Journal of epidemiology and community health
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J Epidemiol Community Health · Dec 2017
A shared data approach more accurately represents the rates and patterns of violence with injury assaults.
To investigate whether sharing and linking routinely collected violence data across health and criminal justice systems can provide a more comprehensive understanding of violence, establish patterns of under-reporting and better inform the development, implementation and evaluation of violence prevention initiatives. ⋯ This study identified that violence is currently undermeasured, demonstrated the importance of continued sharing of routinely collected ED data and highlighted the benefits of using PID from a number of services in a linked way to provide a more comprehensive picture of violence.
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J Epidemiol Community Health · Dec 2017
Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample.
Preventing falls and fall-related injuries among older adults is a public health priority. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool was developed to promote fall risk screening and encourage coordination between clinical and community-based fall prevention resources; however, little is known about the tool's predictive validity or adaptability to survey data. ⋯ The adapted STEADI clinical fall risk screening tool is a valid measure for predicting future fall risk using survey cohort data. Further efforts to standardise screening for fall risk and to coordinate between clinical and community-based fall prevention initiatives are warranted.
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J Epidemiol Community Health · Nov 2017
A glossary for big data in population and public health: discussion and commentary on terminology and research methods.
The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. ⋯ We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms. We provide key distinctions between big data and statistical analysis methods applied to big data. We contextualise the glossary by providing examples where big data analysis methods have been applied to population and public health research problems and provide brief guidance on how to learn big data analysis methods.
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J Epidemiol Community Health · Nov 2017
Are green cities healthy and equitable? Unpacking the relationship between health, green space and gentrification.
While access and exposure to green spaces has been shown to be beneficial for the health of urban residents, interventions focused on augmenting such access may also catalyse gentrification processes, also known as green gentrification. Drawing from the fields of public health, urban planning and environmental justice, we argue that public health and epidemiology researchers should rely on a more dynamic model of community that accounts for the potential unintended social consequences of upstream health interventions. In our example of green gentrification, the health benefits of greening can only be fully understood relative to the social and political environments in which inequities persist. We point to two key questions regarding the health benefits of newly added green space: Who benefits in the short and long term from greening interventions in lower income or minority neighbourhoods undergoing processes of revitalisation? And, can green cities be both healthy and just? We propose the Green Gentrification and Health Equity model which provides a framework for understanding and testing whether gentrification associated with green space may modify the effect of exposure to green space on health.
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J Epidemiol Community Health · Nov 2017
Self-reported vision impairment and incident prefrailty and frailty in English community-dwelling older adults: findings from a 4-year follow-up study.
Little is known about vision impairment and frailty in older age. We investigated the relationship of poor vision and incident prefrailty and frailty. ⋯ Non-frail older adults who experience poor vision have increased risks of becoming prefrail and frail over 4 years. This is of public health importance as both vision impairment and frailty affect a large number of older adults.