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. Author manuscript; available in PMC: 2020 Mar 1.
Published in final edited form as: J Acad Nutr Diet. 2018 Sep 1;119(3):400–415. doi: 10.1016/j.jand.2018.06.006

Table 6.

Per capita daily nutrient consumption according to category of where food was purchased, by SNAPa participation and time period, NHANESb, c

2003–2006 2007–2010

Food Source Grocery Store Sit-down Restaurant Fast Food Other source Total consumption Grocery Store Sit-down Restaurant Fast Food Other source Total consumption
Calories
 SNAP participants 1630 ± 80 95 ± 31 357 ± 47 103 ± 31 2186 ± 91 1690 ± 49 54 ± 15 329 ± 26 110 ± 18 2182 ± 42
 Non-participants 1753 ± 51 190d ± 22 362 ± 39 132 ± 16 2437d ± 53 1593 ± 43 174d ± 25 325 ± 31 127 ± 19 2219 ± 44
Solid Fats (% total energy intake)e
 SNAP participants 12.7 ± 0.9f 0.8 ± 0.2 3.6 ± 0.5 1.0 ± 0.3 18.1 ± 0.1 11.8 ± 0.3 0.4 ± 0.1 2.9 ± 0.2 0.7 ± 0.2 15.9 ± 0.4
 Non-participants 10.9 ± 0.4c 1.3d ± 0.2 3.5 ± 0.3 1.1 ± 0.1 18.9 ± 0.1 10.3d ± 0.4 1.1d ± 0.2 2.9 ± 0.2 0.9 ± 0.1 15.3 ± 0.4
Added Sugars (% total energy intake)
 SNAP participants 16.6 ± 1.0 0.6 ± 0.2 1.9 ± 0.3 1.5 ± 0.7 21.0 ± 1.0 15.9 ± 0.6 0.4 ± 0.1 1.8 ± 0.3 1.0 ± 0.2 19.1 ± 0.6
 Non-participants 15.2 ± 1.1 1.2 ± 0.2 1.2 ± 0.2 1.2 ± 0.2 18.9d ± 1.0 13.0d ± 0.6 0.8 ± 0.2 1.6 ± 0.2 1.3 ± 0.1 16.6d ± 0.7
Non-starchy vegetables (servings)
 SNAP participants 0.6 ± 0.1 0.0 ± 0.0 0.2 ± 0.0 0.1 ± 0.0 0.9 ± 0.1 0.7 ± 0.0 0.0 ± 0.0 0.1 ± 0.0 0.1 ± 0.0 0.9 ± 0.0
 Non-participants 0.7 ± 0.0 0.1d ± 0.0 0.2 ± 0.0 0.1 ± 0.0 1.1d ± 0.1 0.7 ± 0.0 0.1d ± 0.0 0.2 ± 0.0 0.1 ± 0.0 1.1 ± 0.0
Whole fruits (servings)
 SNAP participants 0.6 ± 0.2 0.0 ± 0.0 0.0 ± 0.0 0.1 ± 0.0 0.7 ± 0.2 0.4 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.4 ± 0.1
 Non-participants 0.6 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.1 ± 0.0 0.7 ± 0.1 0.5 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.5 ± 0.0
Whole grains (ounce equivalents)
 SNAP participants 0.4 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.4 ± 0.1 0.4 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.5 ± 0.1
 Non-participants 0.5 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.5 ± 0.1 0.5 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.6 ± 0.0
a

SNAP=Supplemental Nutrition Assistance Program

b

NHANES=National Health and Nutrition Examination Survey

c

Data are for adults aged 20–64 years with an income at or below 130% of the Federal Poverty Limit from NHANES 2003–2004, 2005–2006, 2007–2008 and 2009–2010. The sample size for SNAP participants was 373 in 2003–2006 and 1,056 in 2007–2010. The sample size for income-eligible non-participants was 1,342 in 2003–2006 and 1,498 in 2007–2010. Data are nationally representative and results account for complex survey design. Data samples were pooled, combining 2003–2004 with 2005–2006 and 2007–2008 with 2009–2010. Each nutrient outcome was calculated for each category of food source and included in a separate linear regression model. All models were adjusted for year, age (age and age2), sex, marital status, employment, race-ethnicity (Mexican American, non-Hispanic White, non-Hispanic Black (ref), Other), income (poverty income ratio), education (< high school (ref), high school, some college or college graduate or above), weekend consumption and WIC participation.

d

Significant difference between SNAP participants and income-eligible non-participants within the same time period, significant at p<.025; These results are also bolded

e

Dietary data for solid fats, added sugars, servings and ounce equivalents are from USDA MyPlate Equivalents Database (MPED) 2003–2004 and Food Patterns Equivalents Database (FPED) 2005–2006, 2007–2008 and 2009–2010. Non-starchy vegetables include dark-green and orange vegetables, tomatoes and other vegetables, and exclude starchy vegetables, potatoes and dry beans and peas. Added sugars are those used as ingredients in processed and prepared foods and do not include naturally occurring sugars. Discretionary solid fats include fats from animal sources or hydrogenated vegetable oils.

f

Greyed results reflect models which failed an F-test of overall significance with a p-value >0.05. In other words, the model fails to fit the data better than simply using the intercept, or the mean nutrient intake from a given food source, to predict individual outcomes.

Author note: we suggest this be included as an online table only