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Mobility is a key aspect of active ageing enabling participation and autonomy into later life. Remaining active brings multiple physical but also social benefits leading to higher levels of well-being. With globally increasing levels of urbanisation alongside demographic shifts meaning in many parts of the world this urban population will be older people, the challenge is how cities should evolve to enable so-called active ageing. This paper reports on a co-design study with 117 participants investigating the interaction of existing urban spaces and infrastructure on mobility and well-being for older residents (aged 55 + years) in three cities. A mixed method approach was trialled to identify locations beneficial to subjective well-being and participant-led solutions to urban mobility challenges. Spatial analysis was used to identify key underlying factors in locations and infrastructure that promoted or compromised mobility and well-being for participants. Co-designed solutions were assessed for acceptability or co-benefits amongst a wider cross-section of urban residents (n = 233) using online and face-to-face surveys in each conurbation. Our analysis identified three critical intersecting and interacting thematic problems for urban mobility amongst older people: The quality of physical infrastructure; issues around the delivery, governance and quality of urban systems and services; and the attitudes and behaviors of individuals that older people encounter. This identified complexity reinforces the need for policy responses that may not necessarily involve design or retrofit measures, but instead might challenge perceptions and behaviors of use and access to urban space. Our co-design results further highlight that solutions need to move beyond the generic and placeless, instead embedding specific locally relevant solutions in inherently geographical spaces, populations and processes to ensure they relate to the intricacies of place. [ABSTRACT FROM AUTHOR]

An established body of research has used secondary data sources (such as proprietary business databases) to demonstrate the importance of the neighborhood food environment for multiple health outcomes. However, documenting food availability using secondary sources in low-income urban neighborhoods can be particularly challenging since small businesses play a crucial role in food availability. These small businesses are typically underrepresented in national databases, which rely on secondary sources to develop data for marketing purposes. Using social media and other crowdsourced data to account for these smaller businesses holds promise, but the quality of these data remains unknown. This paper compares the quality of full-line grocery store information from Yelp, a crowdsourced content service, to a "ground truth" data set (Detroit Food Map) and a commercially-available dataset (Reference USA) for the greater Detroit area. Results suggest that Yelp is more accurate than Reference USA in identifying healthy food stores in urban areas. Researchers investigating the relationship between the nutrition environment and health may consider Yelp as a reliable and valid source for identifying sources of healthy food in urban environments. [ABSTRACT FROM AUTHOR]

Allostatic load (AL) is an aggregate measure of wear and tear on the body due to the chronic activation of the stress response system. The goal of this study was to examine the association between racially motivated housing discrimination (HD) and AL score within a sample of Indigenous university students. Data for this cross-sectional study were collected from Indigenous adults attending university in a small city in western Canada between 2015 and 2017 (N = 104; mean age = 27.8 years). An item adapted from the Experience of Discrimination Scale was to assess racially motivated HD in the past 12 months. AL was measured as a composite of 7 biomarkers assessing neuroendocrine, cardiovascular, metabolic, and immune system function. Bias-corrected and accelerated bootstrapped linear regression models were used to examine associations adjusting for age, income, parenthood, and other situations in which discrimination had been experienced. Indigenous university students who experienced racially motivated HD in the past year (16.8% of the sample) had an average AL score of approximately 4, which was almost double that of their peers who had not. In an adjusted model, racially motivated HD was associated with a 1.5 point increase in AL score. This model explained 35% of the adjusted variance in AL score, of which racially motivated HD explained 24%. These results suggest Indigenous adults who experienced racially motivated HD in the past year had early and more pronounced wear and tear on neuroendocrine, cardiovascular, metabolic, and immune system functioning in young and middle adulthood than Indigenous peers who did not. These findings combine with others to highlight the need for increased efforts to prevent racially motivated HD in urban centers. [ABSTRACT FROM AUTHOR]

Approximately 1000 people are killed by police acting in the line of duty each year. Historically, research on these deaths, known as legal intervention homicides (LIH), has been limited by data that is either contextually rich but narrow in scope and not readily available to the public (e.g., police department reports from a single city), or detail-poor but geographically broad, large, and readily available (and maintained by federal agencies) (e.g., vital statistics and supplemental homicide reports). Over the past 5 years, however, researchers have turned to the National Violent Death Reporting System (NVDRS), which captures nearly all lethal police shootings in participating states while providing detailed incident and victim information. The current study extends prior work on police-involved lethal shootings in three important ways. First, we use latent class analysis to construct a data-driven, exhaustive, mutually exclusive typology of these events, using NVDRS data 2014-2015. Second, rather than fitting some, but not all cases into predefined sub-types, every case is assigned membership to a particular emergent class. Third, we use a validated case identification process in NVDRS to identify incidents of lethal police-involved shootings. Seven classes emerge. Classes differ across important incident and victim characteristics such as the event that brought the victim and law enforcement together, the highest level of force used by the victim against law enforcement, and the kind of weapon, if any, used by the victim during the incident. Demographic variables do not distribute uniformly across classes (e.g., the latent class in which the victim appeared to pose minimal threat to law enforcement was the only class in which the plurality of victims was a non-white race). Our approach to generating these typologies illustrates how data-driven techniques can complement subjective classification schemes and lay the groundwork for analogous analyses using police encounter data that include fatal and non-fatal outcomes. [ABSTRACT FROM AUTHOR]