Community Indicators for Your Community

Real, lasting community change is built around knowing where you are, where you want to be, and whether your efforts are making a difference. Indicators are a necessary ingredient for sustainable change. And the process of selecting community indicators -- who chooses, how they choose, what they choose -- is as important as the data you select.

This is an archive of thoughts I had about indicators and the community indicators movement. Some of the thinking is outdated, and many of the links may have broken over time.

Friday, August 24, 2007

Odds of Dying and Years of Potential Life Lost

I came across a couple of interesting tools in search of an indicator more meaningful and scalable than life expectancy. The problem with life expectancy as a community indicator is that many communities are simple too small in terms of population to get a meaningful life expectancy with a margin of error small enough to be able to observe differences. There are a number of personal life expectancy calculators available, but they don't usually address community characteristics.

Besides, if you're working on a neighborhood indicator project, do you really want to do this kind of math?

One alternative is to measure Years of Potential Life Lost. The advantages to this measure are that you can deal with smaller populations with fairly real-time data using straightforward calculations. It also gives heavier weight in your community to those who die young. More about this measure can be found here.

The major problem with YPLL as an indicator is that it takes a moment to explain -- the indicator isn't immediately accessible to the reader/viewer. A different measure, Odds of Dying, has the advantage of grabbing the imagination quickly.

The National Safety Council and National Geographic published a chart on the odds of dying. As the great American philosopher Jim Morrison reminds us, the odds of dying are 1:1 -- "no one here gets out alive." But how we go -- now that's interesting.

Swivel has the data sets available for the NSC calculations for you to play with. You can also see sample charts people have created using the data. For a different tabular list of the data, see this site.

Of course, you can take odds-of-dying calculations to the ridiculous, as these folks have done. but what I think is interesting is using the methodology to look at causes of deaths in your community and the odds of dying. You could use rolling averages if necessary to examine gender or racial disparities in odds of dying.

Have you used these measures before? What do you think about their possibilities?


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