Linking, Exploring and Understanding Population Health Data
Jun 25, 2012, 1:00 PM, Posted by Michael Bader
By Michael Bader, PhD, an assistant professor of sociology at American University and an alumnus of the Robert Wood Johnson Foundation (RWJF) Health & Society Scholars program (2009-2011). His scholarship centers on racial and economic segregation and how unequal neighborhoods might lead to health and nutrition disparities. His recent research focuses on the ways in which people interact within the built environment and how to measure the built environment. This post is part of a series on the RWJF Health & Society Scholars program, running in conjunction with the program’s tenth anniversary. The RWJF Health & Society Scholars program is designed to build the nation’s capacity for research, leadership and policy change to address the multiple determinants of population health.
Data are the sustenance of population health research, and like the food that sustains us, it comes in many forms, shapes and sizes. Also like food, it's best appreciated in combination. A single data source in the absence of context is unfulfilling; but combining datasets that are rich with information and contours — now that's a meal!
One thing I've learned from collecting and interpreting population health data is that not all data sets are created equal. Pundits of late adore "big data"—the troves of market, network and geographic data extracted from our social media accounts. Population health research must learn to harness these tools, while at the same time being careful to avoid blind acceptance of their value.
Google, Facebook and Twitter are in the business of making money, and they design their tools to do so. As a population health community, we must remain mindful of our effort to understand the entire population, not just the money-making part of it. To do that, we need to create our own infrastructure, rather than relying solely on datasets that, while often useful, were designed to serve other purposes.
My research focuses on how the neighborhoods we live in condition our everyday habits in ways that might promote or reduce nutritional health. I'm currently working with an interdisciplinary group of researchers from the RWJF Health & Society Scholars sites at Penn and Columbia to develop a more comprehensive archive of neighborhood conditions across the country. Using Google Street View, we've examined and then rated U.S. streets on the basis of their physical disorder, walkability and aesthetic attractiveness. We will continue our efforts this year by linking these neighborhood data to children's health outcomes.
Beyond our efforts to draw and analyze our own sample, we are also building a platform that would allow other researchers to draw their own sample and conduct their own research. When they do, we will ask them to contribute their data to an archive that would allow the field unprecedented access to big data on micro neighborhood environments.
In addition to making new datasets available in that fashion, we must also begin to pair data in inventive ways, across contexts. The Health & Society Scholars’ wise investment in cross-disciplinary research expanded the definition of contexts important to health. In addition to physicians' offices and hospitals, researchers now consider neighborhoods, schools, housing developments, exposure to marketing and social networks, and more. As we live our lives, we cross these domains daily. We live in one neighborhood, but cross others as we travel to school and work, and along the way we might stop in a local drug store to run an errand and be exposed to a marketing campaign. All of these places and experiences can potentially influence our health.
Population health needs archivists and curators who can help assemble data across these dimensions. Just as important, we need to track these data across time and place. Neighborhoods, after all, change. People move, for example, and businesses open and close. Indeed, a whole range of variables pertinent to population health may be in motion. If we don’t capture such data, and develop and maintain the tools to analyze it, we won’t be able to understand fully the relationship between such events, and their impact on population health.
Still, population health must not get lost in big data; we must also focus on tiny data obtained from ethnographers and qualitative researchers. Without the analyses of these data, we risk misunderstanding the everyday context of the populations we study. Without such knowledge, we can waste valuable resources designing interventions that target the wrong audience.
After spending much of my career quantitatively analyzing aggregated datasets to study neighborhood inequality and obesity, I learned qualitative methods during my two years as a Heath & Society Scholar. This summer I am launching a project to use these skills to discover how the everyday lives of residents enable or constrain their decisions about how they procure, prepare and consume food. Recent research on the influence "food deserts" have on obesity has been conflicting, so such information is key to being able to know what might lead to differences in obesity rates.
The Robert Wood Johnson Foundation's efforts enabled much of population health's progress on these topics. But, we cannot rest on our laurels. As a population health community, in order to meet the emerging needs of population health research, we must advocate for resources not traditionally funded by National Institutes of Health.
First, we must find money not only to link, but to maintain, integrated datasets that link people geographically and over time. Such work does not always fit tidily within the investigator-initiated model of funding individual projects. It will require ongoing funding for infrastructure—especially personnel to help researchers link data from discrete datasets and to help them navigate the intricacies of data use agreements. It will also require a new level of trust among institutions and researchers unaccustomed to sharing data.
Second, we need strategic investment in quality qualitative research, the kind that does not always fit the traditional model of Study Aims. The best of such research leads to important discoveries that result from following paths unexpected at the outset. This type of research is relatively inexpensive, especially compared to clinical trials and population-level studies. Additionally, we must encourage NIH to be more proactive soliciting proposals from qualitative researchers and working with qualitative researchers to help them successfully apply for funding opportunities that already exist.
The RWJF Health & Society Scholars program, and RWJF as a whole, has been a leader in population health, and I hope through our continued efforts we can continue to push population health to better understand the influences, both big and small, on the health of the population.
This commentary originally appeared on the RWJF Human Capital Blog. The views and opinions expressed here are those of the authors.