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Journal of Dental Research, Vol 72, 544-551, Copyright © 1993 by International & American Associations for Dental Research Online Journals


ARTICLES

Familial aggregation of periodontal indices

T. H. Beaty, C. R. Colyer, Y. C. Chang, K. Y. Liang, J. C. Graybeal, N. K. Muhammad and L. S. Levin
Johns Hopkins School of Hygiene & Public Health, Department of Epidemiology, Baltimore, Maryland 21205.

Analysis of three measures of periodontal health (plaque index, gingival index, and attachment loss) was carried out on 178 individuals in 75 families examined as part of a family study of periodontal health. Original participants in this study were volunteers recruited from the University of Maryland Dental Clinic, and were selected independently of any specific dental disease or condition. Relatives were invited to participate in the family study so that the extent of familial aggregation of indices of periodontal health could be assessed. By means of an analysis of variance model for persons nested within families, evidence for familial aggregation of plaque index was found both before and after adjustment for covariates such as age, gender, race, and reported oral hygiene habits. While a substantial fraction of variance in gingival index and attachment loss was also due to differences among families, neither attained statistical significance in these data. Examination of familial correlations (e.g., parent-offspring, sib-sib, spouse correlations) confirmed that plaque index showed greater familial resemblance compared with other measures of periodontal health. Both mean gingival index and mean attachment loss showed a stronger correlation between mothers and offspring compared with fathers and offspring. This suggests that further analysis of models for separating genetic and environmental effects may be appropriate for plaque index, but complete analysis of other periodontal indices will require more flexible statistical models for separation of genetic and cultural inheritance while considering gender-specific expression and transmission, as well as incorporation of information from covariates.





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