Journal of urban health : bulletin of the New York Academy of Medicine
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Causal evidence regarding neighborhood effects on health remains tenuous. Given that children have little agency in deciding where they live and spend proportionally more of their lives in neighborhoods than adults, their exposure to neighborhood conditions could make their health particularly sensitive to neighborhood effects. In this paper, we examine the relationship between exposure to poor neighborhoods from birth to ages 4-10 and childhood asthma. ⋯ Our results demonstrate that [1] living in a poor neighborhood at baseline and follow-up and [2] moving into a poor neighborhood were each associated with higher risk of asthma, compared with children not living in a poor neighborhood at either time. Exposure to impoverished neighborhoods and downward neighborhood poverty mobility matters for children's health, particularly for asthma. Public health practitioners and policymakers need to address downward neighborhood economic mobility, in addition to downward family economic mobility, in order to improve children's health.
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Efforts to increase physical activity have traditionally included either individual-level interventions (e.g., educational campaigns) or neighborhood-level interventions (e.g., additional recreational facilities). Little work has addressed the interaction between spatial proximity and individual characteristics related to facility use. We aimed to better understand the synergistic impact of both physical activity environments and recreational facility membership on objectively measured physical activity. ⋯ Additionally, while amount of facilities within a neighborhood was associated with more physical activity, this association was stronger for individuals reporting gym membership. Interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership. Evaluation of neighborhood opportunities must expand beyond physical presence to consider multiple dimensions of accessibility.
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Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. ⋯ Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras.
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Approximately 25 million people in the United States are limited English proficient (LEP). Appropriate language services can improve care for LEP individuals, and health care facilities receiving federal funds are required to provide such services. Recognizing the risk of inadequate comprehension of prescription medication instructions, between 2008 and 2012, New York City and State passed a series of regulations that require chain pharmacies to provide translated prescription labels and other language services to LEP patients. ⋯ Our findings demonstrate a significant improvement in capacity of chains to assist LEP patients. A higher proportion of chain pharmacies surveyed in 2015 reported printing translated labels, access and use of telephone interpreter services, multilingual signage, and documentation of language needs in patient records. These findings illustrate the potential impact of policy changes on institutional practices that impact large and vulnerable portions of the population.
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Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However, questions remain as to how such indicators can be measured in a cost-effective way. ⋯ This paper aims to broaden perceptions about which types of datasets are available for health and development decision-making. For data scientists, we flag area-level indicators at city and sub-city scales identified by health decision-makers in the SDGs, Urban HEART, and other initiatives. For local health decision-makers, we summarize a menu of new datasets that can be feasibly generated from EO, mobile phone, and other spatial data-ideally to be made free and publicly available-and offer lay descriptions of some of the difficulties in generating such data products.