title: Predictive power of the severity measure of attachment loss for periodontal care need.
abstract: BACKGROUND
  The prevalence of periodontal diseases is high, and >15% of adults have severe gum disease. Clinical attachment loss (AL) is one of the most important measures for periodontal disease severity. With AL, one could measure the worst scenario, the average, or the cumulative sum of AL among all teeth. The objective of this study is to evaluate which of the 15 measures of periodontal problems (e.g., maximum, mean, and cumulative AL) best predict the need for periodontal treatment.
  
  
  METHODS
  Using detailed periodontal data obtained through clinical examination from the National Health and Nutrition Examination Survey 1999 to 2002, weighted logistic regression was used to model the periodontal treatment need of 15 different periodontal disease measures. The outcome measure is the clinically determined periodontal need.
  
  
  RESULTS
  After adjustment for the covariates of age, sex, ethnicity, education, smoking status, and diabetes, the three most predictive measures were identified as: 1) the sum of the maximum mid-buccal (B) and mesio-buccal (MB) measures, which reflects the worst case of both B and MB measures; 2) the sum of the maximum MB measure or the worst case of the MB measure; and 3) the sum of all B and MB measures, or the cumulative AL measures.
  
  
  CONCLUSIONS
  Cumulative periodontal morbidity, particularly the worst case of B and MB measures, has the strongest impact on the need for periodontal care. All the demographic variables and covariates follow the classic pattern of association with periodontal disease.
authors.affiliation: Division of Public Health and Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, CA.
authors.forename: Honghu
authors.initials: H
authors.lastname: Liu
authors.forename: Marvin
authors.initials: M
authors.lastname: Marcus
authors.forename: Carl A
authors.initials: CA
authors.lastname: Maida
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.forename: Jie
authors.initials: J
authors.lastname: Shen
authors.forename: Vladimir W
authors.initials: VW
authors.lastname: Spolsky
mesh_terms: D000293:Adolescent; D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D016301:Alveolar Bone Loss / Q000145:classification; D003920:Diabetes Mellitus / Q000145:classification; D004522:Educational Status; D005260:Female; D005544:Forecasting; D005889:Gingival Recession / Q000145:classification; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D020380:Needs Assessment / Q000706:statistics & numerical data*; D017622:Periodontal Attachment Loss / Q000145:classification*; D010512:Periodontal Index; D010514:Periodontal Pocket / Q000145:classification; D011236:Prediabetic State / Q000145:classification; D012737:Sex Factors; D012907:Smoking; D044465:White People / Q000706:statistics & numerical data; D055815:Young Adult