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Perspective: Essential study quality descriptors for data from nutritional epidemiologic research

Chen Yang UGent, Mariona Pinart, Patrick Kolsteren UGent, John Van Camp UGent, Nathalie De Cock UGent, Katharina Nimptsch, Tobias Pischon, Eamon Laird, Giuditta Perozzi, Raffaella Canali, et al. (2017) ADVANCES IN NUTRITION. 8(5). p.639-651
abstract
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
data quality, observational study, dietary assessment, nutritional epidemiology, data interoperability, CRITICAL-APPRAISAL, SCORING SYSTEM, PUBLIC-HEALTH, VALIDITY, BIAS, TOOL, METAANALYSIS, INSTRUMENTS, INFORMATION, DISEASE
journal title
ADVANCES IN NUTRITION
Adv. Nutr.
volume
8
issue
5
pages
639 - 651
Web of Science type
Article
Web of Science id
000410751300001
ISSN
2161-8313
2156-5376
DOI
10.3945/an.117.015651
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
8532545
handle
http://hdl.handle.net/1854/LU-8532545
date created
2017-09-28 09:28:45
date last changed
2017-11-28 09:46:56
@article{8532545,
  abstract     = {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 {\textacutedbl}study design{\textacutedbl} and 22 to {\textacutedbl}measurement{\textacutedbl} 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.},
  author       = {Yang, Chen and Pinart, Mariona and Kolsteren, Patrick and Van Camp, John and De Cock, Nathalie and Nimptsch, Katharina and Pischon, Tobias and Laird, Eamon and Perozzi, Giuditta and Canali, Raffaella and Hoge, Axelle and Stelmach-Mardas, Marta and Dragsted, Lars Ove and Palombi, St{\'e}phanie Maria and Dobre, Irina and Bouwman, Jildau and Clarys, Peter and Minervini, Fabio and De Angelis, Maria and Gobbetti, Marco and Tafforeau, Jean and Coltell, Oscar and Corella, Dolores and De Ruyck, Hendrik and Walton, Janette and Kehoe, Laura and Matthys, Christophe and De Baets, Bernard and De Tr{\'e}, Guy and Bronselaer, Antoon and Rivellese, Angela and Giacco, Rosalba and Lombardo, Rosario and De Clercq, Sofian and Hulstaert, Niels and Lachat, Carl},
  issn         = {2161-8313},
  journal      = {ADVANCES IN NUTRITION},
  keyword      = {data quality,observational study,dietary assessment,nutritional epidemiology,data interoperability,CRITICAL-APPRAISAL,SCORING SYSTEM,PUBLIC-HEALTH,VALIDITY,BIAS,TOOL,METAANALYSIS,INSTRUMENTS,INFORMATION,DISEASE},
  language     = {eng},
  number       = {5},
  pages        = {639--651},
  title        = {Perspective: Essential study quality descriptors for data from nutritional epidemiologic research},
  url          = {http://dx.doi.org/10.3945/an.117.015651},
  volume       = {8},
  year         = {2017},
}

Chicago
Yang, Chen, Mariona Pinart, Patrick Kolsteren, John Van Camp, Nathalie De Cock, Katharina Nimptsch, Tobias Pischon, et al. 2017. “Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research.” Advances in Nutrition 8 (5): 639–651.
APA
Yang, Chen, Pinart, M., Kolsteren, P., Van Camp, J., De Cock, N., Nimptsch, K., Pischon, T., et al. (2017). Perspective: Essential study quality descriptors for data from nutritional epidemiologic research. ADVANCES IN NUTRITION, 8(5), 639–651.
Vancouver
1.
Yang C, Pinart M, Kolsteren P, Van Camp J, De Cock N, Nimptsch K, et al. Perspective: Essential study quality descriptors for data from nutritional epidemiologic research. ADVANCES IN NUTRITION. 2017;8(5):639–51.
MLA
Yang, Chen, Mariona Pinart, Patrick Kolsteren, et al. “Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research.” ADVANCES IN NUTRITION 8.5 (2017): 639–651. Print.