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Data makes a difference -- even when you're swamped in it

Data makes a difference -- even when you're swamped in it

Picture of Daniela  Velazquez

As I got closer to finishing up my still-untitled fellowship project, my co-worker and I had already Christened it with a nickname befitting the reams of data I'd gathered sitting on Excel spreadsheets. (Warning: Geek alert ahead)

"V'Ger" became an all-encompassing job as it neared a completion. I thought might never happen, so my co-worker's suggestion to name it after the robotic antagonist in the 1979 Star Trek movie that assimilates everything in its path in its quest to evolve seemed beyond appropriate.

As you probably guessed, gathering and making sense of thousands of data entries was one of my project's biggest -- and most rewarding -- challenges.

My pitch was pretty broad: I intended to look at the factors that keep people of color from making healthy decisions.

I was set on figuring out ways to quantify as much as I could, not because I was a data hound (indeed, much of what I ended up doing was new to me) but because I wanted to buttress my stories with as many hard facts as I could find.

When I went to gather the data on obesity, I found that I could only get as local as my county.  But then I learned that Florida is one of a handful of states that requires its school district to record body mass index  (1st, 3rd and 6th grade).

This golden nugget led me to hone in on childhood obesity because I could then look at school data, which would give me some numbers to match to neighborhoods.

As happy as I was to find out this data existed, the joy quickly turned into frustration as I tried to get the data from the school district, which did not keep the past year's records from the schools -- and were still much in the process of measuring and weighing students.

Weeks turned into months. I eventually was literally able to get a hold of about 70 percent of the elementary schools and 10 percent of middle schools. The nursing coordinator gathered more than 100 forms with not all the same information and handed them to me. I then had to calculate the percentage of healthy and overweight kids by hand and plug them all into Excel.

This was the most tedious and stressful process, because I couldn't do much community reporting until I looked at where the heaviest kids were, which means I had to go through all those papers.

All this research paid off for the project and for our newsroom.

I was able to compile a map that included the demographics of every school, BMI (when available), every fast-food restaurant in our county, every grocery store, every public park and the food deserts (which The Reinvestment Fund so kindly sent to me in a map-friendly format).

After the stories were published, I got feedback from readers -- both parents and teachers -- who were grateful that we talked about what the school district was doing in regards to its nutrition program and physical education.

Without the collaboration from a data-savvy colleague and the graphics department, we never would've been able to put this together. But it definitely showed our newsroom has the chops to dream big and map bigger -- plus, it's provided an ongoing resource for the public (and any reporter) who wants to see a snapshot of their local community -- or the whole county -- in a comprehensive way.


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I'd love to see the results of your project! I'm amazed you were able to get hold of real data from school children without jumping through months worth of ethical hoops. I've been involved in research with both real humans and anonymous public health datasets for many years and its always a struggle to get projects approved so I can get my sweaty little hands on the data! You must reveal your secrets! I'm just finishing my MPH on drug dosing errors and pharmacogenetic testing in the South Australian hospital system. It took 5 months for ethical approval in the academic system, plus 4 more to get it from the public health system. I then waited 2 months for the first batch of data and I'm still waiting (16 months since I started) for the other public, anonymous data! If I can't get a job (its pretty unlikely) I'll probably use the 2nd batch of data to start a PhD. I'm interested (as you are) in methods of getting ordinary people to exercise more and eat good food. Information is all very well, but behaviour change is well-nigh impossible- we have to crack it to succeed.

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Are you correlating your data with the availability of things like drinking water in schools, access to fresh fruits and vegetables, safe & inviting parks nearby?

Picture of Daniela  Velazquez

Hi there -- I correlated the data with the location of fast-food restaurants and grocery stores. It was difficult to create county-wide indicators (i.e. I didn't go to every grocery store to see what they sold) but I included the number of employees per store, so you could imagine that a 2-employee store wouldn't have the same fresh produce offerings as a 150-person grocery store. Drinking water would be interesting to see, as would the new CDC report on hidden food environments.I did include a map layer for parks.

As for the secrets to getting the data, I had the Sunshine Law on my side because the schools are required by the state to gather that information, so it's all public record.

Here's the link where you can see the map, stories:


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