Ultra-processed foods - a scoping review for Nordic Nutrition Recommendations 2023.

Ultra-processed foods (UPFs) are increasingly consumed worldwide and have been linked to several chronic diseases. This paper aims to describe the totality of the available evidence regarding UPFs in relation to health-related outcomes as a basis for setting food-based dietary guidelines for the Nordic Nutrition Recommendations 2023. Systematic literature searches were conducted to identify systematic reviews, meta-analyses, randomized controlled trials (RCTs), and prospective cohort studies examining the association between UPF intake and non-communicable diseases or mortality. A total of 12 systematic reviews (including five meta-analyses) and 44 original research studies (43 prospective cohort studies and one RCT) were included. All original research studies were deemed to be of good methodological quality. The current evidence supports that greater consumption of UPFs is associated with weight gain and increased risk of obesity, cardiovascular disease, type 2 diabetes, and all-cause mortality. The available literature also supports an association between UPFs and hypertension, cancer, and depression; however, the limited number of studies and subjects investigated preclude strong conclusions. Due to the highly diverse nature of UPFs, additional studies are warranted, with special emphasis on disentangling mediating mechanisms, whether nutritional or non-nutrient based. Nevertheless, the available evidence regarding UPFs in relation to weight gain, CVD, type 2 diabetes, and all-cause mortality is considered strong enough to support dietary recommendations to limit their consumption.

Associations Between Ultra-processed Food Consumption and Cardiometabolic Health Among Older US Adults: Comparing Older Asian Americans to Older Adults From Other Major Race-Ethnic Groups.

Using data from the National Health and Nutrition Examination Survey (2001-2018; N = 19,602), this study examined whether ultra-processed food (UPF) consumption is associated with cardiometabolic health (obesity, hypertension, high cholesterol, and diabetes), among White, Black, Hispanic, and Asian Americans (AA) US adults 50 or older. Diet was assessed using 24 hour dietary recall. NOVA dietary classification system was used to calculate the percentage of caloric intake derived from UPFs. Cardiometabolic information was assessed through physical examination, blood tests, and self-reported medication information. A median of 54% (IQR: 40%, 68%) of caloric intake was attributed to UPFs and was lowest for AAs (34%, IQR: 20%, 49%) and highest for White adults (56%; IQR: 42, 69%). In multivariable adjusted models, UPF consumption was associated with greater odds of obesity, high cholesterol, and diabetes. UPF consumption is associated with poor cardiometabolic health among all US older adults. For AAs, UPFs may be particularly obesogenic.

Ultra-processed food intake among South Asians in the United States: Specific vulnerabilities of a growing immigrant population group.

South Asians are among the fastest growing immigrant population groups in the United States. Their traditional diets are rich in minimally processed fruits, vegetables, grains, herbs, and spices. However, the proliferation of ultra-processed foods (highly processed, industrially manufactured formulations) around the globe may compromise the nutrition profile of South Asians, threatening to increase their risk of noncommunicable diseases. This commentary discusses the rise in ultra-processed food consumption among South Asians in the United States and hypothesizes that South Asians may be especially vulnerable to the effects of ultra-processed foods due to their unique cardiovascular disease risk profiles. Using these emerging data, we propose several strategies for preventing the overconsumption of ultra-processed foods among South Asian Americans. These include the implementation of policies to encourage the consumption of whole foods over ultra-processed foods and the development of culturally tailored interventions, which include promoting consumption of traditional diets, improving affordability of healthful, culturally appropriate foods, and cultivating healthier food environments for South Asians living in the United States.

Perspective: A Research Roadmap about Ultra-Processed Foods and Human Health for the United States Food System: Proceedings from an Interdisciplinary, Multi-Stakeholder Workshop.

Our objective was to convene interdisciplinary experts from government, academia, and industry to develop a Research Roadmap to identify research priorities about processed food intake and risk for obesity and cardiometabolic diseases (CMD) among United States populations. We convened attendees at various career stages with diverse viewpoints in the field. We held a "Food Processing Primer" to build foundational knowledge of how and why foods are processed, followed by presentations about how processed foods may affect energy intake, obesity, and CMD risk. Breakout groups discussed potential mechanistic and confounding explanations for associations between processed foods and obesity and CMD risk. Facilitators created research questions (RQs) based on key themes from discussions. Different breakout groups convened to discuss what is known and unknown for each RQ and to develop sub-RQs to address gaps. Workshop attendees focused on ultra-processed foods (UPFs; Nova Group 4) because the preponderance of evidence is based on this classification system. Yet, heterogeneity and subjectivity in UPF classification was a challenge for RQ development. The 6 RQs were: 1) What objective methods or measures could further categorize UPFs, considering food processing, formulation, and the interaction of the two? 2) How can exposure assessment of UPF intake be improved? 3) Does UPF intake influence risk for obesity or CMDs, independent of diet quality? 4) What, if any, attributes of UPFs influence ingestive behavior and contribute to excess energy intake? 5) What, if any, attributes of UPFs contribute to clinically meaningful metabolic responses? 6) What, if any, external environmental factors lead people to consume high amounts of UPFs? Uncertainty and complexity around UPF intake warrant further complementary and interdisciplinary causal, mechanistic, and methodological research related to obesity and CMD risk to understand the utility of applying classification by degree of processing to foods in the United States.

Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity.

OBJECTIVES: To examine the feasibility of promoting engagement with data-driven self-management of health among individuals from minoritized medically underserved communities by tailoring the design of self-management interventions to individuals' type of motivation and regulation in accordance with the Self-Determination Theory. METHODS: Fifty-three individuals with type 2 diabetes from an impoverished minority community were randomly assigned to four different versions of an mHealth app for data-driven self-management with the focus on nutrition, Platano; each version was tailored to a specific type of motivation and regulation within the SDT self-determination continuum. These versions included financial rewards (external regulation), feedback from expert registered dietitians (RDF, introjected regulation), self-assessment of attainment of one's nutritional goals (SA, identified regulation), and personalized meal-time nutrition decision support with post-meal blood glucose forecasts (FORC, integrated regulation). We used qualitative interviews to examine interaction between participants' experiences with the app and their motivation type (internal-external). RESULTS: As hypothesized, we found a clear interaction between the type of motivation and Platano features that users responded to and benefited from. For example, those with more internal motivation reported more positive experience with SA and FORC than those with more external motivation. However, we also found that Platano features that aimed to specifically address the needs of individuals with external regulation did not create the desired experience. We attribute this to a mismatch in emphasis on informational versus emotional support, particularly evident in RDF. In addition, we found that for participants recruited from an economically disadvantaged community, internal factors, such as motivation and regulation, interacted with external factors, most notably with limited health literacy and limited access to resources. CONCLUSIONS: The study suggests feasibility of using SDT to tailor design of mHealth interventions for promoting data-driven self-management to individuals' motivation and regulation. However, further research is needed to better align design solutions with different levels of self-determination continuum, to incorporate stronger emphasis on emotional support for individuals with external regulation, and to address unique needs and challenges of underserved communities, with particular attention to limited health literacy and access to resources.

Identifying and Estimating Ultraprocessed Food Intake in the US NHANES According to the Nova Classification System of Food Processing.

BACKGROUND: The degree of food processing may be an important dimension of diet in how it relates to health outcomes. A major challenge is standardizing food processing classification systems for commonly used datasets. OBJECTIVES: To standardize and increase transparency in its application, we describe the approach used to classify foods and beverages according to the Nova food processing classification in the 24-h dietary recalls from the 2001-2018 cycles of What We Eat in America (WWEIA), NHANES, and investigate variability and potential for Nova misclassification within WWEIA, NHANES 2017-2018 data via various sensitivity analyses. METHODS: First, we described how the Nova classification system was applied to the 2001-2018 WWEIA, NHANES data using the reference approach. Second, we calculated the percentage energy from Nova groups [1: unprocessed or minimally processed foods, 2: processed culinary ingredients, 3: processed foods, and 4: ultraprocessed foods (UPFs)] for the reference approach using day 1 dietary recall data from non-breastfed participants aged ≥1 y from the 2017-2018 WWEIA, NHANES. We then conducted 4 sensitivity analyses comparing potential alternative approaches (e.g., opting for more vs. less degree of processing for ambiguous items) to the reference approach, to assess how estimates differed. RESULTS: The energy contribution of UPFs using the reference approach was 58.2% ± 0.9% of the total energy; unprocessed or minimally processed foods contributed 27.6% ± 0.7%, processed culinary ingredients contributed 5.2% ± 0.1%, and processed foods contributed 9.0% ± 0.3%. In sensitivity analyses, the dietary energy contribution of UPFs ranged from 53.4% ± 0.8% to 60.1% ± 0.8% across alternative approaches. CONCLUSIONS: We present a reference approach for applying the Nova classification system to WWEIA, NHANES 2001-2018 data to promote standardization and comparability of future research. Alternative approaches are also described, with total energy from UPFs differing by ∼6% between approaches for 2017-2018 WWEIA, NHANES.

Ultra-processed Foods and Cardiometabolic Health Outcomes: from Evidence to Practice.

PURPOSE OF REVIEW: Poor diet quality is the leading risk factor related to the overall cardiometabolic disease burden in the USA and globally. We review the current evidence linking ultra-processed foods and cardiometabolic health risk and provide recommendations for action at the clinical and public health levels. RECENT FINDINGS: A growing body of evidence conducted in a variety of study populations supports an association between ultra-processed food intake and increased risk of metabolic syndrome, hypertension, type 2 diabetes, overweight and obesity trajectories, and cardiovascular disease. The strongest evidence is observed in relation to weight gain and obesity among adults, as this association is supported by high-quality epidemiological and experimental evidence. Accumulating epidemiologic evidence and putative biological mechanisms link ultra-processed foods to cardiometabolic health outcomes. The high intake of ultra-processed foods in all population groups and its associated risks make ultra-processed foods an ideal target for intensive health promotion messaging and interventions.

Acculturation and Associations with Ultra-processed Food Consumption among Asian Americans: NHANES, 2011-2018.

BACKGROUND: Ultra-processed food (UPF) consumption is linked to adverse health outcomes, including cardiovascular disease and all-cause mortality. Asian Americans (AAs) are the fastest growing ethnic group in the United States, yet their dietary patterns have seldom been described. OBJECTIVES: The aim was to characterize UPF consumption among AAs and determine whether acculturation is associated with increased UPF consumption. METHODS: The NHANES is an annual, cross-sectional survey representative of the US population. We examined 2011-2018 NHANES data, which included 2404 AAs ≥18 y old with valid 24-h dietary recall. Using day 1 dietary recall data, we characterized UPF consumption as the percentage of caloric intake from UPFs, using the NOVA classification system. Acculturation was characterized by nativity status, nativity status and years in the United States combined, home language, and an acculturation index. We assessed the association between acculturation and UPF consumption using linear regression analyses adjusted for age, sex, marital status, education, income, self-reported health, and self-reported diet quality. RESULTS: UPFs provided, on average, 39.3% (95% CI: 38.1%, 40.5%) of total energy intake among AAs. In adjusted regression analyses, UPF consumption was 14% (95% CI: 9.5%, 17.5%; P < 0.05) greater among those with the highest compared with the lowest acculturation index score, 12% (95% CI: 8.5%, 14.7%: P < 0.05) greater among those who speak English only compared with non-English only in the home, 12% (95% CI: 8.6%, 14.7%: P < 0.05) greater among US-born compared with foreign-born AAs, and 15% (95% CI: 10.7%, 18.3%: P < 0.05) greater among US-born compared with foreign-born AAs with <10 y in the United States. CONCLUSIONS: UPF consumption was common among AAs, and acculturation was strongly associated with greater proportional UPF intake. As the US-born AA population continues to grow, UPF consumption in this group is likely to increase. Further research on disaggregated AA subgroups is warranted to inform culturally tailored dietary interventions.

Perspective: Novel Approaches to Evaluate Dietary Quality: Combining Methods to Enhance Measurement for Dietary Surveillance and Interventions.

Refining existing dietary assessment methods to reduce measurement error and facilitate the routine evaluation of dietary quality is essential to inform health policy. Notable advancements in technology in the past decade have enhanced the precision and transformation of dietary assessment methods with applications toward both population health and precision nutrition. Within population health, innovative applications of big data including use of automatically collected food purchasing data, quantitative measurement of food environments, and novel, yet simplified dietary quality metrics provide important complementary data to traditional self-report methods. Precision nutrition is similarly advancing with greater use of validated biomarkers for assessing dietary patterns and understanding individual variability in metabolism. Concurrently enhancing our understanding of diet-disease relations at the population health and precision nutrition levels provides tremendous potential to generate evidence needed to advance public health nutrition policy. This commentary highlights the importance of these advances toward progressing the field of dietary assessment and discusses the application of food purchasing data, data analytics, alternative dietary quality metrics, and -omics technology in population and clinical medicine.

Ultra-processed food consumption among US adults from 2001 to 2018.

BACKGROUND: Accumulating evidence links ultra-processed foods to poor diet quality and chronic diseases. Understanding dietary trends is essential to inform priorities and policies to improve diet quality and prevent diet-related chronic diseases. Data are lacking, however, for trends in ultra-processed food intake. OBJECTIVES: We examined US secular trends in food consumption according to processing level from 2001 to 2018. METHODS: We analyzed dietary data collected by 24-h recalls from adult participants (aged >19 y; N  = 40,937) in 9 cross-sectional waves of the NHANES (2001-2002 to 2017-2018). We calculated participants' intake of minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods as the relative contribution to daily energy intake (%kcal) using the NOVA framework. Trends analyses were performed using linear regression, testing for linear trends by modeling the 9 surveys as an ordinal independent variable. Models were adjusted for age, sex, race/ethnicity, education level, and income. Consumption trends were reported for the full sample and stratified by sex, age groups, race/ethnicity, education level, and income level. RESULTS: Adjusting for changes in population characteristics, the consumption of ultra-processed foods increased among all US adults from 2001-2002 to 2017-2018 (from 53.5 to 57.0 %kcal; P-trend < 0.001). The trend was consistent among all sociodemographic subgroups, except Hispanics, in stratified analyses. In contrast, the consumption of minimally processed foods decreased significantly over the study period (from 32.7 to 27.4 %kcal; P-trend < 0.001) and across all sociodemographic strata. The consumption of processed culinary ingredients increased from 3.9 to 5.4 %kcal (P-trend < 0.001), whereas the intake of processed foods remained stable at ∼10 %kcal throughout the study period (P-trend = 0.052). CONCLUSIONS: The current findings highlight the high consumption of ultra-processed foods in all parts of the US population and demonstrate that intake has continuously increased in the majority of the population in the past 2 decades.

Neighborhood-level Asian American Populations, Social Determinants of Health, and Health Outcomes in 500 US Cities.

Introduction: The US Asian American (AA) population is projected to double by 2050, reaching ~43 million, and currently resides primarily in urban areas. Despite this, the geographic distribution of AA subgroup populations in US cities is not well-characterized, and social determinants of health (SDH) and health measures in places with significant AA/AA subgroup populations have not been described. Our research aimed to: 1) map the geographic distribution of AAs and AA subgroups at the city- and neighborhood- (census tract) level in 500 large US cities (population ≥66,000); 2) characterize SDH and health outcomes in places with significant AA or AA subgroup populations; and 3) compare SDH and health outcomes in places with significant AA or AA subgroup populations to SDH and health outcomes in places with significant non-Hispanic White (NHW) populations. Methods: Maps were generated using 2019 Census 5-year estimates. SDH and health outcome data were obtained from the City Health Dashboard, a free online data platform providing more than 35 measures of health and health drivers at the city and neighborhood level. T-tests compared SDH (unemployment, high-school completion, childhood poverty, income inequality, racial/ethnic segregation, racial/ethnic diversity, percent uninsured) and health outcomes (obesity, frequent mental distress, cardiovascular disease mortality, life expectancy) in cities/neighborhoods with significant AA/AA subgroup populations to SDH and health outcomes in cities/neighborhoods with significant NHW populations (significant was defined as top population proportion quintile). We analyzed AA subgroups including Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and Other AA. Results: The count and proportion of AA/AA subgroup populations varied substantially across and within cities. When comparing cities with significant AA/AA subgroup populations vs NHW populations, there were few meaningful differences in SDH and health outcomes. However, when comparing neighborhoods within cities, areas with significant AA/AA subgroup vs NHW populations had less favorable SDH and health outcomes. Conclusion: When comparing places with significant AA vs NHW populations, city-level data obscured substantial variation in neighborhood-level SDH and health outcome measures. Our findings emphasize the dual importance of granular spatial and AA subgroup data in assessing the influence of SDH in AA populations.

Ultra-processed Foods and Cardiovascular Diseases: Potential Mechanisms of Action.

Ultra-processed foods are industrially manufactured ready-to-eat or ready-to-heat formulations containing food additives and little or no whole foods, in contrast to processed foods, which are whole foods preserved by traditional techniques such as canning or pickling. Recent epidemiological studies suggest that higher consumption of ultra-processed food is associated with increased risk of cardiovascular disease (CVD). However, epidemiological evidence needs to be corroborated with criteria of biological plausibility. This review summarizes the current evidence on the putative biological mechanisms underlying the associations between ultra-processed foods and CVD. Research ranging from laboratory-based to prospective epidemiological studies and experimental evidence suggest that ultra-processed foods may affect cardiometabolic health through a myriad of mechanisms, beyond the traditionally recognized individual nutrients. Processing induces significant changes to the food matrix, for which ultra-processed foods may affect health outcomes differently than unrefined whole foods with similar nutritional composition. Notably, the highly degraded physical structure of ultra-processed foods may affect cardiometabolic health by influencing absorption kinetics, satiety, glycemic response, and the gut microbiota composition and function. Food additives and neo-formed contaminants produced during processing may also play a role in CVD risk. Key biological pathways include altered serum lipid concentrations, modified gut microbiota and host-microbiota interactions, obesity, inflammation, oxidative stress, dysglycemia, insulin resistance, and hypertension. Further research is warranted to clarify the proportional harm associated with the nutritional composition, food additives, physical structure, and other attributes of ultra-processed foods. Understanding how ultra-processing changes whole foods and through which pathways these foods affect health is a prerequisite for eliminating harmful processing techniques and ingredients.

Ultra-Processed Foods and Incident Cardiovascular Disease in the Framingham Offspring Study.

BACKGROUND: Ultra-processed foods provide 58% of total energy in the U.S. diet, yet their association with cardiovascular disease (CVD) remains understudied. OBJECTIVES: The authors investigated the associations between ultra-processed foods and CVD incidence and mortality in the prospective Framingham Offspring Cohort. METHODS: The analytical sample included 3,003 adults free from CVD with valid dietary data at baseline. Data on diet, measured by food frequency questionnaire, anthropometric measures, and sociodemographic and lifestyle factors were collected quadrennially from 1991 to 2008. Data regarding CVD incidence and mortality were available until 2014 and 2017, respectively. Ultra-processed foods were defined according to the NOVA framework. The authors used Cox proportional hazards models to determine the multivariable association between ultra-processed food intake (energy-adjusted servings per day) and incident hard CVD, hard coronary heart disease (CHD), overall CVD, and CVD mortality. Multivariable models were adjusted for age, sex, education, alcohol consumption, smoking, and physical activity. RESULTS: During follow-up (1991 to 2014/2017), the authors identified 251, 163, and 648 cases of incident hard CVD, hard CHD, and overall CVD, respectively. On average, participants consumed 7.5 servings per day of ultra-processed foods at baseline. Each additional daily serving of ultra-processed foods was associated with a 7% (95% confidence interval [CI]: 1.03 to 1.12), 9% (95% CI: 1.04 to 1.15), 5% (95% CI: 1.02 to 1.08), and 9% (95% CI: 1.02 to 1.16) increase in the risk of hard CVD, hard CHD, overall CVD, and CVD mortality, respectively. CONCLUSIONS: The current findings support that higher consumption of ultra-processed foods is associated with increased risk of CVD incidence and mortality. Although additional research in ethnically diverse populations is warranted, these findings suggest cardiovascular benefits of limiting ultra-processed foods.

Trends in food consumption by degree of processing and diet quality over 17 years: results from the Framingham Offspring Study.

Ultraprocessed foods provide the majority of energy content in the American diet, yet little is known regarding consumption trends over time. We determined trends in diet processing level and diet quality from 1991 to 2008 within the prospective Framingham Offspring Cohort. Dietary intakes were collected by FFQ quadrennially 1991-2008 (total of four examinations). The analytical sample included 2893 adults with valid dietary data for ≥3 examinations (baseline mean age = 54 years). Based on the NOVA framework, we classified foods as: unprocessed/minimally processed foods; processed culinary ingredients (salt/sugar/fats/oils); and processed foods and ultraprocessed foods. We evaluated diet quality using the Dietary Guidelines for Americans Adherence Index (DGAI) 2010. Trends in consumption of foods within each processing level (servings/d) and diet quality over the four examinations were evaluated using mixed effects models with subject-specific random intercepts. Analyses were stratified by sex, BMI (<25 kg/m2, 25-29·9 kg/m2, ≥30 kg/m2) and smoking status. Over 17 years of follow-up, ultraprocessed food consumption decreased from 7·5 to 6·0 servings/d and minimally processed food consumption decreased from 11·9 to 11·3 servings/d (Ptrend < 0·001). Changes in intakes of processed foods, culinary ingredients and culinary preparations were minimal. Trends were similar by sex, BMI and smoking status. DGAI-2010 score increased from 60·1 to 61·5, P < 0·001. The current study uniquely describes trends in diet processing level in an ageing US population, highlighting the longstanding presence of ultraprocessed foods in the American diet. Given the poor nutritional quality of ultraprocessed foods, public health efforts should be designed to limit their consumption.

Longitudinal dimensions of alcohol consumption and dietary intake in the Framingham Heart Study Offspring Cohort (1971-2008).

Existing studies addressing alcohol consumption have not captured the multidimensionality of drinking patterns, including drinking frequency, binge drinking, beverage preference and changes in these measures across the adult life course. We examined longitudinal trends in drinking patterns and their association with diet over four decades in ageing US adults from the Framingham Offspring Study (n 4956; baseline mean age 36·2 years). Alcohol intake (drinks/week, drinking frequency, beverage-specific consumption, drinks/occasion) was assessed quadrennially from examinations 1 to 8. Participants were classified as binge drinkers, moderate drinkers or heavy drinkers (4+ and 5+ drinks/occasion; ≤1 and ≤2 drinks/d and >7 and >14 drinks/week for women and men, respectively). Dietary data were collected by a FFQ from examinations 5 to 8 (1991-2008). We evaluated trends in drinking patterns using linear mixed effect models and compared dietary intake across drinking patterns using heterogeneous variance models. Alcohol consumption decreased from 1971 to 2008 (3·7 v. 2·2 oz/week; P < 0·05). The proportion of moderate (66 v. 59·3 %), heavy (18·4 v. 10·5 %) and binge drinkers (40·0 v. 12·3 %) declined (P < 0·05). While average wine consumption increased (1·4 v. 2·2 drinks/week), beer (3·4 v. 1·5 drinks/week) and cocktail intake (2·8 v. 1·2 drinks/week) decreased. Non-binge drinkers consumed less sugary drinks and more whole grains than binge drinkers, and the latter consumed more total fat across all examinations (P < 0·05). There was a significant difference in consumption trends of total grains by drinking level (P < 0·05). In conclusion, alcohol drinking patterns are unstable throughout adulthood. Higher intakes were generally associated with poorer diets. These analyses support the nuanced characterisation of alcohol consumption in epidemiological studies.

Sociodemographic Differences in the Dietary Quality of Food-at-Home Acquisitions and Purchases among Participants in the U.S. Nationally Representative Food Acquisition and Purchase Survey (FoodAPS).

Insufficient research has explored whether sociodemographic differences in self-reported, individual-level diet quality are similarly reflected by grocery purchase quality. This cross-sectional analysis of n = 3961 U.S. households from the nationally representative Food Acquisition and Purchase Survey (FoodAPS) compared Healthy Eating Index (HEI)-2015 scores from 1 week of food-at-home acquisitions across self-reported demographic factors (race/ethnicity, Supplemental Nutrition Assistance Program (SNAP) participation, food security, and household-level obesity status). Multivariable-adjusted, survey-weighted regression models compared household HEI-2015 scores across sociodemographic groups. Respondents were primarily White and female, with a mean age of 50.6 years, 14.0% were food insecure, and 12.7% were SNAP-participating. Mean HEI-2015 scores were 54.7; scores differed across all sociodemographic exposures (p < 0.05). Interactions (p < 0.1) were detected between SNAP participation and (1) food insecurity and (2) household-level obesity, and race/ethnicity and (1) household-level obesity. HEI-2015 scores were higher among food secure, non-SNAP households than among food insecure, SNAP-participating households (53.9 ± 0.5 vs. 50.3 ± 0.7, p = 0.007); non-SNAP households without obesity had significantly higher HEI-2015 scores than other households. Household-level obesity was associated with lower HEI-2015 scores in White (50.8 ± 0.5 vs. 52.5 ± 0.7, p = 0.046) and Black (48.8 ± 1.5 vs. 53.1 ± 1.4, p = 0.018) but not Hispanic households (54.4 ± 1.0 vs. 52.2 ± 1.2, p = 0.21). Sociodemographic disparities in household HEI-2015 scores were consistent with previous research on individual-level diet quality.

Food assistance programs and income are associated with the diet quality of grocery purchases for households consisting of women of reproductive age or young children.

Women's diet quality during reproductive years and children's diet quality during early life influence long term health. Few studies have evaluated the impact of food assistance programs and income on the diet quality of grocery purchases made by households consisting of women of reproductive age and young children. We used data from the Food Acquisition and Purchase Survey 2012-2013 (FoodAPS) to evaluate how household income, Special Supplemental Nutrition Assistance Program for Women, Infants and Children (WIC) participation, and Supplemental Nutrition Assistance Program (SNAP) participation are related to the diet quality of grocery purchases made by households that include women of reproductive age or young children (n = 2436). The diet quality of household grocery purchases was assessed with the Healthy Eating Index (HEI) 2015. HEI-2015 total score (0-100) and component scores were evaluated according to household income (eligible for WIC: income-to-poverty ratio ≤ 185%; ineligible for WIC: income-to-poverty ratio > 185%) and WIC, SNAP, and WIC + SNAP participation. Median HEI-2015 total score was lowest among SNAP households and highest among income ineligible for WIC and WIC households (47.2 and 54.1, respectively). Compared to income ineligible for WIC households, WIC + SNAP and SNAP households had lower HEI-2015 whole fruit (ß = -0.30, 95% CI: -0.59, -0.01 and ß = -0.41, 95% CI: -0.63, -0.20, respectively) and total vegetable scores (ß = -0.58, 95% CI: -0.83, -0.32 and ß = -0.27, 95% CI: -0.45, -0.08, respectively). The diet quality of grocery purchases in this population varies according to household income and food assistance participation.

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

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 (ß = -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.