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Two‐year incidence of tooth loss among South Australians aged 60+ years
Author(s) -
Slade Gary D.,
Gansky Stuart A.,
Spencer A. John
Publication year - 1997
Publication title -
community dentistry and oral epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.061
H-Index - 101
eISSN - 1600-0528
pISSN - 0301-5661
DOI - 10.1111/j.1600-0528.1997.tb01734.x
Subject(s) - medicine , tooth loss , logistic regression , incidence (geometry) , demography , confidence interval , dentistry , relative risk , clinical attachment loss , cohort study , population , gingival recession , cohort , periodontitis , oral health , environmental health , physics , sociology , optics
Tooth loss diminishes oral function and quality of life, and national health targets aim to reduce population levels of tooth loss. Objectives: The purpose of this study was to determine tooth loss incidence and predictors of tooth loss among older adults in South Australia. Methods: Data were obtained from a cohort study of a stratified random sample of community‐dwelling dentate people aged 60+ years. Interviews and oral examinations were conducted among 911 individuals at baseline and among 693 of them (76.1%) 2 years later. Incidence rates and relative risks were calculated for population subgroups and multivariate logistic regression was used to construct risk prediction models. A method was developed to calculate 95% confidence intervals (95% CI) for relative risks (RR) from logistic regression models using a Taylor series approximation. Results: Some 19.5% (95% CI = 15.4‐23.6%) of people lost one or more teeth during the 2 years. Men, people with a recent extraction, people who brushed their teeth infrequently, smokers and people born outside Australia had significantly ( P <0.05) greater risk of tooth loss. Baseline clinical predictors of tooth loss included more missing teeth, retained roots, decayed root surfaces, periodontal pockets and periodontal recession. In a multivariate model that controlled for baseline clinical predictors, former smokers (RR = 2.55, 95% C1=1.48‐4.40) and current smokers (RR = 2.06, 95% CI=0.92‐4.62) had similarly elevated risks of tooth loss compared with non‐smokers. Conclusions: The findings from this population suggest that a history of smoking contributes to tooth loss through mechanisms in addition to clinical disease processes alone.