Literature DB >> 12947420

Comparison of nutrient intake data calculated on the basis of two different databases. Results and experiences from a Swedish-Finnish study.

P Hakala1, L-R Knuts, A Vuorinen, N Hammar, W Becker.   

Abstract

BACKGROUND AND
OBJECTIVE: In international surveys of food consumption and nutrient intake, it is essential that the dietary data are comparable when different databases and calculation programs are used. The aim of the present analysis was to examine the comparability of nutrient intake data calculated on the basis of the Swedish food composition database PC-kost and the Finnish food composition database Nutrica. SUBJECTS AND METHODS: A total of 20 male adults currently living in Sweden were selected from a group of Finnish twins of the Finnish Twin Cohort Study. Food consumption data were collected by means of diet history interviews. The estimated intakes of 30 nutrients calculated on the basis of PC-kost were compared to the corresponding estimates calculated on the basis of Nutrica. The calculation procedures were standardised.
RESULTS: No statistically significant differences were observed in the mean intakes of energy, total fat, saturated fat, carbohydrates, dietary fibre, alcohol, cholesterol, vitamin A, retinol, beta-carotene, vitamin D, alpha-tocopherol, riboflavin, niacin, vitamin B(12), vitamin C or phosphorus. PC-kost yielded a 20% higher intake (NS) for vitamin D and 23% higher intake (P<0.001) for thiamine than Nutrica, which is mainly attributed to the differences in the enrichment of foodstuffs between Sweden and Finland. Conversely, PC-kost yielded 53% lower values (P<0.001) for selenium than Nutrica, owing to the increased selenium content in many Finnish foodstuffs as a result of the addition of selenium to fertilisers. Statistically significant differences were found for protein, monounsaturated fatty acids, vitamin B(6), iron and sodium (5-9% higher values from PC-kost) and for polyunsaturated fatty acids, folate, zinc, calcium, magnesium and potassium (4-10% lower values from PC-kost). The variation in the intake of these nutrients between the two methods may be explained by the differences in foodstuff-specific nutrient values (eg product formulations), or differences in the sources of data, recipes or calculation procedures. The correlation coefficient was > or =0.81 for most nutrients. At least 85% of the subjects in each PC-kost quintile were classified into the same or adjacent Nutrica quintile for all nutrients.
CONCLUSIONS: Our results indicate that, for a dominant part of the examined nutrients, the estimated intakes calculated by means of standardised procedures using the PC-kost and Nutrica databases are comparable between Sweden and Finland. Differences observed for some nutrients reflect either actual differences in foods between the two countries or methodological differences in the assessment of nutrient intakes.

Entities:  

Mesh:

Year:  2003        PMID: 12947420     DOI: 10.1038/sj.ejcn.1601639

Source DB:  PubMed          Journal:  Eur J Clin Nutr        ISSN: 0954-3007            Impact factor:   4.016


  12 in total

1.  Concentrations of calcium, phosphorus, and vitamin D in human foods are not different among 4 food databases.

Authors:  Mikkyla M W Reid; Adronie Verbrugghe; Anna K Shoveller
Journal:  Can Vet J       Date:  2018-02       Impact factor: 1.008

2.  Cross-border use of food databases: equivalence of US and Australian databases for macronutrients.

Authors:  Suzanne S Summer; Nicholas J Ollberding; Trish Guy; Kenneth D R Setchell; Nadine Brown; Heidi J Kalkwarf
Journal:  J Acad Nutr Diet       Date:  2013-07-16       Impact factor: 4.910

3.  Comparison of different approaches to calculate nutrient intakes based upon 24-h recall data derived from a multicenter study in European adolescents.

Authors:  Cristina Julián-Almárcegui; Silvia Bel-Serrat; Mathilde Kersting; German Vicente-Rodriguez; Genevieve Nicolas; Krishna Vyncke; Carine Vereecken; Willem De Keyzer; Laurent Beghin; Stefania Sette; Lena Halström; Eva Grammatikaki; Marcela Gonzalez-Gross; Sandra Crispim; Nadia Slimani; Luis Moreno; Stefaan De Henauw; Inge Huybrechts
Journal:  Eur J Nutr       Date:  2015-03-10       Impact factor: 5.614

4.  Response to evaluation of the food composition tables: Beyond the divergence and agreement of intakes.

Authors:  Md Ruhul Amin; Masum Ali
Journal:  Matern Child Nutr       Date:  2021-05-04       Impact factor: 3.092

5.  Alcohol consumption and dietary patterns: the FinDrink study.

Authors:  Timothy O Fawehinmi; Jenni Ilomäki; Sari Voutilainen; Jussi Kauhanen
Journal:  PLoS One       Date:  2012-06-12       Impact factor: 3.240

6.  Food composition database harmonization for between-country comparisons of nutrient data in the TEDDY Study.

Authors:  Ulla Uusitalo; Carina Kronberg-Kippila; Carin Andren Aronsson; Sally Schakel; Stefanie Schoen; Irene Mattisson; Heli Reinivuo; Katherine Silvis; Wolfgang Sichert-Hellert; Mary Stevens; Jill M Norris; Suvi M Virtanen
Journal:  J Food Compost Anal       Date:  2011-06       Impact factor: 4.520

7.  Development of a semi-quantitative food frequency questionnaire for use in United Arab Emirates and Kuwait based on local foods.

Authors:  Mahshid Dehghan; Nawal Al Hamad; AfzalHussein Yusufali; Fathimunissa Nusrath; Salim Yusuf; Anwar T Merchant
Journal:  Nutr J       Date:  2005-05-27       Impact factor: 3.271

8.  Food composition database development for between country comparisons.

Authors:  Anwar T Merchant; Mahshid Dehghan
Journal:  Nutr J       Date:  2006-01-19       Impact factor: 3.271

9.  Elevated Levels of 1,25-Dihydroxyvitamin D in Plasma as a Missing Risk Factor for Celiac Disease.

Authors:  Seth Scott Bittker
Journal:  Clin Exp Gastroenterol       Date:  2020-01-08

10.  How to use the world's scarce selenium resources efficiently to increase the selenium concentration in food.

Authors:  Anna Haug; Robin D Graham; Olav A Christophersen; Graham H Lyons
Journal:  Microb Ecol Health Dis       Date:  2007-12
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.