No abstract

While both materials provide similar success rates, the shorter treatment time with MTA may translate into higher overall success rates because of better patient compliance.

Dental care is consistently reported as one of the primary medical needs of children with disabilities (IDC). The aim of the present study was to explore the influence of oral health behaviors on the caries experience in children with intellectual disabilities in Guangzhou, China. A cross-sectional study was carried out in 477 intellectually disabled children, 12 to 17 years old, who were randomly selected from special educational schools in Guangzhou. A self-administered parental questionnaire was used to collect data on socio-demographic characteristics and oral health behavior variables, and 450 valid questionnaires were returned. Multiple regression analysis was used to examine the factors associated with dental caries. The average age of those in the sample was 14.6 years (SD = 1.3), 68.4% of whom were male, and the caries prevalence rate was 53.5% (DMFT = 1.5 ± 2.0). The factors significantly affecting the development of dental caries in IDC included gender, the presence or absence of cerebral palsy, and the frequency of dental visits and toothbrushing. In conclusion, the presence of cerebral palsy contributed to an increase risk of caries experience in intellectually disabled children, while toothbrushing more than twice a day and routine dental visits were caries-protective factors. Oral health promotion action may lead to a reduction in dental caries levels in IDC.

Motivated by regression analysis for microbiome compositional data, this article considers generalized linear regression analysis with compositional covariates, where a group of linear constraints on regression coefficients are imposed to account for the compositional nature of the data and to achieve subcompositional coherence. A penalized likelihood estimation procedure using a generalized accelerated proximal gradient method is developed to efficiently estimate the regression coefficients. A de-biased procedure is developed to obtain asymptotically unbiased and normally distributed estimates, which leads to valid confidence intervals of the regression coefficients. Simulations results show the correctness of the coverage probability of the confidence intervals and smaller variances of the estimates when the appropriate linear constraints are imposed. The methods are illustrated by a microbiome study in order to identify bacterial species that are associated with inflammatory bowel disease (IBD) and to predict IBD using fecal microbiome.