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. 2020 Oct 21;17(20):7677. doi: 10.3390/ijerph17207677

Table 2.

Descriptive Characteristics of Included Studies (n = 34).

Author,
Year
Study Purpose Study
Year(s) a
Study
Location
Sample
Size
Intersectional
Attribute(s)
Sample
Demographics b
Stores
Assessed
QA c
Andreyeva, 2012 Describe supermarket beverage purchases of WIC and SNAP households. 2011 New England 39,172 Households Targeted: Low-Income 100% WIC Participation, 54% SNAP Participation Full-Service 6
Appelhans, 2017 Determine if household food purchases predict diet quality and nutrient density. 2014–2016 Chicago, IL 196 Households Targeted: Urban Mean age: 44; 83% female; 31% (NHW), 44% (NHB), 11% (Hisp), 13% (NHO); 38% (PIR: 0–1.99), 29% (2–3.99), 16% (4–5.99), 18% (≥ 6) All Stores 9
Borradaile, 2009 Describe after-school corner stores purchases of low-income children. 2008 Philadelphia, PA 833 Shoppers Targeted:
Low-Income + Urban
Grade range: 4–6 grade; 54% (NHW), 11.6% (NHB), 22.9% (Hisp), 10.8% (NHA); 82.1% of students at participating schools eligible for free/reduced lunch. Limited-Service 5
Caspi, 2017 [1] Examine differences in food and beverage purchases by type of limited-service store. 2014 Minneapolis, MN 661 Shoppers Targeted: Urban 47% (NHW), 34% (NHB), 3% (Hisp), 3% (NHA), 3% (NHO); 38% ≤ high school diploma Limited-Service 7
Caspi, 2017 [2] Determine if food and beverage purchases at limited-service stores with health-promoting features are healthier. 2014 Minneapolis, MN 594 Shoppers Targeted: Urban Mean age: 40; 58% male; 48% (NHW), 36% (NHB), 3% (Hisp), 3% (NHA), 3% (NHO); 36% ≤ high school diploma Limited-Service 9
Chrisinger, 2018 [1] Compare high-calories and low-calorie food purchases of Black women by store type. 2012 Philadelphia, PA 35 Shoppers Targeted:
Black + Urban d
Mean age: 39; 100% female; 100% Black Identifying; 37% Annual Income ≤ FPL All Stores 8
Chrisinger, 2018 [2] Assess the healthfulness of household food purchases by SNAP and WIC participation status. 2012–2013 National 4962 Households RE, SES 17.2% (30–39 years), 18.5% (40–49), 20.2% (50–59), 29.9% (60+); 64% female; 70% (NHW), 10.2% (NHB), 13.7% (Hisp), 6% (NHO); 13.1% (SNAP participant), 19.3% (SNAP-Eligible Non-Participant), 67.6% (Ineligible Non-Participant) Full-Service 8
Crane, 2019 Identify gender differences in the nutrient quality of food purchases. 2014–2016 Midwest 202 Households Targeted:
Urban
29.9% (NHW), 45.6% (NHB), 5.9% (Hisp), 18.6% (NHO); 40.6% receive government food assistance benefits All Stores 8
Cullen, 2007 Characterize food purchases of households by educational level and ethnicity. 2004 Houston, TX 167 Households RE x SES 45.8% (<40 years); 74.8% (female); 11.2% (NHW), 41.1% (NHB), 39.3% (Hisp), 2.8% (NHO); 46.7% (≤ High School Graduate), 28% (Some College), 14% (College Graduate), 6.5% (Advanced Degree) All Stores 8
Ford, 2014 Examine trends in purchases of consumer packaged goods among households with children age 2–5 years old. 2000–2011 National 14,110 Households RE, SES 68.3% (NHW), 10.3% (NHB), 16.8% (Hisp), 4.8% (NHO); 17.3% (<131% FPL), 14% (131–185% FPL), 68.3% (> 185% FPL) All Stores 7
Frankle, 2017 Describe differences in the purchasing of SNAP-eligible foods by SNAP participation status. 2012–2014 New York, New England 188 Stores SES NR Full-Service 7
French, 2019 Assess differences in the nutritional quality of foods and beverages purchased by household income level. 2014–2016 Chicago, IL 202 Households SES 15.3% (18–24 years), 47.5% (30–49), 36.6% (50+); 83% (female); 29.7% (NHW), 43.1% (NHB), 24.7% (Hisp); 24.3% (PIR: 0–1.3), 38.6% (PIR: 1.4–3.4), 37.1 (3.5+) All Stores 7
Gorski Finding, 2018 Determine if neighborhood retail food access is associated with overweight/obesity in children. 2012–2013 National 3748 Children SES SNAP Participants: 32% (NHW), 31.6% (H), 29.7% (NHB), 6.7% (O); SNAP-Eligible Non-Participants: 33.5% (NHW), 41.2% (Hisp), 19.6% (NHB), 5.7% (NHO); Ineligible Non-Participants: 65.0% (NHW), 16.9% (Hisp), 9.8% (NHB), 8.3% (NHO) All Stores 8
Grummon, 2017 Examine the nutritional profile of household food and beverage purchases by SNAP participation status. 2012–2013 National 70,477 Households RE x SES e SNAP Participants: Mean age: 55.5, 77% (NHW), 14% (NHB), 5% (Hisp), 4% (NHO); Income-Eligible Non-Participants: Mean age: 59.1, 82% (NHW), 8% (NHB), 4% (Hisp), 6% (NHO); Higher Income Non-Participants: Mean age: 59.3, 83% (NHW), 8% (NHW), 4% (Hisp), 5% (NHO). All Stores 8
Grummon, 2018 Describe differences in the unhealthy food and beverage purchases by race/ethnicity and SNAP participation status. 2010–2014 National 30,403 Households RE x SES Mean age: 59.2; 87% (NHW), 8% (NHB), 5% (Hisp); 17.5% SNAP Participations; 16% (SNAP among NHW), 27% (SNAP among NHB), 21% (SNAP among Hisp) All Stores 7
Gustafson, 2017 Determine how neighborhood food store availability influences food stores choice and food store purchases. 2012–2013 National 2962 Households SES 53% (SNAP Participants); 47% (SNAP-Eligible Non-Participants) All Stores 6
Jones, 2003 Assess differences in food shopping behaviors and consumption patterns between grocery store customers in low-income and high-income areas. 2001 Columbus, OH 6 Stores SES Low-Income Areas: 76.2% (NHW), 21.7% (NHB), 2.0% (NHO); High-Income Areas: 93.6% (NHW), 3.5% (NHB), 3.0% (NHO) Full-Service 6
Kiszko, 2015 Describe the food and beverage purchases of bodega shoppers in low-income communities. 2012 New York City 779 Shoppers Targeted:
Low-Income + Urban
Mean age: 39.1; 51.5% female; 57.0% (Hisp), 34.9% (NHB), 8.1% (NHO); 53% of shoppers had an annual income ≤ USD 25,000 Limited-Service 5
Lenk, 2018 Assess associations between customer characteristics, shopping patterns, and the healthfulness of purchases in limited-service stores. 2014 Minneapolis, MN 661 Shoppers Targeted:
Urban
47% (NHW), 36% (NHB), 17% (NHO); 38% ≤ high school, 37% (some college), 26% (≥college degree) Limited-Service 6
Lent, 2014 Describe corner store purchases by age group in a low-income urban neighborhood. 2011 Philadelphia, PA 9283 Shoppers Targeted:
Low-Income + Urban
75.5% adults, 15.5% adolescents, 9.9% children; 41.4% female. Limited-Service 6
Lin, 2014 Examine the roles of food prices and supermarket accessibility in determining food purchases of low-income households. 1996–1997 National 882 Households Targeted:
Low-Income
100% SNAP Households All Stores 8
Ng, 2016 Evaluate racial/ethnic and income trends in calories purchased in households with children. 2000–2013 National 64,709 Households RE, SES NR All Stores 7
Ng, 2017 Estimate trends in added sugars in beverage purchases among US households by race/ethnicity and socioeconomic status. 2007–2012 National 110,539 Households RE, SES NR All Stores 8
O’Malley, 2013 Determine the feasibility of increasing fruit and vegetable offerings in corner stores. NR New Orleans, LA 60 Shoppers Targeted:
Low-Income
48.3% female; 88.3% (AA); 63.3% Annual Income < USD 25,000 Limited-Service 6
Palmer, 2019 Explore food store selection and food purchases in the Northeast using 3 different data sources. 2012–2014 Northeast IRI CNP: 12,770 Households
CES:
3428 Households
SES IRI Consumer Network Panel (CNP) data: 19.4% (low income, 80.6% (non-low income); Consumer Expenditure Survey (CES) data: 10% of households on SNAP All Stores 7
Paulin, 2001 Compare food expenditure patterns of Hispanics to Non-Hispanics. 1995–1996 National 13,367 Households RE 9.2% Hispanic Households, 90.8% Non-Hispanic Households All Stores 8
Poti, 2016 Examine associations between race/ethnicity, ready-to-eat, highly-processed food and beverage purchasing. 2000–2012 National 157,142 Households RE x SES 81.3% (NHW), 9.3% (NHB), 7.1% (Hisp) All Stores 7
Stern, 2016 Determine if food store selection is associated with the nutrient profile of package food purchases across racial/ethnic groups 2007–2012 National 356,611 Households RE 81.8% (NHW), 8.7% (NHB, 5.1% (Hisp), 4.2% (NHO); 19.0% (≤185% FPL), 43.0% (185–400% FPL), 38% (≥400% FPL) All Stores 7
Taillie, 2016 Assess the relationship between food retail chain type and the healthfulness of food purchases. 2000–2013 National 164,315 Households RE, SES 81% (NHW), 9% (NHB), 5% (Hisp), 4% (NHO); 10% of households ≤ 130% FPL All Stores 7
Taillie, 2017 [1] Describe the prevalence of price promotions among food and beverage purchases of households with children. 2008–2012 National 90,046,893
Purchases
RE, SES NR All Stores 6
Taillie, 2017 [2] Examine trends in the proportion of packaged food and beverage purchases with a low-nutrient or no-nutrient claim. 2008–2012 National 80,038,247 Purchases RE, SES NR All Stores 7
Taillie, 2018 Compare the nutritional profile of food and beverages of SNAP participants to non-participants. 2010–2014 National 76,458 Households SES SNAP Participants: Mean age: 54.5, 76.5% (NHW), 13.8% (NHB), 5.7% (Hisp), 4.0% (NHO); Income-Eligible Non-Participants: Mean age: 58.4, 82.0% (NHW), 8.3% (NHB), 4.5% (Hisp), 5.3% (NHO); Higher-Income Non-Participants: Mean age: 58.5, 82.9% (NHW), 7.9% (NHB), 4.4% (Hisp), 4.7% (NHO) All Stores 7
Vadiveloo, 2019 Describe geographic differences in the diet quality of household food purchases. 2012–2013 National 3961 Households RE Mean age: 50.6; 70.2% female; 70.3% (NHW), 9.9% (NHB), 13.0% (Hisp), 6.8% (NHO); 16.9% (FPL<130%), 41.1% (130–349%), 42.0% (≥350%); 34.6% rural households All Stores 7
Vadiveloo, 2020 Evaluate racial/ethnic, socioeconomic, and weight-based differences in the diet quality of household food purchases. 2012–2013 National 3961 Households RE x SES Mean age: 50.6; 70.2% female; 70.3% (NHW), 9.9% (NHB), 13.0% (Hisp), 6.8% (NHO); 16.9% (FPL<130%), 41.1% (130–349%), 42.0% (≥350%); 57.8% high degree/some college; 12.7% SNAP participation; 34.6% rural households All Stores 8

Note: AA, African American; FPL, Federal poverty limit; Hisp, Hispanic; NHA, non-Hispanic Asian; NHB, non-Hispanic Black; NHW, non-Hispanic White; NR, None Reported; NHO, non-Hispanic Other (according to the authors’ definition); PIR, Poverty-to-Income ratio; QA, Quality Assessment; RE, Racial/ethnic differences; SES, Socioeconomic differences; SNAP, Supplemental Nutrition Assistance Program; WIC, Special Supplemental Nutrition Program for Women, Infants, and Children. a Study year (s) reflect the year the data was collected. If data collection dates were not provided, the date the statistical analysis was performed was recorded. b Demographic information on race/ethnicity, socioeconomic status, and urban/rural status are provided in the table. If socioeconomic information was not available, descriptive statistics for education level or employment status were recorded (if provided by authors). c The National Heart, Lung, and Blood Institute’s (NHLBI) quality assessment tool for observational cohort and cross-sectional studies was used for quality assessment: https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools. d This targeted study also assessed SES differences. e “X” indicates that intersectional information is provided on the two factors listed.