Table 2.
Studies that evaluated the food and/or nutrition literacy of U.S. adults, including SNAP adults, 2006–2021.
| Lead Author, Year | Study Objective |
Study Location |
Study Population |
Race/Ethnicity of Study Population |
Study Design |
Outcomes Measured Cognitive (C); Behavioral (B); Food Security (FS); Health Status (H) |
Major Finding |
|---|---|---|---|---|---|---|---|
| Amuta-Jimenez et al., 2018 [55] | Assess differences between food label literacy and other factors between respondents. |
National | U.S. adults (n = 3185) with cancer sub-population (n = 459); (F = 280; M = 168) |
African American (n = 36); Asian (n = 7); Caucasian (n = 285); Hispanic (n = 37); Other (n = 9) | Cross-sectional study | C: Food label literacy; confidence in ability to take care of self. B: Food label use; menu use; dietary intake; health information seeking behavior; participation in cancer support group. FS: Not measured. H: Body mass index (BMI). |
Food label use associated with better quality diets. |
| Chang et al., 2017 [56] | Evaluate relationship between nutrition literacy and food insecurity in SNAP participants. | National (house-hold visits with telephone follow up) | U.S. households (n = 4158) with SNAP household sub-population (n = 1342 weighted) | Black (n = 349); Hispanic (n = 318); White (n = 859); Other (n = 148) |
Cross-sectional study | C: Knowledge of U.S. nutrition guidelines. B: Food label use; nutrition guideline use; conscientious or frugal buying; financial management practices. FS: Household-level food security. H: Not measured. |
SNAP participants face unique financial challenges. |
| Coffman et al., 2012 [57] | Test the Spanish Nutrition Literacy Scale and assess relationship between literacy and overweight/obesity. |
Southeast US city | Spanish-speaking U.S. adults (n = 131); (F = 103; M = 28) |
Hispanic (n = 131) |
Cross-sectional study | C: Nutrition literacy; health literacy. B: Not measured. FS: Not measured. H: BMI (overweight and obesity). |
Nutrition literacy scores were lower in overweight or obese respondents. |
| Gibbs et al., 2016 [58] | Test the Nutrition Literacy Assessment for Parents tool and relationships among parental nutrition literacy, parent, and child BMI and child diet quality. |
Kansas City Metropolitan Area | English-speaking U.S. adults in parent-child dyads (n = 101); (F = 86; M = 15) SNAP households (n = 25) |
Black (n = 24); Hispanic (n = 6); White (n = 70); American Indian or Alaskan Native (n = 1) | Cross-sectional study | C: Nutrition literacy by health literacy and nutrition knowledge. B: Dietary intake and quality (parent and child). FS: Not measured. H: BMI (parent and child). |
Parental nutrition literacy is a significant predictor of child diet quality. |
| Grutzmacher et al., 2020 [59] | Examine numeracy skills and Nutrition Fact Label skills in classifying health literacy and NVS performance. | Maryland | SNAP-eligible adults (n = 144); (F = 110; M = 34) |
Racial and ethnic data not reported. | Cross-sectional study | C: Health literacy; nutrition literacy. B: Not measured. FS: Not measured. H: Not measured. |
The NVS literacy tool appears to measure many skills and constructs simultaneously. |
| Jay et al., 2009 [60] | Test multimedia intervention to improve food label comprehension in low-income patients with chronic health conditions. |
New York City | U.S. English-speaking adult patients with chronic health conditions (n = 42); (F = 34; M = 8) |
Asian (n = 5); African American (n = 11); Caucasian (n = 6); Hispanic (n = 16); Other (n = 2) |
Random-ized Interven-tion trial |
C: Food label exposure; confidence interpreting knowledge; health literacy. B: Not measured. FS: Not measured. H: Health status measured at baseline but not at post-test. |
A multimedia intervention can improve short-term food label comprehension in patients with adequate health literacy. |
| Jones and Adkins 2021 [61] |
Examine associations between nutrition literacy and food selections in school-based food pantry. |
Indiana | U.S. adult users of a school food pantry (n = 61); (F = 41; M = 20) |
African American (n = 12); Caucasian (n = 31); Hispanic (n = 2); Other (n = 16) |
Cross-sectional study | C: Nutrition literacy and preferences. B: Food selection at a food pantry. FS: Household-level and child food security. H: Not measured. |
Higher adult nutrition literacy was associated with a selection of a more diverse set of food items in a school-based food pantry. |
| Moore et al., 2020 [62] | Assess and compare nutrition literacy and food insecurity in college students. |
Texas (3 college campuses) |
U.S. adult college students (n = 672); (F = 527; M = 69) SNAP enrolled (n = 14) |
Asian (n = 96); Black (n = 90); Hispanic (n = 111); White (n = 324) |
Cross-sectional study | C: Nutrition literacy. B: Not measured. FS: Individual-level food security. H: Not measured. |
Among students with adequate nutrition literacy, a greater proportion were food secure. |
| Parekh et al., 2018 [63] | Feasibility of nutrition education workshops for cancer survivors to inform the design of a multi-center intervention. | New York City | U.S. adult female English-speaking breast cancer patients post-treatment (n = 59) |
Asian (n = 3); American Indian/Alaskan Native (n = 2); Black (n = 13); White (n = 40); Other (n = 1) |
Random-ized Interven-tion Trial |
C: Nutrition literacy; health literacy. B: Fruit and vegetable, alcohol, and high fiber food intake. FS: Not measured. H: Height; weight. |
The workshop interventions were found to be promising and scalable. |
| Persoskie et al., 2017 [64] | Assess Nutrition Facts label understanding and associations by diet and demographics. |
National | U.S. adults (n = 3815) Nationally representative (F = 1893; M = 1190) |
Black (n = 335); Hispanic (n = 478); White (n = 2140); Other (n = 232) |
Cross-sectional study |
C: Health literacy. B: Sugar sweetened beverages, fruit, and vegetable intake. FS: Not measured. H: Not measured. |
Even with revised or simplified Nutrition Facts label, ability to make calculations was a barrier to greater health literacy. |
| Rhea et al., 2020 [65] | Test multi- factorial nutrition education skill building program for veterinary medical students to improve food literacy scores. |
Louisiana | U.S. adult college veterinary and non-veterinary students (n = 37); (F = 31; M = 6) |
Asian (n = 6); Black (n = 5); Hispanic (n = 1); White (n = 25) |
Four-week interven-tion trial | C: Knowledge and awareness of nutritious foods; food preferences. B: Reads nutrition information before purchase, food selection, food preparation, menu planning, practice cooking skills. FS: Not measured. H: Not measured. |
The intervention raised student awareness and increased behaviors to select, prepare, and eat healthy food. |
| Rosenbaum et al., 2018 [66] | Identify correlates of nutrition literacy; whether nutrition literacy predicted weight loss, food record completion and quality, and session attendance; and associations of race and education. | Mid-Atlantic Metropo-litan Area | U.S. adults with overweight or obesity (n = 320); (F = 250; M = 70) |
Black (n = 80); White (n = 224); Other (n = 16) |
Secondary data analysis of a six-month behavioral weight loss interven-tion | C: Nutrition literacy. B: Food record completion, food record quality, meeting attendance, self-monitoring. FS: Not measured. H: Weight loss at six months. |
Lower nutrition literacy was associated with less weight loss in program participants. Nutrition literacy was lower for Black participants and those with less education. |
| Roth-man et al., 2006 [67] | Patient comprehension of nutrition labels and relationship of label understanding to patient or demographic characteristics, literacy, and numeracy skills. |
TN | U.S. primary health care patient adults (n = 200) (F = 143; M = 57) |
Black (n = 50); White (n = 134); Other (n = 16) |
Cross-sectional study | C: Nutrition label comprehension, reading, and numeracy skills. B: Food label use and frequency; diet plan use. FS: Not measured. H: Chronic disease status; BMI. |
Poor nutrition label comprehension was highly correlated with low literacy and low numeracy skills. |
| Speirs et al., 2012 [68] | Assess demographic characteristics and the relationship between health literacy and nutrition behaviors. |
Maryland | SNAP-eligible adults (n = 142); (F = 108; M = 34) |
African American (n = 75); White (n = 50); Other (n = 17) |
Cross-sectional survey | C: Health literacy. B: Fruit and vegetable intake; consumption of healthy foods. FS: Not measured. H: Not measured. |
Strong relationship between adequate health literacy and healthy consumption behaviors was not found. |
| Taylor et al., 2019 [69] | Describe the relationship between adherence to distinct dietary patterns and nutrition literacy. |
Kansas City Metropolitan Area | U.S. adults (n = 386) with diabetes, hypertension, hyperlipid-emia, and/or overweight or obesity; (F = 274; M = 112) |
African American (n = 131); White (n = 233); Hispanic (n = 36); Other (n = 46) |
Cross-sectional study | C: Nutrition literacy. B: Food intake and practices. FS: Not measured. H: Not measured. |
Nutrition literacy predicted diet quality and diet patterns. |
| Tucker et al., 2019 [70] | Examine results from a culturally sensitive, church-based health promotion intervention among Black adults. |
Florida | U.S. adult church congregants (n = 321); (F = 208; M = 51; no sex reported; n = 62) |
Black (n = 321) |
Random-ized control trial (pre-post interven-tion) |
C: Nutrition label literacy. B: Using health promoting behaviors (i.e., healthy eating, healthy drinking, physical activity). FS: Not measured. H: Weight, blood pressure. |
Intervention group had significantly greater increases in nutrition label literacy and health behaviors than the control group. |
| Zoellner et al., 2009 [71] | Examine the nutrition literacy status and preferred nutrition communication channels of adults. |
Lower MS Delta Region | U.S. adults (n = 177); (F = 124; M = 53) |
African American (n = 144); White (n = 33) |
Cross- sectional study |
C: Awareness and exposure to nutrition and health information and communication channels; nutrition literacy. B: Media use for health, food and diet information. FS: Not measured. H: BMI. |
Results suggest an association between nutrition-seeking behaviors and nutrition literacy. |
| Zoellner et al., 2011 [72] | Evaluate health literacy, diet quality, and sugar-sweetened beverage intake while accounting for demographic variables. | Lower MS Delta Region | U.S. adults (n = 376); (F = 287; M = 89) SNAP-enrolled (n = 103) |
African American (n = 254); non-Hispanic White (n = 116); Other (n = 6) |
Cross-sectional study | C: Health literacy. B: Dietary intake, diet quality (using the Healthy Eating Index), sugary beverage intake. FS: Not measured. H: BMI. |
Better understanding of limited health literacy needed to improve practices. |
Cognitive (C); Behavioral (B); Food Security (FS); Health Status (HS); United States (U.S.); female (F); male (M); Body mass index (BMI); Mississippi (MS); Supplemental Nutrition Assistance Program (SNAP); Tennessee (TN); U.S. Department of Agriculture (USDA).