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Provide names of other journalists involved.

Angus Shafer, graphics journalist Kevin Wiatrowski, data journalist Jeff Scullin, editor Kim Franke-Folstad, editor

List date(s) this work was published or aired.

April 6, 2011 (online) and April 10, 2011 (print)

See this entry.

Provide a brief synopsis of the story or stories, including any significant findings.

My project examined the environmental factors that can affect children from becoming healthy. I was able to quantify some assumptions about the correlation between poverty and obesity by using body-mass index data from our local school district. I also mapped these BMI rates with food deserts, fast-food restaurants, grocery stores and parks.

Explain types of documents, data or Internet resources used. Were FOI or public records act requests required? How did this affect the work?

Florida is one of a handful of states that requires its school district to record body mass index (1st, 3rd and 6th grade). I filed an FOI request for the numbers, but quickly began to realize the district keeps pretty poor records. The results were incomplete, but still helped paint a snapshot of the childhood obesity problem in our area. The district did not keep the past year’s records from the schools — and was still in the process of measuring and weighing students when I requested the information. But gathering and making sense of thousands of data entries was one of my project’s biggest — and most rewarding — challenges. I also gathered data on fast-food restaurants from the state’s division of business regulation agency. The data from the grocery stores mostly came from a research firm. The GIS maps from parks came from a mix of our county’s GIS department and the state of Florida’s. The maps of food deserts were given to me by Philadelphia-based think tank, The Reinvestment Fund.

Explain types of human sources used.

For my project, I talked to several people in the county health department. I also talked involved in wellness interventions within the community, as well as children in the county. I also talked to public health experts in our community, as well as nationally.

Results:

With all of the information on the map, it was clear to see that the assumptions that socioeconomic status correlates to higher rates of obesity. The map did give us one unexpected result. We anticipated that fast-food restaurants would be more abundant in low-income areas. We were wrong. They’re pretty evenly distributed across socioeconomic levels in our area.

Follow-up (if any). Have you run a correction or clarification on the report or has anyone come forward to challenge its accuracy? If so, please explain.

No. I actually received lots of positive feedback from the health department.

Advice to other journalists planning a similar story or project.

I advise any journalist working on a data-driven project to anticipate hitting snags when gathering the raw information. It will happen. Try and talk to the data geeks and not the public information flaks, because many times the communications officer won’t know that the data already exists, but the geeks will.