New distance-based exponential regression method and equations for estimating the chronology of linear enamel hypoplasia (LEH) defects on the anterior dentition

Objectives: We present a new distance-based exponential regression approach based on published histological data to refine the objectivity, accuracy, and precision of age estimates of LEH defect formation on the anterior dentition. Methods: Published histological data of anterior tooth crown growth for two samples (northern European and southern African) were fitted with exponential trendlines to construct exponential regression equations for each tooth type. A theoretical comparison of the age estimates produced by two commonly used methods (decile chart and linear regression), and those based on the exponential regression equations presented in this article were undertaken. Paired-samples t-tests were used to determine whether the estimates obtained by these methods differed significantly. Results: Exponential regression equations were able to accurately replicate age estimates produced by the decile-chart method. For defects that fell precisely on a decile, estimates differed by 1–23 days. Estimates based on the linear regression method were consistently younger by 4.5–16 months. For defects that fell within deciles, the exponential regression equation estimates, when different, were 12 days to 4 months older than those yielded by the decile method. Conclusions: By combining currently published histological data on anterior tooth crown growth with a regression approach, it is possible to produce more accurate age estimates than yielded by methods that do not rely on histological data. Furthermore, this approach also greatly improves the objectivity, precision and replicability of results, especially for defects that fall between deciles, when compared to the decile chart method.