ABSTRACT
The practice pattern of pediatric dentistry has been changing for the last several decades. This change might be influenced by several factors such as development in dental materials and socioeconomic changes. The purpose of this study was to analyze the changing trends of patient distribution and treatment pattern of pediatric dentistry.Patient distribution and practice trends from 2006 to 2015 at the department of pediatric dentistry of Seoul National University Dental Hospital were reviewed. From 2006 to 2015, the proportion of new patient increased from 12.49% to 20.56%. The average age of new patients decreased. In 2006, restorative treatment had highest percentage, followed by preventive treatment, orthodontic treatment, surgical treatment, and pulp treatment. In 2015, preventive treatment had highest percentage, followed by restorative treatment, orthodontic treatment, surgical treatment and pulp treatment Frequency of general anesthesia increased more than 5 times for last 10 years. The proportion of insurance treatment decreased until 2009, and after 2010 it increased steadily.
Subject(s)
Humans , Anesthesia, General , Dental Materials , Insurance , Pediatric Dentistry , SeoulABSTRACT
Epidemiological parameters, such as age-dependent force of infection and average age at infection (
) were estimated for rubella, varicella, rotavirus A, respiratory syncytial virus, hepatitis A and parvovirus B19 infections for a non-immunized Brazilian community, using the same sera samples. The for the aforementioned diseases were 8.45 years (yr) [95 percent CI: (7.23, 9.48) yr], 3.90 yr [95 percent CI: (3.51, 4.28) yr], 1.03 yr [95 percent CI: (0.96, 1.09) yr], 1.58 yr [95 percent CI: (1.39, 1.79) yr], 7.17 yr [95 percent CI: (6.48, 7.80) yr] and 7.43 yr [95 percent CI: (5.68, 9.59) yr], respectively. The differences between average ages could be explained by factors such as differences in the effectiveness of the protection conferred to newborns by maternally derived antibodies, competition between virus species and age-dependent host susceptibility. Our seroprevalence data may illustrate a case of the above-mentioned mechanisms working together within the same population.
Subject(s)
Adolescent , Adult , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Young Adult , Virus Diseases/epidemiology , Brazil/epidemiology , Monte Carlo Method , Prevalence , Seroepidemiologic Studies , Virus Diseases/immunology , Young AdultABSTRACT
This study is aimed to design software to calculate and administer database ‘Sport performance of some Olympic champions’, firstly manage sport performance of 624 Olympic champions in order to calculate their average age. Data was collected by 936 information reports of performance. Results showed that average age of champions was 23.9 years old. This average age was analysed according to continents, countries, and sports