Food Is Medicine: A Presidential Advisory From the American Heart Association.

Unhealthy diets are a major impediment to achieving a healthier population in the United States. Although there is a relatively clear sense of what constitutes a healthy diet, most of the US population does not eat healthy food at rates consistent with the recommended clinical guidelines. An abundance of barriers, including food and nutrition insecurity, how food is marketed and advertised, access to and affordability of healthy foods, and behavioral challenges such as a focus on immediate versus delayed gratification, stand in the way of healthier dietary patterns for many Americans. Food Is Medicine may be defined as the provision of healthy food resources to prevent, manage, or treat specific clinical conditions in coordination with the health care sector. Although the field has promise, relatively few studies have been conducted with designs that provide strong evidence of associations between Food Is Medicine interventions and health outcomes or health costs. Much work needs to be done to create a stronger body of evidence that convincingly demonstrates the effectiveness and cost-effectiveness of different types of Food Is Medicine interventions. An estimated 90% of the $4.3 trillion annual cost of health care in the United States is spent on medical care for chronic disease. For many of these diseases, diet is a major risk factor, so even modest improvements in diet could have a significant impact. This presidential advisory offers an overview of the state of the field of Food Is Medicine and a road map for a new research initiative that strategically approaches the outstanding questions in the field while prioritizing a human-centered design approach to achieve high rates of patient engagement and sustained behavior change. This will ideally happen in the context of broader efforts to use a health equity-centered approach to enhance the ways in which our food system and related policies support improvements in health.

Bitter- and Umami-Related Genes are Differentially Associated with Food Group Intakes: the Framingham Heart Study.

BACKGROUND: As suboptimal diet quality remains the leading modifiable contributor to chronic disease risk, it is important to better understand the individual-level drivers of food choices. Recently, a genetic component of food choices was proposed based on variants (SNPs) in genes related to taste perception (taste-related SNPs). OBJECTIVES: This study aimed to determine the cumulative contribution of taste-related SNPs for basic tastes (bitter, sweet, umami, salt, and sour), summarized as "polygenic taste scores," to food group intakes among adults. METHODS: Cross-sectional analyses were performed on 6230 Framingham Heart Study participants (mean age ± SD: 50 ± 14 y; 54% female). Polygenic taste scores were derived for tastes with ≥2 related SNPs identified in prior genome-wide association studies, and food group intakes (servings per week [sev/wk]) were tabulated from food frequency questionnaires. Associations were determined via linear mixed-effects models, using false discovery rates and bootstrap resampling to determine statistical significance. RESULTS: Thirty-three taste-related SNPs (9 bitter, 19 sweet, 2 umami, 2 sour, 1 salt) were identified and used to derive polygenic taste scores for bitter, sweet, umami, and sour. Per additional allele for higher bitter perception, whole grain intakes were lower by 0.17 (95% CI: -0.28, -0.06) sev/wk, and for higher umami perception, total and red/orange vegetable intakes were lower by 0.73 (95% CI: -1.12, -0.34) and 0.25 (95% CI: -0.40, -0.10) sev/wk, respectively. Subsequent analyses at the SNP level identified four novel SNP-diet associations-two bitter-related SNPs with whole grains (rs10960174 and rs6782149) and one umami-related SNP with total and red/orange vegetables (rs7691456)-which may have been driving the identified associations. CONCLUSIONS: Taste-related genes for bitter and umami were differentially associated with food choices that may impact diet quality. Hence, a benefit could be derived from leveraging knowledge of taste-related genes when developing personalized risk reduction dietary guidance.

Reliability and Validity of Digital Images to Assess Child Dietary Intake in a Quick-Service Restaurant Setting.

BACKGROUND: Development of methods to accurately measure dietary intake in free-living situations-restaurants or otherwise-is critically needed to understand overall dietary patterns. OBJECTIVE: This study aimed to develop and test reliability and validity of digital images (DI) for measuring children's dietary intake in quick-service restaurants (QSRs), validating against weighed plate waste (PW) and bomb calorimetry (BC). DESIGN: In 2016, cross-sectional data were collected at two time points within a randomized controlled trial assessing children's leftovers in QSRs from parents of 4- to 12-year-old children. PARTICIPANTS/SETTING: Parents (n = 640; mean age = 35.9 y; 70.8% female) consented and agreed to provide their child's PW for digital imaging, across 11 QSRs in Massachusetts in areas with low socioeconomic status and ethnically diverse populations. OUTCOME MEASURES: Outcome measures were interrater reliability for DIs, correspondence between methods for energy consumed and left over, and correspondence between methods across varying quantities of PW. ANALYSES PERFORMED: Intraclass correlations, percent agreement, Spearman correlations, Wilcoxon signed rank tests, and Bland-Altman plots were used. RESULTS: Interrater reliability ratings for DIs had substantial intraclass correlations (ICC = 0.94) but not acceptable exact percent agreement (80.2%); DI and PW energy consumed were significantly correlated (r = 0.96, P < 0.001); DI slightly underestimated energy consumed compared with PW (Mdiff = -1.61 kcals, P < 0.001). Bland-Altman plots showed high DI-PW correspondence across various energy amounts and revealed few outliers. Energy left over by BC was highly correlated with DI (r = 0.87, P < 0.001) and PW (r = 0.90, P < 0.001); and mean differences were not significantly different from DI (Mdiff = 9.77 kcal, P = 0.06) or PW (Mdiff = -2.84 kcal, P = 0.20). CONCLUSIONS: Correspondence was high between PW and DI assessments of energy consumed, and high with BC energy left over. Results demonstrate reliability and practical validity of digital images for assessing child meal consumption in QSR settings.

Data-Driven Clustering Approach to Derive Taste Perception Profiles from Sweet, Salt, Sour, Bitter, and Umami Perception Scores: An Illustration among Older Adults with Metabolic Syndrome.

BACKGROUND: Current approaches to studying relations between taste perception and diet quality typically consider each taste-sweet, salt, sour, bitter, umami-separately or aggregately, as total taste scores. Consistent with studying dietary patterns rather than single foods or total energy, an additional approach may be to study all 5 tastes collectively as "taste perception profiles." OBJECTIVE: We developed a data-driven clustering approach to derive taste perception profiles from taste perception scores and examined whether profiles outperformed total taste scores for capturing individual variability in taste perception. METHODS: The cohort included 367 community-dwelling adults [55-75 y; 55% female; BMI (kg/m2): 32.2 ± 3.6] with metabolic syndrome from PREDIMED-Plus, Valencia. Cluster analysis identified subgroups of individuals with similar patterns in taste perception (taste perception profiles); quantitative criteria were used to select the cluster algorithm, determine the optimal number of clusters, and assess the profiles' validity and stability. Goodness-of-fit parameters from adjusted linear regression evaluated the individual variability captured by each approach. RESULTS: A k-means algorithm with 6 clusters best fit the data and identified the following taste perception profiles: Low All, High Bitter, High Umami, Low Bitter & Umami, High All But Bitter and High All But Umami. All profiles were valid and stable. Compared with total taste scores, taste perception profiles explained more variability in bitter and umami perception (adjusted R2: 0.19 vs. 0.63, respectively; 0.40 vs. 0.65, respectively) and were comparable for sweet, salt, and sour. In addition, taste perception profiles captured differential perceptions of each taste within individuals, whereas these patterns were lost with total taste scores. CONCLUSIONS: Among older adults with metabolic syndrome, taste perception profiles derived via data-driven clustering may provide a valuable approach to capture individual variability in perception of all 5 tastes and their collective influence on diet quality. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.

Associations between Taste Perception Profiles and Empirically Derived Dietary Patterns: An Exploratory Analysis among Older Adults with Metabolic Syndrome.

Taste perception is a primary driver of food choices; however, little is known about how perception of all five tastes (sweet, salt, sour, bitter, umami) collectively inform dietary patterns. Our aim was to examine the associations between a multivariable measure of taste perception-taste perception profiles-and empirically derived dietary patterns. The cohort included 367 community-dwelling adults (55-75 years; 55% female; BMI = 32.2 ± 3.6 kg/m2) with metabolic syndrome from PREDIMED-Plus, Valencia. Six taste perception profiles were previously derived via data-driven clustering (Low All, High Bitter, High Umami, Low Bitter and Umami, High All But Bitter, High All But Umami); three dietary patterns were derived via principal component analysis (% variance explained = 20.2). Cross-sectional associations between profiles and tertials of dietary pattern adherence were examined by multinomial logistic regression. Overall, there were several significant differences in dietary pattern adherence between profiles: the vegetables, fruits, and whole grains pattern was significantly more common for the High All But Umami profile (OR range for high vs. low adherence relative to other profiles (1.45-1.99; 95% CI minimum lower, maximum upper bounds: 1.05, 2.74), the non-extra virgin olive oils, sweets, and refined grains pattern tended to be less common for Low All or High Bitter profiles (OR range: 0.54-0.82), while the alcohol, salty foods, and animal fats pattern tended to be less common for Low Bitter and Umami and more common for High All But Bitter profiles (OR range: 0.55-0.75 and 1.11-1.81, respectively). In conclusion, among older adults with metabolic syndrome, taste perception profiles were differentially associated with dietary patterns, suggesting the benefit of integrating taste perception into personalized nutrition guidance.

Exploring changes in the human gut microbiota and microbial-derived metabolites in response to diets enriched in simple, refined, or unrefined carbohydrate-containing foods: a post hoc analysis of a randomized clinical trial.

BACKGROUND: Dietary carbohydrate type may influence cardiometabolic risk through alterations in the gut microbiome and microbial-derived metabolites, but evidence is limited. OBJECTIVES: We explored the relative effects of an isocaloric exchange of dietary simple, refined, and unrefined carbohydrate on gut microbiota composition/function, and selected microbial metabolite concentrations. METHODS: Participants [n = 11; age: 65 ± 8 y; BMI (in kg/m2): 29.8 ± 3.2] were provided with each of 3 diets for 4.5 wk with 2-wk washout, according to a randomized, crossover design. Diets [60% of energy (%E) carbohydrate, 15%E protein, and 25%E fat] differed in type of carbohydrate. Fecal microbial composition, metatranscriptomics, and microbial-derived SCFA and secondary bile acid (SBA) concentrations were assessed at the end of each phase and associated with cardiometabolic risk factors (CMRFs). RESULTS: Roseburia abundance was higher (11% compared with 5%) and fecal SBA concentrations were lower (lithocolic acid -50% and deoxycholic acid -64%) after consumption of the unrefined carbohydrate diet relative to the simple carbohydrate diet [false discovery rate (FDR): all P < 0.05), whereas Anaerostipes abundance was higher (0.35% compared with 0.12%; FDR: P = 0.04) after the simple carbohydrate diet relative to the refined carbohydrate diet. Metatranscriptomics indicated upregulation of 2 cellular stress genes (FDR: P < 0.1) after the unrefined carbohydrate diet compared with the simple carbohydrate or refined carbohydrate diets. The microbial expression of 3 cellular/oxidative stress and immune response genes was higher (FDR: P < 0.1) after the simple carbohydrate diet relative to the refined carbohydrate diet. No significant diet effect was observed in fecal SCFA concentrations. Independent of diet, we observed 16 associations (all FDR: P < 0.1) of taxon abundance (15 phylum and 1 genera) with serum inflammatory markers and also with fecal SCFA and SBA concentrations. CONCLUSIONS: Consuming an unrefined carbohydrate-rich diet had a modest effect on the gut microbiome and SBAs, resulting in favorable associations with selected CMRFs. Simple carbohydrate- and refined carbohydrate-rich diets have distinctive effects on the gut microbiome, suggesting differential mechanisms mediate their effects on cardiometabolic health. This trial was registered at clinicaltrials.gov as NCT01610661.

Weighed Plate Waste Can Accurately Measure Children's Energy Consumption from Food in Quick-Service Restaurants.

BACKGROUND: Quick-service restaurants (QSRs) serve one-third of US children on any given day, yet no methods can directly measure energy (kcal) consumed in QSRs. Weighed plate waste is one feasible option, but the accuracy is unknown. OBJECTIVE: The objective of this study was to determine the accuracy of weighed plate waste for measuring children's energy consumption in QSRs. METHODS: Children's plate waste (entrées and sides) was collected for a larger study assessing a community-wide health messaging campaign to inform parents' orders for children in QSRs; a subsample (n = 194) was used for validation. Gross energy left over estimated by weighed plate waste combined with restaurant-stated nutrition information was compared to gross energy determined by bomb calorimetry, the gold-standard energy assessment technique. Analyses were conducted at the meal level (all food items, combined) and stratified by the number of items per meal (1, 2, or 3). Pearson correlations and paired t tests analyzed agreement; Bland-Altman statistics examined differences between energy estimations for the total and stratified subsample. RESULTS: Overall, significant agreement was observed between weighed plate waste and bomb calorimetry (r = 0.99, P < 0.001). On average, weighed plate waste underestimated energy content by <2 kcal compared with bomb calorimetry (mean percent difference ± SD of 0.3% ± 10.7%); 94% of estimations fell within the limits of agreement (-23.5 to 26.8 kcal), and 63% and 24% of estimations differed by <10 or <20 net kcal, respectively. Although stratification by item number showed slight variation, mean differences for all strata were <5 kcal (t test P > 0.80), suggesting the accuracy of weighed plate waste for measuring meals of various sizes. CONCLUSIONS: Weighed plate waste is an accurate and valid field technique for measuring children's energy consumption from food in QSRs. Future improvements to capturing beverages, self-serve condiments, and sharing behaviors may improve the overall feasibility and accuracy.