Case series of volar juvenile xanthogranuloma: Clinical observation of a peripheral rim of hyperkeratosis

Juvenile xanthogranuloma is a benign histiocytic tumor predominantly occurring in children as yellowish papules on the head and trunk. Presentations on the volar surfaces are rare and may cause diagnostic confusion with pyogenic granuloma, eccrine poroma and digital fibrokeratoma. We report two patients with unusual presentations of solitary juvenile xanthogranuloma on the palm or sole. Both had lesions lacking the classic yellowish color and demonstrating a well‐defined, peripheral hyperkeratotic rim. Histopathological evaluation revealed prominent orthokeratosis corresponding to the rim. Additional histological features, including dermal histiocytes and Touton giant cells, were consistent with the diagnosis of juvenile xanthogranuloma. Given the unusual locations and colors of the lesions, we conclude that histopathological evaluation is central to diagnosing volar juvenile xanthogranuloma. We additionally suggest that juvenile xanthogranuloma should be included in the differential diagnoses of volar lesions displaying a peripheral hyperkeratotic rim.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108660/1/jde12617.pd

Expression of the p40 isoform of p63 has high specificity for cutaneous sarcomatoid squamous cell carcinoma

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109645/1/cup12387.pd

Correlation and high-resolution timing for Paleo-tethys Permian-Triassic boundary exposures in Vietnam and Slovenia using geochemical, geophysical and biostratigraphic data sets

Two Permian-Triassic boundary (PTB) successions, Lung Cam in Vietnam, and Lukač in Slovenia, have been sampled for high-resolution magnetic susceptibility, stable isotope and elemental chemistry, and biostratigraphic analyses. These successions are located on the eastern (Lung Cam section) and western margins (Lukač section) of the Paleo-Tethys Ocean during PTB time. Lung Cam, lying along the eastern margin of the Paleo-Tethys Ocean provides an excellent proxy for correlation back to the GSSP and out to other Paleo-Tethyan successions. This proxy is tested herein by correlating the Lung Cam section in Vietnam to the Lukač section in Slovenia, which was deposited along the western margin of the Paleo-Tethys Ocean during the PTB interval. It is shown herein that both the Lung Cam and Lukač sections can be correlated and exhibit similar characteristics through the PTB interval. Using time-series analysis of magnetic susceptibility data, high-resolution ages are obtained for both successions, thus allowing relative ages, relative to the PTB age at ~252 Ma, to be assigned. Evaluation of climate variability along the western and eastern margins of the Paleo-Tethys Ocean through the PTB interval, using d18O values indicates generally cooler climate in the west, below the PTB, changing to generally warmer climates above the boundary. A unique Black Carbon layer (elemental carbon present by agglutinated foraminifers in their test) below the boundary exhibits colder temperatures in the eastern and warmer temperatures in the western Paleo-Tethys Ocean.ReferencesBalsam W., Arimoto R., Ji J., Shen Z, 2007. Aeolian dust in sediment: a re-examination of methods for identification and dispersal assessed by diffuse reflectance spectrophotometry. International Journal of Environment and Health, 1, 374-402.Balsam W.L., Otto-Bliesner B.L., Deaton B.C., 1995. Modern and last glacial maximum eolian sedimentation patterns in the Atlantic Ocean interpreted from sediment iron oxide content. Paleoceanography, 10, 493-507.Berggren W.A., Kent D.V., Aubry M-P., Hardenbol J., 1995. Geochronology, Time Scales and Global Stratigraphic Correlation. SEPM Special Publication #54, Society for Sedimentary Geology, Tulsa, OK, 386p.Berger A., Loutre M.F., Laskar J., 1992. Stability of the astronomical frequencies over the Earth's history for paleoclimate studies. Science, 255, 560-566.Bloemendal J., deMenocal P., 1989. Evidence for a change in the periodicity of tropical climate cycles at 2.4 Myr from whole-core magnetic susceptibility measurements. Nature, 342, 897-900.Chen J., Shen S-j., Li X-h., Xu Y-g., Joachimski M.M., Bowring S.A., Erwin D.H., Yuan D-x., Chen B., Zhang H., Wang Y., Cao C-q, Zheng Q-f., Mu L., 2016. High-resolution SIMS oxygen isotope analysis on conodont apatite from South China and implications for the end-Permian mass extinction. Palaeogeography, Palaeoclimatology, Palaeoecology, 448, 26-38.Da Silva A-C., Boulvain F., 2002. Sedimentology, magnetic susceptibility and isotopes of a Middle Frasnian carbonate platform: Tailfer Section, Belgium. Facies, 46, 89-102.Da Silva A.-C., Boulvain F., 2005. Upper Devonian carbonate platform correlations and sea level variations recorded in magnetic susceptibility. Palaeogeography, Palaeoclimatology, Palaeoecology, 240, 373-388.Dettinger M.D., Ghil M., Strong C.M., Weibel W., Yiou P., 1995. Software expedites singular-spectrum analysis of noisy time series. EOS. Transactions of the American Geophysical Union, 76, 12-21.Dinarès-Turell J., Baceta J.I., Bernaola G., Orue-Etxebarria X., Pujalte V., 2007. Closing the Mid-Palaeocene gap: Toward a complete astronomically tuned Palaeocene Epoch and Selandian and Thanetian GSSPs at Zumaia (Basque Basin, W Pyrenees). Earth Planetary Science Letters, 262, 450-467.Ellwood B.B., García-Alcalde J.L., El Hassani A., Hladil J., Soto F.M., Truyóls-Massoni M., Weddige K., Koptikova L., 2006. Stratigraphy of the Middle Devonian Boundary: Formal Definition of the Susceptibility Magnetostratotype in Germany with comparisons to Sections in the Czech Republic, Morocco and Spain. Tectonophysics, 418, 31-49.Ellwood B.B., Wang W.-H., Tomkin J.H., Ratcliffe K.T., El Hassani A., Wright A.M., 2013. Testing high resolution magnetic susceptibility and gamma gradiation methods in the Cenomanian-Turonian (Upper Cretaceous) GSSP and near-by coeval section. Palaeogeography, Palaeoclimatology, Palaeoecology, 378, 75-90.Ellwood B.B., Wardlaw B.R., Nestell M.K., Nestell G.P., Luu Thi Phuong Lan, 2017. Identifying globally synchronous Permian-Triassic boundary levels in successions in China and Vietnam using Graphic Correlation. 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(Eds.), Milankovitch and Climate, Part I, Kluwer Academic Publishers, 269-305.Mead G.A., Yauxe L., LaBrecque J.L., 1986. Oligocene paleoceanography of the South Atlantic: paleoclimate implications of sediment accumulation rates and magnetic susceptibility. Paleoceanography, 1, 273-284.Salvador A., (Ed.), 1994. International Stratigraphic Guide: The International Union of Geological Sciences and The Geological Society of America, Inc., 2nd Edition, 214p.Scotese C.R., 2001. Atlas of Earth History, Volume 1, Paleogeography, PALEOMAP Project, Arlington, Texas, 52p.Scotese C.R., 2013. Map Folio 49, Permo-Triassic Boundary (251 Ma), PALEOMAP PaleoAtlas for ArcGIS, Triassic and Jurassic Paleogeographic, Paleoclimatic and Plate Tectonic Reconstructions, PALEOMAP Project, Evanston, IL, 3.Shackleton N.J., Crowhurst S.J., Weedon G.P., Laskar J., 1999. Astronomical calibration of Oligocene-Miocene time. Philosophical Transactions of the Royal Society London, A357, 1907-1929.Shaw A.B., 1964. Time in Stratigraphy. New York, Mc Graw Hill, 365p.Shen S.-Z., Crowley J.L., Wang Y., Bowring S.A., Erwin D.H., Henderson C.M., Ramezani J., Zhang H., Shen Y.,Wang X.-D., Wang W., Mu L., Li W.-Z., Tang Y.-G., Liu X.-L., Liu X.-L., Zeng Y., Jiang Y.-F., Jin Y.-G., 2011a. High-precision geochronologic dating constrains probable causes of Earth’s largest mass extinction. Science, 334, 1367-1372. Doi:10.1126/science.1213454.Swartzendruber L.J., 1992. Properties, units and constants in magnetism. Journal of Magnetic Materials, 100, 573-575.Weedon G.P., Jenkyns H.C., Coe A.L., Hesselbo S.P., 1999. Astronomical calibration of the Jurassic time-scale from cyclostratigraphy in British mudrock formations. Philosophical Transactions of the Royal Society London, A357, 1787-1813.Weedon G.P., Shackleton N.J., Pearson P.N., 1997. The Oligocne time scale and cyclostratigraphy on the Ceara Rise, western equatorial Atlantic. In: Schackleton N.J., Curry W.B., Richter C., and Bralower T.J. (Eds.). Proceedings of the Ocean Drilling Program, Scientific Results, 154, 101-114.Whalen M.T., Day J.E., 2008. Magnetic Susceptibility, Biostratigraphy, and Sequence Stratigraphy: Insights into Devonian Carbonate Platform Development and Basin Infilling, Western Alberta. Papers on Phanerozoic Reef Carbonates in Honor of Wolfgang Schlager. SEPM (Society for Sedimentary Geology) Special Publication, 89, 291-314

Effectiveness of cervical pessary compared to cervical cerclage with or without vaginal progesterone for the prevention of preterm birth in women with twin pregnancies and a short cervix : Study protocol for a two-by-two factorial randomised clinical trial

Peer reviewedPublisher PD

The impact of environmental and climatic variation on the spatiotemporal trends of hospitalized pediatric diarrhea in Ho Chi Minh City, Vietnam.

It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings

On Spatially Distributed Hydrological Ecosystem Services: Bridging the Quantitative Information Gap using Remote Sensing and Hydrological Models

One of the ways in which the CGIAR Research Program on Water, Land and Ecosystems (WLE) addresses the challenge of achieving sustainable growth is by improving our understanding of tradeoffs and synergies related to water, food, environment and energy. Essential to the success of these efforts is the availability of quantitative data on these tradeoffs and synergies, and how they vary across space and time. Specifically for the countries sharing the Mekong River, WLE Greater Mekong seeks to drive and inform research and dialogue around the rivers of the region. Hydrological EcoSystem Services (HESS) are heavily affected by intensive development across the region, such as the construction of hydropower dams and land use changes - in particular deforestation, urbanization and agricultural intensification. The full extent of such changes in the agro-ecological system is often unknown, and it is a challenge to account for tradeoffs in HESS in policy processes. As in many other areas of the world, improving governance and management of water resources and associated land and ecosystems in the Greater Mekong region is not only a matter of generating more data. Sharing of knowledge and practices is a key focus of WLE Greater Mekong, which we strive to promote by enhancing the accessibility of valuable information to a wide diversity of regional stakeholders, and promoting dialogue by facilitating the creation of communities of practice. This white paper demonstrates state-of-the-art methods for assessing different HESS and their tradeoffs under different development scenarios. It explores opportunities for spatial monitoring of HESS and predicting changes under different future scenarios, information that is essential for achieving a balanced and healthy agro-ecological system. By relying on tools in the public domain and leveraging the resulting HESS data through online information platforms, this white paper is an excellent example of current efforts supported by WLE Greater Mekong to stimulate uptake of ecosystem services assessments in decision-making processes

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

The Global Burden of Diseases, Injuries and Risk Factors 2017 includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. METHODS: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting