Assessment of familial patterns of microbial infection in periodontitis.
The purpose of this article is to review approaches to the assessment of familial patterns of microbial infection and disease in periodontitis, and to identify statistical methods appropriate to such considerations of family data. Previous studies have provided evidence for the presence of familial aggregation of periodontal pathogens and periodontitis and have alluded to possible transmissibility of these organisms within families. Modern statistical techniques permit the appropriate analysis of the correlated data inherent in families, properly allowing for these statistical dependencies while including the possibility of adjustment for risk factors which may also aggregate in families. Such approaches as multiple linear regression, multivariate logistic regression, and regressive modeling provide the necessary tools to assess the familial aggregation of risk factors and disease in periodontitis. In particular, regressive models permit the analysis of familiality (membership to family) as a risk factor without reference to a specific underlying biologic mechanism, and also permit the possibility of adjustment for covariates, such as age and access to dental care. They also allow consideration of specific mechanisms, e.g., susceptibility genes of major effect. Using such techniques, it is possible to more completely explore and describe familial patterns of periodontal infection and other aspects of periodontal disease.
Irfan
U M
UM
Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH 44109-1998, USA.
Dawson
D V
DV
Bissada
N F
NF
D018562:Disease Transmission, Infectious; D005192:Family Health; D020022:Genetic Predisposition to Disease; D016905:Gram-Negative Bacterial Infections / Q000635:transmission*; D006801:Humans; D015233:Models, Statistical; D016017:Odds Ratio; D010518:Periodontitis / Q000453:epidemiology / Q000235:genetics / Q000382:microbiology*; D012044:Regression Analysis