0000000000042367

AUTHOR

Philip B. Mitchell

showing 7 related works from this author

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990-2019: a systema…

2020

Publisher's version (útgefin grein)

Index (economics)Servicios de SaludSUSTAINABLE DEVELOPMENT GOALS030204 cardiovascular system & hematologyuniversal health coverage; sustaibale develpment goal; global burden of disease; performance;universal health coveragesystematic analysisGlobal Burden of Disease0302 clinical medicineUniversal Health InsuranceRA042111. SustainabilityPer capitaMedical economicsDisease030212 general & internal medicine10. No inequality11 Medical and Health Scienceseffective coverage of health servicesGBD 2019 Universal Health Coverage Collaboratorseducation.field_of_studyPublic healthMedical careSjúkdómar4. Education1. No povertyHealth coveragePublic Health Global Health Social Medicine and EpidemiologyGeneral MedicineHälsovetenskaper3142 Public health care science environmental and occupational healthHealth services3. Good healthGlobal burden of diseaseGlobal Burden of Disease; Health Expenditures; Humans; Universal Health Insurance; World Health OrganizationPurchasing power parityScale (social sciences)/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingLýðheilsauniversal health coveragCANCER SURVIVALACCESSperformanceHumanHeilsuhagfræðimedicine.medical_specialtyHealth coverage GBDGBDUniversal healthGBD 2019Population2019Health expenditures3122 CancersPopulation healthWorld Health Organization03 medical and health sciencesHealth systemsHeilbrigðisvísindiSDG 3 - Good Health and Well-beingGeneral & Internal MedicineDevelopment economicsHealth SciencesmedicineHeilbrigðisstefnasustaibale develpment goalAlþjóðaheilbrigðisstofnuninHumansQUALITYGlobal Burden of Disease StudyeducationPROGRESSDisease burdenPublic healthHealth services accessibilityCAREHeilbrigðisþjónusta//purl.org/pe-repo/ocde/ford#3.02.00 [https]Health ExpenditureFolkhälsovetenskap global hälsa socialmedicin och epidemiologi3121 General medicine internal medicine and other clinical medicineMorbilityAdministración de los Servicios de SaludMedical policyBusinessHealth ExpendituresHeilbrigðiskerfi
researchProduct

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countr…

2015

Summary Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic develo…

GerontologyMaleCHANGING RELATIONNutrition and DiseaseMESH : Life ExpectancyMESH : AgedECONOMIC-DEVELOPMENTPoison controlMESH: Global HealthGlobal HealthSocioeconomic FactorCommunicable DiseaseMESH : Chronic DiseaseHealth TransitionVoeding en ZiekteQuality-Adjusted Life YearSELF-RATED HEALTHMESH : Socioeconomic FactorsMedicineMESH : FemaleMESH: Mortality Premature2. Zero hungerMESH: Agededucation.field_of_studyMESH: Middle AgedMortality rateMedicine (all)GBD2013 diseases[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologieGeneral MedicineMiddle Aged3. Good healthMESH : Wounds and InjuriesEpidemiological transitionMESH: Quality-Adjusted Life YearsMESH: Communicable DiseasesNONCOMMUNICABLE DISEASESFemaleQuality-Adjusted Life YearsMESH: Life ExpectancyMESH: Health TransitionHumanMESH: Socioeconomic FactorsACUTE MYOCARDIAL-INFARCTIONMESH : MaleMORTALITY TRENDSPopulationMESH : Health TransitionCommunicable DiseasesArticleLife ExpectancyEUROPEAN-UNIONSDG 3 - Good Health and Well-beingGeneral & Internal MedicineSYSTEMATIC ANALYSISDisability-adjusted life yearHumansLife ScienceMESH : Middle AgedMortalityeducationPrematureMESH : Mortality PrematureVLAGAgedMESH: Humansbusiness.industryMortality PrematureMESH: Chronic DiseaseMESH : Communicable DiseasesWounds and InjurieMESH : HumansMESH : Quality-Adjusted Life YearsNon-communicable diseaseAged; Chronic Disease; Communicable Diseases; Female; Global Health; Humans; Male; Middle Aged; Mortality Premature; Quality-Adjusted Life Years; Socioeconomic Factors; Wounds and Injuries; Health Transition; Life Expectancy; Medicine (all)medicine.diseaseMESH: MaleLOW SOCIOECONOMIC-STATUSYears of potential life lostSocioeconomic Factors[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologieMESH: Wounds and InjuriesChronic DiseaseLife expectancyRISK-FACTORSMESH : Global HealthWounds and Injuries[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologiebusinessMESH: FemaleDemographyLancet
researchProduct

The Burden of Mental Disorders in the Eastern Mediterranean Region, 1990-2013.

2017

The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 m…

MaleGerontologyTime FactorsL900Health Statuslcsh:MedicineGlobal HealthGeographical Locations0302 clinical medicineMedicine and Health SciencesGlobal healthPublic and Occupational Health030212 general & internal medicineChildlcsh:ScienceDepression (differential diagnoses)Aged 80 and overeducation.field_of_studyPublic healthMultidisciplinaryMediterranean RegionDepressionMental DisordersAge FactorsMiddle AgedAnxiety DisordersSocioeconomic Aspects of HealthMental illnessChild PreschoolMediterrània orientalAnxietyFemaleEgyptmedicine.symptomResearch ArticleAdultAdolescentEastern MediterraneanPopulationNeuropsychiatric DisordersNeurosesYoung Adult03 medical and health sciencesLife ExpectancySex FactorsMental Health and PsychiatrymedicineHumanseducationDisease burdenAgedMood Disordersbusiness.industrylcsh:RInfant NewbornInfantMental illnessmedicine.diseaseMental healthSalut pública030227 psychiatryHealth CareB900Age GroupsPeople and PlacesAfricaLife expectancyRC0321Population Groupingslcsh:QbusinessMalalties mentalsDemography
researchProduct

Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

2019

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) a…

PharmacologyAdultMaleBipolar DisorderCorrectionBrainDiagnostic markersBiologyTranslational researchmedicine.diseaseMega-White MatterCorpus CallosumWhite matterPsychiatry and Mental healthmedicine.anatomical_structureDiffusion Tensor ImagingNeural PathwaysmedicineHumansFemaleBipolar disorderClinical psychologyNeuropsychopharmacology
researchProduct

What we learn about bipolar disorder from large-scale neuroimaging

2020

Abstract MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Workin…

mega-analysisStress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13]cortical surface areaReview Article0302 clinical medicineManic-depressive illnessMulticenter Studies as TopicSpectrum disorderReview Articlesbipolar disorderCerebral CortexTrastorn bipolarneuroimagingRadiological and Ultrasound Technology05 social sciencesENIGMAHUMAN BRAINMagnetic Resonance Imagingpsychiatry3. Good healthNeurologyMeta-analysisScale (social sciences)AnatomyPsychologyClinical risk factorClinical psychologyMRIMAJOR PSYCHIATRIC-DISORDERSSchizoaffective disorder050105 experimental psychology03 medical and health sciencesMagnetic resonance imagingNeuroimagingMeta-Analysis as TopicSDG 3 - Good Health and Well-beingImatges per ressonància magnèticamedicineHumans0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imagingBipolar disorderHIPPOCAMPAL VOLUMESmega‐analysisGRAY-MATTER VOLUMESPECTRUM DISORDERvolumeDIABETES-MELLITUScortical thicknessCOGNITIVE IMPAIRMENTmedicine.diseaseMental illnessmeta-analysismeta‐analysisRC0321Neurology (clinical)SCHIZOAFFECTIVE DISORDERPSYCHOTIC FEATURES030217 neurology & neurosurgeryHuman Brain Mapping
researchProduct

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

2019

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD);\ud however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical\ud heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with\ud BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered\ud individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean\ud fractional anisotropy (FA) from 43 regions of i…

Pathologymedicine.medical_specialtyCorpus callosumArticleWhite matter03 medical and health sciences0302 clinical medicineFractional anisotropyCingulum (brain)MedicineManic-depressive illnessBipolar disorderPharmacologyTrastorn bipolarbusiness.industryDiagnostic markersAnisotropiaTranslational researchmedicine.disease030227 psychiatryPsychiatry and Mental healthmedicine.anatomical_structureMeta-analysisAnisotropybusiness030217 neurology & neurosurgeryDiffusion MRITractography
researchProduct

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

2018

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generat…

Netherlands Twin Register (NTR)0301 basic medicineMajor Depressive Disorder and Bipolar Disorder Working Groups of the Psychiatric Genomics ConsortiumBipolar DisorderSAMPLEMedicine (miscellaneous)Pedigree chartDisease0302 clinical medicineSCHIZOPHRENIA2.1 Biological and endogenous factorsMedicineAetiologyANTICIPATIONlcsh:QH301-705.5Psychiatry0303 health sciencesDepressionASSOCIATIONSerious Mental IllnessPeer reviewMental HealthSchizophrenia/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingMajor depressive disorderGeneral Agricultural and Biological SciencesEngineering sciences. Technologymedicine.medical_specialtyContext (language use)ArticlePsykiatriGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesAGESDG 3 - Good Health and Well-beingddc:570Behavioral and Social Science/dk/atira/pure/keywords/cohort_studies/netherlands_twin_register_ntr_GeneticsPLINKGenetic TestingBipolar disorderPsychiatryBiology030304 developmental biologybusiness.industryPreventionHuman GenomeAssortative matingmedicine.diseaseBrain Disorders030104 developmental biologyMoodlcsh:Biology (General)Mood disordersAnticipation (genetics)ONSETHuman medicinebusiness030217 neurology & neurosurgery
researchProduct