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Improved Periodontal Disease Prevalence Estimates From Partial-Mouth Data Using Multiple Imputation

Abstract Number:

3494 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Lauren Harrell (1), Danielle LaVine (2), Thomas Belin (2), Vivek Shetty (3)

Institutions:

(1) Google, N/A, (2) University of California-Los Angeles, California, (3) Section of Oral & Maxillofacial Surgery, Department of Biomedical Engineering, University of Califor, California

Co-Author(s):

Danielle LaVine  
University of California-Los Angeles
Thomas Belin  
University of California-Los Angeles
Vivek Shetty  
Section of Oral & Maxillofacial Surgery, Department of Biomedical Engineering, University of Califor

First Author:

Lauren Harrell  
Google

Presenting Author:

Danielle LaVine  
N/A

Abstract Text:

In oral-health epidemiological studies, protocols using partial-mouth periodontal examination (PMPE), where pocket depth and tooth attachment are not assessed at all potential measurement sites, can reduce research costs and participant response burden. But without considering the PMPE structure, simple data summaries tend to underestimate the extent and severity of periodontal disease. Viewing the PMPE structure as inducing a missing-data problem, we outline methods for estimating periodontal disease prevalence using multiple imputation. Specifically, we apply Centers for Disease Control/ American Academy of Periodontology (CDC-AAP) periodontal-disease criteria to data from newly recruited methamphetamine users who received either partial or full-mouth periodontal examinations, making use of a sample with similar background characteristics from the National Health and Nutrition Examination Survey (NHANES) where participants all had full-mouth examinations. Estimates that did not account for PMPE data collection were biased downward, while the proposed strategy succeeded in mitigating bias in prevalence estimates, underscoring the utility of the multiple-imputation framework.

Keywords:

Dentistry|Oral health|Missing data|Epidemiology|Periodontitis|Public health

Sponsors:

Biometrics Section

Tracks:

Missing Data

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