Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. 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.Peer reviewe

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. 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.Peer reviewe

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Comparative evaluation of tensile bond strength and microleakage of conventional glass ionomer cement, resin modified glass ionomer cement and compomer: An in vitro study

Aim: The purpose of this study was to evaluate and compare the tensile bond strength and microleakage of Fuji IX GP, Fuji II LC, and compoglass and to compare bond strength with degree of microleakage exhibited by the same materials. Materials and Methods: Occlusal surfaces of 96 noncarious primary teeth were ground perpendicular to long axis of the tooth. Preparations were distributed into three groups consisting of Fuji IX GP, Fuji II LC and Compoglass. Specimens were tested for tensile bond strength by mounting them on Instron Universal Testing Machine. Ninety-six primary molars were treated with Fuji IX GP, Fuji II LC, and compoglass on box-only prepared proximal surface. Samples were thermocycled, stained with dye, sectioned, and scored for microleakage under stereomicroscope. ANOVA and Bonferrani correction test were done for comparisons. Pearson Chi-square test and regression analysis were done to assess the association between the parameters. Results: Compoglass showed highest tensile strength and Fuji II LC showed least microleakage. There was a significant difference between the three groups in tensile strength and microleakage levels. The correlation between tensile strength and microleakage level in each group showed that there was a significant negative correlation only in Group 3. Conclusion: Fuji II LC and compoglass can be advocated in primary teeth because of their superior physical properties when compared with Fuji IX GP

A comparative evaluation between cheiloscopic patterns and terminal planes in primary dentition

Objective: To assess the correlation between different cheiloscopic patterns with the terminal planes in deciduous dentition. Materials and Methods: Three hundred children who are 3–6 years old with complete primary dentition were recruited, and the pattern of molar terminal plane was recorded in the pro forma. Lip prints of these children were recorded with lipstick-cellophane method, and the middle 10 mm of lower lip was analyzed for the lip print pattern as suggested by Sivapathasundharam et al. The pattern was classified based on Tsuchihashi and Suzuki classification. Results: Type II (branched) pattern was the most predominant cheiloscopic pattern. The predominant patterns which related to the terminal planes were as follows: Type IV (reticular) and Type V (irregular) pattern for mesial step, Type IV (reticular) pattern for distal step, and Type I (complete vertical) pattern for flush terminal plane. No significant relationship was obtained on gender comparison. Conclusion: Lip prints can provide an alternative to dermatoglyphics to predict the terminal plane in primary dentition. Further studies with larger sample size are required to provide an insight into its significant correlations

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Not AvailableTwo major nuclear genes, Rf3 and Rf4, are known to be associated with fertility restoration of wild-abortive cytoplasmic male sterility (WA-CMS) in rice. In the present study, through a comparative sequence analysis of the reported putative candidate genes, viz. PPR9-782-(M,I) and PPR762 (for Rf4) and SF21 (for Rf3), among restorer and maintainer lines of rice, we identified significant polymorphism between the two lines and developed a set of PCR-based codominant markers, which could distinguish maintainers from restorers. Among the five markers developed targeting the polymorphisms in PPR9- 782-(M,I), the marker RMS-PPR9-1 was observed to show clear polymorphism between the restorer (n = 120) and maintainer lines (n = 44) analyzed. Another codominant marker, named RMS-PPR762 targeting PPR762, displayed a lower efficiency in identification of restorers and maintainers, indicating that PPR9-782-(M,I) is indeed the candidate gene for Rf4. With respect to Rf3, a codominant marker, named RMS-SF21-5 developed targeting SF21, displayed significantly lower efficiency in identification of restorers and non-restorers as compared to the Rf4- specific markers. Validation of these markers in a F2 mapping population segregating for fertility restoration indicated that Rf4 has a major influence on fertility restoration and Rf3 is a minor gene. Further, the functional marker RMS-PPR9-1 was observed to be very useful in identification of impurities in a seed lot of the popular hybrid, DRRH3. Interestingly, when RMS-PPR9-1 and RMS-SF21-5 were considered in conjunction with analysis, near-complete, marker– trait co-segregation was observed, indicating that deployment of the candidate gene-specific markers both Rf4 and Rf3, together, can be helpful in accurate identification of fertility restorer lines and can facilitate targeted transfer of the two restorer genes into elite varieties through marker-assisted breeding.Not Availabl

Proceedings of International Web Conference in Civil Engineering for a Sustainable Planet

This proceeding contains articles of the various research ideas of the academic community and practitioners accepted at the "International Web Conference in Civil Engineering for a Sustainable Planet (ICCESP 2021)". ICCESP 2021 is being Organized by the Habilete Learning Solutions, Kollam in Collaboration with American Society of Civil Engineers (ASCE), TKM College of Engineering, Kollam, and Baselios Mathews II College of Engineering, Kollam, Kerala, India. Conference Title: International Web Conference in Civil Engineering for a Sustainable PlanetConference Acronym: ICCESP 2021Conference Date: 05–06 March 2021Conference Location: Online (Virtual Mode)Conference Organizer: Habilete Learning Solutions, Kollam, Kerala, IndiaCollaborators: American Society of Civil Engineers (ASCE), TKM College of Engineering, Kollam, and Baselios Mathews II College of Engineering, Kollam, Kerala, India