Abstract
The Food Compass is a nutrient profiling system (NPS) to characterize the healthfulness of diverse foods, beverages and meals. In a nationally representative cohort of 47,999 U.S. adults, we validated a person’s individual Food Compass Score (i.FCS), ranging from 1 (least healthful) to 100 (most healthful) based on cumulative scores of items consumed, against: (a) the Healthy Eating Index (HEI) 2015; (b) clinical risk factors and health conditions; and (c) all-cause mortality. Nationally, the mean (SD) of i.FCS was 35.5 (10.9). i.FCS correlated highly with HEI-2015 (R = 0.81). After multivariable- adjustment, each one SD (10.9 point) higher i.FCS associated with more favorable BMI (−0.60 kg/m² [−0.70,–0.51]), systolic blood pressure (−0.69 mmHg [−0.91,-0.48]), diastolic blood pressure (−0.49 mmHg [-0.66,-0.32]), LDL-C (−2.01 mg/dl [-2.63,-1.40]), HDL-C (1.65 mg/d [1.44,1.85]), HbAlc (-0.02% [−0.03,−0.01]), and fasting plasma glucose (-0.44 mg/dL [−0.74,−0.15]); lower prevalence of metabolic syndrome (OR = 0.85 [0.82,0.88]), CVD (0.92 [0.88,0.96]), cancer (0.95 [0.91,0.99]), and lung disease (0.92 [0.88,0.96]); and higher prevalence of optimal cardiometabolic health (1.24 [1.16,1.32]). i.FCS also associated with lower all-cause mortality (HR = 0.93 [0.89,0.96]). Findings were similar by age, sex, race/ethnicity, education, income, and BMI. These findings support validity of Food Compass as a tool to guide public health and private sector strategies to identify and encourage healthier eating.
Generated Summary
This research validates the Food Compass, a nutrient profiling system (NPS), by examining its association with a healthy diet, cardiometabolic health, and mortality among U.S. adults. The study utilizes data from the National Health and Nutrition Examination Survey (NHANES) cycles from 1999-2018. The primary goal was to assess the validity of the Food Compass by comparing it with the Healthy Eating Index (HEI) 2015, clinical risk factors, health conditions, and all-cause mortality. The research employed survey-weighted linear and logistic regression models to analyze the associations between the individual Food Compass Score (i.FCS) and the various health outcomes. The study also explored how individual domains of the Food Compass correlated with these outcomes. The study included a large, nationally representative sample and was designed to provide insights into the effectiveness of the Food Compass in evaluating the healthfulness of individual food and beverage products and its potential for informing public health and private sector strategies to encourage healthier eating. The study’s methodology included assessing dietary intake using 24-hour dietary recalls, calculating the HEI 2015, and linking survey data to mortality data from the National Death Index.
Key Findings & Statistics
- The study analyzed a nationally representative sample of 47,999 U.S. adults aged 20-85 years.
- The mean (SD) age of the participants was 47.2 (17.1) years, with 52.2% being female.
- The mean (SD) BMI was 28.8 kg/m² (6.8).
- The mean i.FCS was 35.5 (10.9).
- The mean (SD) HbA1c was 5.6% (0.9).
- The mean fasting plasma glucose was 105.8 mg/dL (30.8).
- The mean (SD) systolic blood pressure was 122.8 mmHg (18.0) and diastolic was 70.9 mmHg (12.5).
- About 42.0% of U.S. adults had metabolic syndrome; 12.9% diabetes; 7.7% clinical CVD; 18.9% lung disease; and 9.8% cancer.
- Only 7.4% had optimal cardiometabolic health.
- The i.FCS correlated highly with HEI-2015 (R = 0.81).
- Each 1 SD (10.9 point) higher i.FCS was associated with a more favorable BMI (-0.60 kg/m² [-0.70,–0.51]), systolic blood pressure (-0.69 mmHg [-0.91,-0.48]), diastolic blood pressure (-0.49 mmHg [-0.66,-0.32]), LDL-C (-2.01 mg/dl [-2.63,-1.40]), HDL-C (1.65 mg/d [1.44,1.85]), HbAlc (-0.02% [−0.03,−0.01]), and fasting plasma glucose (-0.44 mg/dL [-0.74,−0.15]); lower prevalence of metabolic syndrome (OR = 0.85 [0.82,0.88]), CVD (0.92 [0.88,0.96]), cancer (0.95 [0.91,0.99]), and lung disease (0.92 [0.88,0.96]); and higher prevalence of optimal cardiometabolic health (1.24 [1.16,1.32]).
- Each SD increase in i.FCS (~10.9 points) was associated with 15% lower prevalence of metabolic syndrome (OR = 0.85 [95%CI: 0.82, 0.88]), 8% lower prevalence of CVD (0.92 [0.88, 0.96]), 5% lower prevalence of cancer (0.95 [0.91, 0.99]),and 8% lower prevalence of lung disease (0.92 [0.88, 0.96]).
- A nonsignificant trend was seen toward lower prevalence of diabetes (0.96 [0.90, 1.01]).
- Each 1SD (10.9) increase in i.FCS was prospectively associated with a 7% lower risk of all-cause mortality (HR = 0.93 [0.89, 0.96]).
- The mean i.FCS (~36) was not much higher than the identified threshold score (FCS ≤ 30) for individual food and beverage products to be minimized in the diet, and fewer than 1% of U.S. adults had an i.FCS above 70.
- For example, each SD increase in i.FCS (~10.9 points out of 100) was associated with lower BMI (-0.60 kg/m² [-0.70, -0.51]), systolic blood pressure (-0.69 mmHg [-0.91, -0.48]), LDL-C (-2.01 mg/dl [-2.63, -1.40]), HbAlc (-0.02% [-0.03, -0.01]); and fasting plasma glucose (-0.44 mg/ dL [-0.74, -0.15]); and higher HDL-C (1.65 mg/d: [1.44, 1.85]).
Other Important Findings
- Individuals with higher i.FCS (≥70) consumed a greater number of and percentage total energy contribution from products with FCS ≥ 70 (median [IQR] count: 13 [8, 20]; percentage energy: 65.6% [57.9, 71.4%]) compared to products with FCS 31-69 (6 [3, 9]; 14.2% [7.3, 23.2]) or FCS ≤ 30 (2 [1, 4]; 2.3% [0.2, 6.1]).
- The 9 domains of the FCS were not as highly correlated, ranging from 0.23 for i.Specific Lipids to 0.76 for i.Nutrient Ratios.
- For diabetes, i.Nutrient Ratios had the strongest inverse association (0.94 [0.89, 0.99]); for CVD, i.Minerals, i.Food Ingredients, i.Additives, i.Processing, i.Fiber and Protein, and i.Specific Lipids were each inversely associated.
- i.Nutrient Ratios, i.Food Ingredients, i.Additives, i.Processing, i.Fiber and Protein, and i.Specific Lipids were each inversely associated with all-cause mortality.
- The relationship between i.FCS and all-cause mortality appeared potentially nonlinear, with a stronger protective association until an i.FCS of ~40 (approximately the 75th percentile score), with a less strong inverse relationship thereafter, but this potential nonlinearity was not statistically significant (p-nonlinearity = 0.12) (Fig. S3).
- In exploratory analyses, we investigated whether the relationship between i.FCS and total mortality varied in population subgroups according to age, sex, race/ethnicity, education, income, BMI, and plausibility of energy reporting. Findings were similar across subgroups, with no significant differences in the observed protective associations between i.FCS and mortality (p-interaction >0.05 each) (Table S10).
Limitations Noted in the Document
- Cross-sectional analyses preclude assessment of temporality.
- Use of energy-weighting to calculate i.FCS captures overall dietary composition but provides lower weighting to certain foods with lower calories per servings, such as fruits and vegetables.
- Portion- or gram-based weighting would create bias by failing to account for water weight.
- In the future, a more “personalized” FCS could be crafted based on specific characteristics of the individual, such as age, sex, disease status, and more.
- Some nutrients such as Vitamin D, choline, and flavonoids were only available in certain NHANES cycles, requiring imputation in other cycles.
- Misreporting and omission of food items by dietary recall participants was also possible.
- The associations of i.FCS with diet quality, clinical risk factors, and mortality are observational, and residual confounding cannot be excluded.
Conclusion
The Food Compass, a nutrient profiling system, demonstrated a significant correlation between a person’s individual dietary habits, assessed by the Food Compass Score (i.FCS), and a healthy dietary pattern, as measured by the Healthy Eating Index (HEI) 2015. The i.FCS was favorably associated with several clinical risk factors, prevalent disease conditions, and lower all-cause mortality. The findings underscore the potential of the Food Compass as a valuable tool for evaluating the healthfulness of individual food and beverage products. This study supports the validity of the Food Compass as a potential tool to guide public and private strategies to identify and encourage healthier foods and beverages. The consistent scoring of individual foods and beverages, and a person’s overall diet, demonstrated a relationship between the i.FCS and several health outcomes. The results show that, on average, the leading contributors to the American diet are mostly foods and beverages to be minimized or avoided. This research highlights the suboptimal state of U.S. nutrition and the urgent need for interventions across various sectors to improve diet quality. The Food Compass’s ability to consistently score foods, beverages, and mixed meals, along with its comprehensive approach to assessing food healthfulness, positions it as a potential tool for guiding consumers, informing industry practices, and supporting policy decisions. The development of this tool provides a framework for improving the healthfulness of food and beverage products.