Journal of urban health : bulletin of the New York Academy of Medicine
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Greenspace and socioeconomic status are known correlates of diabetes prevalence, but their combined effects at the sub-neighborhood scale are not yet known. This study derives, maps, and validates a combined socioeconomic/greenspace index of individual-level diabetes risk at the sub-neighborhood scale, without the need for clinical measurements. In two Canadian cities (Vancouver and Hamilton), we computed 4 greenspace variables from satellite imagery and extracted 11 socioeconomic variables from the Canadian census. ⋯ The DRI-GLUCoSE index was a significant predictor of diabetes status, exhibiting a small non-significant attenuation with the inclusion of dietary and physical activity variables. The final models achieved a predictive accuracy of 75%, the highest among environmental risk models to date. Our combined index of local greenspace and socioeconomic factors demonstrates that the environmental component of diabetes risk is not sufficiently explained by diet and physical activity, and that increasing urban greenspace may be a suitable means of reducing the burden of diabetes at the community scale.
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The effect of socio-economic factors, ethnicity, and other factors, on the morbidity and mortality of COVID-19 at the sub-population-level, rather than at the individual level, and their temporal dynamics, is only partially understood. Fifty-three county-level features were collected between 4/2020 and 11/2020 from 3,071 US counties from publicly available data of various American government and news websites: ethnicity, socio-economic factors, educational attainment, mask usage, population density, age distribution, COVID-19 morbidity and mortality, presidential election results, and ICU beds. We trained machine learning models that predict COVID-19 mortality and morbidity using county-level features and then performed a SHAP value game theoretic importance analysis of the predictive features for each model. ⋯ Thus, socio-economic features such as ethnicity, education, and economic disparity are the major factors for predicting county-level COVID-19 mortality rates. Between counties, low variance factors (e.g., age) are not meaningful predictors. The inversion of some correlations over time can be explained by COVID-19 spreading from urban to rural areas.
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Promoting active and healthy aging in urban spaces requires environments with diverse, age-friendly characteristics. This scoping review investigated the associations between urban characteristics and active and healthy aging as identified by citizen science (CS) and other participatory approaches. Using a systematic scoping review procedure, 23 articles employing a CS or participatory approach (participant age range: 54-98 years) were reviewed. ⋯ The CSAT demonstrated strengths related to active engagement of residents and study outcomes leading to real-world implications. To advance the potential of CS to enrich our understanding of age-friendly environments, employing co-production to enhance relevance and sustainability of outcomes is an important strategy. Overall, employing CS highlighted the value of systematically capturing the experiences of older adults within studies aimed at promoting active and healthy aging.
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Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. ⋯ NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.
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Unhoused people have higher COVID-19 mortality and lower vaccine uptake than housed community members. Understanding vaccine hesitancy among unhoused people is key for developing programs that address their unique needs. A three-round, rapid, field-based survey was conducted to describe attitudes toward COVID-19 vaccination. ⋯ After implementing a financial incentive program, 97.4% of participants who indicated interest in vaccination were vaccinated that day; the financial incentive was the most cited reason for vaccine readiness (n = 731, 56%). This study demonstrated the utility of an iterative, field-based assessment for program implementation during the rapidly evolving pandemic. Personal engagement, a variety of brand choices, and financial incentives could be important for improving vaccine uptake among unhoused people.