How does indirect air-cooling influence pulp chamber temperature in different volume teeth and absence/presence of resin-based composite during light curing?

Background Light-curing of materials during restorative dental procedures poses a risk for pulp tissue overheating. Therefore, the aim of this study was to investigate the effect of indirect air-cooling on pulp chamber temperatures during light-curing of varying volume teeth and absence/presence of resin-based composite (RBC) at different exposure time. Methods The volume of 11 human teeth was measured by micro computed tomograph. An experimental rig controlled the thermal environment of the teeth and a thermocouple inserted retrograde into the root canal measured temperature changes. Pulp chamber temperature was measured with and without air-cooling on teeth without and with RBC at 15 s, 30 s and 60 s intervals. Generalized estimating equations were used for statistical analysis. Results The temperature increase with air-cooling (versus no air-cooling) was lower in teeth despite absence/presence of RBC (β = − 4.26, 95%CI − 5.33 and β = − 4.47, 95%CI − 5.60, respectively). With air-cooling, the temperature increase in teeth with RBC was lower compared to teeth without RBC (β = − 0.42, 95%CI -0.79; − 0.05). Higher teeth volume resulted in lower temperature increase with air-cooling than without air-cooling (β = − 0.04, 95%CI -0.07; − 0.01 and β = − 0.17, 95%CI -0.30; − 0.05, respectively). Conclusions Air-cooling resulted in lower pulp chamber temperature increase. Using air-cooling, the temperature increase was lower in teeth with RBC compared to teeth without RBC. Lower volume teeth resulted in higher temperature increase, thus they seemed to benefit more from air-cooling compared to higher volume teeth. Air-cooling could be an effective tool in controlling pulp temperature increase during light-curing, especially when the tooth volume is small

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks