G D Slade1, S A Gansky, A J Spencer. 1. Department of Dental Ecology, University of North Carolina, Chapel Hill 27599-7450, USA.
Abstract
UNLABELLED: 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% CI = 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.
UNLABELLED: 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% CI = 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.
Authors: Christopher Bole; Jean Wactawski-Wende; Kathleen M Hovey; Robert J Genco; Ernest Hausmann Journal: Community Dent Oral Epidemiol Date: 2010-12 Impact factor: 3.383
Authors: Jan E Clarkson; Nigel B Pitts; Beatriz Goulao; Dwayne Boyers; Craig R Ramsay; Ruth Floate; Hazel J Braid; Patrick A Fee; Fiona S Ord; Helen V Worthington; Marjon van der Pol; Linda Young; Ruth Freeman; Jill Gouick; Gerald M Humphris; Fiona E Mitchell; Alison M McDonald; John Dt Norrie; Kirsty Sim; Gail Douglas; David Ricketts Journal: Health Technol Assess Date: 2020-11 Impact factor: 4.014