scholarly journals Categorising ultra-processed foods in large-scale cohort studies: evidence from the Nurses’ Health Studies, the Health Professionals Follow-up Study, and the Growing Up Today Study

2021 ◽  
Vol 10 ◽  
Author(s):  
Neha Khandpur ◽  
Sinara Rossato ◽  
Jean-Philippe Drouin-Chartier ◽  
Mengxi Du ◽  
Euridice M. Steele ◽  
...  

Abstract This manuscript details the strategy employed for categorising food items based on their processing levels into the four NOVA groups. Semi-quantitative food frequency questionnaires (FFQs) from the Nurses’ Health Studies (NHS) I and II, the Health Professionals Follow-up Study (HPFS) and the Growing Up Today Studies (GUTS) I and II cohorts were used. The four-stage approach included: (i) the creation of a complete food list from the FFQs; (ii) assignment of food items to a NOVA group by three researchers; (iii) checking for consensus in categorisation and shortlisting discordant food items; (iv) discussions with experts and use of additional resources (research dieticians, cohort-specific documents, online grocery store scans) to guide the final categorisation of the short-listed items. At stage 1, 205 and 315 food items were compiled from the NHS and HPFS, and the GUTS FFQs, respectively. Over 70 % of food items from all cohorts were assigned to a NOVA group after stage 2. The remainder were shortlisted for further discussion (stage 3). After two rounds of reviews at stage 4, 95⋅6 % of food items (NHS + HPFS) and 90⋅7 % items (GUTS) were categorised. The remaining products were assigned to a non-ultra-processed food group (primary categorisation) and flagged for sensitivity analyses at which point they would be categorised as ultra-processed. Of all items in the food lists, 36⋅1 % in the NHS and HPFS cohorts and 43⋅5 % in the GUTS cohorts were identified as ultra-processed. Future work is needed to validate this approach. Documentation and discussions of alternative approaches for categorisation are encouraged.

2021 ◽  
Author(s):  
Neha Khandpur ◽  
Sinara Rossato ◽  
Jean-Philippe Drouin-Chartier ◽  
Mengxi Du ◽  
Euridice Martinez ◽  
...  

AbstractObjectiveThere is limited description and documentation of the methods used for the categorization of dietary intake according to the NOVA classification, in large-scale cohort studies. This manuscript details the strategy employed for categorizing the food intake, assessed using food frequency questionnaires (FFQs), of participants in the Nurses’ Health Studies (NHS) I and II, the Health Professionals Follow-up Study (HPFS), and the Growing Up Today Studies (GUTS) I and II into the four NOVA groups to identify the ultra-processed portion of their diets.MethodsA four-stage approach was employed: (1) compilation of all food items from the FFQs used at different waves of data collection; (2) assignment of food items to a NOVA group by three researchers working independently; (3) checking for consensus in categorization and shortlisting food items for which there was disagreement; (4) discussions with experts and use of additional resources (research dieticians, cohort-specific documents, online grocery store scans) to guide the final categorization of the short-listed items.ResultsAt stage 1, 205 and 315 food items were compiled from the adult and GUTS FFQ food lists, respectively. Over 70% of food items from all cohorts were assigned to a NOVA group after stage 2 and the remainder were shortlisted for further discussion (stage 3). Two rounds of reviews at stage 4 helped with the categorization of 96.5% of items from the adult cohorts and 90.7% items from the youth cohort. The remaining products were assigned to a non-ultra-processed food group and ear-marked for sensitivity analyses. Of all items in the food lists, 36.1% in the adult cohorts and 43.5% in the GUTS cohorts were identified as ultra-processed.ConclusionAn iterative, conservative approach was used to categorize food items from the NHS, HPFS and GUTS FFQ food lists according to their grade of processing. The approach relied on discussions with experts and was informed by insights from the research dieticians, information provided by cohort-specific documents, and scans of online supermarkets. Future work is needed to validate this approach.


2015 ◽  
Vol 137 (4) ◽  
pp. 949-958 ◽  
Author(s):  
Elizabeth A. Platz ◽  
Charles G. Drake ◽  
Kathryn M. Wilson ◽  
Siobhan Sutcliffe ◽  
Stacey A. Kenfield ◽  
...  

Author(s):  
Natalie A. Laframboise ◽  
Jamie A. Seabrook ◽  
June I. Matthews ◽  
Paula D. N. Dworatzek

Purpose: To evaluate foods advertised in discount and premium grocery flyers for their alignment with Canada’s 2007 Food Guide (CFG) and assess if alignment differed by food category, season, page location, and price. Methods: Weekly flyers (n = 192) were collected from discount and premium grocery chains from each of 4 seasons. Health Canada’s Surveillance Tool was used to assess food items as in-line or not in-line with CFG. Results: Of 35 576 food items, 39.7% were in-line with CFG. There were no differences in proportions of foods not in-line in discount versus premium flyers (60.9% and 60.0%, respectively). Other Foods and Meat & Alternatives were advertised most (28.0% and 26.3%, respectively; P < 0.001). Milk & Alternatives were the least advertised food group (10.3%). Vegetables & Fruit (19.6%), Grains (21.6%), Milk & Alternatives (20.6%), and Meat & Alternatives (20.2%) were promoted least in Fall (P < 0.001). A higher proportion of foods advertised on middle pages were not in-line (61.0%) compared with front (56.6%) and back (58.8%) pages (P < 0.001). Not in-line foods were more expensive ($3.49, IQR = $2.82) than in-line foods ($3.28, IQR = $2.81; P < 0.001). Conclusions: While there was no difference in healthfulness of foods advertised in discount versus premium flyers, grocers advertised more foods not in-line with CFG. Government policies to improve the food environment should consider grocery flyers.


2016 ◽  
Vol 124 (10) ◽  
pp. 1529-1536 ◽  
Author(s):  
Ngoan Tran Le ◽  
Fernanda Alessandra Silva Michels ◽  
Mingyang Song ◽  
Xuehong Zhang ◽  
Adam M. Bernstein ◽  
...  

2019 ◽  
Vol 124 ◽  
pp. 153-160 ◽  
Author(s):  
Jared A. Fisher ◽  
Robin C. Puett ◽  
Francine Laden ◽  
Gregory A. Wellenius ◽  
Amir Sapkota ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document