Frequency of Food Pantry Use Is Associated with Diet Quality among Indiana Food Pantry Clients

RESEARCH

Original Research: Brief

Frequency of Food Pantry Use Is Associated with Diet Quality among Indiana Food Pantry Clients Yibin Liu, PhD, CPH; Yumin Zhang, MS; Daniel T. Remley, MSPH, PhD; Heather A. Eicher-Miller, PhD ARTICLE INFORMATION Article history: Submitted 16 February 2018 Accepted 25 February 2019 Available online 27 April 2019

Keywords: Diet quality Food assistance Food pantry Food security Health 2212-2672/Copyright ª 2019 by the Academy of Nutrition and Dietetics. https://doi.org/10.1016/j.jand.2019.02.015

Background Food-insecure households access food pantries to receive supplemental food, yet limited examination of the relationships of food pantry use or household food insecurity with diet quality and health has been documented among food pantry users. Objective This study investigated the associations among food pantry use, household food security, body mass index, self-reported chronic disease and related conditions, and diet quality among food pantry users. Design Food pantry users in central Indiana were recruited for this cross-sectional study and surveyed for sociodemographic characteristics, food pantry use frequency, household food security, diet quality, and chronic disease and related conditions. Measurements of height and weight were obtained. Participants/setting Data from 270 participants, aged 21 to 80 years, were collected from June 2014 to December 2015. Statistical analyses performed Healthy Eating Index-2010 (HEI-2010) total score, component scores, and body mass index were analyzed across food pantry use and household food security groups using multiple linear regression. Odds of reporting chronic disease and related conditions were compared across food pantry use and household food security groups using logistic regression. Results Visiting food pantries more than once a month was associated with higher HEI2010 total score (P¼0.03) and Total Protein Foods score (P¼0.05) than visiting less often. HEI-2010 scores were not significantly different across household food security groups. Body mass index was not different across food pantry use groups or household food security groups. Household food insecurity was associated with higher odds of reporting heart disease (age- and sex-adjusted odds ratio¼2.65; 95% CI, 1.05-6.69) compared with household food security. Conclusions Food pantry use frequency differentiates diet quality, and household food security status differentiates chronic disease and related conditions among lowresource food pantry user subpopulations. J Acad Nutr Diet. 2019;119(10):1703-1712.

OOD PANTRIES PARTNER WITH THE EMERGENCY Food Assistance Program to distribute foods to lowincome households facing critical food shortages and represent the most frequently used grocery program offered as emergency food assistance.1 Use of emergency food assistance has increased in the last decade.2,3 In one study it was estimated that new clients with incomes below 185% of the poverty level tended to remain pantry users for 2 years.4 Many clients depend on food pantries regularly because they provide free food with little to no eligibility restrictions unlike government food and nutrition assistance programs.1,5 According to a survey conducted in 2017, only 54% of food pantry users in the United States had received Supplemental Nutrition Assistance Program (SNAP) benefits in the previous 30 days; only 10% of food pantry users received the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) benefits in the previous 30 days; and about 29% of food pantry users received free or reduced-price school lunches in the previous 30 days.6 Thus food pantries fill a gap in food access.

F

Food pantry users frequently experience food insecurity or limited access to enough food for an active and healthy life.7 Not all households that experience food insecurity access food pantries, but food pantry users tend to be food insecure. About 66% of households accessing food pantries in the United States in 2017 were food insecure.6 Individuals living in food-insecure households may experience reduced food intake and even disrupted eating patterns in addition to poor diet quality.7 The overall prevalence of household food insecurity in the United States has decreased since 2011 and was about 12% in 2017.7 However, the prevalence of household food insecurity in Indiana has increased steadily from 8% to 14% from 1996 to 2017 based on data collected in the nationally representative Current Population Survey of the US Census Bureau.7 Limited research has been devoted to evaluating the nutrition and health challenges faced by US food pantry users,8-14 perhaps because they tend to be transient and hard to reach. Mean fruit and vegetable intakes of US food pantry users have been reported to be below recommendations.9,11,13

ª 2019 by the Academy of Nutrition and Dietetics.

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1703

RESEARCH A low Healthy Eating Index-2005 (HEI-2005) total score of 43 was observed among female food pantry users (19 to 55 years of age) in eastern Alabama,9 which is 15 points below the average of the total US population (aged 2 years and older).15 In contrast, the diet quality provided by The Emergency Food Assistance Program foods16 and emergency food pantries17 was higher than the diet quality of the US population.15,18 Furthermore, a single food pantry visit was associated with increased dietary variety, number of eating occasions, and HEI-2010 component scores for Total Fruit and Whole Fruit among food-insecure rural US midwestern food pantry users in an observational cohort study.14 These findings highlight an interesting but uninvestigated question of whether the frequency of food pantry use as a source of access to potentially high-quality food is associated with improved diet quality. Having difficulty meeting nutritional needs may put food pantry users at risk for developing diet-related health problems.19 High body mass index (BMI; calculated as kg/m2) and high prevalence of obesity among food pantry users have been reported in several studies.9,11,13 Overweight and obesity have been associated with a substantial increase in the risk for hypertension, type 2 diabetes, and cardiovascular disease among US adults.20 Frequency of food pantry use may have an effect on BMI of food pantry users; in one study, investigators reported that pantry foods may contribute up to 25% of the diet of food pantry users in a convenience study sample.21 The proportion could be even higher for frequent users. Yet, previous studies have not examined the relationship between food pantry use and BMI. The prevalence of diabetes and hypertension among client households served by Feeding America (a hunger relief organization with a nationwide network of food banks) was 33% and 58% in 2014, much higher than the national estimates.1 The potential for the prevalence of chronic disease and related conditions among Indiana food pantry users is high, given the increasing trend of food insecurity and pervasive poor access to food.7 Food pantry use may play a critical role in client access to a higher-quality diet, and potentially, improved health; similarly, food insecurity, as an indicator of limited food access has a known relationship with lower-quality diet and health.22,23 Evaluation of both relationships in one sample will enhance the understanding of food access status and use of a food resource with diet and health. Thus the objective of this study was to determine how frequency of food pantry use and household food security status are associated with diet quality, BMI, and self-reported chronic disease and related conditions among Indiana food pantry users aged 21 to 80 years. The primary hypotheses are that greater frequency of food pantry use would be associated with higher diet quality, lower BMI, and lower odds of reporting chronic disease and related conditions compared with lower frequency of food pantry use. Also, household food insecurity would be associated with poorer diet quality, higher BMI, and higher odds of reporting chronic disease and related conditions compared with household food security.

METHODS This study had a cross-sectional design in which data on emergency food pantry use, household food security, diet quality, and chronic disease and related conditions of adult 1704

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

RESEARCH SNAPSHOT Research Question: Are frequency of food pantry use and household food security associated with diet quality, body mass index, and self-reported chronic disease and related conditions among Indiana food pantry users? Key Findings: In this cross-sectional study of 270 Indiana adult food pantry users, visiting food pantries more than once a month was associated with higher Healthy Eating Index-2010 total scores and Total Protein Foods component scores (both P0.05) than visiting less often. food pantry users were collected at food pantries in Indiana. Purdue University Institutional Review Board approved the study protocol (#1307013819), and all participants provided written consent before enrollment.

Participants To the authors’ knowledge, the association between food pantry use with diet quality and chronic disease and related conditions has not been examined previously; therefore, sample size of this study was based on the expected difference of measured BMI between household food security and insecurity in a previous study,24 in which a sample of 215 adults was sufficient to detect a statistically significant association. A sample size of 193 was also shown to be sufficient to detect a statistically significant association among food insecurity, potassium and fiber intake, and fruit consumption among low-income women (15 to 40 years old).25 A proportional allocation method was used to determine the number of participants to be sampled from food pantries representing the area of central Indiana. The 16 counties of this area, served by the Food Finders Food Bank, were grouped into four regions based on relative proximity. Food pantries’ contact information was obtained from the Food Finders Food Bank and the Indiana Emergency Food Resource Network.26 Sixty-three food pantries were contacted by phone, and representatives provided information on the location, size, client choice (pantry clients choosing for themselves what food they receive) or non-client choice (pantry clients receiving a pre-packed or standard bag of groceries), number of households served monthly, and willingness to participate. A 45-mile travel radius to the central county (Tippecanoe) excluded 36 pantries to yield 27 food pantries from eight counties as recruitment sites. The number of adult clients to be recruited in each pantry was determined in proportion to the regional population and estimated household food insecurity rate. A convenience sample of clients was recruited from June 2014 to December 2015, during which time researchers approached and recruited clients waiting in line to receive food. All clients were informed of the study, and those who wanted to participate were screened by a trained interviewer. Eligible participants were English speaking,  21 years of age, and receiving food from the pantry on the day of recruitment. A total of 293 adults were confirmed to be eligible, and 285 adults were enrolled in the study (eight decided not to participate); 270 participants for whom household food security status could be ascertained October 2019 Volume 119 Number 10

RESEARCH were included in the present analyses. Compensation for time spent to complete the surveys was $10.

Survey Instrument and Dietary Assessment Each participant was assisted by a trained research assistant to complete a standardized survey in a semi-private area inside the food pantry. The survey contained questions about sociodemographic characteristics, food assistance participation, food pantry use frequency, self-reported chronic disease and related conditions, and the 18-item US Household Food Security Survey Module.27 Sociodemographic characteristics included age, household size, number of children living in the household, sex, race/ethnicity, highest level of education, employment, household income-to-poverty ratio, and annual household income. Categories for sex were women and men. Categories for race/ethnicity were non-Hispanic white and other because of small cell sizes; other included non-Hispanic black, American Indian, Alaska Native, and Hispanic or Latino. Categories for highest level of education were high school or less and some college or higher. Categories for employment were employed or not employed. Categories for household income-to-poverty ratio were < 100% of the federal poverty level and 100% of the federal poverty level. Categories for annual household income were <$9,999, $10,000 to $29,999, and $30,000. SNAP participation (yes or no) was ascertained using this question: “Did you or anyone in your household receive SNAP benefits in the last 12 months?” Participation in SNAPEducation and WIC in the past 12 months was ascertained using similar questions and respectively categorized as yes or no. Frequency of food pantry use was determined by using the following question: “On average, how many times do you go to a food pantry, counting all food pantries you visit, per month?” Because food pantry guidelines generally allow one visit per month,2 the frequency of food pantry use was categorized as a dichotomous variable (more than once a month or once a month or less). The presence of self-reported chronic disease and related conditions was identified by affirmative answers to the question “Have you been told by a doctor that you have the following problem/s (high blood pressure, high cholesterol, heart disease, stroke, and prediabetes or diabetes)?” The 18-item US Household Food Security Survey Module27 was included as a section in the survey to quantify household food security over the past 12 months. Unanswered items were imputed using previously described methods recommended in the US Department of Agriculture (USDA) guide to measuring household food security.27 Raw scores based on affirmative responses were used to categorize participants into two groups: 1) household food security, with no problems or with anxiety related to obtaining food but few or no changes in diet; 2) household food insecurity, with reduction in diet quality and variety or with disrupted eating and reduced food intake as a result of inadequate resources.28 The use of an additional household food security classification such as marginal, low, and very low food security was not applied because of the small sample size and limited cell sizes for some dependent variables such as chronic disease and related conditions. After completion of the survey, an interviewer-assisted 24hour recall was administered at the food pantry by trained research staff using the Automated Self-Administered 24-Hour Recall version 2014 (ASA24-2014).29,30 The October 2019 Volume 119 Number 10

ASA24-201430 system automatically codes reported foods and performs nutrient analysis using the USDA Food and Nutrient Database for Dietary Studies 2011-201231 and the Food Patterns Equivalents Database 2011-2012.32,33 HEI-2010 total and component scores, developed by the National Cancer Institute and USDA as a metric to examine alignment with dietary guidelines, can be calculated as continuous scores, with higher scores indicating better diet quality and conformance with dietary recommendations.34-36 HEI-2010 scores can be calculated at the level of groups or individuals.34,36,37 For the analyses conducted in the present study, individual- or person-level scores were needed, and thus the SAS macro “ASA24-2014-Per Day-HEI-2010” from the National Cancer Institute37 was used to derive the HEI-2010 scores from the ASA24 recall using previously described methods.36 The HEI2010 total score is composed of nine adequacy component scores and three moderation component scores, which sum to a maximum total score of 100.34,36 The adequacy components (dietary components to emphasize) include the following: Total Fruit (score range, 0-5), Whole Fruit (score range, 0-5), Total Vegetables (score range, 0-5), Greens and Beans (score range, 0-5), Total Protein Foods (score range, 0-5), Seafood and Plant Proteins (score range, 0-5), Whole Grains (score range, 0-10), Dairy (score range, 0-10), Fatty Acids (score range, 0-10).34,36 The moderation components (dietary components to limit) include Refined Grains (score range, 0-10), Sodium (score range, 0-10), and Empty Calories (score range, 0-20).34,36 Because the 2010 USDA Food Patterns recommendations were calculated in amounts that vary according to energy level, the HEI-2010 scores use a density approach to set standards that are expressed as either a percentage of calories or per 1,000 calories; the one exception is Fatty Acids, which are expressed as a ratio of unsaturated fatty acids to saturated fatty acids.36,38 Density standards are useful because they are independent of an individual’s energy requirement.36,38 The standards for assigning maximum scores were the leastrestrictive (easiest to achieve) recommendations among those that vary by energy level, sex, and/or age.36

Anthropometrics Heavy outer clothing, shoes, pocket contents, any heavy accessories, hair ornaments, and hair buns or braids were removed before height and weight measurements were obtained. Height and weight measurement procedures followed the guidelines provided in the National Health and Nutrition Examination Survey Anthropometry Procedures Manual.39 Weight was measured in triplicate with a calibrated digital scale (Seca 869, Seca North America). Height was measured in triplicate with a stadiometer (Seca 213, Seca North America). The averaged values were used to calculate BMI. A categorical variable for BMI was created to classify participants as underweight/normal weight (BMI 24.9), overweight (25 to 29.9), and obese (30).39

Statistical Analyses Data were double entered using Microsoft Access40; any discrepancies were reconciled, and incongruent responses were verified by checking original surveys. Sociodemographic characteristics were compared by food pantry use and household food security groups using c2 tests for categorical variables and one-way analysis of variance models for JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1705

RESEARCH Table 1. Sociodemographic characteristics by household food security status and frequency of food pantry use among food pantry users in Indiana surveyed from June 2014 to December 2015a

Sociodemographic characteristics

Food insecurity (n[214)

Food security (n[56)

Sex, n (%) Male Female

Otherb

Some college or higher

Not employed

23 (41.1)

32 (31.4)

46 (34.9)

33 (58.9)

70 (68.6)

86 (65.2)

180 (84.1)

52 (92.9)

89 (87.3)

109 (82.6)

34 (15.9)

4 (7.1)

13 (12.8)

23 (17.4)

0.13

0.10

151 (70.6)

41 (73.2)

68 (66.7)

101 (76.5)

63 (29.4)

15 (26.8)

34 (33.3)

31 (23.5)

46 (21.5)

15 (26.8)

25 (24.5)

29 (22.0)

168 (78.5)

41 (73.2)

77 (75.5)

103 (78.0)

0.40

0.65

0.0004

<100% Federal poverty level

156 (73.9)

27 (49.1)

100% Federal poverty level

55 (26.1)

28 (50.9)

Annual household income, n (%) <$9,999

0.33

0.70

Household income-to-poverty ratio, n (%)

0.65 70 (70.7)

89 (67.9)

29 (29.3)

42 (32.1)

0.30

0.65

101 (47.6)

20 (37.0)

45 (44.6)

58 (44.3)

$10,000-$29,999

93 (43.9)

27 (50.0)

44 (43.6)

62 (47.3)

$30,000

18 (8.5)

7 (13.0)

12 (11.9)

11 (8.4)

Household SNAPc participation during the last 12 mo, n (%)

0.42

0.18

Yes

120 (56.1)

28 (50.0)

49 (48.0)

75 (56.8)

No

94 (43.9)

28 (50.0)

53 (52.0)

57 (43.2)

d

SNAP-Ed participation during the last 12 mo, n (%)

0.09

Yes

5 (2.5)

4 (7.6)

No

196 (97.5)

49 (92.5)

WICe participation during the last 12 mo, n (%)

P value 0.58

65 (30.4)

Employment, n (%) Employed

Food pantry use >1 time/mo (n[132)

149 (69.6)

Highest level of education, n (%) High school or less

Food pantry use £1 time/mo (n[102)

0.13

Race/ethnicity, n (%) Non-Hispanic white

P value

0.73 3 (3.2)

6 (4.9)

92 (96.8)

117 (95.1)

0.97

0.42

Yes

23 (14.9)

5 (15.2)

12 (13.0)

12 (17.7)

No

131 (85.1)

28 (84.9)

80 (87.0)

56 (82.4)

38 (18.1)

11 (19.6)

23 (23.0)

18 (13.7)

41 (19.5)

13 (23.2)

22 (22.0)

23 (17.6)

131 (62.4)

32 (57.1)

55 (55.0)

90 (68.7) (continued on next page)

BMIf category, n (%) Under/normal weight Overweight Obesity

1706

0.76

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

0.08

October 2019 Volume 119 Number 10

RESEARCH Table 1. Sociodemographic characteristics by household food security status and frequency of food pantry use among food pantry users in Indiana surveyed from June 2014 to December 2015a (continued)

Sociodemographic characteristics

Food insecurity (n[214)

Food security (n[56)

P value

Food pantry use £1 time/mo (n[102)

Food pantry use >1 time/mo (n[132)

P value

Age, y, meanSEMg

45.70.9

52.11.8

0.002

46.81.4

47.71.2

0.65

Household size, n, meanSEM

3.50.1

2.70.3

0.01

3.30.2

3.30.2

0.97

Children aged <18 y, n, meanSEMg

1.20.1

0.60.2

0.003

1.10.1

1.00.1

0.60

g

a Total numbers do not always add up to sample size because of missing values; percentages do not always add up to 100 because of rounding. c2 Analyses were conducted to determine differences between categorical variables. Fisher’s exact test was reported for all variables because of the small sample size in subgroups. One-way analysis of variance models were conducted to compare differences between continuous variables. Statistical significance level was set at P0.05. b Other includes non-Hispanic black (n¼28), American Indian or Alaska Native (n¼4), and Hispanic or Latino (n¼4). These responses were collapsed into one category because of the small sample size. c SNAP¼Supplemental Nutrition Assistance Program. d SNAP-Ed¼Supplemental Nutrition Assistance Program-Education. e WIC¼The Special Supplemental Nutrition Program for Women, Infants, and Children. f BMI¼body mass index (calculated as kg/m2). g SEM¼standard error of the mean.

continuous variables. Primary dependent variables were HEI-2010 scores (continuous variables), BMI (continuous variable), and chronic disease and related conditions (categorical variables). Multiple linear regression models were used to compare HEI-2010 total and component scores across food pantry use groups, with food pantry use frequency of once a month or less being the reference group. Models were adjusted for age, sex, highest level of education, household food security status, SNAP participation in the past 12 months, SNAP-Education participation in the past 12 months, and WIC participation in the past 12 months. Similarly, multiple linear regression models were used to compare HEI-2010 total and component scores across household food security groups, with household food security as the reference group and inclusion of the same covariates (except frequency of food pantry use, rather than household food security status, was a covariate). Besides age and sex, the covariates were selected based on previous literature that indicated factors such as food assistance participation, nutrition knowledge, and level of education may be associated with diet quality.41-43 Multiple linear regression models were also used to compare BMI across household food security groups and food pantry use groups, adjusted with the same covariates as described previously. Food assistance participation, nutrition knowledge, and level of education have also been associated with BMI.44-46 Adjusted leastsquares means were reported for household food security and food pantry use groups and interpreted in terms of BMI. The risk of reporting each chronic disease or condition was evaluated independently across household food security groups and food pantry use groups using logistic regression models. Self-reported prediabetes or diabetes, hypertension, high cholesterol, heart disease, and stroke were dichotomous variables (yes/no). Because disease cases were limited, odds ratios were adjusted only for age and sex and reported with 95% CIs. Data were investigated for normality and outliers and were not transformed before analyses. Model assumptions were checked by the plot of residuals against predicted outcomes, Q-Q plot, and histograms of residuals. Results were October 2019 Volume 119 Number 10

considered significant when P0.05. Statistical analyses were performed using SAS version 9.3 (SAS Institute Inc).47

RESULTS This study sample was 67% women, 86% non-Hispanic white, 71% with highest level of education at or below high school, 77% unemployed, 69% below 100% of the federal poverty level, and 45% with annual household income below $9,999; 53% of the participants used both food pantries and SNAP in the past 12 months, and 15% used WIC in the past 12 months (data not shown but based on data in Table 1). About 56% of participants in the sample visited food panties more than once a month, and the mean number of food pantry visits per month was 2.82.8. The household food insecurity prevalence was 79%, including 32% affected by low food security and 47% affected by very low food security. Clients living in food-insecure households were significantly younger and living in larger households with more children younger than 18 years, and they more frequently reported a household income-to-poverty ratio of below 100% of the federal poverty level (Table 1). Mean HEI-2010 total score was 42.312.3. Scores for a number of components—including Total Fruit, Whole Fruit, Greens and Beans, Seafood and Plant Proteins, and Whole Grains—were less than half of the maximum total. Clients who visited food pantries more than once a month had an HEI-2010 total score 5.2 points higher (P¼0.03) and a Total Protein Foods component score 0.4 point higher (P¼0.05) than those who visited pantries less often (Table 2). The prevalence of those with overweight and obesity were 20% and 61%, respectively. The mean BMI was 33.69.4. BMI was not significantly different between clients in food-secure (35.82.6) and food-insecure households (34.62.2; P¼0.50). BMI was also not significantly different between clients who visited food pantries more than once a month (36.32.3) and those who visited pantries less often (34.02.3; P¼0.11). Chronic disease and related conditions, such as hypertension and heart disease, were prevalent in this group (Table 3). Clients living in food-insecure households had significantly JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1707

RESEARCH higher odds of reporting heart disease compared with clients living in food-secure households (age- and sex-adjusted odds ratio¼2.65; 95% CI, 1.05- 6.69; P¼0.04, Table 3).

DISCUSSION This study is novel in that it brings together household food insecurity and food pantry use frequency to determine their association with diet quality, BMI, and self-reported chronic health status. In this study, visiting food pantries more than once a month was associated with higher scores for diet quality and Total Protein Foods than visiting less often. Household food insecurity was associated with higher odds of reporting heart disease than household food security. More than half of food pantry users in this study visited food pantries more than once a month, which may be a necessary strategy adopted by some users to maintain a household food supply and/or to allocate limited income elsewhere.1,11,13 Many food pantries suggest visiting no more than one time per month to provide equity in distribution to the populations they serve.2 More frequent visits may represent participant need surpassing this guideline.2 The higher total HEI score observed among frequent pantry visitors indicates a potentially positive impact of food pantry use. One explanation for the higher HEI score is that frequent visits to food pantries may provide a greater variety and amount of foods for users to choose from as they balance the options presented by free pantry foods and foods for purchase at other venues. A change in policy to allow greater access might be critical for users who frequently rely on food pantries as a necessary food source. The positive association with HEI score might also be related to higher resilience of frequent food pantry users compared with those not maximizing their use of this resource.48 It is possible that resilience potentially fosters initiative to combine resources from multiple food pantries or to reach out to friends and family to mitigate stressful situations. The trait of resilience has been linked to better diet quality,49 greater consumption of fruits and vegetables,50 more regular physical activity,50 and higher academic achievement.51 However, many households affected by food insecurity are severely impacted, and resilience may have a limited effect in the face of deep poverty, which may help explain the small difference in HEI-2010 total score in relation to food pantry use. The 5-point difference in HEI-2010 total score across food pantry use groups was small and may not be enough to boost food pantry users’ diet quality from grade F (0-59) to a higher grade (D, 60-69; C, 70-79; B, 80-89; A, 90-100),52 given the pervasively poor diet quality observed in this group. Food pantry users in this study had an average diet quality score of 42, which is substantially below the average score observed for US adults (mean HEI-2010 total score¼58, calculated using the same methods), whereas the overall diet quality among US adults was already low.18 Food pantry user households may constantly face trade-offs between paying for food and paying for other essentials.1,53,54 Financial constraints may limit household ability to prioritize the quality and variety of foods recommended in the Dietary Guidelines for Americans35 when obtaining enough food is an issue.55 A recent review suggests that this population does not consume enough fruit, vegetables, dairy, and meat/meat alternatives, with a large proportion not meeting the 1708

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

recommended intake of micronutrients, such as vitamins A, C, D, and B complex; magnesium; iron; zinc; and calcium.56 Mean fruit and vegetable consumption among US food pantry users has been reported to be below the recommendations.9,11 Similarly, evaluation of the 12 HEI component scores in this study suggests that food pantry users had less than the recommended intake of Total Fruit, Whole Fruit, Greens and Beans, Seafood and Plant Proteins, and Whole Grains. These findings indicate the importance of diet and health concerns among food pantry users, given that dietary factors are among the largest contributors to morbidity and mortality.19,35 Considering the prevalent household food insecurity among food pantry users and the potential for interventions to improve not only their health but also the health of the entire household, including children with nutritional demands for growth, interventions to improve dietary quality are urgently needed in this subpopulation. Food insecurity has been associated with negative dietary and health outcomes among US adults.22,23,57-60 However, this study did not reveal a significant association between food insecurity and diet quality. Given the high prevalence of food insecurity and poor diet quality in the sample, there may not be enough variation in food security and in diet quality for an association to be observed. Another explanation is that both food-secure and food-insecure pantry user households experienced dietary quality constraints, as reflected by the low HEI-2010 score in both groups. Food pantries are believed to only be used when access to food resources is limited3; however, 21% of the individuals in the sample were from food-secure households, meaning they reported no indications of compromises in dietary quality, variety, or desirability.7 Food-secure pantry users might be used to consuming lower-quality diets, despite self-reported household food security. The lack of significant association may also be related to the difference in assessment periods of household food security and dietary intake. Household food insecurity may be episodic and not necessarily occur consistently each month and thus may not closely reflect the diet quality at the time of the food pantry visit.7 In contrast, frequency of food pantry use reflects client visits on an average monthly basis, which is more consistently reoccurring and could be more predicative of recent diet quality. On average, US households who reported experiencing food insecurity at some time during 2017 were food insecure for 7 months.7 The frequent occurrence of food insecurity may have a significant impact on diet-sensitive chronic disease and related conditions. In this study, the mean BMI was 33.6; 20% of food pantry users were overweight and 61% were obese. The larger proportion of those with obesity compared with overweight in this study was similar to the findings reported by Duffy and colleagues9 and common among food pantry users despite the regional locations of previous samples.9,11,13 Compared with the general population of US adults, food pantry users in this study had a higher prevalence of obesity (61% vs 38% in 2013-2014),61 overweight and obesity (81% vs 71% in 2013-2014),61 hypertension (44% vs 34% in 2011-2014),62 high cholesterol (37% vs 12% in 20112014),62 and stroke (12% vs 3% in 2011-2014).62 The results of the present study show a significant association between household food insecurity and higher odds of self-reported heart disease among an extremely low-resource and highly food-insecure population. Although this result is based on October 2019 Volume 119 Number 10

RESEARCH Table 2. Associations among frequency of food pantry use, household food security status, and estimated mean Healthy Eating Index-2010 total and component scores among food pantry users in Indiana surveyed from June 2014 to December 2015 HEI-2010a scores (score range)

Household Food pantry use Food pantry Household use £1 time /mob P value food insecurityc food securityc P value >1 time /mob

HEI-2010 total scorea (0-100)

44.13.8

38.93.7

0.03

40.73.6

42.44.1

0.56

Total Fruit (0-5)

1.70.5

1.30.5

0.23

1.30.5

1.60.6

0.50

Whole Fruite (0-5)

1.60.6

1.10.6

0.15

1.30.6

1.40.6

0.84

Total Vegetables (0-5)

3.60.5

3.30.5

0.37

3.30.5

3.50.5

0.52

Greens and Beansf (0-5)

1.20.6

1.30.6

0.79

1.00.5

1.50.6

0.25

d

f

g

Total Protein Foods (0-5)

4.70.4

4.30.4

0.05

4.40.4

4.60.4

0.66

Seafood and Plant Proteinsg,h (0-5)

2.00.6

1.40.6

0.09

1.80.6

1.60.6

0.76

Whole Grains (0-10)

2.70.9

2.10.9

0.27

2.40.8

2.40.9

0.96

Dairyi (0-10)

6.00.9

5.90.9

0.88

6.60.8

5.41.0

0.09

Fatty Acidsj (0-10)

2.30.9

1.80.9

0.31

1.60.8

2.51.0

0.21

Refined Grains (0-10)

7.01.0

6.61.0

0.50

6.11.0

7.41.1

0.11

Sodium (0-10)

2.10.9

2.40.9

0.56

2.30.9

2.31.0

0.99

9.21.8

7.51.8

0.12

8.51.7

8.22.0

0.82

k

Empty Calories (0-20) a

HEI-2010, Healthy Eating Index-2010. Higher HEI-2010 scores indicate better diet quality. HEI-2010 total score is the sum of 12 component scores. Values are adjusted least-squares mean scorestandard error of the mean. Multiple linear regression models were used to determine the differences in Healthy Eating Index-2010 scores across food pantry use frequency groups, adjusted for age, sex, highest level of education, household food security status, and participation in Supplemental Nutrition Assistance Program (SNAP), Supplemental Nutrition Assistance Program-Education (SNAP-Ed), and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in the past 12 months, with food pantry use frequency of once a month or less as the reference group. Household food security status was categorized as household food security or household food insecurity. Highest level of education was categorized as high school or less or some college or higher. SNAP participation in the past 12 months was categorized as yes or no. SNAP-Ed participation in the past 12 months was categorized as yes or no. WIC participation in the past 12 months was categorized as yes or no. Food pantry use frequency was categorized as using food pantry more than once a month or once a month or less. Statistical significance level was set at P0.05. c Values are expressed as adjusted least-squares mean score  standard error of the mean. Multiple linear regression models were used to determine the differences in Healthy Eating Index2010 scores across household food security status, adjusted for age, sex, highest level of education, food pantry use frequency, and participation in SNAP, SNAP-Ed, and WIC in the past 12 months, with household food security as the reference group. Variables were coded as described in footnote b. Statistical significance level was set at P0.05. d Includes fruit juice. e Includes all forms except juice. f Includes any beans and peas not counted as Total Protein Foods. g Beans and peas are included here (and not with vegetables) when the Total Protein Foods standard is otherwise not met. h Includes seafood, nuts, seeds, and soy products (other than beverages), as well as beans and peas counted as Total Protein Foods. i Includes all milk products, such as fluid milk, yogurt, and cheese and fortified soy beverages. j Ratio of polyunsaturated fatty acids and monounsaturated fatty acids to saturated fatty acids. k Calories from solid fats, alcohol, and added sugars; threshold for counting alcohol is >13 g/1,000 kcal. b

findings from a cross-sectional study with a limited number of individuals with heart disease, it is consistent with findings from previous studies conducted in other subpopulations, which indicated that food insecurity is a risk factor for heart disease.63,64 Mixed findings were reported for hypertension and other chronic diseases despite the lack of significant associations with these diseases in this study.23,64 Future research should investigate these associations on a larger scale and include clinical indicators such as hemoglobin A1c, blood pressure, and blood lipid level to characterize these associations. Nutrition education has been shown to improve long-term food security among households with children,65 has been especially effective among participants using food pantries (Rivera R, Sun H, Zhang Y, Maulding MK, Eicher-Miller HA: unpublished data, 2019), and may be a potential intervention to implement at food pantries to help clients stretch food dollars in addition to choosing healthy foods. Yet, stretching food dollars can only go so far, and policies are needed to address the socioeconomic factors underlying poverty to October 2019 Volume 119 Number 10

ameliorate food insecurity. In future studies, investigators may consider examining whether diet quality is influenced by the healthfulness of the food environment at food pantries and the impact of individual choice despite the food environment. Future research may also be done to investigate whether linking clients with resources for jobs, federal food assistance, health care, disease management, and counseling would be helpful to improve knowledge, access, self-efficacy, and adherence to primary care recommendations. Besides supporting provision of healthy foods, allowing more frequent visits, and promoting client choice during distribution, food pantries may serve as potential sites for delivery of targeted interventions that contribute to effective behavior change and reduce disease risks. One limitation of the study is the cross-sectional study design; therefore the onset of chronic disease and conditions preceding food insecurity and food pantry use or vice versa cannot be determined. A second limitation is that HEI scores were determined for each individual based on one recall; the day-to-day variation in diet may be high among low-resource JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1709

RESEARCH Table 3. Age- and sex-adjusted odds ratios showing the associations among self-reported chronic disease and related conditions, household food security status, and frequency of food pantry use among food pantry users in Indiana surveyed from June 2014 to December 2015

Food security and food pantry use

Prediabetes or diabetes

High blood pressure

High cholesterol

Heart disease

Stroke

Prevalence, %

27

44

37

18

12

Food insecurity, n (%)

56 (26.2)

93 (43.5)

74 (34.6)

41 (19.2)

25 (11.7)

Food security, n (%)

17 (30.4)

25 (44.6)

25 (44.6)

7 (12.5)

6 (10.7)

Household food security statusa

Adjusted odds ratio 95% CI P value

0.92 0.46-1.83 0.81

1.38

0.95

0.71-2.71 0.34

0.49-1.85 0.88

2.65 1.05-6.69 0.04

1.25 0.47-3.34 0.66

Food pantry use frequencyb > 1 time/mo, n (%)

42 (31.8)

59 (44.7)

55 (41.7)

22 (16.7)

15 (11.4)

 1 time/mo, n (%)

23 (22.6)

48 (47.1)

34 (33.3)

19 (18.6)

12 (11.8)

Adjusted odds ratio 95% CI P value

1.77 0.95-3.30 0.07

0.86

1.47

0.49-1.52 0.60

0.82-2.64 0.20

0.87 0.43-1.78 0.71

0.89 0.39-2.04 0.78

a Multiple logistic regression models were used to compare the odds of each chronic disease or related conditions across household food security groups, with household food security being the reference group. Each chronic disease or related conditions was categorized as yes or no. Household food security status was categorized as household food security or household food insecurity. Models were adjusted for age and sex. Statistical significance level was set at P0.05. b Separate multiple logistic regression models were used to compare the odds of each chronic disease and related conditions across frequency of food pantry use, with food pantry use frequency of once a month or less being the reference group. Each chronic disease or related conditions was categorized as yes or no. Food pantry use frequency was categorized as using food pantry more than once a month or once a month or less. Models were adjusted for age and sex. Statistical significance level was set at P0.05.

populations, and the HEI scores may not reflect usual diet quality at the individual level. Another limitation was that very infrequent users of food pantries were grouped together with users who visited food pantries one time per month, despite potential differences among these groups. In addition, variables such as child care, transportation, and time that may affect individual’s ability to access a food pantry were not adjusted in the analyses because of the small sample size. Other limitations are that the number of reports for chronic disease and related conditions were limited and that their status was self-reported, which may represent underreporting for cases of undiagnosed disease. Despite these limitations, the results and parameters provide a reference for future studies investigating the relationship between emergency food pantry use, household food insecurity, diet quality, and chronic disease and condition.

2.

Lowe ET, Poubelle A, Thomas G, Batko S, Layton J. The US Conference of Mayors’ Report on Hunger and Homelessness: A Status Report on Homelessness and Hunger in America’s Cities, December 2016. Washington, DC: National Alliance to End Homelessness; February 2017.

3.

Riches G. Food banks and food security: Welfare reform, human rights and social policy. Lessons from Canada? Soc Policy Adm. 2002;36(6):648-663.

4.

Daponte BO, Lewis GH, Sanders S, Taylor L. Food pantry use among low-income households in Allegheny County, Pennsylvania. J Nutr Educ. 1998;30(1):50-57.

5.

Kaiser ML, Cafer A. Understanding high incidence of severe obesity and very low food security in food pantry clients: Implications for social work. Soc Work Public Health. 2018;33(2):125-139.

6.

Coleman-Jensen A, Rabbitt MP, Gregory CA, Singh A. Statistical Supplement to Household Food Security in the United States in 2017. Alexandria, VA: US Department of Agriculture, Economic Research Service; September 2018.

7.

Coleman-Jensen A, Rabbitt MP, Gregory CA, Singh A. Household Food Security in the United States in 2017. Alexandria, VA: US Department of Agriculture, Economic Research Service; September 2018.

CONCLUSIONS

8.

Bell M, Wilbur L, Smith C. Nutritional status of persons using a local emergency food system program in middle America. J Am Diet Assoc. 1998;98(9):1031-1033.

9.

Duffy P, Zizza C, Jacoby J, Tayie FA. Diet quality is low among female food pantry clients in eastern Alabama. J Nutr Educ. 2009;41(6):414419.

10.

Lenhart NM, Read MH. Demographic profile and nutrient intake assessment of individuals using emergency food programs. J Am Diet Assoc. 1989;89(9):1269-1272.

11.

Martin KS, Wu R, Wolff M, Colantonio AG, Grady J. A novel food pantry program food security, self-sufficiency, and diet-quality outcomes. Am J Prev Med. 2013;45(5):569-575.

12.

Miller C. Got milk? Food insecurity in a dairyland community. J Hunger Environ Nutr. 2011;6(3):343-352.

The results of the present study imply that accessing food pantries multiple times per month is associated with a better diet quality; however, the difference is small. Poor diet quality and high prevalence of chronic diseases and conditions among food pantry users inform a need for interventions to improve nutrition and health among this subpopulation.

References 1.

Weinfield NS, Mills G, Borger C, et al. Hunger in America 2014 National Report. Chicago, IL: Feeding America; August 2014.

1710

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

October 2019 Volume 119 Number 10

RESEARCH 13.

Robaina KA, Martin KS. Food insecurity, poor diet quality, and obesity among food pantry participants in Hartford, CT. J Nutr Educ. 2013;45(2):159-164.

35.

US Department of Agriculture and US Department of Health and Human Services. Dietary Guidelines for Americans, 2010. 7th ed. Washington, DC: US Government Printing Office; December 2010.

14.

Wright BN, Bailey RL, Craig BA, et al. Daily dietary intake patterns improve after visiting a food pantry among food-insecure rural midwestern adults. Nutrients. 2018;10(5):583.

36.

Guenther PM, Casavale KO, Reedy J, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113(4):569-580.

37.

15.

Center for Nutrition Policy and Promotion. Diet Quality of Lowincome and Higher Income Americans in 2003-04 as Measured by the Healthy Eating Index-2005. Alexandria, VA: US Department of Agriculture; December 2008.

National Cancer Institute Division of Cancer Control and Population Science Epidemiology and Genomics Research Program. ASA242014-Per Day-HEI-2010. https://epi.grants.cancer.gov/hei/sas-code. html. Published 2010. Accessed June 25, 2018.

38.

16.

Zimmerman T, Sun B, Hu J, Dixit-Joshi S, Eaker E. Nutrient and MyPyramid Analysis of USDA Foods in Five of Its Food and Nutrition Programs. Alexandria, VA: US Department of Agriculture, Food and Nutrition Service, Office of Research and Analysis; January 2012.

US Department of Agriculture Center for Nutrition Policy and Promotion. 2010 USDA Food Patterns. https://www.cnpp.usda.gov/ USDAFoodPatterns. Published September 2011. Accessed June 25, 2018.

39.

17.

Nanney MS, Grannon KY, Cureton C, et al. Application of the Healthy Eating Index-2010 to the hunger relief system. Public Health Nutr. 2016;19(16):2906-2914.

18.

Center for Nutrition Policy and Promotion. Healthy Eating Index reports: HEI-2010 total and component scores for children, adults, and older adults during 2011-2012. https://www.cnpp.usda.gov/ HealthyEatingIndex. Published November 2016. Accessed January 6, 2017.

Center for Disease Control and Prevention. National Health and Nutrition Examination Survey (NHANES) Anthropometry Procedures Manual. https://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/ BodyMeasures_09.pdf. Published January 2009. Accessed July 9, 2018.

40.

Microsoft Access (for Windows) [computer program]. Version 2013. Redmond, WA: Microsoft; 2013.

41.

Gregory CA, Ver Ploeg M, Andrews M, Coleman-Jensen A. Supplemental Nutrition Assistance Program (SNAP) Participation Leads to Modest Changes in Diet Quality, ERR-147. Alexandria, VA: US Department of Agriculture, Economic Research Service; April 2013.

42.

Geaney F, Fitzgerald S, Harrington J, Kelly C, Greiner B, Perry I. Nutrition knowledge, diet quality and hypertension in a working population. Prev Med Rep. 2015;2:105-113.

19.

US Department of Agriculture and US Department of Health and Human Services. 2015-2020 Dietary Guidelines for Americans. 8th ed. Washington, DC: US Government Printing Office; December 2015.

20.

NHLBI Expert Panel on the Identification Evaluation and Treatment of Overweight and Obesity in Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: The evidence report. Obes Res. 1998;6(suppl2):51S-209S.

43.

21.

Verpy H, Smith C, Reicks M. Attitudes and behaviors of food donors and perceived needs and wants of food shelf clients. J Nutr Educ Behav. 2003;35(1):6-15.

Hiza HA, Casavale KO, Guenther PM, Davis CA. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet. 2013;113(2):297-306.

44.

Hanson KL, Connor LM. Food insecurity and dietary quality in US adults and children: A systematic review. Am J Clin Nutr. 2014;100(2):684-692. Seligman HK, Laraia BA, Kushel MB. Food insecurity is associated with chronic disease among low-income NHANES participants. J Nutr. 2010;140(2):304-310.

Nguyen BT, Shuval K, Bertmann F, Yaroch AL. The Supplemental Nutrition Assistance Program, food insecurity, dietary quality, and obesity among US adults. Am J Public Health. 2015;105(7):14531459.

45.

Silveira JA, Taddei JA, Guerra PH, Nobre MR. The effect of participation in school-based nutrition education interventions on body mass index: A meta-analysis of randomized controlled community trials. Prev Med. 2013;56(3-4):237-243.

46.

Hermann S, Rohrmann S, Linseisen J, et al. The association of education with body mass index and waist circumference in the EPICPANACEA study. BMC Public Health. 2011;11:169.

47.

SAS [computer program]. Version 9.3. Cary, NC: SAS Institute Inc; 2011.

48.

Nikolaus CJ, Schierer M, Ellison B, Eicher-Miller HA, Gundersen C, Nickols-Richardson SM. Grit is associated with food security among US parents and adolescents. Am J Health Behav. 2019;43(1):207-218.

49.

Lutz LJ, Gaffney-Stomberg E, Williams KW, et al. Adherence to the Dietary Guidelines for Americans is associated with psychological resilience in young adults: A cross-sectional study. J Acad Nutr Diet. 2017;117(3):396-403.

50.

Perna L, Mielck A, Lacruz ME, et al. Socioeconomic position, resilience, and health behaviour among elderly people. Int J Public Health. 2012;57(2):341-349.

51.

Duckworth AL, Quinn PD. Development and validation of the Short Grit Scale (GRITeS). J Pers Assess. 2009;91(2):166-174.

52.

Krebs-Smith SM, Pannucci TE, Subar AF, et al. Update of the healthy eating index: HEI-2015. J Acad Nutr Diet. 2018;118(9):1591-1602.

53.

Bhattacharya J, DeLeire T, Haider S, Currie J. Heat or eat? Coldweather shocks and nutrition in poor American families. Am J Public Health. 2003;93(7):1149-1154.

22.

23.

24.

Jilcott SB, Wall-Bassett ED, Burke SC, Moore JB. Associations between food insecurity, supplemental nutrition assistance program (SNAP) benefits, and body mass index among adult females. J Am Diet Assoc. 2011;111(11):1741-1745.

25.

Kendall A, Olson CM, Frongillo EA Jr. Relationship of hunger and food insecurity to food availability and consumption. J Am Diet Assoc. 1996;96(10):1019-1024.

26.

27.

28.

29.

Purdue University Extension Indiana Emergency Resource Network. Emergency food providers in Indiana. https://www.purdue.edu/ indianasefrnetwork/Home/Directory. Published 2014. Accessed March 9, 2014. Bickel G, Nord M, Price C, Hamilton W, Cook J. Guide to Measuring Household Food Security, revised 2000. Alexandria, VA: US Department of Agriculture, Food and Nutrition Service; March 2000. Bickel G, Nord M, Hamilton W. United States Household Food Security Survey Module: Three-stage Design with Screeners. Alexandria, VA: US Department of Agriculture, Economic Research Service; September 2006. Subar AF, Kirkpatrick SI, Mittl B, et al. The Automated SelfAdministered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the National Cancer Institute. J Acad Nutr Diet. 2012;112(8):1134-1137.

30.

Automated Self-Administered 24-Hour Recall [computer program]. Version 2014. Bethesda, MD: National Cancer Institute; 2014.

54.

31.

US Department of Agriculture Food and Nutrient Database for Dietary Studies. Version 2011-2012. Beltsville, MD: US Department of Agriculture, Agricultural Research Service; 2014.

Essien UR, Shahid NN, Berkowitz SA. Food insecurity and diabetes in developed societies. Curr Diab Rep. 2016;16(9):79.

55.

US Department of Agriculture Food Patterns Equivalents Database. Version 2011-2012. Beltsville, MD: US Department of Agriculture, Agricultural Research Service; 2014.

Ford JD, Lardeau M-P, Blackett H, Chatwood S, Kurszewski D. Community food program use in Inuvik, Northwest territories. BMC Public Health. 2013;13(1):970.

56.

Raper N, Perloff BP, Ingwersen LA, Steinfeldt L, Anand J. An overview of USDA’s dietary intake data system. J Food Compost Anal. 2004;17(3-4):545-555.

Simmet A, Depa J, Tinnemann P, Stroebele-Benschop N. The dietary quality of food pantry users: A systematic review of existing literature. J Acad Nutr Diet. 2016;117(4):563-576.

57.

Seligman HK, Bindman AB, Vittinghoff E, Kanaya AM, Kushel MB. Food insecurity is associated with diabetes mellitus: Results from the National Health Examination and Nutrition Examination Survey (NHANES) 1999-2002. J Gen Intern Med. 2007;22(7):10181023.

32.

33.

34.

Guenther PM, Kirkpatrick SI, Reedy J, et al. The Healthy Eating Index2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans. J Nutr. 2014;144(3):399-407.

October 2019 Volume 119 Number 10

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

1711

RESEARCH 58.

Seligman HK, Jacobs EA, Lopez A, Tschann J, Fernandez A. Food insecurity and glycemic control among low-income patients with type 2 diabetes. Diabetes Care. 2012;35(2):233-238.

62.

Benjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and stroke statistics-2017 update: A report from the American Heart Association. Circulation. 2017;135(10):e146-e603.

59.

Gucciardi E, Vahabi M, Norris N, Del Monte JP, Farnum C. The intersection between food insecurity and diabetes: A review. Curr Nutr Rep. 2014;3(4):324-332.

63.

Stuff JE, Casey PH, Connell CL, et al. Household food insecurity and obesity, chronic disease, and chronic disease risk factors. J Hunger Environ Nutr. 2007;1(2):43-62.

60.

Feng Z, Smith TM, Colon-Ramos U, Pinard CA, Yaroch AL. Household food insecurity as a determinant of overweight and obesity among low-income Hispanic subgroups: Data from the 2011-2012 California Health Interview. Survey. Appetite. 2016;97:37-42.

64.

Vozoris NT, Tarasuk VS. Household food insufficiency is associated with poorer health. J Nutr. 2003;133(1):120-126.

65.

Rivera RL, Maulding MK, Abbott AR, Craig BA, Eicher-Miller HA. SNAP-Ed (Supplemental Nutrition Assistance Program-Education) increases long-term food security among Indiana households with children in a randomized controlled study. J Nutr. 2016;146(11): 2375-2382.

61.

National Center for Health Statistics. Health, United States. 2016: With chartbook on long-term trends in health. https://www.cdc.gov/nchs/ data/hus/hus16.pdf. Published May 2017. Accessed June 30, 2018.

AUTHOR INFORMATION Y. Liu is a clinical assistant professor, Department of Community Health and Health Behavior, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY. Y. Zhang is a statistical consultant, Department of Statistics and H. A. Eicher-Miller is an associate professor, Department of Nutrition Science, Purdue University, West Lafayette, IN. D. T. Remley is an associate professor and field specialist, Food, Nutrition, Wellness, College of Food, Agricultural, and Environmental Sciences, Ohio State University Extension, Piketon. Address correspondence to: Heather A. Eicher-Miller, PhD, Department of Nutrition Science, Purdue University, 700 W State St, West Lafayette, IN 47907-2059. E-mail: [email protected]

STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.

FUNDING/SUPPORT This project is supported by the Agriculture and Food Research Initiative competitive grant no. 2013–6900420401 of the USDA National Institute of Food and Agriculture and the USDA National Institute of Food and Agriculture, Hatch project IND030489.

AUTHOR CONTRIBUTIONS Y. Liu led the literature review and synthesis, analyzed the data, and wrote the initial article. All authors reviewed and commented on subsequent drafts of the manuscript. D. T. Remley contributed to data interpretation and critical revision. Y. Zhang assisted with statistical analysis and critical revision. H. A. Eicher-Miller supervised, guided, and participated in all aspects of this study, including project design, data collection, data analysis, and writing and editing.

1712

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

October 2019 Volume 119 Number 10