AIM: To calculate age of transition of the mandibular third (M3) molar tooth stages from archived dental radiographs from sub-Saharan Africa, Malaysia, Japan and two groups from London UK (Whites and Bangladeshi).
MATERIALS AND METHODS: The number of radiographs was 4555 (2028 males, 2527 females) with an age range 10-25 years. The left M3 was staged into Moorrees stages. A probit model was fitted to calculate mean ages for transitions between stages for males and females and each ethnic group separately. The estimated age distributions given each M3 stage was calculated. To assess differences in timing of M3 between ethnic groups, three models were proposed: a separate model for each ethnic group, a joint model and a third model combining some aspects across groups. The best model fit was tested using Bayesian and Akaikes information criteria (BIC and AIC) and log likelihood ratio test.
RESULTS: Differences in mean ages of M3 root stages were found between ethnic groups, however all groups showed large standard deviation values. The AIC and log likelihood ratio test indicated that a separate model for each ethnic group was best. Small differences were also noted between timing of M3 between males and females, with the exception of the Malaysian group. These findings suggests that features of a reference data set (wide age range and uniform age distribution) and a Bayesian statistical approach are more important than population specific convenience samples to estimate age of an individual using M3.
CONCLUSION: Some group differences were evident in M3 timing, however, this has some impact on the confidence interval of estimated age in females and little impact in males because of the large variation in age.
METHODS: The aim of this paper is to describe informed consent regulations for dental care in a selection of countries, focusing on children and patients with special health care needs. An online survey was shared with a convenience sample of dental professionals from 13 countries. The information was explored and the processes of consent were compared.
RESULTS: Findings suggest that there are variations in terms of informed consent for medical practice. In Tanzania, South Africa, India, Kenya, Malaysia and Brazil age is the determining factor for competence and the ability to give self-consent. In other countries, other factors are considered alongside age. For example, in Singapore, the United Kingdom, and the United States the principle of Gillick Competence is applied. Many countries' laws and regulations do not specify when a dentist may overrule general consent to act in the "best interest" of the patient.
CONCLUSION: It is recommended that it is clarified globally when a dentist may act in the "best interest" of the patient, and that guidance is produced to indicate what constitutes a dental emergency. The insights gathered provide insights on international practice of obtaining informed consent and to identify areas for change, to more efficient and ethical treatment for children and patients with special needs. A larger follow up study is recommended to include more or all countries.
MATERIALS AND METHODS: The sample comprised 2,200 dentists from 21 countries. Three scales - Subjective Happiness Scale (SHS), Satisfaction With Life Scale (SWLS), and Affect Balance Scale (ABS) - were used to measure the subjective responses. Data related to demographic and social characteristics were recorded. Mann-Whitney and Kruskal-Wallis tests were used as appropriate. Scales were correlated, and multiple linear regression analyses were employed to identify the independent determinants of SHS, SWLS and ABS. Data were analysed using the SPSS software program; a value of P <0.05 was considered significant.
RESULTS: The overall mean scores of SHS, SWLS and ABS were 18.53 ± 5.06, 23.06 ± 6.25 and 1.26 ± 2.40, respectively, with significant differences found across countries: dentists working in Croatia, Peru and Serbia recorded the highest scores, unlike dentists practicing in Yemen, Syria, and Iraq, who recorded the lowest scores. There were significant, moderately positive correlations between the various scales: SHS and SWLS: r = 0.535, P
METHODOLOGY: Data was collected for this cross-sectional study between August 2020 and January 2021 from 11-to-23 years old participants in 43-countries using an electronic validated questionnaire developed in five languages. Data collected included information on the dependent variables (the presence of oral conditions- gingival inflammation, dry mouth, change in taste and oral ulcers), independent variable (COVID-19 infection) and confounders (age, sex, history of medical problems and parents' educational level). Multilevel binary logistic regression was used for analysis.
RESULTS: Complete data were available for 7164 AYA, with 7.5% reporting a history of COVID-19 infection. A significantly higher percentage of participants with a history of COVID-19 infection than those without COVID-19 infection reported having dry mouth (10.6% vs 7.3%, AOR = 1.31) and taste changes (11.1% vs 2.7%, AOR = 4.11). There was a significant effect modification in the association between COVID-19 infection and the presence of dry mouth and change in taste by age and sex (P = 0.02 and
OBJECTIVES: The aim of this study was to assess the self-reported presence of oral lesions by COVID-19-infected young adults and the differences in the association between oral lesions and COVID-19 infection in smokers and non-smokers.
METHODS: This cross-sectional multi-country study recruited 18-to-23-year-old adults. A validated questionnaire was used to collect data on COVID-19-infection status, smoking and the presence of oral lesions (dry mouth, change in taste, and others) using an online platform. Multi-level logistic regression was used to assess the associations between the oral lesions and COVID-19 infection; the modifying effect of smoking on the associations.
RESULTS: Data was available from 5,342 respondents from 43 countries. Of these, 8.1% reported COVID-19-infection, 42.7% had oral manifestations and 12.3% were smokers. A significantly greater percentage of participants with COVID-19-infection reported dry mouth and change in taste than non-infected participants. Dry mouth (AOR=, 9=xxx) and changed taste (AOR=, 9=xxx) were associated with COVID-19- infection. The association between COVID-19-infection and dry mouth was stronger among smokers than non-smokers (AOR = 1.26 and 1.03, p = 0.09) while the association with change in taste was stronger among non-smokers (AOR = 1.22 and 1.13, p = 0.86).
CONCLUSION: Dry mouth and changed taste may be used as an indicator for COVID-19 infection in low COVID-19-testing environments. Smoking may modify the association between some oral lesions and COVID-19-infection.
METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced.
RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes.
CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.