County Profiles of Child Well-Being in Tennessee

Tennessee Index of Child Well-Being Methodology

As the Annie E. Casey Foundation’s (AECF’s) Tennessee partner, the Tennessee Commission on Children and Youth (TCCY) gathers county-level data on almost 100 indicators of child well-being and posts them to the KIDSCOUNT datacenter. Data available at the county level does not exactly mirror state-level data AECF uses for its rankings, but staff at TCCY chose 12 indicators, three in each domain, to make up its Index of Child Well-Being.

Economic Well-Being

·         Percent of children living in poverty

·         Median Household Income

·         Fair Market rent

Education

·         Percent of third- to eighth-grade students who scored as “proficient” or “advanced” on the TNReady reading and language test

·         Percent of third- to eighth-grade students who scored as “proficient” or “advanced” on the TNReady math test

·         Percent of students who graduated from high school based on the NCLB formula

Health

·         Percent of children who lack health insurance;

·         Percent of babies born at low birth weight

·         Rate (per 100,000) of children ages 1 to 19 who died from any cause;

Family & Community

·         Rate (per 1,000) of substantiated instances of child abuse or neglect;

·         Rate (per 1,000) of teens age 15 to 17 were pregnant at some point in the year;

·         Percent of students who were suspended at least once during the school year;

Indicators were chosen with a preference for measures of outcome rather than process. We tried to avoid using indicators that mostly measure the same thing (such as percent of children living in poverty and percent of children eligible for free and reduced-price lunch). We tried to avoid using indicators for which a “better” rate was ambiguous (a low rate of children receiving SNAP benefits could reflect low poverty rates or poor outreach). The indicators are different than those used in past years, so this year’s ranks are not directly comparable to those from previous years.

In previous rankings, we have used a three-year average to smooth changes over time, but this causes a lag between actions or policy that might move the indicators and that movement showing in the data. We have changed to one year of data serving as the basis for the rankings.

Because these rates are scaled differently (some are percent [or per 100], some are per 1,000 and some are per 100,000), they should not simply be summed to create an overall rank. In order to make them comparable, TCCY calculated the z-score for each indicator for each county, summed those for all twelve indicators and ranked the counties based on that total. Sums of the z-scores for the three indicators in each domain serve as the basis for each county’s domain ranks.

For each county, an indicator’s z-score represents the number of standard deviations the value of that indicator is from the average value for all counties. It is calculated as (the difference between a county’s percentage or rate on an indicator and the average value of all counties for that indicator) divided by (the standard deviation for that indicator). This is a common way to make variables or indicators that are measured in different units or have very different scales more comparable. For a full discussion of how to compute z-scores (aimed at non-mathematicians) see this WikiHow explanation.