Methodological reviews, commentaries and meta analyses.

The BEH group has written methodological reviews, commentaries and systematic reviews.  These articles seek to synthesize findings from across the scientific literature and to set priorities and agendas for future research to understand how neighborhood conditions affect health.

Registry Data in Injury Research: Study Designs and Interpretation.” Injury data is frequently captured in registries that form a census of 100% of known cases that meet specified inclusion criteria. These data are routinely used in injury research with a variety of study designs. We reviewed study designs commonly used with injury registry data and evaluated the advantages and disadvantages of each design type.

Machine Learning Approaches for Measuring Neighborhood Environments in Epidemiologic Studies” Innovations in information technology, initiatives by local governments to share administrative data, and growing inventories of data available from commercial data aggregators have immensely expanded the information available to describe neighborhood environments, supporting an approach to research we call Urban Health Informatics. This review evaluates the application of machine learning to this new wealth of data for studies of the effects of neighborhood environments on health. In each domain, we highlight successes and cautions in the application of machine learning, particularly highlighting legal issues in applying machine learning approaches to Google’s geo-spatial data.

The Disclosure of Personally Identifiable Information in Studies of Neighborhood Contexts and Patient Outcomes” describes ways in which researchers inadvertently disclose patient and research participant’s health and identifying information to third parties when conducting neighborhood health effect research.

“Built environments and obesity in disadvantaged populations.” reviewed the literature on how obesity-related health disparities by race/ethnicity and socioeconomic status might relate to obesogenic built environments.

“Disparities in neighborhood food environments: implications of measurement strategies.” sought to model how neighborhood differences in vehicle ownership rates, public transit access, and impediments to pedestrian travel, such as crime and poor traffic safety, might exacerbate or reduce neighborhood disparities in access to supermarkets.  An earlier version of this paper was presented at a conference sponsored by the National Poverty Center at the University of Michigan.

“Steps Forward: Review and Recommendations for Research on Walkability, Physical Activity and Cardiovascular Health” describes the gaps in the current literature on neighborhood walkability and proposes an agenda for the next steps in research on how walkability affects health.

For common outcomes like obesity, the use of odds ratios should be viewed critically and cautiously.  “At Odds: Concerns Raised by Odds Ratios for Common Outcomes in Research on Physical Activity and Obesity”, describes the problems that occur in physical activity and obesity research when odds ratios are used to express effects or associations; information is lost when out come data are dichotomized and there is often a mismatch between the odds ratio scale and the scientific questions of interest. We describe how to calculate prevalence ratios as an alternative to odds ratios when working with common dichotomous outcomes.

Place-focused activity research can potentially improve health and social justice.  However, individuals are perceptive, critical, and deliberative in their behavioral responses, that is they have “agency”.  Place-focused Physical Activity Research, Human Agency, and Social Justice in Public Health: Taking Agency Seriously in Studies of the Built Environment”, describes how attention to human agency can improve the science and ethics of ongoing research.

 “There goes the neighborhood effect: bias owing to nondifferential measurement error in the construction of neighborhood contextual measures.”, describes how the validity of neighborhood health effects studies is threatened when there is measurement error in the underlying data used to construct a neighborhood contextual variable like neighborhood poverty rate.  We show that when individual’s responses to Census questions include measurement error, even non-differential measurement error, analyses of measures constructed from these data, such as neighborhood poverty rate, are biased away from the null.

“Methods to measure the impact of home, social, and sexual neighborhoods of urban gay, bisexual, and other men who have sex with men.”, describes the methods we are using to characterize residential, social and sexual neighborhoods of men who have sex with men.

Association of proximity and density of parks and objectively measured physical activity in the United States: A systematic review.” provides an overview of the literature investigating the impacts of neighborhood park access on physical activity.  We found that the data in this area are quite inconsistent and paper recommends strategies for further research, employing standardized reporting and innovative study designs to better understand the relationship of parks and physical activity.

“Protecting Personally Identifiable Information When Using Online Geographic Tools for Public Health Research” describes our concerns that the use of online geographic and data tools in neighborhood health research can cause the loss of anonymity for study subjects.

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