the city compared to the southern part. A holistic assessment, particularly at a detailed local level, considering both environmental burdens and benefits and their distribution across the population with the different vulnerability, is essential to inform environmental justice debates and to mobilize local stakeholders. Locating “hotspot” areas at this detailed spatial level can serve as a basis to develop interventions that target vulnerable groups to ensure a health conducive equal environment.

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

When evaluating the practices of public participation, one should understand how the participatory process is conceived and implemented. Although many studies have been conducted in this regard, there is hardly a study that used Sustainable Development Goals (SDGs) as the basis for evaluation. In this study, we examine the participatory process of a public participation practice in Indonesia, called Musrenbang, at the village level, applying an SDGs' based assessment. Using the case of the Deli Serdang district, we investigate the participatory process based on SDG indicators 11.3.2 and 16.7.2, applying a set of criteria suggested by various scholars. The results show a misalignment between the Musrenbang practice and the evaluation criteria due to key problems such as planning schedules that do not meet regulations, lack of knowledge integration and learning processes, as well as power struggles amongst stakeholders.