Assessing community variation and randomness in public health indicators

The authors compare the statistical performance of two heterogeneity measures applied to community differences that provide tests for randomness and measures of the percentage of true community variation, as well as estimates of the true variation. One measure comes from the meta-analysis literature and the other from the simple Pearson chi-square statistic. Simulations of populations and an example using real data are provided.The measure based on the simple chi-square statistic seems superior, offering better protection against Type I errors and providing more accurate estimates of the true community variance.The heterogeneity measure based on Pearson's χ2 should be used to assess indices. Methods for improving poor indices are discussed.Evidence-based health indicators are vital to needs-based or results-based programming. Agencies frequently make programming resources available to local jurisdictions based on need. In 2008, the United States Department of Health and Human Services distributed more than $421 million in Mental Health Block Grant funds based, in part, on the number of people at risk within each state [1]. Each state then disperses funds to local communities. The amount dispersed is often determined by a demonstrable index of need.The indicators used in public health funding contexts vary considerably. Common indices include census counts within a certain age group or the percentage of people reporting a particular behavior from a population-based surveillance survey, e.g., the percentage of people reporting binge drinking in the past 30 days. Mortality, arrest, remission, or recidivism rates are also commonly used by different funding agencies. US government agencies such as the Centers for Disease Control and Prevention provide yearly datasets such as the Behavioral Risk Factor Surveillance System (BRFSS) that include prevalence and trend data. State governments and other agencies support various other surveillance systems for local assessments. F