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Processing level and diet quality of the US grocery cart: is there an association?

  • Filippa Juul (a1), Bárbara dos Santos Simões (a2), Jacqueline Litvak (a1), Euridice Martinez-Steele (a3) (a4), Andrea Deierlein (a1), Maya Vadiveloo (a5) and Niyati Parekh (a1) (a6)...

Abstract

Objective:

The majority of groceries purchased by US households are industrially processed, yet it is unclear how processing level influences diet quality. We sought to determine if processing level is associated with diet quality of grocery purchases.

Design:

We analysed grocery purchasing data from the National Household Food Acquisition and Purchase Survey 2012–2013. Household grocery purchases were categorized by the NOVA framework as minimally processed, processed culinary ingredients, processed foods or ultra-processed foods. The energy share of each processing level (percentage of energy; %E) and Healthy Eating Index-2015 (HEI-2015) component and total scores were calculated for each household’s purchases. The association between %E from processed foods and ultra-processed foods, respectively, and HEI-2015 total score was determined by multivariable linear regression. Foods purchased by households with the highest v. lowest ultra-processed food purchases and HEI-2015 total score <40 v. ≥60 were compared using linear regression.

Setting:

USA.

Participants:

Nationally representative sample of 3961 households.

Results:

Processed foods and ultra-processed foods provided 9·2 (se 0·3) % and 55·8 (se 0·6) % of purchased energy, respectively. Mean HEI-2015 score was 54·7 (se 0·4). Substituting 10 %E from minimally processed foods and processed culinary ingredients for ultra-processed foods decreased total HEI-2015 score by 1·8 points (β = −1·8; 95 % CI −2·0, −1·5). Processed food purchases were not associated with diet quality. Among households with high ultra-processed food purchases, those with HEI-2015 score <40 purchased less minimally processed plant-foods than households with HEI-2015 score ≥60.

Conclusions:

Increasing purchases of minimally processed foods, decreasing purchases of ultra-processed foods and selecting healthier foods at each processing level may improve diet quality.

Copyright

Corresponding author

*Corresponding author: Email niyati.parekh@nyu.edu

Footnotes

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Joint first authors.

Footnotes

References

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1.Wilson, MM, Reedy, J & Krebs-Smith, SM (2016) American diet quality: where it is, where it is heading, and what it could be. J Acad Nutr Diet 116, 302310.e1.
2.Miller, PE, Reedy, J, Kirkpatrick, SI et al. (2015) The United States food supply is not consistent with dietary guidance: evidence from an evaluation using the Healthy Eating Index-2010. J Acad Nutr Diet 115, 95100.
3.Bureau of Labor Statistics, US Department of Labor (2017) Consumer Price Index – December 2017 (press release). https://www.bls.gov/news.release/archives/cpi_01122018.pdf (accessed January 2018).
4.Appelhans, BM, French, SA, Tangney, CC et al. (2017) To what extent do food purchases reflect shoppers’ diet quality and nutrient intake? Int J Behav Nutr Phys Act 14, 46.
5.Grant, E, Gearry, RB, Wilson, R et al. (2017) Home availability of fruit and vegetables and obesogenic foods as an indicator of nutrient intake in 50 year olds from Canterbury, New Zealand. Asia Pac J Clin Nutr 26, 524530.
6.Couch, SC, Glanz, K, Zhou, C et al. (2014) Home food environment in relation to children’s diet quality and weight status. J Acad Nutr Diet 114, 15691579.e1.
7.Alber, JM, Green, SH & Glanz, K (2018) Perceived and observed food environments, eating behaviors, and BMI. Am J Prev Med 54, 423429.
8.Cullen, KW, Baranowski, T, Owens, E et al. (2003) Availability, accessibility, and preferences for fruit, 100% fruit juice, and vegetables influence children’s dietary behavior. Health Educ Behav 30, 615626.
9.Ding, D, Sallis, JF, Norman, GJ et al. (2012) Community food environment, home food environment, and fruit and vegetable intake of children and adolescents. J Nutr Educ Behav 44, 634638.
10.Granner, ML & Evans, AE (2011) Variables associated with fruit and vegetable intake in adolescents. Am J Health Behav 35, 591602.
11.Hanson, NI, Neumark-Sztainer, D, Eisenberg, ME et al. (2005) Associations between parental report of the home food environment and adolescent intakes of fruits, vegetables and dairy foods. Public Health Nutr 8, 7785.
12.Neumark-Sztainer, D, Wall, M, Perry, C et al. (2003) Correlates of fruit and vegetable intake among adolescents. Findings from Project EAT. Prev Med 37, 198208.
13.Liberato, SC, Bailie, R & Brimblecombe, J (2014) Nutrition interventions at point-of-sale to encourage healthier food purchasing: a systematic review. BMC Public Health 14, 919.
14.Adam, A & Jensen, JD (2016) What is the effectiveness of obesity related interventions at retail grocery stores and supermarkets? A systematic review. BMC Public Health 16, 1247.
15.Ludwig, DS (2011) Technology, diet, and the burden of chronic disease. JAMA 305, 13521353.
16.Lustig, RH (2017) Processed food – an experiment that failed. JAMA Pediatr 171, 212214.
17.Monteiro, CA, Moubarac, JC, Cannon, G et al. (2013) Ultra-processed products are becoming dominant in the global food system. Obes Rev 14, Suppl. 2, 2128.
18.Poti, JM, Mendez, MA, Ng, SW et al. (2015) Is the degree of food processing and convenience linked with the nutritional quality of foods purchased by US households? Am J Clin Nutr 101, 12511262.
19.Weaver, CM, Dwyer, J, Fulgoni, VL 3rd et al. (2014) Processed foods: contributions to nutrition. Am J Clin Nutr 99, 15251542.
20.Dwyer, JT, Fulgoni, VL, Clemens, RA et al. (2012) Is ‘processed’ a four-letter word? The role of processed foods in achieving dietary guidelines and nutrient recommendations. Adv Nutr 3, 536548.
21.Martinez Steele, E, Popkin, BM, Swinburn, B et al. (2017) The share of ultra-processed foods and the overall nutritional quality of diets in the US: evidence from a nationally representative cross-sectional study. Popul Health Metr 15, 6.
22.Moubarac, JC, Batal, M, Louzada, ML et al. (2017) Consumption of ultra-processed foods predicts diet quality in Canada. Appetite 108, 512520.
23.Adams, J & White, M (2015) Characterisation of UK diets according to degree of food processing and associations with socio-demographics and obesity: cross-sectional analysis of UK National Diet and Nutrition Survey (2008–12). Int J Behav Nutr Phys Act 12, 160.
24.Louzada, ML, Martins, AP, Canella, DS et al. (2015) Impact of ultra-processed foods on micronutrient content in the Brazilian diet. Rev Saude Publica 49, 45.
25.Julia, C, Martinez, L, Alles, B et al. (2018) Contribution of ultra-processed foods in the diet of adults from the French NutriNet-Sante study. Public Health Nutr 21, 2737.
26.Batal, M, Johnson-Down, L, Moubarac, JC et al. (2018) Quantifying associations of the dietary share of ultra-processed foods with overall diet quality in First Nations peoples in the Canadian provinces of British Columbia, Alberta, Manitoba and Ontario. Public Health Nutr 21, 103113.
27.Cediel, G, Reyes, M, da Costa Louzada, ML et al. (2018) Ultra-processed foods and added sugars in the Chilean diet (2010). Public Health Nutr 21, 125133.
28.Eicher-Miller, HA, Fulgoni, VL 3rd, Keast, DR (2012) Contributions of processed foods to dietary intake in the US from 2003–2008: a report of the Food and Nutrition Science Solutions Joint Task Force of the Academy of Nutrition and Dietetics, American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. J Nutr 142, issue 11, 2065S2072S.
29.US Department of Agriculture, Economic Research Service (2019) FoodAPS National Household Food Acquisition and Purchase Survey. https://www.ers.usda.gov/foodaps (accessed March 2019).
30.Mancino, L, Todd, JE & Scharadin, B (2018) USDA’s National Household Food Acquisition and Purchase Survey: Methodology for Imputing Missing Quantities to Calculate Healthy Eating Index-2010 Scores and Sort Foods into ERS Food Groups. Technical Bulletin no. TB-1947. Washington, DC: U.S. Department of Agriculture, Economic Research Service.
31.Moubarac, JC, Parra, DC, Cannon, G et al. (2014) Food classification systems based on food processing: significance and implications for policies and actions: a systematic literature review and assessment. Curr Obes Rep 3, 256272.
32.US Department of Agriculture, Economic Research Service (2016) National Household Food Acquisition and Purchase Survey (FoodAPS): Nutrient Coding Overview. Washington, DC: US Department of Agriculture, Economic Research Service.
33.Guenther, PM, Reedy, J & Krebs-Smith, SM (2008) Development of the Healthy Eating Index-2005. J Am Diet Assoc 108, 18961901.
34.Kennedy, ET, Ohls, J, Carlson, S & Fleming, K (1995) The Healthy Eating Index: design and applications. J Am Diet Assoc 95, 11031108.
35.National Cancer Institute (2018) Comparing the HEI-2015, HEI-2010 & HEI-2005. https://epi.grants.cancer.gov/hei/comparing.html (accessed September 2018).
36.National Cancer Institute (2018) SAS Code: National Cancer Institute. https://epi.grants.cancer.gov/hei/sas-code.html (accessed September 2018).
37.Krebs-Smith, SM, Pannucci, TE, Subar, AF et al. (2018) Update of the Healthy Eating Index: HEI-2015. J Acad Nutr Diet 118, 15911602.
38.Hiza, HA, Casavale, KO, Guenther, PM et al. (2013) Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet 113, 297306.
39.Andreyeva, T, Tripp, AS & Schwartz, MB (2015) Dietary quality of Americans by Supplemental Nutrition Assistance Program participation status: a systematic review. Am J Prev Med 49, 594604.
40.Makarem, N, Bandera, EV, Lin, Y et al. (2018) Consumption of sugars, sugary foods, and sugary beverages in relation to adiposity-related cancer risk in the Framingham Offspring cohort (1991–2013). Cancer Prev Res (Phila) 11, 347358.
41.Food and Agriculture Organization of the United Nations (2015) Guidelines on the Collection of Information on Food Processing through Food Consumption Surveys. Rome: FAO.

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Processing level and diet quality of the US grocery cart: is there an association?

  • Filippa Juul (a1), Bárbara dos Santos Simões (a2), Jacqueline Litvak (a1), Euridice Martinez-Steele (a3) (a4), Andrea Deierlein (a1), Maya Vadiveloo (a5) and Niyati Parekh (a1) (a6)...

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