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. Author manuscript; available in PMC: 2022 Oct 1.
Published in final edited form as: Am J Prev Med. 2021 Jul 8;61(4):563–575. doi: 10.1016/j.amepre.2021.04.033

Self-Rated Diet Quality and Cardiometabolic Health Among U.S. Adults, 2011–2018

Valerie K Sullivan 1, Emily A Johnston 2, Melanie J Firestone 3, Stella S Yi 4, Jeannette M Beasley 5
PMCID: PMC8523030  NIHMSID: NIHMS1722501  PMID: 34246527

Abstract

Introduction:

Self-rated health has been extensively studied, but the utility of a similarly structured question to rate diet quality is not well characterized. This study aims to assess the relative validity of self-rated diet quality, compared with a validated diet quality measure (Healthy Eating Index [HEI]-2015), and examine associations with cardiometabolic risk factors.

Methods:

Analyses were conducted in 2020–2021 using cross-sectional data from the National Health and Nutrition Examination Survey, 2011–2018. Non-pregnant adults who responded to the question How healthy is your overall diet? and provided 2 dietary recalls were eligible (n=16,913). Associations between self-rated diet quality (modeled as a 5-point continuous variable, poor=1 to excellent=5) and HEI-2015 scores and cardiometabolic risk factors were assessed by linear regression, accounting for the complex survey design and adjusted for demographic and lifestyle characteristics.

Results:

Self-rated diet quality was positively associated with total HEI-2015 scores (p<0.001) and all components except Dairy (p=0.94) and Sodium (p=0.66). Higher self-rated diet quality was associated with lower BMI, waist circumference, glucose, insulin, triglycerides, and HbA1c and higher high-density lipoprotein cholesterol (all p<0.01). Positive associations with total diet quality persisted across all racial/ethnic groups, though associations with individual dietary components varied. Higher self-ratings were most consistently associated with better scored diet quality among individuals with BMI <30 kg/m2.

Conclusions:

Self-rated diet quality was associated with HEI-2015 scores and cardiometabolic disease risk factors. This single-item assessment may be useful in time-limited settings to quickly and easily identify patients in need of dietary counseling to improve cardiometabolic health.

INTRODUCTION

Suboptimal diet is a leading risk factor for noncommunicable disease morbidity and mortality.1,2 Consuming a high-quality diet that aligns with dietary guidelines decreases cardiovascular disease incidence and mortality3-5 and reduces the risk of type 2 diabetes,6-8 certain cancers,7 and nonalcoholic fatty liver disease.9-11 Adherence to dietary recommendations in the U.S. is generally poor, with average intakes of sodium, saturated fat, and added sugar exceeding recommended limits and intakes of fruits, vegetables, nuts, legumes and whole grains below recommended targets.2,12 Minor improvements in overall diet quality have been reported since 199913 but the average American diet is still far from ideal.14

Identification of individuals with suboptimal diets could help healthcare providers intervene on this modifiable risk factor by offering basic dietary instruction or referral to a Registered Dietitian–Nutritionist for further counseling. Given the complexity of diet assessment, a quick and simple estimate of diet quality is desirable to identify patients in need of more intensive dietary instruction.15 Single-item self-ratings of health are widely used as inexpensive tools that are strong and consistent independent predictors of health outcomes,16,17 but few studies have assessed the validity of single-item measures of self-rated diet quality. Establishing how well a simple self-rating of diet quality aligns with diet quality scored based on actual dietary intake and health in a nationally representative sample can inform the utility of the measure in clinical practice. Therefore, the objectives of this study are to assess the relative validity of a single-item self-rating of diet quality compared with a validated assessment of diet quality, and to examine the relationship between self-rated diet quality and cardiometabolic health in the U.S. adult population.

METHODS

Study Population

Data were collected as part of the National Health and Nutrition Examination Survey (NHANES), which uses a complex, multistage, probability design to survey the health and nutritional status of non-institutionalized U.S. civilians in 2-year cycles. Sampling methodology has been described previously.18 The NHANES protocol has been approved by the Research Ethics Review Board of the National Center for Health Statistics and all participants provided written informed consent.19

Data from 4 cycles of NHANES (2011–2012, 2013–2014, 2015–2016, 2017–2018) were combined (N=39,156). Respondents were excluded from analyses if they were aged <20 years (n=16,539), pregnant (n=247), or did not provide a response for self-rated diet quality (n=10). Analyses were restricted to individuals with 2 dietary recalls (24-hour) determined to be complete and reliable per NHANES documentation.20 Participants who did not complete any dietary recalls (n=2,982) or only completed 1 recall (n=2,445) were excluded. Finally, participants who only reported consuming water on either of the dietary recalls were excluded (n=20), resulting in an analytic sample of 16,913 adults.

Measures

Participants reported demographic information and completed health questionnaires at a household interview. Self-rated diet quality was assessed through a single question: In general, how healthy is your overall diet? The 5 response levels were: excellent, very good, good, fair, or poor. Demographic characteristics included age, sex, race/ethnicity, educational attainment, and poverty–income ratio. Participants self-identified their race/ethnicity as non-Hispanic White (n=6,629), non-Hispanic Black (n=3,913), non-Hispanic Asian (n=1,868), Hispanic (Mexican American and other Hispanic origin; n=3,880), and other (including multiracial; n=623). Educational attainment was categorized as less than a high school education, high school graduate or equivalent, some college or technical school, or a college degree or above. Poverty–income ratio was calculated by dividing family or individual (for single individual households, or households composed of unrelated individuals) income by year-specific poverty guidelines defined by HHS. Recreational physical activity was quantified as the sum of self-reported weekly minutes of recreational moderate activity and doubled minutes of vigorous activity.21,22 Use of medications to manage blood pressure, cholesterol, and glucose was self-reported.

Dietary intake was assessed by 2 recalls (24-hour). The first recall was administered in person at the mobile examination center by trained interviewers using the U.S. Department of Agriculture automated multiple-pass method.23 A second 24-hour recall was obtained 3–10 days later by telephone using the same method. Diet quality was quantified using the Healthy Eating Index (HEI)-2015, which is a tool used to evaluate adherence to the 2015–2020 Dietary Guidelines for Americans.24,25 It is composed of 13 components that are individually scored and summed. Nine “adequacy” components (total fruits, whole fruits, total vegetables, greens and beans, whole grains, dairy, total protein foods, seafood and plant proteins, and fatty acids) award points for intakes that meet or exceed recommended minimums while the remaining 4 “moderation” components (refined grains, sodium, added sugars, and saturated fats) award points for intakes equal to or less than recommended limits.26 Components are generally weighted equally (10 points each), though some aspects of the diet represented by 2 components are scored out of 5 points each (total fruits and whole fruits, total vegetables and greens and beans, total protein foods and seafood and plant proteins).25 Total scores range from 0 to a maximum of 100, which indicates complete alignment with dietary guidelines. The content validity, construct validity, and reliability of this tool have been established.27 Total and component HEI-2015 scores were calculated for each individual based on averaged intakes from both dietary recalls using the simple HEI scoring method.28

Physical examination and laboratory data were collected at the mobile examination center. Cardiometabolic disease risk factors of interest included BMI; waist circumference; seated blood pressure (systolic, diastolic); fasting plasma glucose; fasting serum insulin; HbA1c; and serum lipids including total cholesterol, high-density lipoprotein cholesterol, fasting low-density lipoprotein cholesterol, and fasting triglycerides. NHANES examination protocols and laboratory methods are detailed elsewhere.29-31 Fasting laboratory values were only assessed in a subset of participants who were examined at a morning session. Other measurements are missing for various reasons detailed in the documentation for each data set.29,30

Statistical Analysis

Analyses were conducted in 2020–2021 using SAS, version 9.4. Survey procedures incorporating sampling weights, strata, and primary sampling units were used to account for the complex survey design. Day 2 dietary weights were used in accordance with the least common denominator approach to selecting sample weights, as advised by NHANES analytic guidelines.18 Fasting subsample weights were substituted in analyses of fasting laboratory data.

Self-rated diet quality was treated as a nominal variable in multivariable linear regression models adjusting for age, sex, race/ethnicity, poverty–income ratio, education, smoking status, and recreational physical activity to estimate mean HEI-2015 scores by category of self-rated diet quality. Cardiometabolic risk factors were estimated similarly, with additional adjustment for BMI (excluding BMI and waist circumference). Total calorie intake did not meaningfully alter estimates and was omitted from the final models (Appendix Tables 1 and 2). Self-rated diet quality was treated as a continuous variable (poor=1 to excellent=5) to test covariate-adjusted linear associations with HEI-2015 scores and cardiometabolic health indicators. The consistency of associations across population subgroups was explored in analyses stratified by self-identified race/ethnicity and by BMI class, defined by NIH.32 Estimates are not presented for underweight (<18.5 kg/m2) adults owing to the small sample size (n=253). Two-sided p-values <0.01 were considered statistically significant.

RESULTS

Most U.S. adults (41.2%) rated their diet quality as good (Table 1). Nearly one third (31.6%) reported having an excellent or very good diet, and the remaining 27.2% rated their diets as fair or poor. Adults with higher self-rated diet quality tended to be older and non-Hispanic White, with higher incomes and more education. Adults with higher self-rated diet quality also smoked less and reported greater recreational physical activity, compared with those with lower self-rated diet quality.

Table 1.

Demographic Characteristics and Health Behaviors by Self-Rated Diet Quality for Adults in NHANES 2011–2018a

Characteristics Poor Fair Good Very
good		 Excellent
n (% of population) 1,047 (5.5) 3,995 (21.7) 6,955 (41.2) 3,517 (23.4) 1,399 (8.2)
Sex, % female 52.8 48.8 52.5 53.3 46.5
Age, %
 20–39 years 43.7 41.1 37.0 29.1 26.3
 40–59 years 37.8 39.7 36.1 36.6 31.3
 ≥60 years 18.4 19.2 27.0 34.3 42.4
Race/Ethnicity, %
 Asian 2.1 3.4 5.3 8.0 7.5
 Black 17.7 14.6 10.7 7.7 11.1
 Hispanic 21.1 21.6 15.1 8.1 9.1
 White 53.9 57.2 65.3 73.2 70.0
 Other 5.2 3.3 3.6 3.0 2.3
Poverty income ratio,b %
 <130% 34.1 29.6 21.8 13.2 19.9
 130%–185% 16.7 13.2 11.0 8.4 8.3
 >185% 49.3 57.3 67.2 78.4 71.8
Education, %
 Less than high school 21.9 18.7 12.2 7.0 12.6
 High school 32.9 26.7 23.2 16.6 17.8
 Some college 35.2 34.9 33.4 29.1 27.6
 4-year degree or higher 10.0 19.6 31.2 47.3 41.9
Current smoker, % 33.6 25.3 17.0 11.4 12.7
Physical activity, minutes/weekc 101 171 215 316 363
BMI, %
 Underweight (<18.5 kg/m2) 1.3 1.6 1.0 1.7 1.7
 Normal (18.5–24.9 kg/m2) 18.6 17.8 26.4 35.3 38.9
 Overweight (25–29.9 kg/m2) 20.3 27.4 33.1 36.1 36.9
 Obese (30–34.9 kg/m2) 23.4 24.8 23.6 16.2 15.8
 Obese (>35–39.9 kg/m2) 14.7 15.1 9.7 7.0 4.1
 Obese (≥40 kg/m2) 21.8 13.4 6.3 3.8 2.6
Use blood pressure-lowering medications, % 24.1 24.9 24.2 23.3 23.6
Use glucose-lowering medications, % 10.4 11.6 9.8 7.2 5.9
Use lipid-lowering medications, % 16.1 17.9 19.4 20.3 19.6
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a

Non-pregnant adults ≥20 years of age who completed 2 dietary recalls were included in analyses. Percentages are survey weighted.

b

Poverty income ratio is calculated by dividing family or individual (for single individual households, or households comprised of unrelated individuals) income by the poverty guideline.

c

Weekly physical activity sums minutes of moderate-intensity recreational activity and doubled minutes of vigorous-intensity recreational activity.

NHANES, National Health and Nutrition Examination Survey.

Mean total HEI-2015 scores increased with increasing self-rated diet quality (β=2.8, 99% CI=2.4, 3.2) (Table 2). Relative to individuals that rated their diets as poor, those rating their diets as excellent had 8.9 points greater total HEI-2015 scores. Component scores also increased with self-rated diet quality (p<0.01), except for Dairy (p=0.94) and Sodium (p=0.66). Expressed as percentages of total possible points per component, Whole Fruits differed most comparing excellent versus poor categories of self-rated diet quality (+20%), followed by Total Fruits (+18%) and Total Vegetables (+18%) (Appendix Figure 1).

Table 2.

HEI-2015 Scores by Self-Rated Diet Quality, Stratified by Race/Ethnicity, for Adults in NHANES 2011–2018a

HEI component Poor Fair Good Very
good		 Excellent β SE p-
value
Total score (100)b
 Overall 49.4 50.1 52.6 56.8 58.3 2.8 0.16 <0.001
 Asian 45.3 52.2 56.1 58.8 61.2 3.2 0.52 <0.001
 Black 48.6 49.4 51.1 54.3 53.9 1.7 0.24 <0.001
 Hispanic 50.6 52.1 52.9 58.4 55.4 1.8 0.45 <0.001
 White 47.7 47.8 51.0 55.4 57.6 3.2 0.21 <0.001
 Otherc 49.7 48.0 51.2 51.6 57.5 1.8 0.64 0.007
Total Fruits (5)
 Overall 1.9 1.9 2.2 2.6 2.8 0.3 0.02 <0.001
 Asian 1.6 1.9 2.4 2.8 3.0 0.4 0.07 <0.001
 Black 1.8 2.0 2.2 2.4 2.5 0.2 0.04 <0.001
 Hispanic 2.2 2.3 2.5 2.7 2.1 0.1 0.06 0.16
 White 1.6 1.6 1.9 2.4 2.7 0.3 0.03 <0.001
 Other 2.0 1.5 1.8 1.7 2.8 0.1 0.11 0.20
Whole Fruits (5)
 Overall 1.9 2.0 2.3 2.7 2.9 0.3 0.03 <0.001
 Asian 1.8 2.1 2.7 3.1 3.3 0.4 0.09 <0.001
 Black 1.5 1.8 2.0 2.3 2.1 0.2 0.04 <0.001
 Hispanic 2.1 2.4 2.5 2.7 2.2 0.1 0.07 0.14
 White 1.7 1.8 2.1 2.6 2.8 0.3 0.04 <0.001
 Other 2.0 1.8 2.0 2.4 3.4 0.3 0.14 0.04
Total Vegetables (5)
 Overall 2.7 3.0 3.2 3.4 3.6 0.2 0.02 <0.001
 Asian 2.9 3.3 3.4 3.7 3.8 0.2 0.05 <0.001
 Black 2.6 2.8 3.0 3.3 3.2 0.2 0.03 <0.001
 Hispanic 2.9 3.3 3.4 3.7 3.4 0.1 0.04 <0.001
 White 2.5 2.7 3.0 3.3 3.5 0.3 0.02 <0.001
 Other 2.4 2.8 3.1 3.2 3.2 0.2 0.10 0.04
Greens and Beans (5)
 Overall 1.7 1.8 2.1 2.4 2.5 0.2 0.03 <0.001
 Asian 1.9 2.3 2.6 2.9 3.0 0.3 0.07 <0.001
 Black 1.8 1.6 1.9 2.0 1.7 0.1 0.04 0.08
 Hispanic 2.2 2.5 2.5 2.9 2.7 0.2 0.07 0.02
 White 1.2 1.2 1.6 1.9 2.1 0.3 0.04 <0.001
 Other 1.4 1.4 1.8 2.3 2.2 0.3 0.12 0.008
Whole Grains (10)
 Overall 2.2 2.3 2.7 3.2 3.4 0.4 0.04 <0.001
 Asian 1.6 3.0 2.9 3.2 3.9 0.3 0.11 0.004
 Black 1.8 2.2 2.5 2.8 2.9 0.3 0.07 <0.001
 Hispanic 2.3 2.1 2.2 3.3 2.8 0.3 0.09 0.005
 White 2.2 2.3 2.8 3.3 3.5 0.4 0.06 <0.001
 Other 1.9 2.2 2.8 2.3 3.8 0.3 0.17 0.10
Dairy (10)
 Overall 4.8 4.5 4.7 4.7 4.5 0.0 0.04 0.94
 Asian 4.4 3.6 3.5 3.7 4.3 0.1 0.15 0.36
 Black 3.9 3.7 3.9 3.9 3.6 0 0.06 0.80
 Hispanic 5.0 4.9 5.1 5.5 5.0 0.1 0.10 0.22
 White 5.8 5.4 5.6 5.6 5.2 0 0.05 0.52
 Other 4.4 5.4 5.0 5.1 5.7 0.1 0.15 0.40
Total Protein Foods (5)
 Overall 4.3 4.5 4.5 4.5 4.5 0 0.01 0.009
 Asian 4.7 4.6 4.7 4.7 4.6 0 0.04 0.80
 Black 4.4 4.6 4.6 4.7 4.5 0 0.02 0.26
 Hispanic 4.3 4.6 4.6 4.6 4.7 0 0.02 0.06
 White 4.1 4.3 4.4 4.4 4.4 0 0.02 0.03
 Other 4.1 4.4 4.3 4.4 4.2 0 0.06 0.65
Seafood and Plant Proteins (5)
 Overall 2.5 2.6 2.8 3.2 3.2 0.2 0.02 <0.001
 Asian 1.9 3.0 3.4 3.4 3.3 0.2 0.07 0.03
 Black 2.1 2.3 2.6 2.8 2.7 0.2 0.04 <0.001
 Hispanic 2.7 3.1 3.2 3.3 3.6 0.2 0.06 0.003
 White 2.3 2.4 2.6 3.0 3.0 0.2 0.03 <0.001
 Other 2.2 2.4 2.6 2.8 2.5 0.1 0.12 0.29
Fatty Acids (10)
 Overall 5.0 5.0 5.2 5.4 5.7 0.2 0.04 <0.001
 Asian 4.8 6.0 6.7 6.8 6.5 0.2 0.14 0.10
 Black 5.5 5.5 5.5 5.7 6.1 0.1 0.08 0.16
 Hispanic 4.7 5.0 4.7 5.2 5.3 0.1 0.08 0.24
 White 4.2 4.2 4.4 4.6 4.9 0.2 0.06 <0.001
 Other 5.3 4.5 5.2 5.0 5.7 0.1 0.18 0.41
Refined Grains (10)
 Overall 6.0 5.7 6.0 6.6 7.0 0.4 0.05 <0.001
 Asian 4.7 4.8 5.1 5.4 5.7 0.3 0.14 0.04
 Black 6.7 6.8 6.7 6.9 7.1 0.1 0.06 0.19
 Hispanic 4.8 4.7 5.1 6.3 6.0 0.5 0.10 <0.001
 White 6.6 6.2 6.5 7.2 7.8 0.4 0.06 <0.001
 Other 7.1 6.5 6.3 6.3 5.8 −0.2 0.15 0.10
Sodium (10)
 Overall 4.7 4.2 4.1 4.2 4.3 0.0 0.04 0.66
 Asian 3.0 2.5 2.4 2.5 2.8 0.1 0.09 0.57
 Black 4.6 4.2 3.9 4.4 4.4 0 0.07 0.86
 Hispanic 4.8 4.2 4.2 4.4 4.4 0 0.09 0.61
 White 4.9 4.5 4.4 4.6 4.6 0 0.06 0.97
 Other 5.3 4.4 4.2 3.1 5.4 −0.3 0.22 0.17
Added Sugars (10)
 Overall 5.9 6.3 6.6 7.2 7.3 0.4 0.04 <0.001
 Asian 6.0 7.8 8.1 8.4 8.5 0.4 0.07 <0.001
 Black 5.3 6.0 6.1 6.7 6.5 0.3 0.07 <0.001
 Hispanic 6.6 6.7 6.9 7.3 6.9 0.2 0.08 0.07
 White 5.4 5.8 6.2 6.8 7.0 0.4 0.06 <0.001
 Other 5.8 5.2 6.1 7.2 6.2 0.5 0.24 0.05
Saturated Fats (10)
 Overall 6.0 6.2 6.3 6.6 6.8 0.2 0.04 <0.001
 Asian 5.9 7.3 8.1 8.3 8.4 0.4 0.09 <0.001
 Black 6.4 6.0 6.1 6.4 6.8 0.1 0.06 0.03
 Hispanic 6.1 6.3 6.0 6.6 6.4 0 0.08 0.55
 White 5.0 5.3 5.5 5.7 6.0 0.2 0.07 <0.001
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Notes: Boldface indicates statistical significance (p<0.01).

a

Non-pregnant adults ≥20 years of age who completed 2 dietary recalls were included in analyses. Overall estimates are adjusted for age, sex, race/ethnicity, education level, poverty income ratio, current smoking status, and recreational physical activity. Race/ethnicity was excluded from models for subgroup estimates.

b

Maximum attainable score.

c

Individuals who did not identify as Asian, Black, Hispanic, or White were coded as Other; this category also includes persons who identify non-Hispanic multi-racial.

HEI, Healthy Eating Index; NHANES, National Health and Nutrition Examination Survey.

The most prominent gradation in total HEI scores across levels of self-rated diet quality was observed among Asian adults (β=3.2, 99% CI=1.8, 4.6), with a 15.9-point difference between poor and excellent self-rated categories. Excellent self-raters were primarily distinguished by higher scores for Total Fruits, Whole Fruits, Added Sugars, and Saturated Fats (all β=0.4, p<0.001). Higher self-rated diet quality was similarly associated with total HEI scores in non-Hispanic White adults (β=3.2, 99% CI=2.6, 3.7), largely explained by higher Whole Grains, Refined Grains, and Added Sugars scores (all β=0.4, p<0.001). Positive, albeit weaker, associations between self-rated versus measured diet quality were also observed among Black and Hispanic adults. Scores for Whole Grains and Added Sugars differed most across levels of perceived diet quality in Black adults (both β=0.3, p<0.001), while greater Refined Grains scores (indicating lower refined grain intakes) were most strongly associated with self-ratings in Hispanic adults (β=0.5, p<0.001).

Better self-rated diet quality was most consistently and strongly associated with higher HEI scores among adults with BMI <30 kg/m2 (Table 3). Self-ratings were positively associated with intakes of vegetables (Total Vegetables, and Greens and Beans) across all BMI groups, and with Seafood and Plant Proteins in all groups except BMI ≥40 kg/m2.

Table 3.

HEI-2015 Scores by Self-Rated Diet Quality, Stratified by BMI Category, for Adults in NHANES 2011–2018a

HEI component Poor Fair Good Very
good		 Excellent β SE p-
value
Total score (100)b
 18.5–24.9 48.4 49.7 52.1 55.5 58.8 2.9 0.25 <0.001
 25–29.9 49.3 51.1 53.7 58.9 58.4 3.0 0.28 <0.001
 30–34.9 50.9 50.4 53.0 54.8 56.1 1.7 0.34 <0.001
 35–39.9 50.6 51.4 51.9 58.3 55.4 2.1 0.54 <0.001
 ≥40 48.3 47.6 49.9 50.9 52.3 1.2 0.54 0.03
Total Fruits (5)
 18.5–24.9 1.5 1.7 2.2 2.5 2.7 0.3 0.04 <0.001
 25–29.9 1.7 2.1 2.3 2.9 2.9 0.4 0.04 <0.001
 30–34.9 2.5 1.9 2.2 2.2 2.7 0.1 0.06 0.08
 35–39.9 2.1 2.1 2.0 2.5 2.2 0.1 0.07 0.16
 ≥40 1.5 1.8 1.9 1.9 2.1 0.1 0.07 0.09
Whole Fruits (5)
 18.5–24.9 1.4 1.8 2.3 2.5 2.7 0.3 0.05 <0.001
 25–29.9 1.7 2.2 2.4 3.1 3.1 0.4 0.05 <0.001
 30–34.9 2.6 2.0 2.3 2.3 2.7 0.1 0.07 0.14
 35–39.9 2.2 2.4 2.2 2.9 2.2 0.1 0.08 0.17
 ≥40 1.6 2.0 2.1 1.9 2.1 0.1 0.09 0.23
Total Vegetables (5)
 18.5–24.9 2.5 2.9 3.1 3.4 3.5 0.2 0.04 <0.001
 25–29.9 2.6 2.9 3.1 3.5 3.5 0.2 0.03 <0.001
 30–34.9 2.8 3.1 3.3 3.2 3.5 0.1 0.04 0.002
 35–39.9 2.8 3.0 3.1 3.5 3.8 0.2 0.07 <0.001
 ≥40 2.8 2.9 3.3 3.6 3.9 0.3 0.05 <0.001
Greens and Beans (5)
 18.5–24.9 1.6 1.8 2.0 2.3 2.3 0.2 0.05 0.002
 25–29.9 1.8 1.8 2.1 2.5 2.3 0.2 0.05 <0.001
 30–34.9 1.8 1.8 2.1 2.3 2.6 0.2 0.07 0.001
 35–39.9 1.6 1.9 2.1 2.5 3.0 0.3 0.09 0.002
 ≥40 1.7 1.6 2.0 2.2 2.8 0.2 0.08 0.005
Whole Grains (10)
 18.5–24.9 2.3 2.1 2.4 3.1 3.4 0.4 0.08 <0.001
 25–29.9 2.2 2.3 3.1 3.3 3.6 0.4 0.07 <0.001
 30–34.9 2.3 2.5 2.9 3.2 3.0 0.3 0.10 0.009
 35–39.9 3.1 2.9 2.9 3.5 2.3 0.1 0.14 0.64
 ≥40 1.8 2.1 2.5 2.3 2.7 0.2 0.17 0.16
Dairy (10)
 18.5–24.9 5.4 4.4 4.6 4.7 4.4 0.0 0.08 0.57
 25–29.9 4.9 4.7 4.8 4.8 4.3 −0.1 0.07 0.19
 30–34.9 4.6 4.6 4.6 4.7 4.8 0.0 0.09 0.59
 35–39.9 4.3 4.6 4.6 4.8 3.5 0.0 0.13 0.89
 ≥40 4.1 4.2 4.5 4.6 4.2 0.2 0.12 0.18
Total Protein Foods (5)
 18.5–24.9 4.0 4.4 4.4 4.4 4.5 0.1 0.03 0.05
 25–29.9 4.2 4.5 4.5 4.6 4.5 0.0 0.02 0.03
 30–34.9 4.3 4.5 4.5 4.5 4.5 0.0 0.03 0.48
 35–39.9 4.2 4.5 4.6 4.6 4.8 0.1 0.03 0.003
 ≥40 4.7 4.6 4.6 5.0 4.8 0.1 0.05 0.18
Seafood and Plant Proteins (5)
 18.5–24.9 2.5 2.7 2.8 3.1 3.3 0.2 0.05 <0.001
 25–29.9 2.7 2.8 2.9 3.2 3.1 0.2 0.05 0.001
 30–34.9 2.1 2.4 2.8 3.0 2.9 0.2 0.06 <0.001
 35–39.9 2.5 3.0 3.2 3.8 4.1 0.4 0.09 <0.001
 ≥40 2.7 2.5 2.7 3.2 2.8 0.1 0.11 0.24
Fatty Acids (10)
 18.5–24.9 4.5 5.2 5.2 5.3 6.0 0.2 0.07 0.002
 25–29.9 4.5 5.1 5.1 5.7 5.6 0.3 0.07 <0.001
 30–34.9 5.1 4.9 5.3 5.1 5.1 0.1 0.10 0.55
 35–39.9 5.2 4.8 5.0 5.7 6.4 0.3 0.16 0.06
 ≥40 5.5 4.7 4.9 4.9 4.2 −0.2 0.14 0.25
Refined Grains (10)
 18.5–24.9 6.2 5.7 5.8 6.3 7.3 0.4 0.09 <0.001
 25–29.9 6.5 5.7 6.1 6.8 6.9 0.4 0.08 <0.001
 30–34.9 6.1 5.7 5.9 6.4 6.4 0.2 0.10 0.06
 35–39.9 5.9 5.8 5.9 6.8 6.5 0.3 0.11 0.006
 ≥40 5.9 6.0 6.2 6.6 6.8 0.2 0.14 0.09
Sodium (10)
 18.5–24.9 4.8 4.3 4.2 4.1 4.4 −0.1 0.09 0.54
 25–29.9 5.4 4.4 4.3 4.5 4.5 0.0 0.08 0.55
 30–34.9 4.2 4.4 4.1 4.4 4.2 0.0 0.09 0.77
 35–39.9 4.3 4.2 3.8 4.5 3.3 −0.1 0.10 0.43
 ≥40 4.2 3.7 3.2 2.6 2.5 −0.5 0.13 <0.001
Added Sugars (10)
 18.5–24.9 5.7 6.1 6.4 7.3 7.4 0.5 0.07 <0.001
 25–29.9 5.5 6.7 6.7 7.4 7.4 0.4 0.07 <0.001
 30–34.9 6.0 6.3 6.9 6.8 6.9 0.3 0.11 0.02
 35–39.9 6.6 6.0 6.7 7.2 7.6 0.4 0.13 0.003
 ≥40 6.3 6.2 6.8 6.8 7.6 0.3 0.12 0.01
Saturated Fats (10)
 18.5–24.9 6.0 6.4 6.6 6.4 6.8 0.1 0.08 0.13
 25–29.9 5.6 5.9 6.3 6.8 6.7 0.3 0.08 <0.001
 30–34.9 6.4 6.4 6.1 6.6 6.8 0.1 0.11 0.36
 35–39.9 5.8 6.3 5.8 6.0 5.9 −0.1 0.14 0.59
 ≥40 5.6 5.4 5.3 5.5 5.7 0.0 0.14 0.83
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Notes: Boldface indicates statistical significance (p<0.01).

a

Non-pregnant adults ≥20 years of age who completed 2 dietary recalls were included in analyses. Estimates are adjusted for age, sex, race/ethnicity, education level, poverty income ratio, current smoking status, and recreational physical activity.

b

Maximum attainable score.

HEI, Healthy Eating Index; NHANES, National Health and Nutrition Examination Survey.

Higher self-rated diet quality was associated with lower BMI (β= −1.6, p<0.001) and waist circumference (β= −3.8, p<0.001), after adjustment for demographic and lifestyle covariates (Table 4). These inverse associations persisted across all races and ethnicities (Appendix Table 3). In the overall adult population, higher self-rated diet quality was also associated with higher high-density lipoprotein cholesterol and lower triglycerides, glucose, insulin, and HbA1c, after controlling for BMI. However, these associations were not consistent across subgroups defined by race/ethnicity or BMI (Appendix Table 4).

Table 4.

Cardiometabolic Risk Factors by Self-Rated Diet Quality for Adults in NHANES 2011–2018a

Risk factor nb Poor Fair Good Very
good		 Excellent ß SE p-
value
BMI (kg/m2) 15,278 32.3 30.9 28.6 27.3 26.2 −1.6 0.1 <0.001
Waist circumference (cm) 14,923 106.1 103.8 98.6 95.3 92.4 −3.8 0.2 <0.001
SBP (mmHg) 14,978 125.8 125.3 125.3 125.3 124.8 −0.1 0.2 0.46
DBP (mmHg) 14,942 70.5 72.4 71.7 71.4 70.9 −0.2 0.1 0.13
Total cholesterol (mg/dL) 14,617 194.3 195.6 192.7 191.7 190.4 −1.4 0.6 0.02
HDL-C (mg/dL) 14,617 51.8 51.2 50.9 53.0 53.6 0.7 0.2 <0.001
LDL-C (mg/dL) 6,669 119.1 116.6 114.5 113.3 112.6 −1.6 0.7 0.02
Triglycerides (mg/dL) 6,760 126.3 132.4 130.3 116.6 112.6 −5.7 1.6 0.001
Glucose (mg/dL) 6,832 111.8 112.9 110.5 108.5 105.2 −2.0 0.4 <0.001
Insulin (μU/mL) 6,655 15.2 14.8 14.2 13.5 13.2 −0.6 0.2 0.003
HbA1c (%) 14.795 5.86 5.91 5.86 5.76 5.77 −0.05 0.01 <0.001
Open in a new tab

Notes: Boldface indicates statistical significance (p<0.01).

a

Non-pregnant adults ≥20 years of age who completed 2 dietary recalls were included in analyses. Estimates are adjusted for age, sex, race/ethnicity, education level, poverty income ratio, current smoking status, recreational physical activity, and BMI. BMI was excluded from models for BMI and waist circumference.

b

Unweighted n.

DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NHANES, National Health and Nutrition Examination Survey; SBP, systolic blood pressure.

DISCUSSION

This study assessed the relative validity of a single-item diet quality self-rating, compared with an established diet quality measure scored based on reported intake, and examined the relationship between self-rated diet quality and cardiometabolic health. Total HEI-2015 scores increased with self-rated diet quality, explained by higher scores for all components except Dairy and Sodium. Self-rated diet quality was also associated with several cardiometabolic disease risk factors. However, associations with specific dietary components and risk factors varied across racial and ethnic subgroups of the U.S. adult population and were not consistently observed across BMI classes. Thus, a single-item rating of self-perceived diet quality may quickly identify individuals with the greatest need for dietary modification to improve their cardiometabolic health, but a more thorough dietary assessment is warranted to identify specific changes to target.

Previously, self-rated diet quality was shown to be associated with greater household availability and consumption of healthier foods and beverages33,34 Associations with overall diet quality have also been reported in various populations. In a diverse sample of New York City residents, average total HEI-2010 scores for excellent versus poor self-raters differed by 14.8 points (p<0.01).35 However, estimates were not adjusted for covariates. As both diet quality and self-ratings of diet have been shown to vary by sociodemographic factors,36,37 analyses presented herein controlled for their possible confounding effect. Woglom et al.38 similarly controlled for demographic covariates and reported an 8.4-point total HEI-2010 score difference in young adults who rated their diets as excellent versus poor (p<0.001), which is comparable to the difference reported here (8.9 points). Diet quality differences of similar magnitude have been associated with long-term reductions in cardiovascular disease incidence and mortality, and all-cause mortality, in several large cohorts.3,5,39 An 8.9-point distinction between poor and excellent self-raters is thus substantial and could lead to increased disease risk if not identified and improved.

Although self-ratings of diet quality are, on average, associated with a summary measure of overall diet quality, perceptions of what defines a “healthy” diet may differ across population subgroups. Self-rated diet quality was associated with better adherence to a Dietary Approaches to Stop Hypertension diet among non-Hispanic White and Black U.S. adults but not Mexican Americans, in whom adherence scores differed little across levels of self-rated diet quality.40 In the present study, positive associations between self-rated diet quality and HEI scores were observed in all racial and ethnic groups, though the distinction between higher versus lower self-raters was less prominent for Black and Hispanic adults compared with Asian and White adults. Some dietary components consistently increased with higher self-ratings (e.g., Total Vegetables, Whole Grains), whereas other scores poorly aligned with self-ratings within specific subgroups (e.g., Fruits and Whole Fruits scores in Hispanics). Associations also varied across BMI-defined subgroups, though vegetable intakes consistently increased with higher self-ratings. Subgroup differences in the alignment between self-rated versus objective diet quality may arise from differential susceptibility to social desirability bias,41,42 possibly explained or exacerbated by the face-to-face administration of survey questions by sociodemographically unmatched interviewers.43 Research also suggests that differing valuations or definitions of “healthy” foods,44-46 knowledge,47-49 or feelings of self-efficacy45,50,51 might explain why perceptions do not consistently align with actual intakes. Thus, a singular definition of a “healthy” diet should not be assumed across the U.S. population.

Total Protein Foods, Dairy, and Sodium scores were not associated with self-rated diet quality in most subgroups. As most Americans meet total protein foods recommendations, it is not surprising that scores across levels of self-rated diet quality were similar. By contrast, 90% of Americans do not meet dairy intake recommendations.12 “Dairy” includes nutritionally diverse foods (e.g., whole, low-fat, and soy milk, cheese, yogurt, ice cream). Differences in sources—rather than amount consumed—may distinguish higher from lower self-raters; however, food sources were not examined in the present study. Sodium is ubiquitous in packaged and prepared foods,12,52 and most Americans (89%) exceed recommended limits.53 Major sources vary by racial/ethnic group and include foods that may be regarded as healthy (e.g., whole grain breads, soups, stir fry),52,54 which may explain the lack of association between self-rated diet quality and sodium intake observed in this study and previously.40

Single-item self-ratings of general health have been studied widely and linked to mortality and morbidity in multiple populations.17,55-57 In a review, Jylhä58 posits that self-rated health is comprehensive, inclusive, and non-specific—thereby capturing dimensions of health that cannot be captured by more detailed questions, and thus serving as a complement to more detailed health questions. Similarly, self-rated diet quality offers a more global method of assessing dietary behaviors. From their work on dietary patterns, Kant and colleagues59 state, “It appears unlikely that the average consumer can understand and implement complex dietary guidance that includes numerical goals for nutrient and food group intake.” A simple single-item assessment of diet quality may capture an overall view of one’s diet and be easier for an individual to conceptualize and respond.

Though self-ratings may provide a simple preliminary step to identify patients with the worst diets for further dietary counseling, the suboptimal average HEI-2015 scores at all levels of self-rated diet quality indicate that all adults have room for improvement. The mean score in even the highest category (excellent, 58.3) is still considered “failing” (F), per recommended grading cut points.25 Diet-focused behavioral interventions administered in primary care settings have been shown to improve markers of cardiometabolic health, even in adults without known risk factors,60 suggesting that most people could benefit from dietary improvements. Clinician-administered dietary counseling has been shown to improve diet quality and cardiometabolic health and is thus recommended in routine care.15 However, few physician visits include any nutrition counseling,61 largely because of lack of time in the office visit.62,63 Currently available rapid screeners designed for dietary assessment in primary care have not been widely adopted in routine practice.15 A single self-rating of diet quality could easily be assessed in primary care visits and integrated into electronic health records, providing opportunities for clinicians to emphasize the importance of nutrition to patients and refer them to more intensive, personalized counseling.

A strength of these analyses is use of a large nationally representative sample of U.S. adults, which supports the generalizability of findings. Another strength is assessment of a validated measure of overall diet quality and the underlying component scores, as well as physiological markers of cardiometabolic health, to demonstrate the utility of a single-item self-rating of diet quality. Finally, associations within population subgroups were explored to better understand the consistency of findings across the U.S. adult population.

Limitations

A limitation of this study is the calculation of HEI scores based on averaged intakes from just 2 dietary recalls, which may not represent usual intakes. However, existing statistical methods for estimating usual intake are intended to obtain group-level estimates of intake whereas person-level HEI scores were required to assess the association with individuals’ self-rated diet quality.64 As dietary intakes were self-reported, systematic over- or under-reporting of certain foods or nutrients cannot be excluded. Estimated mean HEI scores will be biased to the extent that the 24-hour dietary recalls are biased measures of intake. However, the standardized method used to obtain recalls has been validated against true (observed) intakes and biomarkers of intake,65-69 and more accurately quantifies actual, rather than perceived, intakes compared with other dietary assessment methods (e.g., food frequency questionnaires).23 Finally, unmeasured or residual confounding may influence observed associations; however, a series of nested models were run to better understand the impact of covariate adjustments.

Future qualitative investigation into subpopulation differences in diet quality self-ratings is warranted. Individuals’ knowledge and sociocultural context influence their perceptions and reporting of health status70-72 and likely also shape their perceptions of diet quality. Understanding how the association between adherence to dietary guidelines and perceived diet quality is modified by such factors could improve the utility of this item in practice.

CONCLUSIONS

Few Americans meet recommendations for consumption of healthy foods and adhere to limits on unhealthy foods. A single-item assessment of self-rated diet quality may be useful for identifying patients requiring further nutrition counseling. More detailed dietary assessments could subsequently be administered by a Registered Dietitian–Nutritionist to identify specific areas of concern and inform personalized interventions.

Supplementary Material

1

ACKNOWLEDGMENTS

This research was supported by the National Heart, Lung, and Blood Institute, NIH (T32 HL007024 and R01HL141427) and the National Institute on Minority Health and Health Disparities, NIH (U54MD000538). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. SY, JMB, and MF designed the study; VKS analyzed the data; and VKS, EJ, and JMB drafted the manuscript, with revisions from MF and SY. All authors approve the manuscript for publication. No financial disclosures were reported by the authors of this paper.

Footnotes

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