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RESEARCH PRODUCT
Perspective: Essential study quality descriptors for data from nutritional epidemiologic research
Jildau BouwmanNiels HulstaertEamon LairdJohn Van CampGiuditta PerozziMarta Stelmach-mardasPatrick KolsterenAxelle HogeStéphanie Maria PalombiMaria De AngelisChen YangIrina DobreHendrik De RuyckCarl LachatRosario LombardoGuy De TréChristophe MatthysKatharina NimptschPeter ClarysAngela A. RivelleseDolores CorellaDolores CorellaRaffaella CanaliMarco GobbettiJean TafforeauFabio MinerviniTobias PischonSofian De ClercqLaura KehoeAntoon BronselaerMariona PinartLars O. DragstedBernard De BaetsJanette WaltonNathalie De CockRosalba GiaccoOscar ColtellOscar Coltellsubject
0301 basic medicineDatabases FactualMedicine (miscellaneous)StorageBiomedical InnovationOntology (information science)Bioinformatics0302 clinical medicineLifedata interoperabilityObservational studyData interoperabilityMedicine030212 general & internal medicineAdipositymedia_commonNutrition and DieteticsAnthropometryOntologydietary assessmentNutritional assessmentObservational Studies as TopicIdentification (information)Research DesignDietary assessmentControlled vocabularyHealthy LivingPerspectivesHumanConsensusmedia_common.quotation_subject03 medical and health sciencesControlled vocabularyHumansQuality (business)Data QualityBiologyCross-sectional studyNutritional epidemiologyNutritional epidemiologybusiness.industryData qualityStudy designData scienceDietEpidemiologic StudiesCritical appraisalnutritional epidemiologyNutrition Assessment030104 developmental biologyMSB - Microbiology and Systems BiologyCardiovascular and Metabolic DiseasesData qualitySystematic reviewObservational studyobservational studyELSS - Earth Life and Social SciencesbusinessMeta analysisFood Sciencedescription
Pooled analysis of secondary data increases the power of research and enables scientific discovery in nutritional epidemiology. Information on study characteristics that determine data quality is needed to enable correct reuse and interpretation of data. This study aims to define essential quality characteristics for data from observational studies in nutrition. First, a literature review was performed to get an insight on existing instruments that assess the quality of cohort, case-control, and cross-sectional studies and dietary measurement. Second, 2 face-to-face workshops were organized to determine the study characteristics that affect data quality. Third, consensus on the data descriptors and controlled vocabulary was obtained. From 4884 papers retrieved, 26 relevant instruments, containing 164 characteristics for study design and 93 characteristics for measurements, were selected. The workshop and consensus process resulted in 10 descriptors allocated to "study design" and 22 to "measurement" domains. Data descriptors were organized as an ordinal scale of items to facilitate the identification, storage, and querying of nutrition data. Further integration of an Ontology for Nutrition Studies will facilitate interoperability of data repositories. © 2017 American Society for Nutrition.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-09-01 |