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

Chen Yang; Mariona Pinart; Patrick Kolsteren; John Van Camp; Nathalie De Cock; Katharina Nimptsch; Tobias Pischon; Eamon Laird; Giuditta Perozzi; Raffaella Canali; Axelle Hoge; Marta Stelmach-Mardas; Lars Ove Dragsted; Stéphanie Maria Palombi; Irina Dobre; Jildau Bouwman; Peter Clarys; Fabio Minervini; Maria De Angelis; Marco Gobbetti; Jean Tafforeau; Oscar Coltell; Dolores Corella; Hendrik De Ruyck; Janette Walton; Laura Kehoe; Christophe Matthys; Bernard De Baets; Guy De Tré; Antoon Bronselaer; Angela Rivellese; Rosalba Giacco; Rosario Lombardo; Sofian De Clercq; Niels Hulstaert; Carl Lachat

doi:10.3945/an.117.015651

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

Chen Yang, Mariona Pinart, Patrick Kolsteren, John Van Camp, Nathalie De Cock, Katharina Nimptsch, Tobias Pischon, Eamon Laird, Giuditta Perozzi, Raffaella Canali, Axelle Hoge, Marta Stelmach-Mardas, Lars Ove Dragsted, Stéphanie Maria Palombi, Irina Dobre, Jildau Bouwman, Peter Clarys, Fabio Minervini, Maria De Angelis, Marco GobbettiJean Tafforeau, Oscar Coltell, Dolores Corella, Hendrik De Ruyck, Janette Walton, Laura Kehoe, Christophe Matthys, Bernard De Baets, Guy De Tré, Antoon Bronselaer, Angela Rivellese, Rosalba Giacco, Rosario Lombardo, Sofian De Clercq, Niels Hulstaert, Carl Lachat

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6 Citationer (Scopus)

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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.

Originalsprog	Engelsk
Tidsskrift	Advances in Nutrition
Vol/bind	8
Udgave nummer	5
Sider (fra-til)	639-651
Antal sider	13
ISSN	2161-8313
DOI	https://doi.org/10.3945/an.117.015651
Status	Udgivet - 1 sep. 2017

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10.3945/an.117.015651Licens: CC BY

Yang et al_Advances in Nutrition_2017_Vol 8_639-651Forlagets udgivne version, 892 KBLicens: CC BY

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Yang, C., Pinart, M., Kolsteren, P., Van Camp, J., De Cock, N., Nimptsch, K., Pischon, T., Laird, E., Perozzi, G., Canali, R., Hoge, A., Stelmach-Mardas, M., Dragsted, L. O., Palombi, S. M., Dobre, I., Bouwman, J., Clarys, P., Minervini, F., De Angelis, M., ... Lachat, C. (2017). Perspective: Essential study quality descriptors for data from nutritional epidemiologic research. Advances in Nutrition, 8(5), 639-651. https://doi.org/10.3945/an.117.015651

Yang, C, Pinart, M, Kolsteren, P, Van Camp, J, De Cock, N, Nimptsch, K, Pischon, T, Laird, E, Perozzi, G, Canali, R, Hoge, A, Stelmach-Mardas, M, Dragsted, LO, Palombi, SM, Dobre, I, Bouwman, J, Clarys, P, Minervini, F, De Angelis, M, Gobbetti, M, Tafforeau, J, Coltell, O, Corella, D, De Ruyck, H, Walton, J, Kehoe, L, Matthys, C, De Baets, B, De Tré, G, Bronselaer, A, Rivellese, A, Giacco, R, Lombardo, R, De Clercq, S, Hulstaert, N & Lachat, C 2017, 'Perspective: Essential study quality descriptors for data from nutritional epidemiologic research', Advances in Nutrition, bind 8, nr. 5, s. 639-651. https://doi.org/10.3945/an.117.015651

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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.",

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note = "CURIS 2017 NEXS 248",

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doi = "10.3945/an.117.015651",

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T2 - Essential study quality descriptors for data from nutritional epidemiologic research

AU - Yang, Chen

AU - Pinart, Mariona

AU - Kolsteren, Patrick

AU - Van Camp, John

AU - De Cock, Nathalie

AU - Nimptsch, Katharina

AU - Pischon, Tobias

AU - Laird, Eamon

AU - Perozzi, Giuditta

AU - Canali, Raffaella

AU - Hoge, Axelle

AU - Stelmach-Mardas, Marta

AU - Dragsted, Lars Ove

AU - Palombi, Stéphanie Maria

AU - Dobre, Irina

AU - Bouwman, Jildau

AU - Clarys, Peter

AU - Minervini, Fabio

AU - De Angelis, Maria

AU - Gobbetti, Marco

AU - Tafforeau, Jean

AU - Coltell, Oscar

AU - Corella, Dolores

AU - De Ruyck, Hendrik

AU - Walton, Janette

AU - Kehoe, Laura

AU - Matthys, Christophe

AU - De Baets, Bernard

AU - De Tré, Guy

AU - Bronselaer, Antoon

AU - Rivellese, Angela

AU - Giacco, Rosalba

AU - Lombardo, Rosario

AU - De Clercq, Sofian

AU - Hulstaert, Niels

AU - Lachat, Carl

N1 - CURIS 2017 NEXS 248

PY - 2017/9/1

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N2 - 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.

AB - 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.

KW - Data quality

KW - Observational study

KW - Dietary assessment

KW - Nutritional epidemiology

KW - Data interoperability

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DO - 10.3945/an.117.015651

M3 - Journal article

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SN - 2161-8313

VL - 8

SP - 639

EP - 651

JO - Advances in Nutrition

JF - Advances in Nutrition

IS - 5

ER -

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

Abstract

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