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Wilde, P. E. 2007. Measuring the effect of food stamps on food insecurity and hunger: Research and policy considerations. Journal of Nutrition 137(2):307-310.

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3 Food Security and Access to a Healthy Diet in Low-Income Populations To set the stage for its examination of evidence to support the feasibil- ity of defining the adequacy of Supplemental Nutrition Assistance Program (SNAP) allotments, the committee first reviewed evidence on relationships between participation in SNAP and the potential for participants to reach the goals of improved food security and access to a healthy diet. This evidence on program outcomes underpins the committee’s examination of individual, household, environmental, and program-related factors that serve as com- ponents of a science-driven definition of the adequacy of SNAP allotments. The chapter first examines trends in food production, availability, and con- sumption at the population level. Although food availability data do not account for spoilage and other losses and do not provide a direct measure of consumption, they do serve as an indicator of food consumption trends over time. Next, the chapter examines food purchasing patterns and dietary intake among low-income households and SNAP participants. The chapter then describes evidence on access to a healthy diet and food insecurity among low-income SNAP-eligible as well as SNAP-participating households, includ- ing evidence on the impact of SNAP benefits. Next is a discussion of the data and analytical challenges faced in assessing the adequacy of SNAP allotments. The final section presents a summary of findings and conclusions. FOOD PRODUCTION, AVAILABILITY, AND CONSUMPTION AT THE POPULATION LEVEL Changes in food production over the course of the last century have led to an increase in total calories available per capita, as well as a change in 57

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58 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM FIGURE 3-1  Per capita total grain availability, 1970-2005. Figure 3-1.eps NOTE: Data for 2005 based on a 2,000-calorie diet. SOURCE: Wells and Buzby, 2008. USDA, ERS Food Availability (per capita) Data bitmap System. 3,000 2,500 2,000 Average Daily Calories Meat, eggs, and nuts Dairy 1,500 Fruit Vegetables Flour and cereal products 1,000 Added fats and oils and dairy fats Caloric sweeteners Total 500 0 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 Year FIGURE 3-2  Increase in average daily per capita energy (calorie) availability in the United States between 1970 and 2009. Figure 3-2.eps SOURCE: Data from ERS, 2012. ERS Food Availability (per capita) Data System, adjusted for spoilage and other waste.

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 59 the composition of foods available. In particular, over the past four ­ ecades, d production and availability have increased for grains more than for other types of foods. Grains of all types—including wheat, corn, rice, and oats— have become more readily available in the food supply. Total grain avail- ability per person increased from 137 pounds in 1970 to 192 pounds in 2005 (Wells and Buzby, 2008; see Figure 3-1). According to a 2008 U.S. Department of Agriculture (USDA) report on the major trends in food availability,1 not only did the availability of grains increase by 41 percent from 1970 to 2005, but the availability of all major food groups increased as well—fruits and vegetables (by 19 percent); meat, eggs, and nuts (8 percent); and milk/dairy products (6 percent). In addition, availability increased for fats and oils (62 percent) and added sugars and sweeteners (19 percent) (Wells and Buzby, 2008). As a result of increased production of grains and other foods, per capita total energy availability has risen substantially during the last 30 years—from 2,169 to 2,594 calo- ries between 1970 and 2009 (Figure 3-2), with the largest proportion of the increase coming from fats and processed grain products (ERS, 2012). On the other hand, per capita availability of vegetables, fruits, and dairy products currently is less than 70 percent of the recommended amounts (Figure 3-3). These aggregate production numbers may simply reflect Americans’ consumption preferences and choices. If so, then if the U.S. population were to make healthier choices, that change might be reflected in the aggregate production numbers. Alternatively, people may eat what is available. In this case, if the overall availability of different types of foods is inconsistent with current dietary recommendations—as the evidence suggests—individuals are unlikely to be able to meet the recommendations. FOOD PURCHASING PATTERNS AND DIETARY INTAKE AMONG LOW-INCOME HOUSEHOLDS AND SNAP PARTICIPANTS Food Purchasing Patterns As discussed in Chapter 1, dietary intake is complex and multi­ dimensional and includes food preferences, cultural appropriateness, prepa- ration methods, meal patterns, and individual health needs, among other components. The following section reviews evidence on overall expen- ditures on food, the marginal propensity to consume food, where SNAP 1  Food availability is defined as the total amount of food available for consumption and is calculated as the sum of annual production, beginning stocks, and imports minus exports, ending stocks, and nonfood uses.

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60 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM FIGURE 3-3 Loss-adjusted per capita food availability compared with dietary recommendations. Figure 3-3.eps NOTE: Data for 2005 based on a 2,000-calorie diet. bitmap SOURCE: Wells and Buzby, 2008. USDA, ERS Food Availability (Per Capita) Data System. participants purchase food, and the types of food purchased by low-income and SNAP populations. Overall Expenditures The origin of the federal poverty measure is Statistical Policy Directive No. 14, developed in 1968 and revised in 1969 and 1981 (OMB, 2012). As discussed in Chapter 2, the basis of the poverty measure is USDA’s economy food plan, which was derived from a 1955 Survey of Food Consumption. This survey found that the average American household spent about one- third (30 percent) of its income on food (U.S. Census Bureau, 1982). The 30 percent figure, however, has been criticized as no longer being relevant to expenditure patterns among U.S. households; the implication for SNAP participants is that they cannot supplement their benefit with the income amount assumed by this figure. Castner and Mabli (2010) used data from the 2005 Consumer Ex- penditure Survey to examine the allocation of resources (including SNAP benefits) for household expenditures (including food) across various con- sumption categories for SNAP, SNAP-eligible but not participating, and SNAP-ineligible groups. They found that SNAP households allocate about 22 percent of their total household expenditures for food consumed at home, compared with 18 percent for SNAP-eligible but not participat- ing households. SNAP households use a greater proportion of their total

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 61 expenditures as well as a greater total amount, $4,013 annually, for food, compared with SNAP-eligible nonparticipants, who spend about $3,443 annually for food. Although SNAP-ineligible households spend the most on food, $4,709, that amount represents a smaller percentage of their income than is the case for either SNAP or SNAP-eligible but not participating households. These findings, along with other recent evidence (Frazao et al., 2007; Schnepf and Richardson, 2009), are generally consistent with Engel’s Law, which states that as a household’s income rises, the amount of that income spent on food also rises, but the proportion of income spent on food declines. As with general food spending, SNAP participants spend more than eligible nonparticipants on food consumed at home. Specifically, SNAP par- ticipants spend 24 percent more than eligible nonparticipants but 5 percent less than ineligible nonparticipants on food consumed at home. By contrast, SNAP participants spend significantly less than eligible and noneligible non­ participants on food consumed away from home. In terms of actual dollars spent, the 2005 Consumer Expenditure Survey showed that an individual SNAP participant spent about $445 per year on food consumed away from home, compared with $560 for eligible nonparticipants and $945 for non- eligible nonparticipants (Castner and Mabli, 2010). Marginal Propensity to Consume The marginal propensity to consume is defined as the amount by which expenditures on goods and services in a budget category will increase in response to an increase in income of $1.00. A different but related measure is the marginal propensity to consume food with SNAP benefits, which reflects the change in food expenditures that results from a $1.00 increase in these benefits (Castner and Mabli, 2010). The increase in food spending that accompanies an increase in income is not necessarily the same as the increase that accompanies an increase in SNAP benefits since, unlike regular income, these benefits must be spent on food. If participants’ desired spend- ing on food exceeds their benefits, however, economic theory predicts that an increase in SNAP benefits and an increase in income will have the same influence on food expenditures. Still, the marginal propensity to consume as applied to SNAP benefits has been estimated to be $0.17 to $0.47, com- pared with an average of $0.10 as applied to regular income (Breunig and Dasgupta, 2003; Burnstein et al., 2005; Fox et al., 2004; Fraker, 1990). The difference between the effects of cash income and SNAP benefits on food expenditures was illustrated in the “food stamp cashout” studies of the 1980s. In these studies, participants were randomly assigned to receive their benefits either in the form of cash or, as was standard at the time, in the form of food stamps. Researchers examined participants’ food expendi-

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62 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM tures, and found that food spending was about 7 percent higher when the benefits came in the form of food stamps rather than an equivalent amount of cash (Breunig et al., 2001; Fraker et al., 1995). These findings implied a marginal propensity to consume food with SNAP benefits of $0.18-$0.28, which falls within the $0.17 to $0.47 range noted above. Hoynes and Schanzenbach (2009) studied the influence of the receipt of nutrition assistance benefits, such as SNAP, through in-kind transfer, such as vouchers or Electronic Benefit Transfer (EBT) cards, on the pur- chasing power of low-income households. They examined data from the Panel of Income Dynamics from 1968 to 1978 to determine the impact of SNAP on food consumption and the effect of SNAP participation on labor supply. Collectively, their findings support the theory that SNAP benefits decrease overall out-of-pocket food spending but increase total spending on food. The analysis also found a decrease in the tendency of SNAP participants to consume food away from home, although the overall food envi­onment during their study period of 1968-1978 was very dif- r ferent from the food environment of today. In addition, the program at that time had a “purchase requirement” that participants purchase food stamps, which could then be redeemed in stores to obtain foods having a value greater than the original price of the stamps; this requirement was eliminated in 1977. In contrast to the findings reported above, however, the marginal propensity to consume with SNAP income appears to be similar to that for cash income. Where SNAP Participants Purchase Food As described above, Frazao and colleagues (2007) and Castner and Mabli (2010) found that expenditures of SNAP participants and low- income households on food consumed at home represent the largest share of total food expenditures. A Canadian study derived similar results from a secondary analysis of nationally representative food expenditure data (Kirkpatrick and Tarasuk, 2003). Among the population groups studied, low-income households spent less overall on food but also spent 83.5 per- cent of their total food budget on food consumed at home, compared with 73.3 percent among higher-income households. Evidence from USDA’s Food and Nutrition Service (FNS) on where food for consumption at home is purchased suggests that the majority of SNAP participants use larger food outlets as their primary source for food and that they shop outside their immediate neighborhood. Mantovani and Welsh (1996) and Ohls and colleagues (1999) both report that about 90 percent of SNAP participants used a supermarket as their main food shopping outlet. However, many also shopped at other types of food out- lets, including convenience stores, bakeries, produce stands, and farmers’

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 63 markets as secondary food sources. More recent data from USDA-FNS (Castner and Henke, 2011) about where EBT cards were used by partici- pants show that about 64 percent of EBT purchases were made at super- markets, accounting for 84 percent of the dollar value of foods purchased with SNAP benefits. Types of Food Purchased by Low-Income and SNAP Populations Leibtag and Kaufman (2003) analyzed food store scanner data to examine how low-income households economize on food purchases. They found that low-income households purchase more discounted items and private-label store brand products; take greater advantage of volume dis- counts; and purchase less expensive versions of a given product compared with higher-income households. Among the food types purchased, they found that low-income households purchase fewer fruits and vegetables and pay less for them than high-income households. Frazao and colleagues (2007) found that among the lowest-income households, the largest food expenditure at grocery stores is for “other foods”—frozen prepared meals, canned and packaged prepared foods, snack foods, condiments and seasonings, sugar and other sweets, fats and oils, and nonalcoholic beverages. Meat purchases account for about 30 percent of the money spent on food in grocery stores, followed by fruits and vegetables (fresh, frozen, canned, dried, or juice), and lastly c ­ ereals and bakery products or dairy products. Stewart and Blisard (2008) found that, compared with middle- and upper-income households, those with an income at or below 130 percent of the poverty threshold spent significantly less on six of the seven food categories studied—bread and baked goods, milk and dairy, beef, fruits, vegetables, and frozen prepared foods; only the amount spent on eggs did not vary by household income. However, a small increase in income cor- responded to households allocating more money to only two of the seven categories—beef and frozen prepared foods. The authors note that these two categories of foods may be priorities for reasons of taste and conve- nience. For additional money to be allocated to fruits and vegetables, a household’s income must be slightly greater than 130 percent of the federal poverty threshold. Mabli and colleagues (2010b) did not directly examine what foods were purchased by SNAP participants but instead examined changes in the proportion of food expenditures going to foods identified in the 2010 DGA as “foods recommended for frequent consumption” and “foods not recommended for frequent consumption” when households spend more on food overall. In general, the study found that households spending more on food overall allocated a higher proportion of their total food expen-

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64 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM ditures to foods such as fruits, vegetables, and dried beans and peas (i.e., foods recommended for frequent consumption), but also spent a higher proportion on “foods not recommended for frequent consumption” (e.g., baked desserts, salty snacks, other sweets) compared with households with lower total food expenditures. Because SNAP benefits raise households’ purchasing power, the implication is that the benefits at least have the po- tential to raise the share of a household’s food expenditures going toward these recommended foods. Finally, to investigate whether additional SNAP benefits result in i ­ncreased purchases of fruits and vegetables, Frazao and colleagues (2007) analyzed 2004-2005 data on household spending from the Consumer Ex- penditure Survey (BLS, 2012). They found that additional income influenced food purchasing patterns for fruits and vegetables only at incomes above $70,000 per year. Further, their analysis suggested that the cost of fruits and vegetables affects low-income households’ purchases in the expected direction, but the magnitude of this effect is modest. A 10 percent discount in the price of fruits and vegetables leads to a 5 to 6 percent increase in purchases by low-income households, while coupons for 10 percent off lead to a 2 to 11 percent increase in purchases. These magnitudes are small enough to suggest that reductions in the cost of these foods would not have a large influence on the proportion of low-income households achieving recommended intakes of fruits and vegetables (Dong and Leibtag, 2010). Dietary Intake The committee considered evidence about the quality of dietary in- take. In particular, the committee reviewed evidence on whether the steep increase in the quantity of grains available in the U.S. food supply as de- scribed earlier suggests an overall increase in carbohydrate intake among the U.S. population. Kant and Graubard (2007) examined secular trends in the association be- tween diet and indicators of socioeconomic position. Data from the National ­ Health and Nutrition Examination Survey (NHANES) were analyzed for total carbohydrate intake over time, by poverty/income ratio and level of education, as indicators of socioeconomic position. The authors found per- sistent positive associations of poverty/income ratio and education level with consumption of nutrient-dense foods, particularly fruits and vegetables, and higher intakes of vitamins A and C and calcium. Across time, the percent- age of obese adults increased in all socioeconomic groups, although the poverty/income ratio differential in obesity prevalence persisted (Kant and Graubard, 2007). The study further identified a positive association between socio­ conomic position and amount of food and energy intake, as well as e p ­ otassium intake, an association that has persisted over three decades.

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 65 Kirkpatrick and colleagues (2012) extended this research and assessed the extent to which Americans met dietary standards between 2000 and 2004. They found that few Americans met dietary recommendations for total fruits (17.5 percent), whole fruits (25.1 percent), total vegetables (12.9 per- cent), dark green vegetables (5.9 percent), orange vegetables (1.9 percent), dry beans and peas (3.5 percent), starchy vegetables (38.3 percent), whole grains (0.8 percent), and milk (7.7 percent). In addition, individuals from middle- and low-income households had significantly lower intakes for all of these food groups except dry beans and peas and starchy vegetables. Among racial/ethnic groups, the lowest percentage of those meeting the recommendations were African Americans. Most children also failed to meet current recommendations, although fewer differences were found by income in this age group. Most adults and children had high consumption of solid fats and added sugars. Using data from the What We Eat in America component of NHANES (2007-2008), the committee reviewed intakes of selected micronutrients and macronutrients for Americans 2 years of age and older. In the bivariate ­ analysis presented below, the committee made no attempt to adjust the estimated intake levels for the demographic characteristics of individuals in each of the groups examined. For example, lower-income and higher- income Americans may have different age distributions, which, in turn, could explain differences in their intake levels, as opposed to different consumption patterns. While NHANES has excellent measures of dietary intake and clinical markers of nutritional status, income and participation in nutrition assistance are not well measured. The survey does include the full 18-item Core Food Security Module, as well as information on SNAP participation. Nevertheless, it is but one dataset that includes only about 5,000 persons located in 15 counties across the country each year. The bivariate analysis may suggest whether there are substantial differences in dietary patterns between Americans at different intake levels that are w ­ orthy of further investigation. On the other hand, data from the Institute of Medicine report Strategies to Reduce Sodium Intake (IOM, 2010) show that the median sodium intake from foods for individuals aged 2 years and over from households at greater than 185 percent of the poverty threshold was 3,362 mg/day, compared with 3,098 and 3,079 mg/day for those from households at 131-185 per- cent and at or below 131 percent of the poverty threshold, respectively (NHANES 2003-2006), suggesting, as noted above, that individuals from low-income households limited their sodium intake more than did those from higher-income households. Findings of a report by Cole and Fox (2008), based on NHANES data, suggest that for all vitamins, minerals, and macronutrients assessed, the dietary intake among SNAP participants was comparable to that of

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66 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM S ­ NAP-eligible nonparticipants. Compared with higher-income adults, how- ever, SNAP participants had lower intakes of several vitamins and minerals. SNAP participants also had significantly lower scores for several of the components of the Healthy Eating Index (HEI)-2005, including total fruits, whole fruits, total vegetables, whole grains, milk, and healthy oils and solid fats and added sugars (Cole and Fox, 2008). (The HEI is discussed further below.) On the other hand, scores on the HEI-2005 components of dark green and orange vegetables, total grains, meat and beans, saturated fats, and sodium were no different for SNAP participants and higher-income individuals. Finally, Fernandes (2012) found that SNAP participation was not associated with frequency of consumption of soft drinks, 100 percent fruit juice, or milk among youth. Overall, the HEI-2005 score was statisti- cally lower among SNAP participants compared with higher-income non- participants (Figure 3-4). The available evidence does lead to one clear conclusion. Given changes in the availability of certain nutrients in the food supply and lower availability of fruits, vegetables, and low-fat or nonfat milk products, relative to current recommendations, along with evidence for a positive association between socioeconomic status and amount of food and energy intake, many U.S. population groups fall short of meeting current dietary recommendations. 100 80 Total HEI-2005 Score 68 69 63 56* 58* 57* 59* 60 52 53 53 56* 51 40 20 0 All Ages Children Adults Older Adults FSP participants Income-eligible nonparticipants Higher-income nonparticipants FIGURE 3-4  Healthy Eating Index-2005: Total scores. NOTES: FSP = Food Stamp Program; HEI = Healthy Eating Index. Figure 3-4.eps *Denotes statistically significant difference from Food Stamp Program participants at the 0.05 level or better. Estimates are age adjusted. SOURCE: Cole and Fox, 2008.

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 67 ACCESS TO A HEALTHY DIET Role of the DGA (Dietary Guidelines for Americans) As noted in Appendix G, the DGA (USDA and HHS, 2010) serve as the scientific basis for all federal nutrition policy and nutrition programs, including SNAP. Since 1980 when the first DGA were published (USDA and USDHEW, 1980), the goals of the guidelines have evolved with changes in understanding of nutritional health needs. Today, however, a large propor- tion of the population, while meeting or exceeding the goals for intake of fat, saturated fat, grains, and protein, is failing to meet the goals for intake of fruits and vegetables, dietary fiber, and milk (Wells and Buzby, 2008). This finding may be driven by a number of personal (individual), ­ ocial, s and environmental factors. As captured in the committee’s framework (see Chapter 1), personal choice, food preferences, and taste are primary influ- ences on food selection (see also Chapter 4). At the same time, environ- mental factors in some locales, such as limited availability of healthy foods, greater availability of highly processed foods, and limited access to outlets that offer a variety of food choices, may be key modifiable variables with an impact on food purchasing power—a particularly important concern for participants in nutrition assistance programs such as SNAP. To assess the extent to which SNAP allotments are adequate to pur- chase a healthy diet, it is useful to have a tool for measuring the quality of participants’ diets. While there is no single standard tool for this purpose, the HEI (Box 3-1) is one of several measures considered for assessing diet quality among SNAP households, maintenance of an adequate level of nu- trition, and access to a healthy diet (see Chapter 1). The HEI was designed to measure and monitor the quality of diets consumed by the U.S. popula- tion and the low-income subpopulation (CNPP, 2012). Figure 3-5 shows that scores on the components of the original HEI remained relatively stable over the first decade of its use. The HEI serves not only as a monitor for dietary intake over time but also as a predictor of health outcomes. To examine the effectiveness of the HEI in predicting health outcomes, McCullough and colleagues (2000a) used a food frequency questionnaire to measure the index (HEI-f) among healthy adults and estimated their risk for certain chronic diseases. They found that, compared with adults with good HEI-f scores (>80), a poor HEI-f score was only modestly associated with an increased risk of cardio­ vascular disease among women and with an increased risk of chronic disease and cardiovascular disease among men, and no associations were found between HEI-f score and cancer risk. The authors conclude that the weak association found between HEI-f score and markers of chronic disease may be due either to methodological limitations or to failure of the HEI

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86 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM approach can capture these multiple dimensions. The most commonly used summary measure of diet quality is the HEI-2005, and improvement in HEI scores among both the general population and low-income groups is a performance measure for the goal of “improving the nation’s nutrition and health” in USDA’s Strategic Plan for 2005-2010. HEI-2005 scores show that most Americans, including SNAP partici- pants and other low-income groups, are falling short of meeting the current DGA. This failure among Americans at all income levels highlights that the HEI-2005 (or other measures of diet quality) should not be used as a sole measure of the adequacy of SNAP allotments. SNAP participants—and other Americans—may have reasons for choosing foods with low nutrient density, and limited household resources for obtaining food is just one of these reasons. A related challenge to assessing access to a healthy diet is entailed in measuring diet quality. A number of methodologies are used to collect data on dietary intake. Interviewer-administered 24-hour di- etary recalls are appropriate for a less educated population for monitoring and surveillance purposes. This method decreases respondent burden and greatly improves data quality compared with other methods; however, it is expensive, and a protocol using multiple 24-hour recalls is challenging to complete. A limited number of datasets include dietary intake at the individual level. Most national-level datasets cannot be used to assess individual-level diet quality because this type of data cannot be aggregated by income level or program participation. Given these limitations, NHANES is currently the best dataset available for examining diet quality in low-income, including SNAP, populations because it is based on state-of-the-art data collection on dietary intake, includes the full 18-item Core Food Security Module, and includes information on SNAP participation. Nevertheless, NHANES is only one dataset, and although it examines a nationally representative sample, only about 5,000 persons located in 15 counties across the country are sampled each year. Furthermore, inherent challenges arise in identifying whether respondents within the same household are related and with link- ing individuals to external data sources. In addition, NHANES measures SNAP participation through self-report and includes substantial measure- ment error. Linking the NHANES data to another administrative data source with more accurate reporting of SNAP participation might improve understanding of the association between SNAP participation and dietary intake. Another limitation of NHANES is that, because it is cross-sectional, it does not permit tracking changes in food security or access to a healthy diet over time. More research is needed to test the validity of the HEI as a compre- hensive measure that captures overall diet quality, whether it is internally reliable and therefore highly correlated with other important components of

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 87 the diet, and whether it is a reliable measure across time and across studies. It will be difficult to evaluate the adequacy of SNAP allotments until agree- ment is reached on the type of diet quality index needed for this purpose. Thus, longitudinal data on SNAP participation, food security, and dietary intake are needed. With such data, researchers could track changes in the outcomes of food security and diet quality over time and re- late changes in SNAP participation to changes in these outcomes. While assess­ ent of the adequacy of SNAP allotments may be based on ex- m amining whether program participants appear to be meeting the goals of improving food security and access to a healthy diet, it is not clear what standards should be used to determine whether food security has been sufficiently improved or whether participants truly have access to a healthy diet. For example, what level of food security among participants would be required to determine that SNAP benefits are adequate? Should SNAP benefits be expected to eliminate low and/or very low food security entirely (if both, this would imply that the resulting rate of food insecu- rity should be zero percent among participants for benefits to be judged adequate)? Or would a more appropriate standard be to expect the rate of low and/or very low food security to be approximately the same among participants as among low-income nonparticipants? And what standards of nutrient adequacy should be expected—perhaps an HEI-2005 score equal to that of nonparticipants? Key to defining the adequacy of SNAP allotments is having estimates of the impact of these benefits on such outcomes as diet quality, obesity, or food security. However, self-selection into SNAP greatly complicates such estimates. Because individuals and households choose whether to partici- pate in the program if they are eligible, the unmeasured characteristics of participants may differ in important ways from those of nonparticipants. Further, these differences in unmeasured characteristics may be related to key outcomes of interest. Thus, a difference in outcomes between partici- pants and nonparticipants could be due either to differences in their un- measured characteristics or to the effect of program participation. Although a number of sophisticated methods have been developed to address this challenge, none of these methods is perfect, and critics have challenged their validity. FINDINGS AND CONCLUSIONS In assessing the feasibility of defining the adequacy of SNAP allotments, the committee considered a range of evidence on the impact of SNAP program participation on achieving the program goals of improving food security and access to a healthy diet. In general, the committee found that it would be useful to conduct further research examining food security and

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88 SUPPLEMENTAL NUTRITION ASSISTANCE PROGRAM access to a healthy diet among program participants and estimating the impact of SNAP benefits on these outcomes. Food Security Overall, the evidence on the impact of SNAP participation on food insecurity is moderately strong. While there have been no randomized controlled trials that can shed light on how SNAP affects household food insecurity, the nonexperimental studies reviewed have made serious efforts to account for the possibility of selection bias in their impact estimates. In particular, these studies have used various methods to account for observed and unobserved factors that lead some households to receive SNAP benefits and others not to participate. The evidence suggests that food insecurity is common among SNAP participants. As discussed above, data from 2011 show that just under half of SNAP households (48 percent) were food secure, with 29 percent having low food security and 23 percent having very low food security. These rates of low and very low food security were nearly twice the rates for income-eligible households that did not participate in the program, 16 percent of which had low food security and 11 percent very low food security. Among higher-income households (those with incomes above 185 percent of the federal poverty threshold), more than 90 percent were food secure.6 Subgroups for which food insecurity is particularly prevalent include female-headed ­ ouseholds with children and African American– and h Hispanic-headed households (Coleman-Jensen et al., 2012a). Although the prevalence of food insecurity is relatively high among SNAP participants, the most recent research suggests that it would be even higher absent SNAP benefits—in other words, that SNAP benefits have positive impacts on participants’ food security (i.e., reducing households’ likelihood of food insecurity). This finding raises the question of whether the high prevalence of food insecurity among SNAP households could be further reduced with higher benefit levels. Taken together, the evidence suggests that SNAP benefits help alleviate food insecurity, but not enough to reduce the level of insecurity to that of either higher-income households or lower-income households that do not participate in the program. Evidence is less complete on the levels of food insecurity and impacts of benefits among subgroups of participants. 6 These statistics are based on the 12-month measure of food insecurity and thus may be influenced by the households’ experiences prior to entering SNAP. The patterns of food in- security based on the 30-day measure were similar to those reported here, although the food insecurity rates were somewhat lower (Coleman-Jensen et al., 2012a).

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FOOD SECURITY AND ACCESS TO A HEALTHY DIET 89 Access to a Healthy Diet As discussed above, many SNAP households have diets that are not nu- tritious in all respects. The committee found that evidence on the question of whether SNAP benefits contribute to improving dietary quality is limited and insufficient to permit drawing conclusions on this question. In addi- tion, significant methodological challenges arise in assessing diet quality in the SNAP population. Along with these challenges, the lack of evidence on this issue may be due to the time lag between receipt of the SNAP benefits and subsequent dietary intake and the failure of many studies to account for selection bias. REFERENCES Alaimo, K., C. M. Olson, E. A. Frongillo Jr., and R. R. Briefel. 2001. Food insufficiency, f ­ amily income, and health in U.S. preschool and school-aged children. American Journal of Public Health 91(5):781-786. Andrews, M., and M. Nord. 2009. Food insecurity up in recessionary times. Amber Waves, http://webarchives.cdlib.org/sw1vh5dg3r/http://ers.usda.gov/AmberWaves/December09/ Features/FoodInsecurity.htm (accessed April 8, 2013). Bartfeld, J., and R. Dunifon. 2006. State-level predictors of food insecurity among households with children. Journal of Policy Analysis and Management 25(4):921-942. Basiotis, P. P., and M. Lino. 2002. Food insufficiency and prevalence of overweight among adult women, Nutrition Insight 26. Washington, DC: USDA, CNPP. http://www.cnpp. usda.gov/Publications/NutritionInsights/Insight26.pdf (accessed August 23, 2012). Basiotis, P. P., A. Carlson, S. A. Gerrior, W. Y. Juan, and M. Lino. 2002. The Healthy Eating Index: 1999-2000, CNPP-12. Washington, DC: USDA, CNPP. http://www.cnpp.usda. govpublications/hei/hei99-00report.pdf (accessed June 13, 2012). Bauer, K. W., M. O. Hearst, K. Escoto, J. M. Berge, and D. Neumark Sztainer. 2012. Parental employment and work-family stress: Associations with family food environments. Social Science and Medicine 75(3):496-504. Baum, C. L. 2011. The effects of food stamps on obesity. Southern Economic Journal 77(3):623-651. Beckles, G. L., J. Zhu, and R. Moonesinghe. 2011. Diabetes—United States, 2004 and 2008. Morbidity and Mortality Weekly Report 60(Suppl. 1):90-93. http://www.cdc.gov/mmwr/ preview/mmwrhtml/su6001a20.htm (accessed September 10, 2012). Bhattacharya, J., T. DeLeire, S. Haider, and J. Currie. 2003. Heat or eat? Cold-weather shocks and nutrition in poor American families. American Journal of Public Health 93(7):1149-1154. Bhattacharya, J., J. Currie, and S. Haider. 2004. Poverty, food insecurity, and nutritional out- comes in children and adults. Journal of Health Economics 23(4):839-862. BLS (Bureau of Labor Statistics). 2012. Consumer Expenditure Survey. http://www.bls.gov/ cex (June 7, 2012). Borjas, G. J. 2004. Food insecurity and public assistance. Journal of Public Economics 88(7-8):1421-1443. Bowman, S. A., M. Lino, S. A. Gerrior, and P. P. Basiotis. 1998. The Healthy Eating ­Index: 1994-96, CNPP-5. Washington, DC: USDA, CNPP. http://www.cnpp.usda.gov/­ publications/hei/hei94-96report.PDF (accessed June 13, 2012). Breunig, R., and I. Dasgupta. 2003. Are people ashamed of paying with food stamps? Journal of Agricultural Economics 54(2):203-225.

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