» Articles » PMID: 20216562

Should Nutrient Profile Models Be 'category Specific' or 'across-the-board'? A Comparison of the Two Systems Using Diets of British Adults

Overview
Journal Eur J Clin Nutr
Date 2010 Mar 11
PMID 20216562
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

Background/objectives: Nutrient profile models have the potential to help promote healthier diets. Some models treat all foods equally (across-the-board), some consider different categories of foods separately (category specific). This paper assesses whether across-the-board or category-specific nutrient profile models are more appropriate tools for improving diets.

Subjects/methods: Adult respondents to a British dietary survey were split into four groups using a diet quality index. Fifteen food categories were identified. A nutrient profile model provided a measure of the healthiness of all foods consumed. The four diet quality groups were compared for differences in (a) the calories consumed from each food category and (b) the healthiness of foods consumed in each category. Evidence of healthier diet quality groups consuming more of healthy food categories than unhealthy diet quality groups supported the adoption of across-the-board nutrient profile models. Evidence of healthier diet quality groups consuming healthier versions of foods within food categories supported adoption of category-specific nutrient profile models.

Results: A significantly greater percentage of the healthiest diet quality group's diet consisted of fruit and vegetables (21 vs 16%), fish (3 vs 2%) and breakfast cereals (7 vs 2%), and significantly less meat and meat products (7 vs 14%) than the least healthy diet quality group. The foods from the meat, dairy and cereals categories consumed by the healthy diet quality groups were healthier versions than those consumed by the unhealthy diet quality groups.

Conclusions: All other things being equal, nutrient profile models designed to promote an achievable healthy diet should be category specific but with a limited number of categories. However models which use a large number of categories are unhelpful for promoting a healthy diet.

Citing Articles

Development of a Nutrient Profiling Model for Processed Foods in Japan.

Takebayashi J, Takimoto H, Okada C, Tousen Y, Ishimi Y Nutrients. 2024; 16(17).

PMID: 39275341 PMC: 11397564. DOI: 10.3390/nu16173026.


Validating nutrient selection for product-group-specific nutrient indices for use as functional units in life cycle assessment of foods.

Karlund A, Kytta V, Pellinen T, Tuomisto H, Pajari A, Kolehmainen M Br J Nutr. 2024; 131(12):2049-2057.

PMID: 38606563 PMC: 11361913. DOI: 10.1017/S0007114524000709.


Nutri-Score 2023 update.

Merz B, Temme E, Alexiou H, Beulens J, Buyken A, Bohn T Nat Food. 2024; 5(2):102-110.

PMID: 38356074 DOI: 10.1038/s43016-024-00920-3.


Perspective: How to Develop Nutrient Profiling Models Intended for Global Use: A Manual.

Drewnowski A, Amanquah D, Gavin-Smith B Adv Nutr. 2021; 12(3):609-620.

PMID: 33724302 PMC: 8166553. DOI: 10.1093/advances/nmab018.


The SENS algorithm-a new nutrient profiling system for food labelling in Europe.

Darmon N, Sondey J, Azais-Braesco V, Maillot M Eur J Clin Nutr. 2017; 72(2):236-248.

PMID: 29259339 PMC: 5842883. DOI: 10.1038/s41430-017-0017-6.


References
1.
Becker W, Welten D . Under-reporting in dietary surveys--implications for development of food-based dietary guidelines. Public Health Nutr. 2001; 4(2B):683-7. DOI: 10.1079/phn2001154. View

2.
Seymour J, Calle E, Flagg E, Coates R, Ford E, Thun M . Diet Quality Index as a predictor of short-term mortality in the American Cancer Society Cancer Prevention Study II Nutrition Cohort. Am J Epidemiol. 2003; 157(11):980-8. DOI: 10.1093/aje/kwg077. View

3.
Scarborough P, Rayner M, Stockley L . Developing nutrient profile models: a systematic approach. Public Health Nutr. 2007; 10(4):330-6. DOI: 10.1017/S1368980007223870. View

4.
Scagliusi F, Ferriolli E, Pfrimer K, Laureano C, Cunha C, Gualano B . Under-reporting of energy intake is more prevalent in a healthy dietary pattern cluster. Br J Nutr. 2008; 100(5):1060-8. DOI: 10.1017/S0007114508971300. View

5.
Gibson S, Neate D . Sugar intake, soft drink consumption and body weight among British children: further analysis of National Diet and Nutrition Survey data with adjustment for under-reporting and physical activity. Int J Food Sci Nutr. 2007; 58(6):445-60. DOI: 10.1080/09637480701288363. View