The relationship between alveolar bone height and age in the primary dentition. A retrospective longitudinal radiographic study. 1995

L Shapira, and E Tarazi, and L Rosen, and E Bimstein
Department of Periodontics, Hebrew University, Hadassah Faculty of Dental Medicine, Jerusalem, Israel.

The natural history of changes in attachment level in the primary dentition should be determined before considering diagnostic criteria for periodontal diseases in children. The present study was designed to describe longitudinal changes in the distance between the alveolar bone crest and the cementoenamel junction (ABC-CEJ) determined radiographically. Bite-wing radiographs were obtained from 33 children as part of a routine annual dental examination in a rural community. The ABC-CEJ distance of 1500 sites located at the mesial and distal aspects of primary molars and distal aspect of primary cuspids were measured. An analysis of variance model was used to assess the effect of age, sex, tooth, side of the mouth, jaw, site and patient on the ABC-CEJ measurements. The side of the mouth (left, right) and the site (mesial, distal) had no significant effect on the ABC-CEJ distance. ABC-CEJ distances in the upper jaw were greater than in the lower jaw, and different teeth exhibited different ABC-CEJ distances. Canines had the greatest distance and second molars the smallest. The most interesting relationship was between alveolar bone height and age. The overall ABC-CEJ distance seemed to increase with age; however, this was not a linear relationship but followed the pattern of facial growth, with two spurts separated by a period of minimal increase. The results indicate that different levels of ABC-CEJ distance might be considered as a cut-off value for radiographic diagnosis of alveolar bone loss at different ages, for different primary teeth and for different jaws.

UI MeSH Term Description Entries
D008137 Longitudinal Studies Studies in which variables relating to an individual or group of individuals are assessed over a period of time. Bogalusa Heart Study,California Teachers Study,Framingham Heart Study,Jackson Heart Study,Longitudinal Survey,Tuskegee Syphilis Study,Bogalusa Heart Studies,California Teachers Studies,Framingham Heart Studies,Heart Studies, Bogalusa,Heart Studies, Framingham,Heart Studies, Jackson,Heart Study, Bogalusa,Heart Study, Framingham,Heart Study, Jackson,Jackson Heart Studies,Longitudinal Study,Longitudinal Surveys,Studies, Bogalusa Heart,Studies, California Teachers,Studies, Jackson Heart,Studies, Longitudinal,Study, Bogalusa Heart,Study, California Teachers,Study, Longitudinal,Survey, Longitudinal,Surveys, Longitudinal,Syphilis Studies, Tuskegee,Syphilis Study, Tuskegee,Teachers Studies, California,Teachers Study, California,Tuskegee Syphilis Studies
D008297 Male Males
D009811 Odontometry Measurement of tooth characteristics.
D012016 Reference Values The range or frequency distribution of a measurement in a population (of organisms, organs or things) that has not been selected for the presence of disease or abnormality. Normal Range,Normal Values,Reference Ranges,Normal Ranges,Normal Value,Range, Normal,Range, Reference,Ranges, Normal,Ranges, Reference,Reference Range,Reference Value,Value, Normal,Value, Reference,Values, Normal,Values, Reference
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002648 Child A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL. Children
D002675 Child, Preschool A child between the ages of 2 and 5. Children, Preschool,Preschool Child,Preschool Children
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000367 Age Factors Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time. Age Reporting,Age Factor,Factor, Age,Factors, Age

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