Supplemental Nutrition Assistance Program (SNAP) Analysis

08 Aug 2017 15 Sep 2017

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Food expenditures patterns of households participating in the Supplemental Nutrition Assistance Program: Analysis of grocery receipts

Sanjeevi N, Freeland-Graves JH, Kaang P, Sands J 

Abstract

Background The Supplemental Nutrition Assistance Program (SNAP) increases the food purchasing power of its clients by distribution of monthly benefits. The goal of this study was to determine compliance of food purchasing patterns of SNAP participants to recommendations.

Design A total of 160 women receiving SNAP benefits participated in the study. They were instructed to save grocery receipts for one month. At visit 2, grocery receipts were collected, a demographics questionnaire was administered, and participants were measured for height and weight. Foods listed on the grocery receipts were divided into 29 categories. The household percentage expenditure on each food category was calculated and compared to the Thrifty Food Plan (TFP) 2015 recommendation. A sign test with a Bonferroni-Holm correction was utilized to determine differences between actual and recommended expenditures for 29 food categories. Regression analyses was conducted to determine the relationship between compliance of the monthly grocery expenditure to the TFP recommended total cost and amount spent on 29 food categories.

Results Food categories that were significantly greater than the TFP recommendations included refined grains; red meat; frozen entrees; and soft drinks, fruits drinks and ades. Those that were significantly lower were dark green vegetables, whole grain breads, rice and pasta, orange vegetables, and ready-to-serve and condensed soups. A greater amount spent on monthly groceries relative to the TFP recommended total cost was significantly associated with higher compliance of spending on low fat dairy, vegetables, whole grains and fruits to the recommendations.

Conclusions Food purchasing choices of this sample of SNAP participants did not meet TFP recommendations. Thus, it is vital to provide nutrition education to SNAP participants so that they can achieve a low-cost, healthy diet. Furthermore, monthly grocery expenditures lower than the TFP recommended total cost adversely affected the amounts spent on low fat dairy, whole grains, fruits and vegetables. Future research could focus on psychosocial factors associated with inadequate grocery spending among SNAP participants.

Introduction

Food insecurity is a public health problem among low-income populations in the United States (U.S.) [1,2]. A number of nutrition assistance programs have been created to combat this problem [3]. Of these, the Supplemental Nutrition Assistance Program (SNAP) (previously Food Stamps) is the largest in the U.S [4,5]. It aims to strengthen food purchasing power by distribution of monthly benefits [6]. These benefits enable an individual to buy most foods and beverages, with the exception of alcohol, tobacco, dietary supplements, and hot or prepared foods [7]. In 2015, nearly $69.7 billion was distributed as SNAP benefits to 45.8 million individuals [8]. The best possible and most effective use of these benefits is essential, so that SNAP participants can achieve low-cost, healthy diets.

Food purchasing behavior is an important determinant of diets in low-income population, as 72% of the energy intake is accounted for by foods consumed at-home [9]. Household food inventories [10-16], scanner data [17-20] and grocery receipts [21-28] are methods used to assess food expenditures of households. Of these, grocery receipts are considered to provide a detailed representation of household food purchases over a multi-week time period [29]. The combination of receipt data with household characteristics identifies families that may be at the highest risk for making choices of lower quality foods [23]. In a sample of 50 families, DeWalt et al. found that spending patterns across food categories were related to the number of meals eaten away from home [25]. Other studies that utilized grocery receipt data reported that spending patterns were associated with ethnicity [26], income [27], and perceived body size [28]. Food expenses obtained from other sources, such as the Family Food Expenditure Survey, also have been related to educational level [30], household composition [30] and income [30,31].

Food plans developed by the United States Department of Agriculture's (USDA) suggest recommended amounts to be spent on groceries in order to help low-income families achieve a nutritious diet [32]. These include the thrifty-, low-cost, moderate-cost and liberal-cost plans. This paper focuses on the thrifty food plan (TFP) which provides guidance on food spending for households that are at or below 130% of the Federal Poverty Level. The objective of this study was to discern monthly food expenditure patterns of SNAP clients by analysis of grocery receipts, and to compare these to the TFP recommendations. Although the TFP offers low-cost food choices, SNAP households may not spend the recommended amount for total groceries [33]. Subsequently, this disparity may affect the purchasing patterns of certain food categories. A secondary goal of this study was to determine the influence of the amount spent on total groceries on expenditure patterns of food groups.

Methods

Design

A sample of 160 women successfully completed the study. On the first encounter, women were instructed to save household grocery receipts for one month. At a second visit, receipts for the 1-month period were collected, and participants were administered a demographics questionnaire and measured for height and weight.

ParticipantsEnrollment criteria were: participation in the SNAP program, ages 18-50 years old, and Hispanic, non-Hispanic White or African-American ethnicity. Since women were the primary grocery shoppers in this population, male SNAP participants were not recruited. Pregnant or lactating women and women with any serious illness were excluded. A total of 217 women who met the criteria were recruited from low-income residential housing and neighborhood centers in Central Texas from January-December 2015. Of the 217 women recruited, 166 completed the study. Six participants were excluded due to insufficient grocery receipt data; thereby resulting in a final sample of 160. This study was granted an exempt status by the Institutional Review Board at The University of Texas at Austin, based on 45 46.101 (b)(2) Code of Federal Regulations. Participation in the study was voluntary and informed consent was obtained from participants. The receipts and demographics questionnaire were numbered sequentially.

Demographic Questionnaire

A modified demographics questionnaire, developed by the author [34], was used to record information regarding ethnicity, age, education, amount of monthly SNAP benefits, income, household size, and age of each household member.

Anthropometrics

Height was measured with a stadiometer (Health O Meter, McCook, Illinois) and weight was determined using a digital weighing scale (Health O Meter, McCook, Illinois). Weight (kilograms) / height (meters) 2was used to calculate BMI.

Thrifty Food Plan (TFP) 2015

The TFP is the basis of the amount of SNAP benefits that are needed to achieve a healthy diet at a minimal cost32. The cost of the TFP is based primarily on raw ingredients over convenience foods, and assumes that all meals are prepared at home. The 2015 plan provides the percentage expenditure that should be spent on 29 food categories for 15 age-gender groups. These recommendations were determined from a weighted average of the percentage expenditure of food categories for each of the age-gender classifications, in which average was weighted, according to the number of household members in each age-gender cohort. The total monthly recommended cost for groceries also was calculated by summation of the indicated costs on 29 food categories (Personal Communication, Lino M).

Food Receipts

Participants were asked to collect all grocery receipts for one month, as SNAP clients receive their program benefits once a month. Moreover, distribution of benefits once every month has been associated to a trend of decreased grocery expenditures towards the end of the month [35-37]. Thus, a 1-month time period would be inclusive of these changes in expenditures. The amounts related to SNAP benefits for one month were recorded from the receipts, and compared to the benefit amount specified in the demographic questionnaire. If the total expenditure obtained from the receipts was less than 90% of the benefit amount denoted in the demographics questionnaire, the receipts of the respective participant were excluded from analysis. By this criterion six participants were excluded, decreasing the sample size to 160. A cut-off of 90% of the total amount of benefits received from SNAP, as indicated in the demographics survey, was utilized since program benefits are sometimes carried over to the next month. Consequently, some individuals may not spend their entire benefits within one month. By this method, the average SNAP-related expenditure for the sample of 160 women was 100.5% of the monthly benefit amount specified in the demographics.

Each food item in the receipts was classified into one of the 29 TFP food categories, with the percentage amount spent determined. Food items with indistinct description on receipts were clarified by consulting with the listed retailer. Four TFP food categories were expanded for a more detailed analysis of expenditure patterns, including 1) refined grains; 2) whole milk, yogurt and cream; 3) potato and potato products; and 4) soft drinks, sodas, fruit drinks and ades. For example, refined grains was divided further into refined grains bread, rice and pasta; sweet snacks; salty snacks; and cereals.

Statistical Analysis

Descriptive statistics were used for all demographic characteristics. A sign test with a Bonferroni-Holm correction was conducted to determine differences between actual household food expenditures and recommendations for the 29 TFP food categories. This method was chosen over the traditional Bonferroni correction, in order to retain greater statistical power [38]. A simple linear regression was used to determine the association between demographic variables, such as household size, number of children and socio-economic status indicator, and compliance of total grocery expenditure to TFP recommended cost. Univariate linear regression analyses were conducted using the difference between the total grocery expenditure and TFP recommended cost as the independent variable. The difference between the amount spent on each food category and its respective TFP recommendation was used as the dependent variable. The standardized β coefficient, and adjusted R2 are reported, with p<0.05 used for significance. All the analyses were performed using the Statistical Package for the Social Sciences (SPSS 22, Armonk, NY, 2013) [39].

Results

Demographics

The age of participants ranged from 19-50 years, and the median household size was three. The household income was adjusted for family size by dividing it by the Census Bureau-based poverty threshold, as described by Duncan et al., in order to obtain an optimal socioeconomic status indicator [40]. The mean value of this indicator was 0.68. The proportion of participants who were classified as overweight/obese (BMI≥25 kg/m2) was 71.3%. The overwhelming majority of the total sample was Hispanic (71%). About 38% of the participants had a partial college degree, and 62% had an educational level less than partial college.

Food purchasing patterns and TFP recommendations

Figure 1 shows a comparison of recommendations of the TFP for 29 food categories with monthly percentage food expenditures of SNAP households. Significant differences between actual expenditure and TFP recommendation were found for numerous food categories, with the exception of other vegetables, gravies and condiments, fats, and coffee and tea. Food categories and the percentage by which the actual expenditures exceeded recommendations were: refined grains (48.3%); red meat (46.6%); frozen entrees (98.9%); soft drinks, fruits drinks and ades (99.0%); bacon, sausage and lunch meats (94.7%); sugar, sweets and candies (97.3%); cheese (87.9%); milk drinks and desserts (98.2%); whole milk, yogurt and cream (58.1%); eggs (70.2%); and dry soups (87.9%). Categories in which the expenditures were significantly lower than recommendations were whole grain breads, rice and pasta (92.4%); whole grain cereals (41.8%); potatoes and potato products (29.9%); dark green vegetables (87.7%); orange vegetables (81.2%); whole grain snacks (36.2%); legumes (85.4%); whole fruits (35.8%); fruit juices (58.4%); low fat dairy (73.2%); seafood (26.7%); poultry (20.1%); nuts and nut butters (66.2%); and ready-to-serve and condensed soups (87.2%). Food categories for which the percent expenditure did not significantly differ from recommendations were: other vegetables, gravies and condiments, fats, and coffee and tea. Refined grains, red meat, whole fruits and other vegetables represented the highest proportions of expenditure; whereas, food categories with the lowest percentage expenditures were soups (ready-to-serve and condensed), soups (dry), orange vegetables, and whole grain breads, rice and pasta. The monthly amount of purchase was highest for refined grains ($45.53), followed by red meat ($32.35).

Figure 2 illustrates that bread, rice, and pasta and sweet snacks collectively were 75% of the total expenditure within refined grains. A breakdown of potato and potato products showed that expenditure on potato chips and products ($3.81) was more than three times that of potatoes ($1.58). Whole milk ($3.31) and cream ($2.91), such as sour cream, cream substitutes and dips accounted for a greater share than full fat yogurt ($0.68). Finally, the purchase amount of soft drinks ($8.14) was the highest within the soft drinks, fruit drinks, and ades category.

Adherence of monthly grocery expenditure to TFP recommended cost

Table 2 indicates the average monthly grocery expenditure, the monthly TFP recommended total cost, and the amount of spending accounted by SNAP benefits. The monthly grocery expenditure, $309, was lower than the mean TFP market basket calculated for the participating households ($476) (p<0.001). Household size (β= -0.789, p<0.001) and number of children (β= -0.635, p<0.001) were negatively associated with compliance of monthly grocery expenditure to the TFP recommended cost; no significant relationship was observed for household size-adjusted family income.

Table 3 shows the relationship between total grocery expenditure and food category spending relative to Thrifty Food Plan recommendations among Supplemental Nutrition Assistance Program participants using univariate regression analyses.A greater amount spent on monthly groceries relative to the TFP cost was significantly associated with an increased adherence to recommendations for majority (20 of the 29) of the food categories. Moreover, a standardized β coefficient of greater than 0.6 was observed for low fat dairy, legumes, dark green vegetables, whole grain breads, rice and pasta, orange vegetables, fruits, other vegetables, and potato and potato products. The amount spent on monthly groceries did not significantly influence the compliance of the following food categories to TFP recommendations: cheese, frozen entrees, sugars, sweets and candies, milk drinks and milk desserts, soups (dry), bacon, sausage and lunchmeat, soft drinks, sodas, fruit drinks and ades, whole milk, yogurt and cream, and coffee and tea.

Discussion

These results show that food spending patterns of SNAP participants did not meet the majority of the recommendations of the TFP. Thus, this population did not make the best possible food choices, and may consume diets that lack optimal nutritional quality. Of particular concern is that soft drinks, sodas, fruit drinks and ades represented 5.7% of the total market basket expenditure. The amount spent on this category is similar to that obtained by Andreyeva et al. who utilized grocery scanner data from a supermarket chain to assess beverage purchases of households [41]. Expenditures comparable to ours were observed for soft drinks (2.6% vs 2.7%), fruit drinks (1.4% vs 1.5%) and energy drinks (0.3% vs 0.2%) [41], respectively. However, their reported spending was slightly lower for 100% fruit juices (1.2% vs 2.2%) and diet beverages (0.07% vs 0.9%), but higher for sports drinks (0.9% vs 0.4%), respectively. Moreover, spending on soft drinks, sodas, fruit drinks and ades was comparable to that reported by Garasky et al. using point-of-sale transaction data from 2011 [42].

The total of refined grains and red meat combined represented one-quarter of the monthly household expenditure share on grocery purchases. The percentage expenditure on these two food categories were double the TFP recommendations. It is noteworthy that the percentage amount spent on the food category, other vegetables, was similar to that of the TFP recommendation. This congruence might be attributed to the high percentage of a Hispanic population in our sample, as the amount spent on vegetables is greater among Hispanics when compared to Non-Hispanic Whites and African Americans [26].

The mean SNAP benefits ($243) in our study represented 79% of total household food expenditure, indicating these benefits are a critical resource for food supply in this low-income population. The monthly benefit amount and total grocery expenditure were lower than the TFP recommended market basket cost by approximately 49% and 35%, respectively. Moreover, total grocery expenditures lower than the TFP allotted amount were reported for 84% of the households. However, the TFP assumes that SNAP clients prepare all their meals from scratch using raw ingredients. In contrast, the average meal preparation time in the US has been shown to be less than that indicated by the TFP model [43]. Thus, families with lower grocery expenditures could be relying on food away from home due to lack of time or other resources. The share of groceries accounted by frozen entrees (5.9%) in the present study suggests a limited use of convenience foods in this population. This study also found that the number of children negatively affected the compliance of monthly grocery spending to the TFP recommended cost. The presence of children could influence eating patterns of the household, such as greater consumption of food away from home, thereby explaining the observed lower grocery expenditure.

A higher expenditure for total monthly groceries was associated with greater adherence to the recommended spending of several nutrient-dense food groups, including low fat dairy, vegetables, whole grain breads and fruits. But, the average amounts spent on these food groups did not meet the TFP recommendations. The limited purchasing of these nutrient-dense food categories in SNAP households should be addressed in nutrition education efforts, especially in families that spend substantially lower than recommended amounts for groceries.

Snacks that are high in sugar and fat accounted for about 52% of the refined grain-based purchases. Thus, it would be helpful for the TFP to define sub-groups within the refined grains category, and provide recommended expenditures for these groups. Finally, adherence of the monthly grocery expenditure to the TFP market basket cost did not change the amount spent on other major food groups that were greater than the recommendations, including frozen entrees, sugar, sweets and candies, bacon, sausage and lunchmeat, and soft drinks, fruit drinks, sodas and ades.

The use of grocery receipts has an advantage as an unbiased indicator of nutrition behavior since it excludes errors that may occur with self-report. However, a limitation is that the type of foods purchased may vary widely from one shopping trip to another, and receipt data from a single shopping occasion may not represent consistent food purchasing behaviors of an individual. Thus, collection of grocery receipts for one month as done in this study reduces bias that could arise from a one-time assessment of food purchasing patterns. The matching of benefits received versus the total benefit amount on the receipts validates the completeness of the receipts for the 1-month time period. Similar validation criterion could not be adopted for expenditure data that was not accounted by SNAP benefits, such as cash.

In the present study, interpretation of grocery receipts in this study was based solely on expenditure data. Spending patterns at the household level may not necessarily reflect an individual's total dietary intake. Sekula et al. reported good agreement between data obtained from budget survey and consumption of potatoes, vegetables, meat, poultry, and animal fats; whereas, comparisons with other food groups were less [44]. Moreover, some food items represented in the receipts may not be consumed by the participant or other household members. Another limitation is that the cost of individual diets was not assessed which would be useful to determine diet expenditure and disease associations [45]. Finally, ambiguity may arise due to classification of different foods into specific food categories. For example, foods such as frozen pizza, frozen lasagna and frozen pot pie were classified jointly under one food category, frozen entrees. But the utilization of food categories helped define expenditure patterns due to the large number of foods present in grocery receipts.

This study focused on foods that are consumed primarily at home, and does not consider for foods purchased from restaurants and fast food establishments. Also foods might be obtained from sources that do not provide receipts, such as friends and family. Any changes in habitual shopping behaviors during the data collection period are also potential for bias. Finally, this research utilizes a relatively small sample size when compared to the participation of SNAP at a national level.

Conclusions

These results have important policy implications that emphasize the critical need to enhance the food purchasing behaviors of at-risk SNAP families. Comparison of food spending across several food categories specified those that were a predominant expenditure share of the TFP market basket. This study also implies that SNAP households may spend more on low fat dairy, vegetables, whole grains and fruits with increases in food purchasing power. Future research could focus on psychosocial factors associated with inadequate grocery spending. An understanding of factors involved in food selection decisions may help health professionals better design interventions that target SNAP participants.



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