The Early Childhood Oral Health Impact Scale (ECOHIS) measures the impact of dental diseases on Oral Health-Related Quality of Life both in children and their families. The aim of this study was to develop a Chilean Spanish version of the ECOHIS that is conceptually equivalent to the original and to assess its acceptability, reliability and validity in the preschool population of Chile. The Chilean version of the ECOHIS was obtained through a process including forward and back-translation, expert panel, and cognitive debriefing interviews. To assess metric properties, a cross-sectional study was carried out in Carahue, Southern Chile (April–October 2016). Children younger than six years old without systemic diseases, disabilities or chronic medication from eleven public preschools were included. Parents were invited to complete the Chilean version of the ECOHIS, PedsQL™4.0 Generic Core and PedsQL Oral Health scales, and to answer global questions about their children’s general and oral health. A subsample was administrated ECOHIS a second time 14–21 days after. A clinical examination was performed to assess dental caries, malocclusion, and traumatic dental injuries. Reliability was evaluated using measures of internal consistency (Cronbach’s alpha) and reproducibility (Intraclass correlation coefficient - ICC). Construct validity was assessed by testing hypotheses based on available evidence about known groups and relationships between different instruments. The content comparison of the back-translation with the original ECOHIS showed that all items except one were conceptually and linguistically equivalent. The cognitive debriefing showed a suitable understanding of the Chilean version by the parents. In the total sample (n = 302), the ECOHIS total score median was 1 (IQR 6), floor effect was 41.6%, and ceiling effect 0%. Cronbach’s alpha was 0.89 and the ICC was 0.84. The correlation between ECOHIS and PedsQL™4.0 Generic Core was weak (r = 0.21), while it was strong-moderate (r = 0.64) with the PedsQL Oral Health scale. In the known groups comparison, the ECOHIS total score was statistically higher in children with poor than excellent/very good oral health (median 11.6 vs 0, p < 0.01), and in the high severity than in the caries-free group (median 8 vs 0.5, p < 0.01). No differences were found according to malocclusion and traumatic dental injuries groups. These results supported the feasibility, reliability and validity of the Chilean version of ECOHIS questionnaire for preschool children through proxy.

It is unclear how well self-rated oral health (SROH) reflects actual oral health status in the rural Australian population. Therefore, this study aimed to compare the clinically assessed oral health status and SROH of adults living in rural Australia. The data were from 574 participants who took part in the Crossroads II cross-sectional study. Three trained and calibrated dentists evaluated the oral health status of participants based on WHO criteria. SROH was assessed with the question ‘Overall, how would you rate the health of your teeth and gums?’, with a score ranging from excellent = 5 to poor = 1. A logistic regression analysis (LRA) was performed, allowing us to assess factors associated with SROH. The mean age of participants was 59.2 years (SD 16.3), and 55.3% were female. The key results from the LRA show poorer SROH in those with more missing teeth (OR = 1.05; 95% CI; 1.01–1.08), more decayed teeth (OR = 1.28; 95% CI: 1.11–1.46), and more significant clinical attachment loss of periodontal tissue (6mm or more) (OR = 2.63; 95% CI: 1.29–5.38). This study found an association between negative SROH and clinical indicators used to measure poor oral health status, suggesting that self-rated oral health is an indicator of oral health status. When planning dental healthcare programs, self-reported oral health should be considered a proxy measure for oral health status.

Objectives: To determine the prevalence of frailty among community-dwelling older adults in regional Victoria, Australia. Methods: Frailty status of 376 participants from the Crossroads II cross-sectional study was assessed by selected markers of frailty. The selected variables were psychometrically tested. Associations between frailty and socio-demographic, environmental and health factors were analysed using chi-square, ANOVA and binary logistic regression (BLR). Results: Estimated prevalence of frailty was 39.4%. BLR indicated that frailty decreased with higher educational attainment, (OR = .23; 95% CI: .10–.51) increased for divorced/separated participants (OR = 2.68; 95% CI: 1.29–5.56) and when having three (OR = 3.27; 95% CI: 1.07–9.98), four (OR = 7.20; 95% CI: 2.22–23.31) or five or more chronic conditions (OR = 9.18; 95% CI: 2.83–29.72). Discussion: Frailty in this Australian regional community-dwelling sample was higher than other studies conducted in urban areas of Australia. Present results highlight the importance of exploring the multidimensionality of the frailty construct to have a better understanding which factors are associated with the development of this syndrome.