0000000001321148

AUTHOR

Gulfaraz Khan

showing 11 related works from this author

Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 3…

2017

Importance: Cancer is the second leading cause of death worldwide. Current estimates on the burden of cancer are needed for cancer control planning.Objective: To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 32 cancers in 195 countries and territories from 1990 to 2015.Evidence Review: Cancer mortality was estimated using vital registration system data, cancer registry incidence data (transformed to mortality estimates using separately estimated mortality to incidence [MI] ratios), and verbal autopsy data. Cancer incidence was calculated by dividing mortality estimates through the modeled MI ratio…

0301 basic medicineGerontologyCancer ResearchPopulationArticle03 medical and health sciences0302 clinical medicineBreast cancerGlobal healthcancerMedicineDisability-adjusted life yeareducationDisease burdeneducation.field_of_studyestimate mortalityCancer preventioncancer preventionbusiness.industryMortality rate1. No povertymedicine.disease3. Good health030104 developmental biologyYears of potential life lostOncology030220 oncology & carcinogenesisbusinessearly diagnosisDemography
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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for th…

2020

Background: Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods: We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuri…

Low income countriesmedicine.medical_treatment030204 cardiovascular system & hematologyGlobal HealthTHERAPYGlobal Burden of Disease0302 clinical medicinePrevalenceGlobal healthMedicineWATER030212 general & internal medicineChildren11 Medical and Health SciencesIncidenceMortality rateIncidence (epidemiology)1. No povertyGeneral Medicine3142 Public health care science environmental and occupational healthDiarrhoea3. Good healthChild PreschoolMiddle income countriesA990 Medicine and Dentistry not elsewhere classifiedTERRITORIESLife Sciences & BiomedicineInfantsDiarrheaAFRICAmedicine.medical_specialtyChildhood deathsRJsanitationDeveloping countryChildhood diarrhoeal morbidityITC-HYBRID03 medical and health sciencesMedicine General & InternalGeneral & Internal MedicineEnvironmental healthSYSTEMATIC ANALYSISLife ScienceHumansHealthcare DisparitiesOral rehydration therapyRisk factorhand washingDeveloping CountriesDisease burdenGlobal NutritionWereldvoedingScience & TechnologySEX-SPECIFIC MORTALITYbusiness.industryCHOLERAPublic healthBayes Theoremdiarrheal diseaseLocal Burden of Disease Diarrhoea CollaboratorsITC-ISI-JOURNAL-ARTICLENAHuman medicineDiarreabusiness
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Department of Error

2018

Reiner RC Jr, Hay SI. Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17: analysis for the Global Burden of Disease Study 2017. Lancet 2020; 395: 1779–801—In this Article, the author byline has been amended to Local Burden of Disease Diarrhoea Collaborators. This correction has been made to the online version as of June 4, 2020, and the printed version is correct. © 2020 Elsevier Ltd

Burden of disease030219 obstetrics & reproductive medicinebusiness.industryLow income and middle income countriesGeneral MedicineSpecific mortality030204 cardiovascular system & hematologyArticle3. Good health03 medical and health sciencesGeography0302 clinical medicineEnvironmental healthMedicine030212 general & internal medicineGeographical inequalitiesbusinessDemographyThe Lancet
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Age–sex differences in the global burden of lower respiratory infections and risk factors, 1990–2019: results from the Global Burden of Disease Study…

2022

Funding: Bill & Melinda Gates Foundation. Background: The global burden of lower respiratory infections (LRIs) and corresponding risk factors in children older than 5 years and adults has not been studied as comprehensively as it has been in children younger than 5 years. We assessed the burden and trends of LRIs and risk factors across all age groups by sex, for 204 countries and territories.  Methods: In this analysis of data for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we used clinician-diagnosed pneumonia or bronchiolitis as our case definition for LRIs. We included International Classification of Diseases 9th edition codes 079.6, 466–469, 470.0, 480–4…

AdultMaleGlobal HealthTimeGlobal Burden of DiseaseSDG 3 - Good Health and Well-beingRisk FactorsRA0421RA0421 Public health. Hygiene. Preventive MedicineHumansAmbient air-qualityChildRespiratory Tract InfectionsAgedAged 80 and overMCCSex CharacteristicsMalnutritionPyridinolcarbamateBayes Theorem3rd-DAS3142 Public health care science environmental and occupational healthInfectious Diseases3121 General medicine internal medicine and other clinical medicineChild PreschoolFemaleParticulate MatterQuality-Adjusted Life YearsCovid-19LRI
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The global burden of cancer attributable to risk factors, 2010–19 : A systematic analysis for the Global Burden of Disease Study 2019

2022

Background: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 20…

MaleDEATHSDALY cancer risk factorsMedizinsystematic analysisGlobal HealthRisk AssessmentCancer preventionGlobal Burden of DiseaseRC0254Risk-attributable cancer deathsSDG 3 - Good Health and Well-beingRA0421Risk FactorsRA0421 Public health. Hygiene. Preventive MedicineQuality-Adjusted Life YearNeoplasmscancerHumansGlobal Burden of Disease StudyUKMedicine(all)MCCRC0254 Neoplasms. Tumors. Oncology (including Cancer)Risk FactorSmokingCOVID-193rd-DASGeneral MedicineDisability-adjusted life-yearsSOCIAL DETERMINANTSRisk assessmentsrisk factorCardiovascular and Metabolic Diseases3121 General medicine internal medicine and other clinical medicineOBESITYCancer burden/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingNeoplasmFemaleLIFE-STYLEQuality-Adjusted Life YearsHEALTHRAHumanRC
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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
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Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for …

2015

Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included…

MaleAgingPediatricsNutrition and DiseaseDatabases FactualDisease030204 cardiovascular system & hematologyGlobal HealthMedical and Health SciencesDOUBLE-BLIND0302 clinical medicineAdolescent; Adult; Aged; Aged 80 and over; Cause of Death; Child; Child Mortality; Child Preschool; Databases Factual; Female; Global Health; Humans; Infant; Infant Newborn; Life Expectancy; Life Tables; Male; Middle Aged; Models Statistical; Mortality; Sex Distribution; Young AdultModelsVoeding en ZiekteCause of DeathEpidemiologyGlobal health80 and over2.2 Factors relating to the physical environmentLife Tables030212 general & internal medicineAetiologyChildINFLUENZAE TYPE-B11 Medical and Health SciencesCause of deathPediatricAged 80 and overPLACEBO-CONTROLLED-TRIALLife TableMortality rateMedicine (all)1. No povertyGeneral MedicineCHILDHOOD PNEUMONIAMiddle AgedStatistical3. Good healthInfectious DiseasesChild PreschoolPNEUMOCOCCAL CONJUGATE VACCINEChild MortalityFemaleInfectionLife Sciences & BiomedicineHumanAdultmedicine.medical_specialtyAdolescentINTEGRATED APPROACHCHILDREN YOUNGER187 COUNTRIESDatabase03 medical and health sciencesDatabasesYoung AdultMedicine General & InternalLife ExpectancyGeneral & Internal MedicinemedicineLife ScienceHumansMortalitySex DistributionPreschoolFactualVLAGAgedScience & TechnologyModels Statisticalbusiness.industryPreventionPOPULATION HEALTHInfant NewbornENTERIC MULTICENTERInfantGBD 2013 Mortality and Causes of Death CollaboratorsNewbornVerbal autopsyChild mortalityGood Health and Well BeingLife expectancyRISK-FACTORSbusiness2.4 Surveillance and distributionDemographyModel
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Additional file 3 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

2023

Additional file 3: Supplemental figures.Figure S1. Prevalence of male circumcision. Figure S2. Prevalence of signs and symptoms of sexually transmitted infections. Figure S3. Prevalence of marriage or living as married. Figure S4. Prevalence of partner living elsewhere among females. Figure S5. Prevalence of condom use during most recent sexual encounter. Figure S6. Prevalence of sexual activity among young females. Figure S7. Prevalence of multiple partners among males in the past year. Figure S8. Prevalence of multiple partners among females in the past year. Figure S9. HIV prevalence predictions from the boosted regression tree model. Figure S10. HIV prevalence predictions from the gener…

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Additional file 1 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

2023

Additional file 1: Supplemental information.1. Compliance with the Guidlines for Accurate and Transparent Health Estimates Reporting (GATHER). 2. HIV data sources and data processing. 3. Covariate and auxiliary data. 4. Statistical model. 5. References.

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Additional file 2 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

2023

Additional file 2: Supplemental tables.Table S1. HIV seroprevalence survey data. Table S2. ANC sentinel surveillance data. Table S3. HIV and covariates surveys excluded from this analysis. Table S4. Sources for pre-existing covariates. Table S5. HIV covariate survey data. Table S6. Fitted model parameters.

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Additional file 4 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

2023

Additional file 4: Supplemental results.1. README. 2. Prevalence range across districts. 3. Prevalence range between sexes. 4. Prevalence range between ages. 5. Age-specific district ranges.

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