0000000000950818

AUTHOR

Afshin Maleki

showing 9 related works from this author

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

2020

Artículo con numerosos autores, sólo se mencionan el primero, los de la UAM y grupo colectivo

MaleLocal patternsDouble burdenBörnResearch & Experimental MedicineSjúkdómseinkenniDOUBLE BURDENChildhood overweightLífefnafræðiLæknisfræði0302 clinical medicineSyndemicChild11 Medical and Health Sciencesunder 5 years of ageGeneral Medicine3. Good healthGeographyMedicine Research & ExperimentalChild PreschoolIncomeGROWTHAFRICAmedicine.medical_specialtyBiochemistry & Molecular BiologyRJMedicinaImmunologyeducationMODELSwa_395General Biochemistry Genetics and Molecular BiologyArticleG03 medical and health sciencesHumansAuthor CorrectionDeveloping CountriesPovertyBiologyLBD Double Burden of Malnutrition CollaboratorsDemographyScience & TechnologyWasting SyndromePublic healthMORTALITYInfantNæringarskorturmedicine.diseaseObesityTRENDSsigns and symptomsSocial ClassRisk factorsSameindalíffræðiITC-ISI-JOURNAL-ARTICLEUNDERNUTRITIONHuman medicineClinical Medicine030217 neurology & neurosurgeryPediatric ObesityobesityOffitaÁhættuþættirGeographic MappingOverweightRA0421Global healthrisk factors030212 general & internal medicineSigns and symptomsWastingMalnutrition Global Burden of Diseases Global Nutrition low- and middle-income countries2. Zero hungerPublic health1. No povertyPublic Health Global Health Social Medicine and EpidemiologyA900 Others in Medicine and DentistryChildhood wastingPREVALENCEChemistryMappingFemaleLýðheilsamedicine.symptomLife Sciences & BiomedicineGROWTH FAILURENutritional StatusmalnutritionITC-HYBRIDws_115childrenEnvironmental healthmedicineErfðafræðiObesitywd_200MalnutritionInfant NewbornKlinisk medicinCell BiologyOverweightMalnutritionFolkhälsovetenskap global hälsa socialmedicin och epidemiologi3121 General medicine internal medicine and other clinical medicineNA
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Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning

2021

Recent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitabil…

OncocercosisDecision AnalysisRC955-962Onchocerciasislaw.inventionGeographical LocationsMedical Conditions0302 clinical medicinelawArctic medicine. Tropical medicineMedicine and Health Sciences030212 general & internal medicineOnchocerca11 Medical and Health SciencesData ManagementbiologyPharmaceuticswc_695Enfermedades ParasitariasOnchocerciasi3. Good healthInfectious DiseasesGeographyTransmission (mechanics)Helminth InfectionsEngineering and TechnologyMass Drug AdministrationOnchocercaPublic aspects of medicineRA1-1270Management EngineeringCartographyHumanResearch ArticleNeglected Tropical DiseasesComputer and Information SciencesDrug Administration030231 tropical medicineDecision treewa_395Dermatologywc_765Environmentwc_885Research and Analysis MethodsSkin Diseases03 medical and health sciencesDrug TherapySDG 3 - Good Health and Well-beingDiagnostic MedicineTropical MedicineParasitic DiseasesmedicineHumansDisease EradicationSpatial analysisIvermectinData collectionReceiver operating characteristicData VisualizationDecision TreesPublic Health Environmental and Occupational Health06 Biological SciencesOnchocerciasis ; Elimination planning ; Africa ; Implementation units ; Public healthTropical Diseasesmedicine.diseasebiology.organism_classificationHealth CareROC CurvePeople and PlacesAfricaHealth StatisticsMorbidityOnchocerciasisScale (map)ForecastingPLOS Neglected Tropical Diseases
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Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

2020

Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the…

MaleNutritional SciencesSpecific riskContaminación del Aire Interior030204 cardiovascular system & hematologySocioeconomic Factorsystematic analysisGlobal HealthBody Mass IndexGlobal Burden of DiseaseHealth Risk BehaviorHealth Risk BehaviorsDisease studies0302 clinical medicineRisk FactorsMETABOLIC RISKS030212 general & internal medicine11 Medical and Health SciencesFactores de Riesgo2. Zero hungereducation.field_of_studyPublic healthInjuriesPublic Health Global Health Social Medicine and EpidemiologyGeneral MedicineGBD; risck factors; attributable burden of disease;3142 Public health care science environmental and occupational health3. Good healthRelative riskEnvironmental healthHealthHypertension/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingGlobal Burden of Diseases Injuries Risk FactorsA990 Medicine and Dentistry not elsewhere classifiedFemaleLeading risk factorsGlobal Health MetricsCohort studyHumanmedicine.medical_specialtySubstance-Related DisordersPopulationUNITED-STATESRisk AssessmentDIETITC-HYBRID03 medical and health sciencesLife ExpectancyUNITED-STATES; MORTALITY; DISABILITY; POLLUTION; CLUSTERS; DIETSDG 3 - Good Health and Well-beingPOLLUTIONGeneral & Internal MedicineEnvironmental healthmedicineHumansGlobal Burden of Disease StudyRisk factoreducationGlobal burdenbusiness.industryPublic healthRisk FactorMORTALITYDISABILITYMalnutritionKlinisk medicinGlobal Burden of DiseasesEnvironmental Exposuremedicine.diseaseEnfermedades//purl.org/pe-repo/ocde/ford#3.02.00 [https]MalnutritionFolkhälsovetenskap global hälsa socialmedicin och epidemiologiYears of potential life lostSocioeconomic FactorsRisk factorsDisease studyRelative riskHyperglycemiaITC-ISI-JOURNAL-ARTICLENAClinical MedicinebusinessCLUSTERSRA
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Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

2019

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained ra…

SurvivalRJ101Mortalidad InfantilHBUNDER-5 MORTALITYGlobal HealthPediatrics0302 clinical medicine3123 Gynaecology and paediatricsChild deathInfant MortalityEpidemiologyGlobal healthMiddle income countryNacimiento vivo030212 general & internal medicine10. No inequalityChildPOPULATIONDeveloping worldeducation.field_of_studyPublic healthMultidisciplinaryGeographyMortality ratewa_9001. No povertyRSUCCESSPediatrikA900 Others in Medicine and Dentistry3142 Public health care science environmental and occupational health3. Good healthChild MortalityDeath childrenVACCINATIONHEALTHws_100INTERVENTIONSAFRICAmedicine.medical_specialtyUnited NationsGeneral Science & Technology030231 tropical medicinePopulationDeveloping countryArticleHealthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18]ITC-HYBRID03 medical and health sciencesAll institutes and research themes of the Radboud University Medical CenterSocial JusticeRecién nacidoNeonatal deathsmedicineSYSTEMATIC ANALYSISOrganizational ObjectivesHumanseducationDeveloping Countriesbusiness.industryPublic healthInfant NewbornInfantCIVIL REGISTRATIONPaediatricsChild survivalNewbornPREVENTIONMortality rateInfant mortalitywa_320ws_200Child mortalitySocioeconomic FactorsITC-ISI-JOURNAL-ARTICLEHuman medicinePaediatrics Public health Developing worldbusinessDemography
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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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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2·5 air pollution, 1990–2019: an analysis of data from the G…

2022

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution.Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regress…

Contaminación del AireHealth (social science)Type II DiabetesType 2 diabetes deathsair pollutionand YLLs attributable to all PM2·5 air pollutionMedicine (miscellaneous)and change from 1990 to 2019DALYsburden of diseaseGlobal Burden of DiseaseCarga Global de EnfermedadesMELLITUSINFLAMMATIONand household PM2·5 pollution from solid fuels in seven GBD super-regions and globally in 2019Diabetes MellitusHumansBiologyASSOCIATIONSRISKINSULIN-RESISTANCEGBD 2019 Diabetes and Air Pollution CollaboratorsHealth PolicyMaterial ParticuladoPublic Health Environmental and Occupational HealthBayes TheoremLONG-TERM EXPOSUREHumanosYLDsChemistryDiabetes Mellitus Type 23121 General medicine internal medicine and other clinical medicineAños de Vida Ajustados por Calidad de Vidaambient PM2·5 pollutionParticulate MatterQuality-Adjusted Life YearsHuman medicineFINE PARTICULATE MATTERRAType II Diabetes; air pollution; burden of disease;The Lancet Planetary Health
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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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