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

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.

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.


2012 ◽  
Vol 175 (7) ◽  
pp. 696-705 ◽  
Author(s):  
J. Zhou ◽  
S. Smith ◽  
E. Giovannucci ◽  
D. S. Michaud

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

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

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Bernard Srour ◽  
Marie Beslay ◽  
Caroline Méjean ◽  
Benjamin Allès ◽  
Thibault Fiolet ◽  
...  

AbstractIntroductionPrevious epidemiological studies have found associations between the consumption of ultra-processed foods and the risk of obesity-related outcomes, such as post-menopausal breast cancer, cardiovascular diseases, hypertension and mortality. However, only one Spanish prospective study has explored the associations between the consumption of ultra-processed foods and the risk of overweight and obesity. The aim of this study is to investigate the associations between ultra-processed food consumption and the risk of overweight and obesity, as well as the associations between ultra-processed food consumption and weight trajectories, in middle-aged adults included in the French large scale NutriNet-Santé cohort.MethodsOverall, 110260 participants aged at least 18 years from the French NutriNet-Santé cohort (2009–2019) were included. Dietary intakes were collected using repeated 24 hour dietary records, merged with a food composition database of 3300 different products. These were categorized according to their degree of processing by the NOVA classification. Associations between ultra-processed food intake and risks of overweight and obesity were assessed using multivariable Cox proportional hazard models. Associations between ultra-processed food intake and weight trajectories were assessed using multivariable linear mixed models for repeated measures with random slope and intercept. Models were adjusted for known risk factors (sociodemographic, lifestyle, and nutritional factors).ResultsUltra-processed food intake was associated with a higher risk of overweight (n = 7063 incident cases; hazard ratio for an absolute increment of 10 in the percentage of ultra-processed foods in the diet = 1.11 (95% confidence interval 1.08 to 1.14); P < 0.0001, median follow-up: 4.1y, 260304 person-years) and obesity (n = 3066 incident cases; HR = 1.09 (95% confidence interval 1.05 to 1.13); P < 0.0001, median follow-up: 8.0y 365344 person-years). Higher consumers of ultra-processed foods (4th quartile) were more likely to present an increase in body mass index over time (change of BMI/time-unit in Q4 vs Q1 = 0.04, P < 0.0001). These results remained statistically significant after adjustment for several markers of the nutritional quality of the diet (fruits and vegetables and sugary drinks consumption, intakes of saturated fatty acids, sodium, sugar, dietary fiber or Healthy/Western patterns derived by principal component analysis) and after a large range of sensitivity analyses.ConclusionIn this large observational prospective study, higher consumption of ultra-processed foods in the diet was associated with a higher risk of overweight and obesity. Public health authorities in several countries recently started to recommend privileging unprocessed/minimally processed foods and limiting ultra-processed food consumption.


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

2019 ◽  
Vol 2 (2) ◽  
pp. 126-134 ◽  
Author(s):  
Mary K. Downer ◽  
Christopher B. Allard ◽  
Mark A. Preston ◽  
Kathryn M. Wilson ◽  
Stacey A. Kenfield ◽  
...  

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