WIC Participation Patterns

An Investigation of Delayed 

Entry and Early Exit

Alison Jacknowitz

Laura Tiehen

Economic

Research

Service

Economic

Research

Report

Number 109

December 2010

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Recommended citation format for this publication: 

Jacknowitz, Alison, and Laura Tiehen. WIC Participation Patterns: 

An Investigation of Delayed Entry and Early Exit, ERR-109, U.S. 

Department of Agriculture, Economic Research Service, December 2010.

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A Report from the Economic Research Service

Abstract

USDA’s Special Supplemental Nutrition Program for Women, Infants, and Children 

(WIC) provides nutritious foods, nutrition counseling, and referrals to health and other 

social services to low-income women and their infants/children up to age 5. Despite the 

health benefi ts of WIC participation, many eligible women do not participate during pregnancy, and many households exit WIC when a participating child turns 1 year old. The 

authors of this report use the fi rst two waves of the Early Childhood Longitudinal StudyBirth Cohort (ECLS-B) to understand these transitions into and out of WIC. Findings 

show that households that are more economically advantaged are more likely to delay 

entry into the program or exit after a child turns 1 year old. Some of the mothers exiting 

the program reported that WIC requires too much effort and that its benefi ts are not 

worth the time (26.2 percent of those exiting) or that they have scheduling and transportation problems (almost 10 percent of those exiting), suggesting that the costs of participation may be a barrier to continued WIC participation.

Keywords: Special Supplemental Nutrition Program for Women, Infants, and Children, 

WIC, participation dynamics

Acknowledgments

The authors thank Tracy Fox Salmons and Steven Putansu of American University 

for research assistance. Nancy Burstein from Abt Associates; Philip Gleason from 

Mathematica Policy Research; Jay Hirschman and Janis Johnston from USDA’s Food 

and Nutrition Service; Ephraim Leibtag, Victor Oliveira, and Mark Prell from USDA’s 

Economic Research Service; and participants at the 2006 and 2007 Association for 

Public Policy Analysis and Management Conference, the 2007 National Association for 

Welfare and Research Statistics Conference, the 2006 University of Kentucky Center for 

Poverty Research (UKCPR) Small Grants Conference, a 2007 National Poverty Center 

Alison Jacknowitz

Laura Tiehen, ltiehen@ers.usda.gov

WIC Participation Patterns 

An Investigation of Delayed 

Entry and Early Exit

Economic 

Research 

Report 

Number 109

December 2010
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seminar, a 2008 UKCPR seminar, and a 2007 U.S. Department of Health and 

Human Services, Administration for Children and Families seminar provided 

valuable comments on an earlier version of the paper. Alison Jacknowitz 

thanks the following organizations for funding: UKCPR through the U.S. 

Department of Health and Human Services, Offi ce of the Assistant Secretary 

for Planning and Evaluation, grant number 2U01PE000002-04; and USDA, 

Economic Research Service. Thanks also go to our editor, Angela Anderson, 

and to Wynnice Pointer-Napper for graphic design and layout.

About the Authors

Alison Jacknowitz is an associate professor of public administration and 

policy in the School of Public Affairs at American University. Laura Tiehen 

is an economist with USDA’s Economic Research Service (ERS).
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Contents

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

How WIC Works: Program Administration and Outcomes . . . . . . . . . . 3

Services Provided by WIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

WIC Eligibility Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Research on WIC Participation and the Outcomes Associated 

 With Participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

The ECLS-B Provides Unique Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Additional Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Coding WIC Eligibility and Participation. . . . . . . . . . . . . . . . . . . . . . . . . 8

Constructing the Analysis Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

A Conceptual Model of Household Program Participation. . . . . . . . . . . 13

Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Results on Dynamic WIC Participation Patterns . . . . . . . . . . . . . . . . . . 17

Descriptive Analysis of Dynamic Participation Patterns . . . . . . . . . . . . 17

Comparability of ECLS-B Coverage Rates and Offi cial 

 Coverage Rates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Dynamic WIC Participation Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Results for Postnatal-Infant WIC Entrants . . . . . . . . . . . . . . . . . . . . . . . 19

Results for Participants Exiting WIC . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Self-Reported Explanations for Early Exits . . . . . . . . . . . . . . . . . . . . . . 25

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Appendix: State-Level WIC Policies and Practices . . . . . . . . . . . . . . . . 37
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Summary

What Is the Issue?

Despite the health benefi ts of participation, many eligible households do not 

participate in USDA’s Special Supplemental Nutrition Program for Women, 

Infants, and Children (WIC). While roughly half of infants born in the 

United States receive WIC benefi ts, USDA statistics indicate that eligible 

pregnant women and children 1-5 years of age are far less likely to participate in WIC than eligible infants and postpartum women. This implies that a 

number of pregnant women delay enrollment until after having a child, and 

that many households leave the program when a participating child turns 1 

year old. Research on the factors that infl uence the dynamics of WIC participation can inform outreach and targeting efforts, so that vulnerable populations receive adequate exposure to the benefi ts of WIC participation.

What Did the Study Find?

There are notable differences in the timing of household participation in the 

WIC program. 

• Among the mother-child pairs (referred to as households) eligible for 

WIC, 79.1 percent participated in the program at some time during the 

period between the child’s birth and when the child turned 1 year old (the 

“postnatal-infant period”). 

• Of those who participated in the WIC program during the postnatalinfant period, 17.6 percent did not enroll in the program until after the 

child was born and 22.9 percent exited the program when the child turned 

1 year old.

Postnatal Enrollment in WIC

The following types of households were more likely than others to delay 

participating in WIC until after their child was born:

• Households with higher income and those with private insurance. 

• Households in which the mother has a college degree and was employed 

the year before giving birth. 

• Households in the Northeast and those in urban areas with a population 

of at least 50,000.

By contrast, prenatal Medicaid recipients were much less likely to delay WIC 

enrollment until after having a child. 

Exits From WIC 

When a child turns 1 year old, the WIC household must recertify its eligibility for benefi ts. Roughly 90 percent of postnatal-infant participants 

retained eligibility after the child turned 1 year old. The following types of 

households were more likely than others to exit WIC after their child turns 

1 year old:
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• Households with higher income. 

• Households in which mothers are more educated and were employed after 

the child’s birth. 

• Mothers who did not breastfeed and those who breastfed for less than 

6 months. 

By contrast, households with income below the poverty line and those that 

participated in prenatal Medicaid were less likely to exit WIC after their child 

turned 1 year old. Approximately 33 percent of households that left the WIC 

program reported that they believed they were no longer eligible once the 

child turned 1 year old, and 27.8 percent reported that they no longer needed 

food benefi ts.

When a child turns 1 year old, the eligible WIC household no longer receives 

the infant food package, which contains infant formula for those who are not 

being breastfed exclusively, and transitions to the child food package, which 

has a signifi cantly lower retail value. This change in WIC food benefi ts may 

play a role in a household’s decision to exit WIC.

Although WIC is not an entitlement program, few households reported that 

they were denied benefi ts due to lack of program funds. Some households 

reported, however, that the program requires too much effort and the benefi ts are not worth the time (26.2 percent of those exiting) or that they have 

scheduling and transportation problems (almost 10 percent of those exiting), 

suggesting that such transaction costs of participation may be a barrier to 

continued participation in WIC. 

How Was the Study Conducted?

Researchers used data from the Early Childhood Longitudinal Study-Birth 

Cohort (ECLS-B), a nationally representative longitudinal dataset of children 

born in 2001. The dataset provides demographic and economic information 

collected from the child’s biological mother when the child is 9 months and 

24 months old, as well as information from the child’s birth certifi cate. The 

ECLS-B collects extensive information about the WIC participation of the 

mother and children in the household, and the timing of that participation. In 

addition, a subset of mothers who left the WIC program was asked to report 

why they stopped receiving WIC benefi ts for their child.

The researchers used probit regression analysis to examine the factors that 

infl uence postnatal, rather than prenatal, enrollment in WIC and the factors 

that infl uence a household’s exit from WIC once the child turns 1 year old. 

The researchers’ analysis focused on the factors that infl uence a household’s 

participation: perceived benefi ts, the stigma or transaction costs associated 

with participation, and the availability of information on the program and its 

eligibility requirements. The researchers also used multinomial logit regression to examine WIC household characteristics that may have infl uenced 

WIC participants’ self-reported explanation for leaving the program.
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Introduction

The Special Supplemental Nutrition Program for Women, Infants, and 

Children (WIC) provides nutritious foods, nutrition counseling, and referrals 

to health and other social services for low-income pregnant and postpartum 

women and their infants and children up to age 5. WIC has grown from 

serving 88,000 participants in fi scal year 1974 to approximately 8.7 million 

in fi scal year 2008 (U.S. Department of Agriculture (USDA), 2010a). In fi scal 

year 2006, approximately a quarter of participants were women (categorized 

as either pregnant, breastfeeding, or nonbreastfeeding post-partum), approximately a quarter were infants, and approximately half were children 1-5 years 

of age (Oliveira and Frazão, 2009).

To be eligible for WIC, in addition to belonging to 1 of the 5 demographically 

targeted groups discussed above, an individual must have low income and be 

at nutritional risk. Not everyone who is eligible for WIC chooses to participate. The percent of the eligible population receiving WIC benefi ts is referred 

to as the “coverage rate.” The offi cial WIC coverage rate is calculated as the 

number of WIC participants (derived from administrative data) divided by 

the number of individuals eligible for WIC (estimated using survey data). 

WIC’s offi cial coverage rate in 2007 was 55.9 percent (USDA, 2009).

Participation in WIC varies across categories. As shown in fi gure 1, coverage 

rates for 2007 were higher among women in the year after giving birth (77.8 

percent) than for pregnant women (65.7 percent).1 The coverage rate for 

infants (81.3 percent) was higher than that for children 1-5 years old (47.3 

percent) (USDA, 2009). Among the fi ve participant categories, infants had 

the highest coverage rate. Arranging coverage rates in time sequence shows 

a hump-shaped pattern, with a peak in WIC coverage during the year after a 

woman gives birth. This pattern is also evident in the offi cial coverage rates 

from 1994 to 2007 reported by USDA (2009).

1Women who participate in WIC 

after giving birth are divided into two 

groups: those who breastfeed (participation rate of 68.1 percent) and those 

who do not breastfeed (participation 

rate of 78.8 percent).

Figure 1

WIC coverage rates, 2007 

Percent

Note: Coverage rate equals the number of WIC participants as a percent of the number 

of persons estimated to be eligible for WIC. 

Source: U.S. Department of Agriculture, 2009.

Breastfeeding and 

postpartum 

women

Pregnant women Infants Children

65.7

77.8 81.3

47.3
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While pregnant women and children 1-5 years old have relatively low participation rates, previous research suggests that participation in WIC does confer 

health benefi ts to these groups. In addition, studies demonstrate that eligible 

pregnant women and children who do not participate exhibit need across a 

variety of dimensions (Bitler, Gundersen, and Marquis, 2005; Gundersen, 

2005; Tiehen and Jacknowitz, 2008). For example, Bitler, Gundersen, and 

Marquis (2005) found that among eligible children who did not participate 

in WIC, 5.5 percent lived in households that are food insuffi cient (sometimes 

or often do not get enough to eat) and 19.5 percent lived in households that 

could not afford to eat balanced meals. Focusing on pregnant women, Tiehen 

and Jacknowitz (2008) found that 32.7 percent of eligible nonparticipants had 

household income below the poverty line.

In this study, we examined why eligible participant households are less likely 

to participate during the prenatal period and after a child turns 1 year old 

than in the year after birth.2 Specifi cally, we examined factors associated 

with the decision of households that participate in WIC during the year after 

the birth of a child (the postnatal-infant period) to (1) delay their entry into 

the WIC program until after the child’s birth and (2) exit the program when a 

child turns 1 year old. We considered three sets of factors: 

1. Household demographic and socio-economic characteristics; 

2. WIC policies; and 

3. Self-reported reasons for exiting the program after the child turns 

1 year old. 

We used the fi rst two waves of the Early Childhood Longitudinal Study-Birth 

Cohort (ECLS-B) data to document and analyze the participation patterns of 

mother-child pairs from the time of the mother’s pregnancy until the child’s 

second birthday. While the relatively low coverage rates for children pertain 

to children up to their fi fth birthday, the ECLS-B data used for this study 

provided information up to the child’s second birthday. We were able to estimate WIC participation in each of three periods for the same set of households. In contrast to the cross-sectional program data and survey data on 

which most analysis of WIC is based, the longitudinal nature of the ECLS-B 

permits analysis of the dynamic participation patterns of WIC-eligible 

mother-child pairs.

From a program perspective, if those who delay entry into WIC or those who 

exit early are more advantaged economically and less in need of program 

benefi ts, then the program is well-targeted. If eligible nonparticipants exhibit 

need, research results can be used to facilitate outreach efforts and to guide 

program reforms to prolong the participation of underserved groups. Given 

that households that participated during the year after the birth of a child 

demonstrated program awareness and the willingness to participate, outreach 

activities and program changes could be effective for these groups. Program 

awareness, however, may be delayed for those who enroll after giving birth.

2This work is an extension of 

Jacknowitz and Tiehen (2009).
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How WIC Works 

Program Administration and Outcomes

Services Provided by WIC

The overarching objective of the WIC program is to counteract the negative 

effects of poverty on prenatal and child health. WIC participants typically 

receive vouchers to purchase specifi c supplemental foods from authorized 

retailers. These foods are good sources of nutrients, such as protein, iron, 

calcium, and vitamins A and C.

WIC food packages do not vary by household income, but they do vary by 

low-income target group. The contents of WIC food packages were revised 

in 2009 to refl ect changes in dietary recommendations.3 During the period 

of this study, WIC food packages for most participant categories, other than 

infants, included milk, eggs, cheese, dried beans, peanut butter, and breakfast 

cereals that are high in iron and low in sugar. Infants who were not exclusively breastfed received iron-fortifi ed infant formula from 0-12 months of 

age as well as infant cereal and fruit or vegetable juice from 4-12 months of 

age. The price of infant formula creates most of the variation in the value of 

food packages across participant categories. In fi scal year 2005, the average 

retail value of the WIC food package for infants was $97.86 per month, while 

the average retail value of the child package was $39.97 per month (USDA, 

2007).4 In addition, while Federal guidelines limit the maximum amount of 

food in each food package, States have some discretion over the content of 

food packages. For example, some States allow WIC agencies to tailor the 

food packages of some participants for sucrose content or the type of milk.5

In addition to the supplemental foods, WIC also provides nutrition education 

to its participants. Nutrition education includes lessons on recommended food 

patterns, but can also cover topics like breastfeeding and health behaviors, 

such as avoiding alcohol, smoking, and drugs. States must offer participants 

two nutritional education sessions every 6 months, though participants are 

not required to attend them. WIC also provides referrals to health and social 

services, such as preventative medicine and other assistance programs, particularly Medicaid (Oliveira and Frazão, 2009).

WIC Eligibility Requirements

In addition to being categorically eligible (i.e., belonging to 1 of the 5 

groups discussed earlier), an individual must meet two other criteria to be 

WIC eligible. 

1. The individual must reside in a household with income at or below 

185 percent of the Federal poverty threshold (i.e., income eligible) or 

be enrolled in another assistance program, such as the Food Stamp 

Program,6 Temporary Assistance for Needy Families (TANF), or 

Medicaid (i.e., adjunctively eligible). Some States allow participants 

in the National School Lunch Program or the Supplemental Security 

Income (SSI) Program to be adjunctively eligible for WIC. 

3For more information, see Oliveira 

and Frazão (2009).

4Manufacturer rebates to the WIC 

program lower the cost to USDA of 

certain WIC foods, especially infant formula, below the retail value 

(Oliveira and Frazão, 2009).

5Davis and Leibtag (2005) studied 

the sources of State variation in the 

retail value of WIC food packages.

6The Food Stamp Program was 

renamed the Supplemental Nutrition 

Assistance Program (SNAP) in October 

2008. We refer to it as the Food Stamp 

Program, since the name change 

occurred after the period of our study.
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2. The individual must be assessed as nutritionally at risk:7

• Medically based risks, such as anemia, underweight, overweight, or 

history of pregnancy complications or poor outcomes; and 

• Diet-based risks, such as failure to meet dietary guidelines. During 

the period of our study, States varied on how they collected information about nutritional risk. For example, some States required 

individuals to recall food intake over a 24-hour period and others 

just required that individuals complete a food frequency checklist 

(USDA, 2002).8

Participants are certifi ed as WIC eligible for a specifi ed period of time, which 

varies by participant category. A pregnant participant is certifi ed for the 

duration of her pregnancy and does not have to recertify her eligibility until 

6 weeks after the birth of her infant. Postpartum women who do not breastfeed are eligible for WIC for up to 6 months after delivery, while mothers 

who breastfeed are certifi ed for 6 months at a time up to 1 year after delivery 

as long as they continue to breastfeed. Infants are generally certifi ed until 

they turn 1 year old, while children 1-5 years old are certifi ed for a 6-month 

period. WIC is not an entitlement program, which means that eligible applicants are not guaranteed to receive services. When an agency does not have 

suffi cient funds to serve all eligible applicants, it creates a waiting list and 

allocates available resources based on a system that ensures that those with 

the greatest nutritional needs are served fi rst.9 As noted by Oliveira and 

Frazão (2009), anecdotal evidence suggests that in recent years States have 

received suffi cient funding to provide benefi ts to all eligible WIC applicants.

Research on WIC Participation 

and the Outcomes Associated With Participation

Most national-level studies of WIC participation have used a cross-sectional 

design to examine factors associated with participation (Ku, 1989; Brien and 

Swann, 1997; Kowaleski-Jones and Duncan, 2000; Chatterji et al., 2002; 

Bitler et al., 2003; Bitler and Currie, 2005a), while others used a dynamic 

design (Burstein et al., 2000; Gundersen, 2005; Swann, 2007; Tiehen and 

Jacknowitz, 2008). Most studies examined prenatal participation, while 

relatively few examined children’s participation (Burstein et al., 2000; 

Gundersen, 2005; Castner et al., 2009). Two studies examined the correlates 

of WIC participation around the birth of a child, though they did not distinguish prenatal from postnatal participation (Bitler et al., 2003; Chatterji et al., 

2002).10

Among the studies that focused on prenatal participation, some concentrated on what factors infl uenced prenatal participation (Ku, 1989; Swann, 

2007; Tiehen and Jacknowitz, 2008), while others focused on understanding 

prenatal participation to estimate the effect of WIC on birth outcomes (Bitler 

and Currie, 2005a; Brien and Swann, 1997; Kowaleski-Jones and Duncan, 

2000). The primary interest of Ku (1989), Swann (2007), and Tiehen and 

Jacknowitz (2008) was to understand factors associated with the timing of 

prenatal participation.

7All WIC applicants, except infants 

under 9 months, must undergo a blood 

test for anemia (Oliveira and Frazão, 

2009).

8The 24-hour food intake recall is no 

longer used to determine nutritional risk.

9For additional information on WIC 

eligibility, see the USDA, Food and 

Nutrition Service website at http://

www.fns.usda.gov/wic/howtoapply/

eligibilityrequirements.htm.

10Chatterji et al. (2002) examined 

WIC participation during the year of 

a child’s birth (i.e., end of pregnancy 

and immediately after birth) as part of a 

study that examined the effect of WIC 

on breastfeeding.
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Three studies focused on the dynamics of WIC participation among infants 

and children, using the Survey of Income and Program Participation (SIPP) 

(Burstein et al., 2000; Gundersen, 2005; Castner et al., 2009). Gundersen 

(2005) used the 1996 SIPP to compare the economic health of three groups of 

infants and children who were found to be eligible during a single month in 

late 1996 or early 1997. The three groups were based on their WIC participation patterns over a 48-month period: nonparticipants, participants who left 

WIC at any time during the 48-month period, and participants who remained 

in the program for the entire 48-month period. Gundersen (2005) found that 

infants and children who never participated were, on average, more economically advantaged than infants and children who did participate. In addition, 

those who participated for only a portion of the 48-month period were generally more economically advantaged than those who remained in the program 

for the 48-month period. Burstein et al. (2000) and Castner et al. (2009) both 

used the SIPP to track the participation patterns of infant participants as they 

aged and examined the factors associated with their exit from the program. 

Both studies found that exits were strongly associated with increases in 

household income and exits from other public assistance programs.

Recent reviews of the literature by Currie (2003); Fox, Hamilton, and Lin 

(2004); and Oliveira and Frazão (2009) concluded that the research, taken 

as a whole, suggests that WIC has a benefi cial impact on the intake of food 

energy and nutrients during pregnancy and on birth outcomes, such as mean 

birthweight, gestational age, and the likelihood of low birthweight. While 

some recent studies (e.g., Bitler and Currie, 2005a; Figlio et al., 2009) found 

that WIC participation was associated with improved birth outcomes, debate 

has emerged over the role that WIC participation plays in the improvement 

of birth outcomes (Besharov and Germanis, 2001; Bitler and Currie, 2005b; 

Joyce et al., 2005; Joyce et al., 2008; Ludwig and Miller, 2005). One of the 

underlying issues in this debate is whether WIC participants would be more 

likely to have better birth outcomes than eligible nonparticipants, regardless 

of whether they participated in WIC.11 A more thorough understanding of the 

factors associated with WIC participation, as well as the timing of participation, can contribute to the debate over WIC effectiveness.

Evidence also shows that children benefi t from participation in WIC, though 

it was not as strong or consistent as the evidence relating to prenatal WIC 

participation. Many studies of WIC’s effect on children were not consistent with current methods for assessing dietary intake (Oliveira and Frazão, 

2009). Fox, Hamilton, and Lin (2004), however, noted that there was credible evidence that WIC reduces the prevalence of iron-defi ciency anemia. 

Some evidence also indicated that WIC participation may improve children’s growth, health care use, immunization status, and overall health (Fox, 

Hamilton, and Lin, 2004).

This report advances the literature on WIC participation in several ways: 

• We examined the dynamics of mother-child pair WIC participation from 

the time of a woman’s pregnancy until her child reaches 2 years old. 

Previous studies focused on either pregnant women participants (Swann, 

2007; Tiehen and Jacknowitz, 2008) or infant and/or child participants 

(Burstein et al., 2000; Gundersen, 2005; Castner et al., 2009). While 

Burstein et al. (2000) and Castner et al. (2009) tracked WIC participation 

11Another underlying issue in this 

debate, less relevant for this study, is the 

role of gestational age bias in assessing 

the effectiveness of WIC. Gestational 

age bias can lead to a spurious positive association between prenatal WIC 

participation and birth outcomes that 

depends on length of gestation, since 

women whose pregnancies last longer 

have more opportunity to enroll in WIC.
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of infants as they aged, no previous study identifi ed mother-child pairs 

and tracked the dynamics of their participation over this timeframe. 

• We examined why women who enter WIC in the postnatal-infant period 

did not enter the program earlier. To our knowledge, this issue has not 

been examined. 

• We examined the characteristics associated with the decision to leave 

WIC when an infant turns 1 year old, and the mother’s reasons for exiting 

the program at that time. Such information has not previously been available in a nationally representative survey. 

• Our dataset captured the period after recent policy changes, which standardized WIC eligibility requirements and expanded Medicaid eligibility. 
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Data

The ECLS-B Provides Unique Data

The primary data source for this study was the Early Childhood Longitudinal 

Study-Birth Cohort. The ECLS-B is a longitudinal dataset collected by the 

National Center for Education Statistics (NCES). The sample of 10,700 children was designed to be nationally representative of children born in 2001 

and oversampled children who are American Indian, Chinese, a member of 

another Asian and Pacifi c Islander group, a twin, or low and very low birthweight children.12 The ECLS-B follows these children from birth through 

kindergarten, collecting data when the child is approximately 9 months, 2 

years, 4 years old (at pre-school), and at kindergarten entry.13 This study used 

data from the fi rst two waves (sample at 9 months and at 2 years old). Of the 

10,700 children with a parent who participated in the fi rst wave of the survey, 

9,850 of their parents participated in the second wave.14 

In the fi rst two waves of the data, information was collected from children 

and both parents, including nonresidential fathers, birth certifi cates, and child 

care providers. The ECLS-B contains information on the timing of WIC 

participation, explanations for exiting the WIC program, demographic characteristics, income and assets, participation in other assistance programs, and 

health status and behaviors. 

While program administrative data are often utilized for studies of entry 

into and exit out of participation in many programs, the ECLS-B was a more 

appropriate dataset for this analysis than available WIC administrative data. 

The national-level WIC administrative data come from a biennial census of 

WIC participants in the month of April collected since 1992. WIC administrative data provide valuable information on WIC participation and program 

characteristics, which are published in a series of USDA reports (see, for 

example, USDA (2010b)). Although administrative data provide the most 

accurate count of program participants, there is not suffi cient information to 

link members of a single household that receives WIC or to follow changes in 

a household’s WIC participation over time.

Additional Data Sources

Because some WIC policies vary at the State level, we used a variety of 

State-level data:

• 2000 data on State policies from WIC Participants and Program 

Characteristics 2000, including the benefi ts of WIC food packages (e.g., 

the value of the food package) and the transaction costs of enrolling in 

WIC and receiving the food packages (e.g., whether WIC vouchers are 

issued monthly or less frequently). For more information on these policies, see “Appendix A: State-Level WIC Policies and Practices.”

• Information on the number of WIC-only stores (stock only or predominantly WIC food items and serve only or predominantly WIC customers) 

in the State from The Integrity Profi le Report for Fiscal Year 2000. 

12All unweighted sample sizes were 

rounded to the nearest 50 per NCES 

rules governing use of restricted data.

13There was variation in the age 

of the survey child at the time of the 

9-month survey. For example, over half 

of the ECLS-B survey children were 

over 9 months old at the fi rst wave. 

However, very few (about 10 percent) 

were 12 months of age or older.

14Nonresponse rates for the second 

wave of the survey were fairly similar 

across maternal education, region of 

residence, and child’s race ethnicity 

(Nord et al., 2006). Survey instruments 

are available from NCES at http://nces.

ed.gov/ecls/Birth.asp.
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• 2000 State Medicaid income-eligibility thresholds for pregnant women 

(National Governors Association, 2001) in our determination of respondents’ eligibility for WIC.

We relied on 2000 data, the most recent information available on WIC State 

policies and the year during which many mothers in the sample were pregnant. It is unlikely that WIC State policies changed between 2000 and 2002 

(the period of our study), as Bitler and Currie (2005a) and USDA (2002) 

noted that these policies changed little during the 90s. Therefore, households that were deciding whether to enter WIC in the postnatal period or 

exit WIC in the child period most likely faced the same policies that were 

in place in 2000.

Coding WIC Eligibility and Participation

To be eligible to receive WIC services, an individual must meet categorical, 

income, and nutritional risk requirements. To meet the income requirement, 

a household must have income at or below 185 percent of the poverty line or 

participate in the Food Stamp Program, TANF, or Medicaid. We calculated 

the household income-to-poverty ratio using household income over the year 

before the 9-month survey, household size from the 9-month survey, and 

U.S. Department of Health and Human Services poverty guidelines. Because 

income information is bracketed in the ECLS-B, the midpoint of each bracket 

was used to calculate the income-to-poverty ratio. 

Because Medicaid participants are deemed adjunctively eligible for WIC, 

we considered all women who reported prenatal Medicaid participation as 

eligible for WIC. In addition, the income threshold for Medicaid eligibility 

varies by State and can be higher than the income threshold for WIC eligibility. If the State’s income threshold for Medicaid eligibility was higher than 

185 percent of the income-to-poverty ratio, we used the Medicaid threshold to 

estimate eligibility.15

There were some notable limitations to using the ECLS-B for coding WIC 

eligibility that may infl uence our results. First, adequate information was 

not available to precisely model changes in eligibility over the three periods 

of our study. Household incomes vary over time, affecting whether any one 

household would be determined to be eligible at an actual WIC offi ce at a 

given time. Ideally, adequate information would be available to estimate eligibility for the prenatal, postnatal-infant, and child periods separately. Instead, 

we focused on a fi xed sample of households where the mother was eligible 

based on her annual income during the year before the 9-month survey and 

based on her receipt of prenatal Medicaid. Therefore, the income measure 

used to estimate WIC eligibility captured income during the prenatal and 

postnatal period.16 We examined the role of estimated changes in eligibility 

status in our analysis of WIC exits when the survey child reached 1 year old.

Another issue related to the use of annual household income to estimate 

eligibility was that WIC agencies do not necessarily use annual income to 

determine eligibility, since they have wide discretion over the period used 

to determine a household’s income (Ver Ploeg and Betson, 2003). Ver Ploeg 

and Betson (2003) noted that, given WIC certifi cation periods, a researcher’s 

use of annual income to estimate eligibility will underestimate the number 

15This is an upper bound estimate 

of the number of WIC-eligible households, since a number of States have 

Medicaid income eligibility thresholds 

above 185 percent of the poverty line. 

We created a lower bound estimate of 

WIC-eligible households that included 

those with income above 185 percent 

of the poverty line only if the mother 

participated in Medicaid in the prenatal 

period, and the estimation results were 

quite similar.

16There was variation in the age 

of the survey child at the time of the 

9-month survey, so the period of the 

annual income measure will also vary. 

For example, 9 percent of the analysis 

sample was between 12 and 17 months 

old at the time of the 9-month survey.
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of eligible households, because households with annual income above 185 

percent of the poverty guideline but with at least 1 month of income eligibility will be misclassifi ed as ineligible. We found that 250 households in the 

sample reported prenatal WIC participation, but were coded as ineligible.17

Based on the midpoint of the income brackets, a household whose income 

falls within an income bracket that contains the relevant eligibility threshold 

may be assigned the wrong eligibility status. We tested other methods of 

coding eligibility, including a more restrictive measure that considered only 

households with income below the bracket that contained the WIC eligibility 

threshold. We found that the primary regression results were not sensitive to 

our eligibility defi nition. 

The ECLS-B does not include data to determine whether a woman is at nutritional risk. However, research that used nationally representative data with 

information on medical and dietary risk characteristics estimated that at least 

97 percent of women, infants, and children ages 2-5 years who are incomeeligible for WIC also met the program’s criteria for nutritional risk (Ver Ploeg 

and Betson, 2003). The study also concluded that the prevalence of nutritional risk among children ages 1-2 years was likely as high as for the other 

groups of WIC participants (Ver Ploeg and Betson, 2003).

Finally, the ECLS-B does not have information on prenatal participation in 

the Food Stamp Program or TANF, so we cannot account for households who 

would be income-eligible for WIC through participation in these programs. 

This will lead us to misclassify as ineligible households with annual income 

above 185 percent of the poverty line, but that participated in either the Food 

Stamp Program or TANF in the prenatal period. Given the stricter eligibility 

criteria for these two programs, however, this type of misclassifi cation was 

likely minimal.

WIC participation was estimated for three distinct periods: a prenatal period, 

a postnatal-infant period from birth until the child’s fi rst birthday, and a child 

period. In this study, the child period extends from the child’s fi rst to second 

birthday. While children may participate in WIC until their fi fth birthday, the 

ECLS-B data used for this study did not extend for that length of time. We 

estimated WIC participation based on responses to a series of questions about 

WIC participation in the fi rst two waves of the survey. We tracked only the 

WIC participation of the mother-child survey pair and did not account for the 

participation of older children in the household. 

A household was coded as a prenatal participant if the mother indicated 

that she participated in WIC prior to giving birth. Due to the timeframe 

and wording of the WIC questions, it was diffi cult to fully capture the WIC 

participation of each individual in the household during the postnatal-infant 

period (i.e., the year after the child’s birth). Therefore, we coded WIC 

participation in the postnatal-infant period at the household level, capturing 

participation by the mother, the infant, or both. A household was considered 

a participant in the postnatal-infant period if the mother responded that she 

used WIC vouchers to buy food for herself during the 6 months after giving 

birth, or if the mother used WIC vouchers to buy food for herself, the survey 

child, or twin during the 30 days before the 9-month survey and the child 

or twin was less than 12 months old at the time. Finally, a household was 

17There are other explanations for the 

presence of 250 ineligible WIC participants in the ECLS-B (approximately 

5.3 percent of the analysis sample), 

such as misreporting income to the 

WIC agency or misreporting income 

or WIC participation in the ECLS-B.
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considered a participant in the child period if the mother responded that the 

survey child or the twin of the survey child received WIC benefi ts in the last 

30 days and the survey child was over 12 months old at the time.

Our measures of participation did not capture the duration of participation in 

a given period. It was easier to discuss transitions into and out of the prenatal, 

postnatal-infant, and child periods as if the transitions all occurred at the 

thresholds of “birth” and “fi rst birthday.” Strictly speaking, not all transitions 

occurred at those thresholds. Nevertheless, our measures of participation still 

provided an informative analysis sample to examine the factors that infl uenced whether a household delays entry into WIC or exits from the program.

Constructing the Analysis Sample

We constructed a sample of 8,250 mother-child pairs from the 10,700 children in the ECLS-B, of which 4,650 were estimated to be eligible for WIC 

based on information from the 9-month dataset. We used the following 

criteria to restrict the sample (the number of observations excluded for each 

criterion in parentheses) to: 

• Observations with State identifi ers (100); 

• Households with parents who participated in the second wave of data 

collection (850);18

• Households with the biological mother of the survey child (150); 

• One mother-child pair per household, even if the woman had a multiple 

birth (750);19 

• Households with a survey child 18 months of age or younger in the fi rst 

wave of data (50). We excluded mothers of infants older than 18 months 

at the 9-month data collection because, due to the structure of the survey, 

we cannot ascertain their prenatal WIC participation status; 

• Households that provided information on WIC participation in all 

periods (100); and20 

• Observations with complete information for all relevant variables, with 

the exception of maternal welfare use as a child (500).21 Due to the relatively high number of missing values on the mother’s use of welfare as 

a child, we assigned the mode to each of the approximately 100 missing 

value data points, and included a variable in the regression analysis that 

indicated whether the observation was missing data on mother’s use of 

welfare as a child.

Table 1 compares the analysis sample of postnatal-infant participants with 

eligible nonparticipants. Among eligible households, those that chose to 

participate in WIC during at least the postnatal-infant period were more 

disadvantaged than those who never participated. For example, postnatalinfant participants were more likely to have less than a high school education, to be younger, to be unmarried, to have income that falls below the 

poverty line, and to participate in other assistance programs than their 

nonparticipant counterparts.

18We estimated equations that 

explained panel attrition among all 

households as a function of WIC 

eligibility and among WIC-eligibles as 

a function of WIC participation (results 

available from authors). Controlling for 

a number of demographic variables, we 

found that households eligible for WIC 

were slightly more likely (1.4 percentage points) to exit between the fi rst 

and second waves of the survey. WIC 

participation was not associated with 

the probability of attrition between the 

fi rst and second waves of the survey.

19In less than 1 percent of households 

with twins, the household reported that 

only one of the twins participated in 

WIC. In those cases, we counted the 

mother-child pair as a participant if 

either the child or the twin participated.

20Households that participated in 

WIC during the prenatal period, but 

were coded as ineligible, were excluded from the analysis sample (250). 

Because these ineligible participants 

were signifi cantly more advantaged, on 

average, than eligible households, and 

we could not determine why they were 

misclassifi ed, we excluded them from 

the analysis. We found that our results 

were largely robust to the inclusion of 

the ineligibles in the analysis sample.

21The observations excluded for 

missing data had very similar socioeconomic characteristics to those 

included in the analysis sample. Probit 

regression analysis indicated that 

Hispanics (relative to non-Hispanic 

Whites), high school and college graduates (relative to high school dropouts), 

mothers age 20 and older (relative to 

teens), those in the Midwest or South 

(relative to the West), and those in 

areas with a population of 2,500 to 

49,999 (relative to those in cities with 

a population of 50,000 or more) were 

slightly less likely to be excluded from 

the analysis sample due to missing data 

(results available from authors).
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Table 1

Characteristics of WIC participants and eligible nonparticipants

 Proportion of

 Proportion of participants

 eligible in postnatal- 

 nonparticipants infant period

Mother’s characteristics:

Non-Hispanic White 0.613* 0.391

Non-Hispanic Black 0.074* 0.226

Hispanic 0.242* 0.332

Other 0.071* 0.050

Did not graduate high school 0.236* 0.474

High school graduate 0.249 0.281

Some college or vocational/technical degree 0.343* 0.218

College degree 0.172* 0.027

Younger than 20 years old 0.059* 0.136

Age 20-34 0.770 0.776

Age 35 or older 0.171* 0.087

Mother is a U.S. citizen 0.846* 0.787

Mother’s relationship status:

Married 0.747* 0.420

At least one other child under age 5 in household 0.455* 0.393

At least one child 5-17 years old in household 0.471 0.458

Child is twin or higher-order birth 0.011* 0.017

Income, employment, and assets:

Household income below poverty level 0.210* 0.483

Household income between poverty level and 185

 percent poverty 0.541* 0.394

Household income above 185 percent poverty level 0.249* 0.123

Household income increased between surveys 0.611* 0.461

Owns home 0.477* 0.214

Mother employed during year before birth 0.660 0.650

Mother did not work anytime after birth 0.353 0.321

Program participation:

Participated in other programs since birth of child 0.308* 0.761

Mother received cash welfare most/all of childhood 0.022* 0.065

Mother received cash welfare some/half of childhood 0.040* 0.090

Mother did not receive cash welfare as a child 0.938* 0.844

Prenatal care and infant health:

Prenatal care paid by private insurance 0.644* 0.227

Prenatal care paid by Medicaid 0.247* 0.664

Prenatal care paid by neither Medicaid 

 nor private health insurance 0.099 0.091

No prenatal care received 0.010 0.019

Mother smoked at least 100 cigarettes 

 during her lifetime 0.359 0.381

Child never breastfed 0.265* 0.411

Child breastfed for less than 6 months 0.358 0.383

Child breastfed 6 months or more 0.378* 0.206

Child had low birthweight 0.065* 0.082

—continued
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Table 1

Characteristics of WIC participants and eligible 

nonparticipants—continued

 Proportion of

 Proportion of participants

 eligible in postnatal- 

 nonparticipants infant period

Region and urbanicity:

Northeast 0.128 0.141

Midwest 0.225 0.201

South 0.309* 0.413

West 0.338* 0.246

Population of 50,000 and over 0.729* 0.681

Population of 2,500 to 49,999 0.121 0.148

Population less than 2,500 0.150 0.171

State-level WIC policies and practices in 2000:

SSI confers WIC eligibility 0.093 0.085

School lunch confers WIC eligibility 0.164 0.141

Food packages tailored for type of milk 0.837 0.864

Food packages tailored to reduce sucrose 0.093 0.095

WIC voucher issued monthly 0.283* 0.229

Average retail value of WIC food packages ($s) 49.258 49.385

WIC offi ces per 1,000 below the poverty level 0.072 0.071

WIC-only stores per 1,000 below the poverty level 0.019 0.016

All nutritional risk criteria documented 0.804* 0.721

Dietary intake information required of all participants 0.854 0.863

Twenty-four hour recall used to obtain dietary 

 intake information 0.841* 0.794

Observations 700 3,700

SSI=Supplemental Security Income.

* Indicates that the value is signifi cantly different from that of eligible postnatal-infant participants 

at the 5 percent level using a two-tailed test.

Notes: “Eligible nonparticipants” are mother-infant pairs who were eligible for WIC, but did not 

participate between the mother’s pregnancy and the child’s second birthday. “Participants in the 

postnatal-infant period” are eligible households that participated between the birth of the child 

and the child’s fi rst birthday. Statistics are weighted. Sample sizes are rounded to the nearest 

50, per National Center for Education Statistics’ regulations. 

Source: Authors’ calculations using the Early Childhood Longitudinal Study-Birth Cohort.
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Methods

A Conceptual Model 

of Household Program Participation

Individuals who are eligible for benefi ts from means-tested transfer programs 

do not always receive them, prompting research on nonparticipation among 

potentially needy households. Most economic research uses a cost-benefi t 

framework to explain the participation decision of eligible individuals. A 

utility-maximizing individual will participate if the benefi ts outweigh the 

costs associated with participation. This model may also explain the timing 

of participation, with an individual re-evaluating her decision to participate in 

the program at certain intervals.

As described by Currie (2006), economic research has focused on two primary 

costs of participation—stigma and transaction costs—to explain nonparticipation among eligible individuals. Stigma was fi rst incorporated into the costbenefi t framework by Moffi tt (1983), who describes stigma as the “disutility 

arising from participation in a welfare program per se” (p. 1023). A utilitymaximizing individual may feel embarrassed or ashamed of receiving assistance from the Government, particularly if others know about this assistance. 

Transaction costs are the costs (both money and time) associated with applying 

for a program, documenting eligibility, complying with program rules, and 

redeeming benefi ts.

The cost-benefi t framework assumes that participants have complete information about the costs and benefi ts of participation. Currie (2006) noted that 

research also considered whether a lack of information about the program 

and its eligibility criteria infl uenced program participation.22

Regression Analysis

We used probit regression analysis to estimate equations explaining: 

1. Delayed entry into the WIC program in the postnatal-infant period; 

and 

2. Exit from the program when a child reaches 1 year old. 

In the delayed entry equation, the dependent variable is a binary variable 

with a value of 1 if the household entered the WIC program in the postnatal-infant period, and 0 if the household participated in both the prenatal 

and postnatal-infant periods. In the early exit equation, the dependent variable is a binary variable with the value of 1 if the household exited the 

program after the child turns 1 year old, and 0 if the household participated 

in both the postnatal-infant and the child periods. As noted previously, the 

unit of analysis was the mother-child survey pair, which we also refer to as 

the household.

This empirical strategy allowed us to focus on the factors that explain delayed 

entry and early exit among participants. This sample restriction means, 

however, that our regression results must be interpreted as conditional on 

WIC participation during the postnatal-infant period. Thus, it should be noted 

22Most notably, Daponte, Sanders, 

and Taylor (1999) found evidence that 

providing nonparticipating households 

with information about their potential 

food stamp benefi ts increased participation, primarily among those who were 

eligible for large benefi ts.
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that the study results cannot be generalized to explain the behavior of those 

who do not participate in the postnatal-infant period and, in particular, households that never participate in WIC during any of the three study periods. 

The equations include independent variables that may infl uence the transition into and out of WIC through their infl uence on the size of the benefi ts, 

the transaction costs associated with participation, stigma, or the availability of program information. Many of the included variables could be 

attributable to more than one of these explanations; therefore, we did not 

assign each variable to a specifi c factor. We focused on households that 

participated in the program in an attempt to reduce the role of stigma as a 

possible explanation for periods of nonparticipation. In addition, we eliminated lack of program awareness as an explanation for households exiting 

after the child turned 1 year old since they had participated previously in 

WIC.23 The equations also included independent variables to control for 

socio-economic characteristics.24

The characteristics displayed in table 1 are included as explanatory variables in at least one of the regression equations. We included variables for 

the mother’s race and ethnicity (with non-Hispanic White as the basis), the 

mother’s education (with did not graduate from high school as the basis), the 

mother’s age (with age younger than 20 years as the basis), the mother’s citizenship status, the mother’s marital status, the presence of a child (other than 

the interview child or twin) under age 5 in the household, the presence of a 

child between the ages of 5 and 17 in the household, and whether the survey 

child is a twin or higher-order birth.

We included an indicator variable for household income below the poverty 

line and an indicator for household income between the poverty line and 

185 percent of the poverty line (with household income above 185 percent 

of the poverty line as the basis). In the early exit equation, we also included 

a variable that indicates whether household income increased between the 

9-month and the 2-year survey. The income variables were included to refl ect 

varying degrees of need for WIC benefi ts within the WIC-eligible population. 

We characterized the household’s assets with an indicator variable for home 

ownership. We included an indicator variable for being employed any time 

during the 12 months prior to the child’s birth and, in the early exit equation, 

a variable to capture the mother’s return to work after giving birth.

We captured the mother’s experience with other assistance programs in the 

early exit equation with an indicator variable for participation in TANF, 

the Food Stamp Program, or Medicaid since the birth of the child. We also 

included variables to capture the mother’s use of welfare as a child (with no 

cash welfare receipt as the basis).

We included variables to describe characteristics related to a woman’s 

prenatal care and her smoking history. The equations included variables that 

indicated whether the woman had prenatal care other than her WIC visits and 

how she paid for it (with payment through private insurance as the basis) and 

a variable that indicated whether the mother had smoked at least 100 cigarettes during her lifetime.

23A lack of program awareness could 

still play a role in the delay of WIC enrollment until after the birth of a child.

24It should be noted that some of the 

variables included as explanatory variables, such as other program participation, may be jointly determined with 

WIC participation.
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Two variables in the early exit equation captured the initiation and duration 

of breastfeeding. One variable indicated that the child was never breastfed 

and the other variable indicated that the child was breastfed for less than 6 

months (with the child breastfed 6 months or more as the basis). An additional variable in the early exit equation indicated whether the child was 

low birthweight.

We included indicator variables for the region of residence (with residence in 

the West as the basis) and for the population size of the locality for the household (with population of 50,000 and above as the basis). 

We included variables to capture State-level WIC policies that may affect 

WIC participation. Understanding the relationship between State-level WIC 

policies and WIC participation can help inform decisions regarding policy 

design. However, these policies are likely to be correlated with other unobserved characteristics of the State, and therefore the coeffi cient estimates 

on these variables should be interpreted with caution. A number of these 

policies are expected to decrease the transaction costs of WIC participation, 

thus decreasing the likelihood of delayed entry or early exit. In some States, 

household receipt of Supplemental Security Income or certifi cation for free or 

reduced-price meals in the National School Lunch Program confers income 

eligibility for WIC, so participants in these programs do not have to document income to establish income eligibility for WIC. The number of WIC 

offi ces per 1,000 people living in poverty per State is included as a measure 

of access to the program. WIC-only stores are designed to facilitate the 

redemption of WIC vouchers and reduce the stigma of doing so. Therefore, 

we also included the number of WIC-only stores per 1,000 people living in 

poverty in the State.

Another set of State policy variables may increase the transaction costs of 

WIC participation, thus increasing the likelihood that households will delay 

entry or exit early. One variable indicated whether States require prenatal 

WIC participants to pick up WIC vouchers every month, rather than every 2 

or 3 months. A variable was included to indicate that the State documents all 

identifi ed nutritional risks of participants, rather than just the primary nutritional risks. We included an indicator variable for whether WIC offi ces in the 

State collected dietary intake information from all, rather than just high-risk, 

participants and an indicator variable for whether dietary intake information 

was collected through 24-hour recall, which is estimated to be more time 

consuming than a food frequency checklist, the other primary method for 

collecting dietary intake information (Institute of Medicine, 2002). 

Finally, three variables were included to represent State-level differences in 

WIC benefi t packages. As mentioned earlier, larger perceived benefi ts were 

expected to increase the likelihood of entering early or exiting late. Two of 

the variables indicated whether a certifi ed WIC staff person was allowed by 

the State to tailor an individual’s food package according to their nutritional 

needs or preferences. One variable indicated whether the State allowed caseworkers to specify the type of milk to reduce fat, lactose, or calories, while 

another variable indicated whether the State allowed the sucrose content of 

cereal to be reduced. It is not clear how these tailoring practices will infl uence WIC participation. The average retail value of the WIC food package, 
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which can vary across States as a result of food package tailoring practices 

and differences in food prices, was also included.

All descriptive and regression analyses were weighted using a weight 

constructed to refl ect population totals and to adjust for survey nonresponse.25

The standard errors of all regression models were adjusted to account for 

heteroskedasticity and for clustering at the State level since all mothers in a 

State face the same WIC policies. The results from the probit analyses are 

presented as marginal effects evaluated at the means of the independent variables. The results from the multinomial logit regression analysis are presented 

as odds ratios.

25For more information on the construction of the weights in the ECLS-B, 

see Nord et al. (2006).
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Results on Dynamic 

WIC Participation Patterns

We conducted two types of analysis of WIC participation dynamics for 

WIC-eligible households. 

1. A descriptive analysis of the estimated prevalence of WIC dynamic 

participation patterns. 

2. A multivariate regression analysis of the factors that may explain the 

WIC dynamic participation patterns.

Descriptive Analysis 

of Dynamic Participation Patterns

Table 2 shows the eight possible transitions into and out of WIC participation 

between the prenatal period, the postnatal-infant period, and the child period 

among eligible households. For example, pattern 1 describes a household that 

participates in all three study periods, while pattern 2 describes a household 

that participates in the fi rst two periods and exits the program at the child 

period. Patterns 1 through 8 describe all possible transitions over the three 

study periods.

The estimated prevalence of each of the eight dynamic participation patterns 

shows that about half (51.2 percent) of eligible households participated in 

WIC during all three periods of the study (pattern 1), while 15.6 percent 

never participated (pattern 8). The remaining 33.2 percent of eligible households participated in either one or two, but not all, of the three study periods 

(patterns 2 through 7). 

Table 2 also shows the distribution of participation patterns within the 

subgroup of participants in each time period. For example, while households 

that participated in all three study periods comprised 51.2 percent of all 

eligible households, they comprised 74.9 percent of prenatal participants.

Table 2

WIC participation patterns of mother/child pairs from prenatal period to child period, among U.S. children 

born in 2001

Participation 

pattern

Participate in period? Percent with each participation pattern 

Prenatal period

Postnatalinfant period Child periodAll eligible 

households

Prenatal 

participants

Postnatalinfant 

participants

Child 

participants

———————— Percent ————————

1 Yes Yes Yes 51.2 74.9 64.7 78.7

2 Yes Yes No 14.0 20.5 17.7

3 Yes No Yes 1.7 2.5 2.7

4 Yes No No 1.4 2.0

5 No Yes Yes 9.8 12.4 15.1

6 No Yes No 4.1 5.2

7 No No Yes 2.3 3.5

8 No No No 15.6 

Notes: Percentages are weighted. A blank cell indicates that the participation pattern is not exhibited by participant subgroup.

Source: Authors’ calculations using the Early Childhood Longitudinal Study-Birth Cohort.
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Comparability of ECLS-B Coverage Rates 

and Offi cial Coverage Rates

The information in table 2 can be used to estimate WIC coverage rates within the 

longitudinal framework of the ECLS-B, which we refer to as ECLS-B coverage 

rates. As noted previously, the ECLS-B does not have adequate information to 

estimate eligibility separately for the prenatal, postnatal-infant, and child periods. 

We created an eligible sample using data from the 9-month survey, which most 

closely matched the prenatal and postnatal-infant periods. Therefore, our ECLS-B 

coverage rates were derived by dividing the number of eligible households that 

participated in WIC in each period by a fi xed number of eligible households. In 

contrast, the offi cial WIC coverage rates were calculated using cross-sectional 

data on the number of WIC participants (either in total or by category) relative 

to the estimated number of eligible individuals in that category. The ECLS-B 

coverage rates are not intended to replace the offi cial methodology for computing 

coverage rates. Instead, we estimated the ECLS-B coverage rates to assess their 

comparability with offi cial coverage rates.

We found that the ECLS-B coverage rates, created by tracking the same set of 

eligible mother-child pairs over time, followed the same hump-shaped pattern 

observed in the offi cial 2007 WIC coverage rates in fi gure 1. The ECLS-B 

coverage rate among prenatal households was 68.3 percent (the sum of rates 

for participation patterns 1, 2, 3, and 4 in table 2). The ECLS-B coverage 

rate increased to 79.1 percent in the postnatal-infant period (the sum of rates 

for participation patterns 1, 2, 5, and 6), and fell to 65.0 percent in the child 

period (the sum of rates for participation patterns 1, 3, 5, and 7). The most 

notable disparity was seen in the child period, where the ECLS-B coverage 

rate of 65.0 was higher than the offi cial WIC coverage rate for children, 

which has ranged from 45.0 to 47.3 percent in recent years (USDA, 2009). 

This disparity is likely a result of two major differences in the measures. 

First, the ECLS-B coverage rate used data only up to the child’s second 

birthday, while the offi cial WIC coverage rates for children used data on children up to their fi fth birthday. Second, the ECLS-B coverage rate calculation 

relied on a fi xed sample of eligible households, while the offi cial coverage 

rate used estimates of concurrent numbers of eligible households.

In addition to producing comparable patterns of WIC coverage over time, the 

ECLS-B produced similar demographic statistics on WIC participants as those 

generated using administrative data. Tiehen and Jacknowitz (2008) demonstrated that the demographic characteristics, such as race, ethnicity, and age, 

of prenatal WIC participants in the ECLS-B were quite similar to those of 

participants in administrative data. The comparability of coverage rates and the 

demographic characteristics of WIC participants is evidence that the ECLS-B 

data are appropriate for our analysis of WIC participation dynamics.

Dynamic WIC Participation Rates

In table 3, we arranged the eight possible WIC dynamic participation patterns 

into groups that display the dynamic transitions in participation that are the 

focus of our study. Panel A of table 3 shows the percentage of WIC participants who remained in the program from one study period to the next, as 

well as the percentage who exited the program between study periods. As 
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shown in panel A, almost all prenatal participants (95.4 percent) stayed in the 

program during the postnatal-infant period; only 4.6 percent left the program 

between the prenatal and postnatal-infant periods. While it is unusual for a 

prenatal WIC participant to leave WIC during the postnatal-infant period, 

the rate of exit between the postnatal-infant period and the child period was 

much higher. Almost a fourth (22.9 percent) of postnatal-infant participants 

left WIC when the survey child turned 1 year old.26

Panel B of table 3 displays the percentage of WIC participants in the later two 

study periods who had participated in a previous period, and the percentage 

that entered the program between study periods. About a fi fth (17.6 percent) 

of postnatal-infant participants entered WIC after the survey child’s birth.27 In 

contrast, it was unusual for a participating household to enter WIC between the 

survey child’s fi rst and second birthdays. Almost all (96.5 percent) participants 

in the child period had received WIC in a previous period.

In summary, among households that participated in WIC at some point during 

the study periods, the two most common transitions in participation were: 

1. From nonparticipation in the prenatal period to participation in the 

postnatal-infant period (delayed entrance); and 

2. From participation in the postnatal-infant period to nonparticipation 

in the child period (early exit). 

Given the importance of these two transitions, we focused on postnatal-infant 

participants, examining the factors associated with a delay in their WIC 

enrollment until after an eligible woman gives birth and the exit from WIC 

after a child turns 1 year old.

Results for Postnatal-Infant WIC Entrants

As shown in table 4, delayed entrants appear to be more advantaged than 

households that participated in both the prenatal and postnatal-infant periods 

26It is important to note that we only 

observed households up to the second 

wave of the survey, when the child was 

approximately 2 years old.

27The fi nding that 17.6 percent of 

postnatal-infant participants entered 

WIC after the survey child’s birth is 

consistent with evidence from Cole et 

al. (2001) that 22 percent of mothers of 

WIC infants did not participate in WIC 

while pregnant.

Table 3

Entry and exit patterns of eligible WIC households from prenatal period to child period

Participation 

pattern

Prenatal 

participants

Postnatal-infant 

participants

Child 

participants

—————— Percent ——————

Panel A: Continuation and exit rates

Continuation rate for prenatal to postnatal-infant period 1 and 2 95.4

Exit rate for prenatal period 3 and 4 4.6

Continuation rate for postnatal-infant period to child period 1 and 5 77.1

Exit rate for postnatal-infant period 2 and 6 22.9

Panel B: Previous participation and entry rates

Previous participation for postnatal-infant period 1 and 2 82.4

New entry rate for postnatal-infant period 5 and 6 17.6

Previous participation for child period 1, 3, and 5 96.5

New entry rate for child period 7 3.5

Notes: See table 2 for a description of each participation pattern. Percentages are weighted. A blank cell indicates that the participation pattern is 

not exhibited by participant subgroup.

Source: Authors’ calculations using the Early Childhood Longitudinal Study-Birth Cohort.
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with respect to maternal education, marital status, participation in other 

assistance programs, employment, and utilization of private insurance to pay 

for prenatal care. The estimated marginal effects from the probit regression 

of postnatal WIC entry are displayed in table 5. It is important to note that, 

because the analysis compared those who entered in the postnatal period with 

those who entered in the prenatal period, it did not provide information on the 

factors that prevent WIC receipt altogether. 

The regression results supported the fact that WIC participants in better 

economic circumstances were more likely to delay WIC participation until 

the postnatal-infant period. WIC participants with better maternal education 

and higher household income relative to the poverty line were more likely 

to delay entrance until the postnatal-infant period. For example, a household 

with a mother holding a college degree was 8.6 percentage points more likely 

to delay entry than a household with a mother without a high school degree. 

These factors suggest that households that delay entry into the program may 

not have been eligible in the prenatal period. 

The regression results also indicated a strong relationship between prenatal 

Medicaid coverage and prenatal receipt of WIC. Compared with those 

covered by private health insurance, WIC participants with Medicaid 

coverage during the prenatal period were 15.0 percentage points less likely to 

delay WIC participation until the postnatal period. Given that participation 

in Medicaid provides adjunctive eligibility for WIC, these fi ndings were not 

surprising. Those with neither private insurance nor Medicaid were also less 

likely to delay receipt of WIC until the postnatal period, although the estimated marginal effect was relatively small. 

There was also evidence that geographic location may be a factor in the 

timing of WIC participation; women who reside in the Northeast and those 

who reside in urban areas with a population of at least 50,000 (the omitted 

category) were more likely to delay participation until after having a child.

State policies also infl uence the decision to delay participation. WIC participants residing in States where participation in SSI confers WIC eligibility 

were less likely to delay, while those living in States that allow the food 

package to be tailored to reduce sucrose content were more likely to delay. 

Counter to expectations, participants in States with a greater number of WIC 

offi ces per 1,000 individuals living below the poverty level were more likely 

to delay. As noted previously, it was diffi cult to identify the effect of Statelevel policies in a cross-sectional analysis, given that they may be correlated 

with other unobserved State characteristics. To test the sensitivity of our 

regression results to the inclusion of the State policy variables, we examined 

two other specifi cations of both the delayed entry and early exit equations. 

The two other specifi cations were identical to our full specifi cation, except 

that the fi rst excludes the WIC State policy variables and the second includes 

State fi xed effects (results available from authors). The results were generally 

not sensitive to these two alternative specifi cations.

Results for Participants Exiting WIC 

As shown in table 4, households that exited the program after a child turned 

1 year old were more economically advantaged than those that remained on 
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Table 4

Characteristics of postnatal-infant WIC participants, 

by the timing of WIC participation

 Proportion that Proportion that

 delayed entry: exited early:

 Enters WIC Exits WIC

 in postnatal period as a child

 Yes No Yes No

Mother’s characteristics:

Non-Hispanic White 0.400 0.389 0.440* 0.376

Non-Hispanic Black 0.224 0.227 0.247 0.220

Hispanic 0.316 0.336 0.260* 0.354

Other 0.061 0.048 0.054 0.049

Did not graduate high school 0.423* 0.485 0.409* 0.493

High school graduate 0.248 0.288 0.303 0.274

Some college or vocational/technical degree 0.280* 0.205 0.238 0.213

College degree 0.049* 0.022 0.050* 0.020

Younger than 20 years old 0.132 0.137 0.124 0.140

Age 20-34 0.745 0.783 0.827* 0.761

Age 35 or older 0.124* 0.079 0.049* 0.099

Mother is a U.S. citizen 0.767 0.792 0.850* 0.769

Mother’s relationship status:

Married 0.478* 0.408 0.417 0.422

At least one other child under age 5 

 in household 0.381 0.395 0.406 0.389

At least one child age 5-17 years old 

 in household 0.476 0.454 0.420 0.470

Child is twin or higher-order birth 0.022 0.016 0.014 0.018

Income, employment, and assets:

Household income below poverty level 0.430* 0.494 0.395* 0.509

Household income between poverty level 

 and 185 percent poverty level 0.429 0.387 0.423 0.385

Household income above 185 percent 

 poverty level 0.141 0.119 0.182* 0.106

Household income increased between 

 surveys 0.506* 0.448

Owns home 0.233 0.210 0.225 0.210

Mother employed during year before birth 0.706* 0.638 0.699* 0.635

Mother did not work anytime after birth 0.257* 0.340

Program participation:

Participated in other programs since 

 birth of child 0.719* 0.773

Mother received cash welfare most/all 

 of childhood 0.061 0.066 0.052 0.069

Mother received cash welfare some/half 

 of childhood 0.070 0.095 0.091 0.090

Mother did not receive cash welfare 

 as a child 0.869 0.839 0.857 0.841

Prenatal care and infant health:

Prenatal care paid by private insurance 0.375* 0.195 0.276* 0.212

Prenatal care paid by Medicaid 0.498* 0.699 0.620* 0.677

Prenatal care paid by neither Medicaid 

 nor private health insurance 0.081 0.093 0.077 0.095

No prenatal care received 0.047* 0.013 0.027 0.017

Mother smoked at least 100 cigarettes 

 during her lifetime 0.356 0.387 0.437* 0.365

—continued
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Table 4

Characteristics of postnatal-infant WIC participants, by the timing of 

WIC participation—continued

 Proportion that Proportion that

 delayed entry: exited early:

 Enters WIC Exits WIC

 in postnatal period as a child

 Yes No Yes No

Prenatal care and infant health:—continued

Child never breastfed 0.432 0.404

Child breastfed for less than 6 months 0.404 0.377

Child breastfed 6 months or more 0.165* 0.218

Child had low birthweight 0.080 0.082

Region and urbanicity:

Northeast 0.205* 0.127 0.127 0.145

Midwest 0.196 0.202 0.194 0.203

South 0.389 0.418 0.459* 0.399

West 0.210 0.253 0.220 0.253

Population of 50,000 and over 0.753* 0.666 0.716 0.671

Population of 2,500 to 49,999 0.120 0.154 0.150 0.147

Population less than 2,500 0.127* 0.180 0.135* 0.181

State-level WIC policies and practices in 2000:

SSI confers WIC eligibility 0.092 0.084 0.083 0.086

School lunch confers WIC eligibility 0.183* 0.132 0.146 0.140

Food packages tailored for type of milk 0.864 0.865 0.890* 0.857

Food packages tailored to reduce sucrose 0.107 0.092 0.161* 0.075

WIC voucher issued monthly 0.183* 0.239 0.175* 0.245

Average retail value of WIC food 

 packages ($s) 49.120 49.441 49.728* 49.282

WIC offi ces per 1,000 below the poverty 

 level 0.076 0.071 0.070 0.072

WIC-only stores per 1,000 below the poverty 

 level 0.014 0.017 0.014* 0.017

All nutritional risk criteria documented 0.750 0.715 0.720 0.722

Dietary intake information required of 

 all participants 0.857 0.864 0.826* 0.873

Twenty-four hour recall used to obtain 

 dietary intake information 0.757 0.802 0.794 0.794

Observations 700 2,950 800 2,900

SSI=Supplemental Security Income.

* Indicates that the value is signifi cantly different from that of those in the “no” category at the 5 

percent level using a two-tailed test.

Notes: Statistics are weighted. Sample sizes are rounded to the nearest 50, per National Center 

for Education Statistics’ regulations. No statistic is reported for variables that are not included in 

the delayed entry regression equation.

Source: Authors’ calculations based on the Early Childhood Longitudinal Study-Birth Cohort.
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Table 5

Marginal effects from probit regression: 

Delayed entry into WIC among postnatal-infant WIC participants

 Marginal Standard

 effect error

 (1) (2)

Mother’s characteristics:

Non-Hispanic Black -0.016 (0.027)

Hispanic -0.048* (0.027)

Other -0.008 (0.031)

High school graduate -0.016 (0.019)

Some college or vocational/technical degree 0.034* (0.020)

College degree 0.086* (0.052)

Age 20-34 -0.039 (0.029)

Age 35 or older -0.002 (0.039)

Mother is a U.S. citizen -0.037 (0.029)

Mother’s relationship status:

Married 0.025 (0.028)

At least one other child under age 5 in the household 0.003 (0.016)

At least one child age 5-17 years old in household 0.009 (0.016)

Child is twin or higher-order birth 0.025 (0.032)

Income, employment, and assets:

Household income below poverty level -0.036* (0.019)

Household income between poverty level and 

 185 percent poverty level -0.038** (0.019)

Owns home -0.005 (0.020)

Mother employed during year before birth 0.028* (0.015)

Program participation:

Mother received cash welfare most/all of childhood 0.007 (0.035)

Mother received cash welfare some/half of childhood -0.037 (0.042)

Prenatal care and mother’s smoking:

Prenatal care paid by Medicaid -0.150*** (0.025)

Prenatal care paid by neither Medicaid nor private 

 health insurance -0.082*** (0.019)

No prenatal care received 0.104 (0.075)

Mother smoked at least 100 cigarettes during her lifetime -0.002 (0.015)

Region and urbanicity:

Northeast 0.128* (0.069)

Midwest 0.025 (0.035)

South 0.047 (0.038)

Population between 2,500 and 49,999 -0.050** (0.019)

Population less than 2,500 -0.072*** (0.023)

State-level WIC policies and practices:

SSI confers WIC eligibility -0.055** (0.023)

School lunch confers WIC eligibility 0.053* (0.032)

Food packages tailored for type of milk -0.001 (0.034)

Food packages tailored to reduce sucrose 0.049* (0.025)

—continued
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the program along a variety of outcomes, including their household income 

relative to the poverty line, maternal employment before and after birth, and 

participation in other assistance programs. Interestingly, households that 

exited were less likely to have breastfed their child for 6 months or more.

Table 6 shows the estimated marginal effects from the probit regression 

of early exit from the WIC program. The estimation results in columns 1 

and 2 of table 6 provide further evidence that households exiting the WIC 

program after the child turns 1 year old were more advantaged than those 

that remained in the program. Households in which the mother has a college 

degree were more likely to exit, and those in which the mother had not been 

employed since the birth of her child were less likely to exit. In addition, 

there was a negative association between a participating household’s income 

relative to the poverty level and the likelihood that the household exits WIC. 

As noted previously, our analysis sample consists of households that were 

estimated to be eligible in the year before the 9-month survey. Therefore, it 

is possible that more advantaged households leave the WIC program because 

they lose their eligibility, which we did not capture in our primary analysis 

sample. Table 6 demonstrates that postnatal-infant WIC participants who 

experienced an increase in household income between the two waves of the 

survey were 6.0 percentage points more likely to leave WIC than those whose 

incomes remained constant or decreased.

In order to address the possible loss of program eligibility, we used data from 

the second wave of the ECLS-B to estimate eligibility for WIC after the child 

turned 1 year old. Unfortunately, the timing and structure of the survey questions in the second wave did not allow us to estimate WIC eligibility as 

Table 5

Marginal effects from probit regression: 

Delayed entry into WIC among postnatal-infant WIC participants—

continued

 Marginal Standard

 effect error

 (1) (2)

State-level WIC policies and practices:—continued

WIC voucher issued monthly -0.013 (0.034)

Average retail value of WIC food packages ($s) -0.004** (0.002)

WIC offi ces per 1,000 below the poverty level 0.294** (0.125)

WIC-only stores per 1,000 below the poverty level 0.049 (0.615)

All nutritional risk criteria documented 0.010 (0.035)

Dietary intake information required of all participants -0.001 (0.031)

Twenty-four hour recall used to obtain dietary intake 

 information -0.007 (0.038)

Observations 3,700

SSI=Supplemental Security Income.

*** p<0.01, ** p<0.05, and * p<0.1.

Notes: Estimates are weighted. Marginal effects were calculated at the means of the independent variables. Standard errors were adjusted to account for heteroskedasticity and multiple 

observations from the same State. The specifi cations included a variable that indicated data on 

maternal receipt of welfare as a child was missing. Sample sizes are rounded to the nearest 50, 

per National Center for Education Statistics’ regulations.

Source: Authors’ calculations based on the Early Childhood Longitudinal Study-Birth Cohort.
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precisely in the child period as in the year before the 9-month survey.28 Using 

a rough estimate of WIC eligibility, however, can shed some light on the role 

of loss of program eligibility on program exits. We estimated that 8.9 percent 

of all postnatal-infant WIC participants and 19.2 percent of exiting households lost WIC eligibility in the year prior to the second wave of the ECLS-B.

Columns 3 and 4 of table 6 display the results of the probit regression of child 

exits from WIC among the sample of roughly 90 percent of postnatal-infant 

WIC participants that were estimated to have remained WIC eligible after 

the survey child turned 1 year old (the restricted sample). Even among the 

sample that retained eligibility, the regression results indicated that WIC exits 

were more likely among more advantaged households, although the estimated 

marginal effects were not as large.

Among both the primary analysis sample and the restricted sample, WIC 

households in which the mother never breastfed or breastfed for less than 6 

months were more likely to exit than WIC households in which the mother 

breastfed for 6 months or more. This fi nding suggests that the transition from 

receipt of the infant food package, which contains infant formula, to receipt 

of the child food package may play a role in the decision to exit WIC. 

Self-Reported Explanations for Early Exits

The ECLS-B contains information from a subset of mothers on why they 

stopped receiving WIC benefi ts for their child.29 Mothers were asked:

 “Why are you no longer using WIC vouchers to buy food or formula for 

[CHILD] or [TWIN]?” 

Possible responses included: 

 “Not eligible anymore,” 

 “Eligible but denied benefi t due to lack of program funds,” 

 “No longer need food benefi t,” 

 “Program is too much effort (benefi ts are not worth the time and effort to 

get them),” 

 “Lack of transportation and/or scheduling problems,” and 

 “Temporary administration issues prevent child from participating (plan 

to reapply to program).” 

Mothers were allowed to choose only one response. Table 7 shows that 

approximately a third of exiting households reported that they no longer 

participated because they believed they were no longer eligible. Over a fourth 

(27.8 percent) of mothers reported that their children exited the program 

because they no longer needed the food benefi ts. For exiting households that 

reported a lack of eligibility or a lack of need, the program appears to be 

operating as intended. However, of exiting households that reported lack of 

eligibility, we estimated only a third lost eligibility in the year prior to the 

second wave of the ECLS-B. This discrepancy may be due to the limitations 

28There are two primary limitations 

to estimating WIC eligibility in the 

child period. The fi rst limitation is that, 

for over half of the primary analysis 

sample, the second wave of data collection occurred after the survey child 

turned 2 years old. For these households, the data collected on income 

during the previous 12 months did not 

cover the point at which they exited 

WIC. The second limitation is that the 

structure of the questions on program 

participation (used to determine adjunctive eligibility) between the two surveys 

made it diffi cult to ascertain the time 

period for program participation.

29Not all mothers were asked about 

the reasons for their children exiting the 

WIC program when the child turned 1 

year old. Mothers of children who exited 

during the fi rst wave of data were not 

asked about the reason for their exit. 

Households where only the mother 

participated in the postnatal-infant 

period and then exited were not asked 

the survey question.
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Table 6

Marginal effects from probit regressions: 

Early exit from WIC among postnatal-infant WIC participants

 Households estimated 

 Primary analysis to remain eligible 

 sample in child period

 Marginal Standard Marginal Standard

 effect error effect error

 (1) (2) (3) (4)

Mother’s characteristics:

Non-Hispanic Black 0.013 (0.023) 0.021 (0.026)

Hispanic -0.039* (0.021) -0.031 (0.023)

Other 0.010 (0.040) 0.034 (0.042)

High school graduate 0.024 (0.022) 0.024 (0.024)

Some college or vocational/technical 

 degree -0.001 (0.027) -0.004 (0.022)

College degree 0.224*** (0.065) 0.147** (0.069)

Age 20-34 0.022 (0.025) 0.029 (0.026)

Age 35 or older -0.108*** (0.035) -0.084* (0.039)

Mother is a U.S. citizen 0.041 (0.037) 0.040 (0.039)

Mother’s relationship status:

Married -0.002 (0.023) -0.013 (0.023)

At least one other child under age 5 

 in the household 0.029 (0.019) 0.024 (0.019)

At least one child age 5-17 years old 

 in household -0.014 (0.017) -0.008 (0.018)

Child is twin or higher-order birth -0.053*** (0.019) -0.034* (0.020)

Income, employment, and assets:

Household income below poverty level -0.141*** (0.031) -0.093** (0.037)

Household income between poverty 

 level and 185 percent poverty -0.097*** (0.026) -0.067* (0.033)

Household income increased 

 between surveys 0.060*** (0.019) 0.024 (0.019)

Owns home 0.006 (0.022) -0.003 (0.025)

Mother employed during year 

 before birth 0.008 (0.021) 0.008 (0.024)

Mother did not work anytime 

 after birth -0.033** (0.016) -0.024 (0.016)

Program participation:

Participated in other programs since 

 birth of child -0.041 (0.027) -0.039* (0.024)

Mother received cash welfare most/all 

 of childhood -0.037 (0.021) -0.026 (0.020)

Mother received cash welfare some/all 

 of childhood 0.005 (0.027) -0.001 (0.025)

Prenatal care and infant health:

Prenatal care paid by Medicaid -0.059** (0.031) -0.051* (0.029)

Prenatal care paid by neither Medicaid 

 nor private health insurance -0.032 (0.047) -0.014 (0.045)

No prenatal care received 0.102 (0.087) 0.118 (0.089)

Mother smoked at least 100 cigarettes 

 during her lifetime 0.048** (0.023) 0.038* (0.023)

Child never breastfed 0.048** (0.019) 0.051** (0.020)

Child breastfed child less than 6 months 0.041** (0.020) 0.054*** (0.016)

Child had low birth weight -0.005 (0.015) -0.008 (0.014)

—continued
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of our estimate of WIC eligibility in the child period, or it may indicate that 

these households were not clear about WIC eligibility rules.

In addition, other explanations cited by mothers, including that the program 

requires too much effort or that they have scheduling and/or transportation 

problems, suggest that the costs of participation may be a barrier to continued 

WIC participation for some children. Interestingly, very few households 

(less than 1 percent) reported that they were eligible for the program, but 

were denied benefi ts due to the lack of program funds. This fi nding offers 

important evidence that, although WIC is not an entitlement program, very 

few WIC households exit the program when a child turns 1 year old due to 

funding shortfalls. 

Table 6

Marginal effects from probit regressions: 

Early exit from WIC among postnatal-infant WIC participants—continued

 Households estimated 

 Primary analysis to remain eligible 

 sample in child period

 Marginal Standard Marginal Standard

 effect error effect error

 (1) (2) (3) (4)

Region and urbanicity:

Northeast -0.072 (0.051) -0.077 (0.044)

Midwest -0.016 (0.031) -0.018 (0.032)

South -0.033 (0.030) -0.033 (0.028)

Population between 2,500 and 49,999 -0.007 (0.035) -0.010 (0.035)

Population less than 2,500 -0.091*** (0.020) -0.076*** (0.020)

State-level WIC policies and practices 

 in 2000:

SSI confers WIC eligibility -0.032 (0.023) -0.040* (0.022)

School lunch confers WIC eligibility -0.015 (0.025) 0.003 (0.022)

Food packages tailored for type of milk 0.046* (0.025) 0.031 (0.023)

Food packages tailored to reduce 

 sucrose 0.127*** (0.031) 0.081*** (0.028)

WIC voucher issued monthly -0.062* (0.032) -0.063** (0.028)

Average retail value of WIC food 

 packages ($s) 0.000 (0.003) 0.001 (0.002)

WIC offi ces per 1,000 below the 

 poverty level -0.228* (0.125) -0.187 (0.120)

WIC-only stores per 1,000 below the 

 poverty level -0.575 (0.706) -0.827 (0.628)

All nutritional risk criteria documented 0.012 (0.029) 0.011 (0.025)

Dietary intake information required of 

 all participants -0.077*** (0.027) -0.070*** (0.022)

Twenty-four hour recall used to obtain 

 dietary intake information -0.008 (0.033) -0.008 (0.031)

Observations 3,700 3,350

SSI=Supplemental Security Income.

*** p<0.01, ** p<0.05, and * p<0.1.

Notes: Estimates are weighted. Marginal effects were calculated at the means of the independent variables. Standard errors were adjusted to account for heteroskedasticity and multiple 

observations from the same State. The specifi cations included a variable that indicated data on 

maternal receipt of welfare as a child was missing. Sample sizes are rounded to the nearest 50, 

per National Center for Education Statistics’ regulations.

Source: Authors’ calculations based on the Early Childhood Longitudinal Study-Birth Cohort.
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To gain further insight into these exits from WIC, we used multinomial logit 

regression to examine the factors associated with the four most common explanations for WIC exits. The regression results, presented in table 8, compare 

each of the four groups leaving WIC with those who stayed in the program. 

The estimates are presented as odds ratios, which indicate how the ratio of the 

probability of exiting WIC for a specifi c reason to the probability of remaining 

on the program changes with a 1 unit change in the independent variable. 

Therefore, an odds ratio greater than 1 implies that the characteristic was associated with an increased probability of leaving WIC for the specifi ed reason.

Households that were more economically advantaged had a greater chance of 

leaving WIC because they were no longer eligible or because they no longer 

needed the food benefi ts. WIC participants with more education and those 

who had an increase in income between the two surveys were more likely to 

exit the program due to reported ineligibility. Those with low income relative 

to the poverty line and those who participated in other assistance programs 

in the 9 months after the birth of the survey child were less likely to exit 

the program due to reported ineligibility. In addition, if the mother did not 

work after the birth of the survey child, there was a lower likelihood that the 

household would exit WIC due to a lack of need for food benefi ts.

No breastfeeding and a shorter duration of breastfeeding by the mother 

were associated with a greater chance that the household would leave 

WIC because the household no longer needed the benefi ts. This result 

corroborates the evidence from the probit regression on early exit that 

infant feeding practices play a role in the decision to exit the program and 

suggests that some nonbreastfeeding mothers who stop receiving infant 

formula when their child turns 1 year old may not see a need for the lowervalue WIC benefi ts available in the child package. It is important to note 

that the relationship between breastfeeding and WIC exits may differ in the 

context of the revised WIC food packages, which have been available since 

2009, after the period of this study.

The other two explanations for WIC exits indicated that the household was 

challenged by the effort required to participate in WIC. Living in the South 

or the Northeast was associated with a higher likelihood of exiting WIC 

Table 7

Explanations for WIC exits once the child turns 1 year old

Percent

Explanation reporting

Not eligible anymore 32.3

No longer need food benefi ts 27.8

Program is too much effort; benefi ts are not worth the time 26.2

Lack of transportation and/or scheduling problems 9.3

Other 2.5

Temporary administrative issues prevent participation, 

 but plan to participate again 1.3

Eligible but denied benefi ts due to lack of program funds 0.5

Observations 600

Notes: Percentages are weighted. Sample size is rounded to the nearest 50, per National 

Center for Education Statistics’ regulations.

Source: Authors’ calculations using the Early Childhood Longitudinal Study-Birth Cohort.
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because the program required too much effort and the benefi ts were not 

worth the time.30

Residing in a State that allows WIC food packages to be tailored to reduce 

sucrose was associated with a greater likelihood of exiting WIC for three of 

the four reasons discussed, but the policy was more strongly associated with 

WIC exits due to the program requiring too much effort and/or scheduling or 

transportation problems than to exits due to lack of perceived eligibility.

30It should be noted that when we 

make a Bonferroni adjustment to the 

signifi cance level cut-offs to account 

for the multiple hypotheses tested with 

the multinomial logit, the estimated 

effect of the region variables becomes 

insignifi cant.
30

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Table 8

Multinomial logit results: Factors associated with WIC exits, by reason for exit

No longer 

eligible

No longer 

need food 

benefi ts

Program too 

much effort, 

benefi ts not 

worth the time

Transportation

or scheduling 

problems

Mother’s characteristics:

Non-Hispanic Black 0.774 1.671** 1.556* 0.996

(0.185) (0.431) (0.401) (0.385)

Hispanic 0.716 1.298 1.141 0.769

(0.178) (0.372) (0.360) (0.358)

Other 0.956 0.883 0.899 1.074

(0.221) (0.271) (0.299) (0.480)

High school graduate 1.521** 1.333 1.181 0.701

(0.302) (0.288) (0.245) (0.240)

Some college or vocational/technical degree 1.548** 1.621** 0.750 0.836

(0.331) (0.380) (0.195) (0.315)

College degree 4.700*** 2.164 0.976 1.132

(1.407) (1.041) (0.551) (0.897)

Age 20-34 1.018 0.652* 0.895 1.531

(0.270) (0.159) (0.224) (0.665)

Age 35 or older 0.795 0.159*** 0.288** 0.960

(0.282) (0.090) (0.151) (0.649)

Mother is a U.S. citizen 1.203 0.930 1.150 0.789

(0.297) (0.268) (0.374) (0.358)

Mother’s relationship status:

Married 1.095 0.976 0.883 0.564*

(0.191) (0.194) (0.184) (0.190)

At least one other child under age 5 in household 0.862 1.519** 0.952 1.309

(0.141) (0.270) (0.177) (0.359)

At least one child age 5-17 years old in household 1.107 0.747 1.019 0.669

(0.173) (0.134) (0.182) (0.184)

Child is twin or higher-order birth 0.715 0.463* 0.785 2.045*

(0.206) (0.189) (0.266) (0.773)

Income, employment, and assets:

Household income below poverty level 0.260*** 0.496*** 0.708 1.539

(0.065) (0.135) (0.224) (0.804)

Household income between poverty level and 185 percent poverty 0.514*** 0.580** 1.107 1.096

(0.114) (0.149) (0.330) (0.576)

Household income increased between surveys 2.369*** 1.260 1.161 0.869

(0.382) (0.226) (0.210) (0.242)

Owns home 1.229 1.127 0.872 0.718

(0.218) (0.245) (0.203) (0.291)

Mother employed during year before birth 0.951 1.163 1.381 0.831

(0.175) (0.239) (0.291) (0.245)

Mother did not work anytime after birth 0.979 0.648** 0.964 1.147

(0.177) (0.142) (0.199) (0.342)

Program participation:

Participated in other programs since birth of child 0.610*** 0.691 0.791 0.913

(0.116) (0.160) (0.199) (0.380)

Mother received cash welfare most/all of childhood 1.280 0.217** 1.172 0.284*

(0.411) (0.130) (0.356) (0.213)

Mother received cash welfare some/half of childhood 1.758** 0.469** 0.625 1.154

(0.419) (0.169) (0.208) (0.443)

—continued
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Table 8

Multinomial logit results: Factors associated with WIC exits, by reason for exit—continued

No longer 

eligible

No longer 

need food 

benefi ts

Program too 

much effort, 

benefi ts not 

worth the time

Transportation

or scheduling 

problems

Prenatal care and infant health:

Prenatal care paid by Medicaid 0.666** 1.011 0.961 1.091

(0.133) (0.247) (0.248) (0.440)

Prenatal care paid by neither Medicaid nor private insurance 0.819 1.006 0.726 0.569

(0.235) (0.368) (0.327) (0.392)

No prenatal care received 0.725 1.519 2.462* 0.000

(0.460) (0.809) (1.147) (0.000)

Mother smoked at least 100 cigarettes during her lifetime 1.102 1.530** 1.457* 1.686*

(0.191) (0.299) (0.292) (0.516)

Child never breastfed 1.370 2.098** 1.125 1.199

(0.307) (0.629) (0.343) (0.543)

Child breastfed less than 6 months 1.178 1.747* 1.257 1.413

(0.252) (0.508) (0.373) (0.606)

Child had low birthweight 0.830 1.006 0.875 1.086

(0.155) (0.204) (0.178) (0.334)

Region and urbanicity:

Northeast 0.766 0.544 4.150** 1.729

(0.326) (0.266) (2.430) (1.314)

Midwest 1.330 0.942 1.642 0.872

(0.444) (0.348) (0.833) (0.535)

South 1.058 0.611 3.278** 1.482

(0.340) (0.223) (1.576) (0.915)

Population between 2,500 and 49,999 0.832 0.843 0.748 0.771

(0.185) (0.211) (0.213) (0.314)

Population less than 2,500 0.532*** 0.498** 0.758 0.295**

(0.124) (0.143) (0.194) (0.150)

State-level WIC policies and practices in 2000:

SSI confers WIC eligibility 1.022 0.987 0.432** 0.653

(0.300) (0.328) (0.176) (0.441)

School lunch confers WIC eligibility 0.621* 0.737 1.250 2.177

(0.172) (0.226) (0.417) (1.140)

Food packages tailored for type of milk 1.502 1.498 0.884 0.582

(0.442) (0.483) (0.299) (0.267)

Food packages tailored to reduce sucrose 1.805** 1.663 2.634*** 3.105**

(0.535) (0.548) (0.891) (1.549)

WIC voucher issued monthly 0.588 0.824 0.639 0.815

(0.208) (0.303) (0.345) (0.496)

Average retail value of WIC food packages ($s) 0.975 1.008 1.056** 0.991

(0.021) (0.024) (0.027) (0.041)

WIC offi ces per 1,000 below the poverty level 0.363 0.190 11.010 0.410

(0.462) (0.286) (18.200) (1.223)

WIC-only stores per 1,000 below the poverty level 42.840 0.036 10.520 100.000

(268.600) (0.236) (98.630) (1146.000)

All nutritional risk criteria documented 1.181 0.758 1.138 0.670

(0.318) (0.223) (0.359) (0.300)

Dietary intake information required of all participants 0.477*** 0.718 1.797 2.528

(0.128) (0.209) (0.662) (1.466)

Twenty-four hour recall used to obtain dietary intake information 0.888 0.860 1.070 0.878

(0.212) (0.232) (0.306) (0.372)

Constant 0.608 0.102 0.001*** 0.0215

(0.805) (0.152) (0.001) (0.054)

Observations 3,450 3,450 3,450 3,450

SSI=Supplemental Security Income. *** p<0.01, ** p<0.05, and * p<0.1.

Notes: Estimates are odds ratios and represent the estimated change in the ratio of the probability of the specifi ed outcome over the probability of 

not leaving WIC due to a change in the independent variable. Odds ratios are weighted. Standard errors in parentheses were adjusted to account 

for heteroskedasticity and multiple observations from the same State. Sample size is rounded to the nearest 50, per National Center for Education 

Statistics’ regulations.

Source: Authors’ calculations based on the Early Childhood Longitudinal Study-Birth Cohort.
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Discussion

Our fi ndings show that economically advantaged households were more 

likely to delay WIC participation until the postnatal period and more likely 

to exit after a child turns 1 year old. We also found that prenatal Medicaid 

coverage was strongly correlated with earlier receipt of WIC, suggesting 

that each program may serve as a gateway for the other, especially since 

Medicaid recipients are adjunctively eligible for WIC. Results suggest 

that WIC’s provision of infant formula and participants’ breastfeeding 

decisions played a role in the early exit from the program. Households in 

which the mother breastfed for a longer time were less likely to exit WIC. 

Other explanations that play a role in the early exit from the WIC program 

included loss of eligibility, reduced need, and diffi culties accessing benefi ts. 

There were almost no reports from participants exiting WIC that they were 

denied benefi ts due to lack of program funds, which supports anecdotal 

evidence that States have received suffi cient funds in recent years to provide 

benefi ts to all eligible people. 

The regression results, indicating that economically advantaged households 

were more likely to delay entry into the program and to exit early, and the 

maternal self-reports on exit reasons suggest that loss of eligibility played 

a role in nonparticipation. Results also suggest that nonparticipants had a 

reduced need for benefi ts, indicating that the program was operating effectively for many households. We found evidence, however, that late entrants 

and early leavers still exhibit need and may be confused about their WIC 

eligibility, suggesting that increased outreach or program changes could 

increase the duration of these participants’ exposure to WIC services. For 

example, mothers in participant households who did not breastfeed or 

breastfed for less than 6 months were more likely to exit, and therefore may 

warrant special attention by WIC agencies.
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Appendix: State-Level WIC Policies 

and Practices

WIC Eligibility Variables

States may offer automatic WIC income eligibility to individuals who participate in Supplemental Security Income (SSI), the National School Lunch 

Program, or other means-tested transfer programs. Prior to 2000, some 

States required that applicants provide income documentation, such as pay 

stubs, W-2 forms, and letters from employers, while other States allowed 

applicants to self-declare their income. Federal guidelines, effective in 2000, 

now require that all applicants provide income documentation, unless they 

are adjunctively eligible for WIC through participation in other means-tested 

transfer programs. WIC eligibility variables include:

• SSI confers WIC eligibility indicates whether participation in the SSI 

program confers automatic WIC income eligibility.

• School lunch confers WIC eligibility indicates whether household participation in the free or reduced-price lunch program confers automatic WIC 

income eligibility.

WIC Food Package and Voucher 

Distribution Variables

Federal guidelines limit the maximum amount of food that States can 

distribute in each food package. Within this limit, State and local agencies 

may allow food packages to be tailored to better meet the nutritional needs 

or preferences of individual WIC participants. For example, some States may 

allow WIC staff to alter the types of milk offered, such as reduced-fat or soy, 

or to specify cereal with reduced sucrose content. States also have discretion over the frequency that vouchers (food instruments) are distributed to 

WIC participants, with distribution periods ranging from 1-3 months. There 

are seven different WIC food packages, which vary by type of participant. 

The average retail cost of the food packages for all WIC participants varies 

by State (from $33.38 to $61.84 in 2000), depending on differences in food 

prices and tailoring allowances (USDA, 2002). The WIC food package and 

voucher distribution variables include:

• Food packages tailored for type of milk indicates whether a State can 

tailor the type of milk in food packages.

• Food packages tailored to reduce sucrose indicates whether a State can 

tailor the type of cereal in food packages to reduce sucrose content.

• WIC voucher issued monthly indicates that a pregnant participant1 must 

collect the WIC food voucher each month, rather than less frequently.

• Average retail value of WIC food packages is the real average cost of 

food packages for all WIC participants in 2000 dollars.

1The authors of this report only used 

the information on voucher frequency 

for pregnant participants to create this 

variable. A State could have different 

policies for pregnant and post-natal 

participants.
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WIC Offi ces and WIC-Only Stores

There were 2,196 local WIC offi ces in the United States in 2000. The 

number of WIC-only stores, which serve only or predominantly WIC 

customers, began to increase rapidly in the late 1990s. In 2000, there were 

523 WIC-only stores in 13 States (Neuberger and Greenstein, 2004). These 

stores carry only WIC products and may reduce the challenges and stigma 

associated with redeeming WIC vouchers. WIC offi ce and WIC-only store 

variables include:

• WIC offi ces per 1,000 below the poverty level; and

• WIC-only stores per 1,000 below the poverty level.

WIC Nutritional Risk Variables

To receive WIC, an applicant must be determined to be at nutritional risk. 

Although there is evidence that nearly all income-eligible individuals are at 

nutritional risk (Ver Ploeg and Betson, 2003), the documentation of nutritional risk can vary across States. Some States require dietary intake information from all participants as part of the nutritional risk assessment, while 

other States require this information only from high-risk participants. States 

also may have various methods for collecting dietary intake information. The 

two most common collection methods routinely used by States during the 

period of our study are the 24-hour recall and the food frequency checklist. A 

recent study (Institute of Medicine, 2002) notes that 24-hour recall takes an 

average of 20-30 minutes to complete, while a food frequency checklist takes 

an average of 10-15 minutes to complete. Nutritional risk variables include:

• All nutritional risk criteria documented indicates that WIC agencies in 

a State must document all of the nutritional risks faced by a participant, 

rather than documenting just the primary nutritional risks.

• Dietary intake information required of all participants indicates whether 

States require dietary intake information be collected from all participants, rather than just high-risk participants, to determine WIC nutritional risk eligibility.

• Twenty-four hour recall used to obtain dietary intake information indicates that the State routinely uses the 24-hour recall method to collect 

dietary intake information.