OBJECTIVE: The aim of this study was to describe differences in dental attendance and dental self-care behaviour between socioeconomic groups and to investigate the extent to which the socioeconomic gradient in oral health was explained by these behaviours. METHODS: We used data from a representative sample of adults in Australia, surveyed by telephone interview and by self-complete questionnaire. The dependent variables were self-reported missing teeth and the social impact of oral conditions evaluated with the 14-item Oral Health Impact Profile (OHIP-14). Socioeconomic position was measured at the small-area level. We conducted bivariate analysis using one-way analysis of variance and 95% confidence intervals (95% CI) and adjusted for the effect of age. After adjusting for age, dental behavioural variables were entered individually into multivariate linear regression models. RESULTS: Data were obtained for 3678 dentate adults aged 18-91 years. Missing teeth and OHIP-14 scores followed a social gradient with poorer adults experiencing poorer outcomes. Routine dental attendance and diligent dental self-care were associated with inverse monotonic gradients in missing teeth (P < 0.05) and OHIP-14 scores (P < 0.05). Although adults living in areas with the least disadvantage had a preventive dental attendance orientation, no socioeconomic pattern was found for dental self-care. In multivariate analysis, the slope of the socioeconomic gradient [beta estimate for Index of Relative Socioeconomic Disadvantage (IRSD)] in missing teeth was not significantly attenuated by either dental attendance or dental self-care. For OHIP-14 scores, the slope of the socioeconomic gradient was significantly attenuated by dental visiting, but not by dental self-care and not by the combined effect of both behaviours. CONCLUSION: The commonly held view that the poor oral health of poor people is explained by personal neglect was not supported in this study.
OBJECTIVE: The aim of this study was to describe differences in dental attendance and dental self-care behaviour between socioeconomic groups and to investigate the extent to which the socioeconomic gradient in oral health was explained by these behaviours. METHODS: We used data from a representative sample of adults in Australia, surveyed by telephone interview and by self-complete questionnaire. The dependent variables were self-reported missing teeth and the social impact of oral conditions evaluated with the 14-item Oral Health Impact Profile (OHIP-14). Socioeconomic position was measured at the small-area level. We conducted bivariate analysis using one-way analysis of variance and 95% confidence intervals (95% CI) and adjusted for the effect of age. After adjusting for age, dental behavioural variables were entered individually into multivariate linear regression models. RESULTS: Data were obtained for 3678 dentate adults aged 18-91 years. Missing teeth and OHIP-14 scores followed a social gradient with poorer adults experiencing poorer outcomes. Routine dental attendance and diligent dental self-care were associated with inverse monotonic gradients in missing teeth (P < 0.05) and OHIP-14 scores (P < 0.05). Although adults living in areas with the least disadvantage had a preventive dental attendance orientation, no socioeconomic pattern was found for dental self-care. In multivariate analysis, the slope of the socioeconomic gradient [beta estimate for Index of Relative Socioeconomic Disadvantage (IRSD)] in missing teeth was not significantly attenuated by either dental attendance or dental self-care. For OHIP-14 scores, the slope of the socioeconomic gradient was significantly attenuated by dental visiting, but not by dental self-care and not by the combined effect of both behaviours. CONCLUSION: The commonly held view that the poor oral health of poor people is explained by personal neglect was not supported in this study.
Authors: A E Sanders; G D Slade; M T John; J G Steele; A L Suominen-Taipale; S Lahti; N M Nuttall; P Finbarr Allen Journal: J Epidemiol Community Health Date: 2009-04-06 Impact factor: 3.710