Predicting dental treatment workload of U.S. military personnel

As the demographic composition of the U.S. armed forces shifts, so does dental treatment workload (DTW). To date, the effects of such shifts on DTW have been speculative. This study seeks to build regression models to predict the DTW of recruit and active duty military personnel as service demographic factors shift. The data come from a 1994-1995 random sample of 13,050 active duty and 2,711 recruit personnel. Dental treatment needs were charted for all participants. Patient demographic variables--age, sex, race, education, branch of service, and annual dental utilization (for all); home region and marital status (recruits only); and rank (active duty only)--were noted. Treatment needs were converted to composite time values. Respondent demographic factors were regressed on composite time values to determine which factors influence DTW using backward, stepwise, linear regression. Results show that DTW varies across demographic categories. The magnitude and direction of change in DTW as service demographic variables shift can be predicted with linear regression models.