Literature DB >> 20374682

Selecting informative food items for compiling food-frequency questionnaires: comparison of procedures.

Marja L Molag1, Jeanne H M de Vries, Niels Duif, Marga C Ocké, Pieter C Dagnelie, R Alexandra Goldbohm, Pieter van't Veer.   

Abstract

The authors automated the selection of foods in a computer system that compiles and processes tailored FFQ. For the selection of food items, several methods are available. The aim of the present study was to compare food lists made by MOM2, which identifies food items with highest between-person variance in intake of the nutrients of interest without taking other items into account, with food lists made by forward regression. The name MOM2 refers to the variance, which is the second moment of the nutrient intake distribution. Food items were selected for the nutrients of interest from 2 d of recorded intake in 3524 adults aged 25-65 years. Food lists by 80 % MOM2 were compared to those by 80 % explained variance for regression on differences between the number and type of food items, and were evaluated on (1) the percentage of explained variance and (2) percentage contribution to population intake computed for the selected items on the food list. MOM2 selected the same food items for Ca, a few more for fat and vitamin C, and a few less for carbohydrates and dietary fibre than forward regression. Food lists by MOM2 based on 80 % of variance in intake covered 75-87 % of explained variance for different nutrients by regression and contributed 53-75 % to total population intake. Concluding, for developing food lists of FFQ, it appears sufficient to select food items based on the contribution to variance in nutrient intake without taking covariance into account.

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Year:  2010        PMID: 20374682     DOI: 10.1017/S0007114510000401

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  25 in total

1.  Development of the HELIUS food frequency questionnaires: ethnic-specific questionnaires to assess the diet of a multiethnic population in The Netherlands.

Authors:  M H Beukers; L H Dekker; E J de Boer; C W M Perenboom; S Meijboom; M Nicolaou; J H M de Vries; H A M Brants
Journal:  Eur J Clin Nutr       Date:  2014-09-17       Impact factor: 4.016

2.  The Maastricht Study: an extensive phenotyping study on determinants of type 2 diabetes, its complications and its comorbidities.

Authors:  Miranda T Schram; Simone J S Sep; Carla J van der Kallen; Pieter C Dagnelie; Annemarie Koster; Nicolaas Schaper; Ronald M A Henry; Coen D A Stehouwer
Journal:  Eur J Epidemiol       Date:  2014-04-23       Impact factor: 8.082

3.  Development and evaluation of a diet quality screener to assess adherence to the Dutch food-based dietary guidelines.

Authors:  Mariëlle G de Rijk; Anne I Slotegraaf; Elske M Brouwer-Brolsma; Corine W M Perenboom; Edith J M Feskens; Jeanne H M de Vries
Journal:  Br J Nutr       Date:  2021-11-15       Impact factor: 4.125

4.  Feasibility of dietary assessment methods, other tools and procedures for a pan-European food consumption survey among infants, toddlers and children.

Authors:  Marga Ocké; Henny Brants; Marcela Dofkova; Heinz Freisling; Caroline van Rossum; Jiri Ruprich; Nadia Slimani; Elisabeth Temme; Ellen Trolle; Stefanie Vandevijvere; Inge Huybrechts; Evelien de Boer
Journal:  Eur J Nutr       Date:  2014-08-10       Impact factor: 5.614

5.  A prospective cohort study of dietary patterns of non-western migrants in the Netherlands in relation to risk factors for cardiovascular diseases: HELIUS-Dietary Patterns.

Authors:  Louise H Dekker; Marieke B Snijder; Marja H Beukers; Jeanne H M de Vries; Henny A M Brants; Evelien J de Boer; Rob M van Dam; Karien Stronks; Mary Nicolaou
Journal:  BMC Public Health       Date:  2011-06-07       Impact factor: 3.295

6.  Socio-economic status and ethnicity are independently associated with dietary patterns: the HELIUS-Dietary Patterns study.

Authors:  Louise H Dekker; Mary Nicolaou; Rob M van Dam; Jeanne H M de Vries; Evelien J de Boer; Henny A M Brants; Marja H Beukers; Marieke B Snijder; Karien Stronks
Journal:  Food Nutr Res       Date:  2015-06-02       Impact factor: 3.894

7.  Associations of Dietary Glucose, Fructose, and Sucrose with β-Cell Function, Insulin Sensitivity, and Type 2 Diabetes in the Maastricht Study.

Authors:  Louise J C J den Biggelaar; Simone J P M Eussen; Simone J S Sep; Andrea Mari; Ele Ferrannini; Martien C J M van Dongen; Karlijn F M Denissen; Nicole E G Wijckmans; Miranda T Schram; Carla J van der Kallen; Annemarie Koster; Nicolaas Schaper; Ronald M A Henry; Coen D A Stehouwer; Pieter C Dagnelie
Journal:  Nutrients       Date:  2017-04-13       Impact factor: 5.717

8.  Dietary patterns and colorectal cancer risk in a Korean population: A case-control study.

Authors:  Yoon Park; Jeonghee Lee; Jae Hwan Oh; Aesun Shin; Jeongseon Kim
Journal:  Medicine (Baltimore)       Date:  2016-06       Impact factor: 1.889

9.  A National Dietary Assessment Reference Database (NDARD) for the Dutch Population: Rationale behind the Design.

Authors:  Elske M Brouwer-Brolsma; Martinette T Streppel; Linde van Lee; Anouk Geelen; Diewertje Sluik; Anne M van de Wiel; Jeanne H M de Vries; Pieter van 't Veer; Edith J M Feskens
Journal:  Nutrients       Date:  2017-10-18       Impact factor: 5.717

10.  External Validation Study of First Trimester Obstetric Prediction Models (Expect Study I): Research Protocol and Population Characteristics.

Authors:  Linda Jacqueline Elisabeth Meertens; Hubertina Cj Scheepers; Raymond G De Vries; Carmen D Dirksen; Irene Korstjens; Antonius Lm Mulder; Marianne J Nieuwenhuijze; Jan G Nijhuis; Marc Ea Spaanderman; Luc Jm Smits
Journal:  JMIR Res Protoc       Date:  2017-10-26
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