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.