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The Personal Responsibility Work Opportunity and Reconciliation Act (PRWORA), or welfare reform law of 1996, signaled a profound political shift in American policy toward poor families. The act replaced the previous federal cash assistance program, Aid to Families with Dependent Children (AFDC), with block grants to the states and renamed the program Temporary Assistance to Needy Families (TANF). The bill effectively ended the federal guarantee of income support to poor families with children, imposed a lifetime limit on public assistance and new work requirements, and permitted states to tie assistance to compliance with specified maternal behaviors, including reproductive and marital decisions.' The bill also curtailed federal regulation of welfare programs and "devolved" responsibility for standards and oversight to the states. Although the federal government does not require that states assess the impact of these changes, a series ofboth public and private evaluations are under way to examine the employment and earnings experiences of former recipients.2- (For an extensive list of studies of welfare reform, visit www. researchforum.org, the Research Forum on Children, Families and the New Federalism, National Center for Children in Poverty.) The central concern of this discussion, however, is health. The PRWORA has the potential to influence the health of millions of American families, both by affecting family resources and living conditions and by determining access to medical services.5 Despite this potential impact and despite the fact that the federal and state versions of welfare reform explicitly target certain health-related behaviors and reproductive outcomes, a recent General Accounting Office report underscored the continuing paucity of information on the health status of former welfare recipients.6 Our discussion is intended to frame a technical approach to such an evaluation by outlining the reproductive health out-

comes that are most likely to be sensitive to altered welfare policies, which indicators might be used as proxies to assess these outcomes, and specific methods and data sources that would best address such a challenge.

Background A central objective of the new welfare policies has been to require persons participating in TANF to work ("workfare") and to leave TANF quickly for paid employment. Failure to meet work requirements generally leads to sanctions and thus to reduced or terminated benefits. A major difference between the previous AFDC program and the new TANF program is the adoption of time limits; a person can receive TANF benefits only for a specified amount of time, assessed cumulatively over his or her life. Determination of the time limit falls to the states, although federal law stipulates that it can be no longer than 5 years. In some of the 19 states with shorter time limits (e.g., Tennessee [18 months] and Connecticut [21 months]), the first cohort of families has already reached the limit.7 The PRWORA also barred many legal immigrants from receiving food stamps and gave the states greater latitude to restrict immigrants' access to a variety of other benefit programs.8 In the past, there was an automatic linkage between AFDC and Medicaid. Both were entitlement programs in which income eligiPaul Wise is with the Department of Pediatrics, Boston University School of Medicine, Boston, Mass. Wendy Chavkin and Diana Romero are with the Center for Population and Family Health, Columbia University, New York City. Requests for reprints should be sent to Wendy Chavkin, MD, MPH, Joseph L. Mailman School of Public Health, Columbia University, 60 Haven Ave, B-3, New York, NY 10032 (e-mail: wc9@columbia. edu). This article was accepted July 27, 1999.

October 1999, Vol. 89, No. 10

Welfare Reform and Health

bility guaranteed provision ofbenefits. TANF is not an entitlement program; the funding designated for TANF support is capped through the block grant, and eligibility does not guarantee receipt of benefits. Medicaid, however, remains an entitlement program with eligibility guidelines similar to those that existed under the former AFDC program. TANF and Medicaid have been "decoupled" so that women and children can maintain health insurance even if they lose income support. Dramatic reductions in Medicaid enrollment subsequent to the administrative separation of Medicaid and TANF have occurred, however, 9-11 as well as declines in food stamp participation.'2 The PRWORA specifies that Medicaid should continue for a transitional year (12 states provide more than 1 year7) for women leaving TANF for employment. This provision implicitly recognizes that the jobs available to this population may not provide health insurance. The State Child Health Insurance Plan was established in 1997 so that children can be covered even if their parents are not. Many states have explicitly established goals that include guidelines for maternal behaviors as well as disincentives for childbearing (Table 1). These mandates could have a positive impact on health if recipients comply with the mandated behaviors, or they might have an inadvertent negative effect if women are sanctioned for noncompliance and lose financial resources. Critics have expressed concern that compelling women to identify fathers and to cooperate with child support collection'3 could lead to lower informal paternal contributions and might exacerbate domestic violence. (Paternal payments generally go to reimburse the state and do not augment the family's income, although some states have maintained the AFDC child support pass-throughs, instituted income "disregards," or raised existing levels.'4) The Family Violence Option, which exempts women from TANF work requirements if they are at risk ofabuse, was designed in response to this concern but has been adopted by only 31 states, with varying levels of implementation.7 Although welfare policies can affect the health of all family and community members, their primary impact is likely to be on women and children. This is because women and children are the primary participants in TANF and because it is the explicit intention of some TANF and state regulations to alter women's work and reproductive behaviors. In this article, we focus on the broad categories of childbearing, pregnancy outcome, and infant health. In a subsequent article, we will discuss the potential impact of welfare policy on children's and women's health. October 1999, Vol. 89, No. 10

Welfare Effects on Childbearing The "illegitimacy bonus" (the federal award of $20 million to each of the top 5 states that reduce their out-of-wedlock birth rate) and "family cap" (the child exclusion policy in more than 20 states that restricts additional TANF funds to women who have children while receiving assistance) are 2 components of welfare reform that reflect explicit intentions to decrease childbearing among TANF recipients without increasing abortion rates. An underlying assumption is that women on welfare have children in order to obtain benefits. However, most studies ofthis issue do not support such an assumption.'S'8 In order for welfare policies to affect birth rates, they must lead to reduced sexual activity, to increased use of contraception, to increased abortion, or to increased fetal loss. In general, the available studies suggest that welfare receipt has little direct impact on sexual activity.19'20 Studies of the relationship between AFDC payments and abortion rates have also found weak or no effects. 17,21-25 This issue has been revisited in the context of family cap programs. During the early 1990s, before passage of the PRWORA, New Jersey and Arkansas both received Section 1115 waivers allowing the institution of family cap measures and requiring the evaluation of these programs by means of a formal randomized experimental design. Arkansas reported no apparent effect on birth rates, although the investigators found that almost half of the female case heads were not even fertile, owing to sterilization or postmenopausal status (i.e., grandmothers caring for children).26 In New Jersey, the family cap policy was associated with a decline in births and an increase in abortions and family planning visits.27 Efforts to understand the determinants of fertility must take into account highly dynamic secular trends in the components composing birth rates. Over the past several decades, the age at which sexual activity is initiated has fallen,28 and the age at which women marry has risen29; together, these events are associated with an increase in the rate of sexual activity before marriage. Both contraceptive use and female sterilization have increased.30 Abortion rates, on the other hand, have been declining for the past decade,31 although rates vary by sociodemographic group, geographic location, and availability of providers.24'31'32 Teen pregnancy rates, a subject of particular concern to welfare reformers, had begun to fall before passage of the PRWORA. Between 1991 and 1996, the birth rate among teenagers (15-19 years) dropped by 12% overall, with a 21% drop among

African American women, a 9% drop among non-Hispanic Whites, and almost no change among Hispanics.33 Thus, the components composing birth rates have been changing in different directions. Sexual activity, including nonmarital sexual activity, has increased, as have contraceptive use and sterilization, while abortion has declined. Moreover, these trends obscure variation within subgroups. In sum, the empirical evidence does not support a consistent direct relationship between welfare receipt and sexual behavior or reproductive decisions. These complex secular trends must be juxtaposed with domestic economic developments, the state of the job market, and the profound alterations in the health care system associated with managed care.

Pregnancy Outcome While early pregnancy loss and congenital anomalies have not been strongly associated with social gradients, late fetal loss, low birthweight, and infant mortality have all been closely linked with poverty. The PRWORA could have an impact on the risk of these adverse effects through changes in the risk status of women, primarily via altered social conditions and the imposition of work requirements and via diminished access to health care. There are few data to suggest that receipt of cash assistance in itself affects birth outcomes, although it may serve as a proxy for other social factors.34'35 Very low birthweight has been shown to be influenced by a variety of social factors, including poverty.36'37 There appear to be multiple, multifaceted pathologic mechanisms leading to very-low-birthweight deliveries, including infectious causes, social and occupational stress, and the underlying health status of women preceding their pregnancy.38 Serious deterioration in the social conditions of reproductive-aged women may therefore elevate the risk for premature birth. Many studies have attempted to assess whether employment-related physical activity affects pregnancy outcomes.39 While there is no consensus, several studies indicate that prolonged standing and long working hours are associated with preterm delivery. Women complying with workfare requirements and leaving TANF for paid employment, like other low-wage workers, are likely to be in physically demanding jobs.4' In addition, the working conditions associated with such employment generally erect major logistical barriers for women who are breast-feeding or seeking medical care for their children. American Journal of Public Health 1515

Wise et al.

TABLE 1-Personal Responsibility Work Opportunity and Reconciliation Act of 1996: Federal Ceilings and State Options for Temporary Assistance to Needy Families (TANF)6'45,7577

Lifetime limit on TANF benefits Must start working while receiving benefits Child care guarantee Transitional child care after benefits end Transitional Medicaid after benefits end Immunization-pediatric health care

5 years 2 years Not required Not required 1 year Not required

Child exclusion ("family cap") policy Family planning services

Not required Not required

Out-of-wedlock births ("illegitimacy ratio") Child support cooperation

Bonus to 5 states with greatest decrease Requires states to determine whether recipient is cooperating in good faith Drug felons ineligible for TANF unless state opts out or narrows provision Allows states to exempt women at risk of abuse from TANF work requirements

Drug-related prohibitions Family Violence Option

State Options

Federal Ceiling/Mandate

TANF Component

19 statesa will provide less than 5 years 28 statesa impose work requirements before 2 years At least 14 statesa do not guarantee child careb At least 13 statesa do not guarantee child carec 12 statesa will provide more than 1 year At least 17 and 8 states,d respectively, have requirements 23 states have some form of child exclusion policy At least 9 statesd have some family planning requirement 34 states have a stated goal to collect the "bonus" At least 21 statesd require full cooperation (6 mention "paternity identification") 35 states deny benefits to drug felons; at least 10 states test for drug usee 22 statesa have not adopted the option

aBased on a total of 54, including 50 states, Washington, DC, Puerto Rico, Guam, and the US Virgin Islands. bSeven states not included in the 14 condition child care assistance on income eligibility rather than TANF status; thus, they may or may not provide child care. CNine states not included in the 13 condition child care assistance on income eligibility and not TANF status; thus, they may or may not provide child care. dBased on a total of 37 states for which individual responsibility agreements were available. ein a study we recently conducted, several states reported that testing TANF applicants for drug use is currently before their legislatures.70

If the documented declines in Medicaid since its decoupling from TANF result in reduced rates of insurance coverage,15 access to primary health care and prenatal care services could become problematic for many women. This, in turn, could result in higher rates of adverse outcomes for those women who experience problems amenable to medical intervention. It is also important to recognize that high-risk obstetric interventions and intensive health care services for critically ill newborns have driven down neonatal mortality rates in the United States over the past 2 decades. Consequently, if disenrollment in Medicaid leads to a reduction in access to these services, it could result in an increase in local neonatal and infant mortality or morbidity rates. Conversely, access to intensive medical services for neonates could mitigate the consequences of worsened social circumstances for their mothers.

Methodological Considerations Although we have outlined theoretically plausible pathways by which welfare policies might affect certain reproductive health outcomes, the ability to detect associations will be limited by both the availability of relevant data and the ability to effectively control for potential confounders. A primary challenge is to determine whether there is a relationship 1516 American Journal of Public Health

between the independent variable of interest, welfare participation, and the dependent variables, reproductive and infant health outcomes.

Different methodological approaches be considered for evaluating the effects of welfare reform. Experimental designs are usually considered the best approach to detecting the effect(s) of an intervention and were indeed proposed as the method of choice for evaluating new welfare policies under Section 11 15 waivers. Numerous investigators, however, have pointed to the potential flaws associated with using experimentation to evaluate behavior- and incomerelated outcomes in environments susceptible to contamination among treatment and concan

trol groups.27,4245

Time-series analyses provide one alternative to experimental designs, although they focus on trends over time at the population level (e.g., birth or marriage rates). Comparison-site methods can also be used wherein a geographic area or site is compared with a "control site" where conditions or policies are similar to the "experimental site" prior to welfare reform. This approach can address the "cross-sectional" question, for example, whether changes in welfare benefits lead to increases or decreases in marriage or fertility rates, holding all other covariates fixed. However, this will not completely account for all of the differences between 2 localities, nor will it address the relative contribution of

welfare reform to trends in marriage or fertil-

ity rates.15,27 A common alternative to these methods is the quasi-experimental pre-post design, which uses individual-level data on behavior before and after an intervention (i.e., policy change). This approach permits within-site analyses, controlling for changing caseload composition and economic, environmental, and other factors that may influence the outcome; however, factors not controlled for may have an impact on estimates of program effects.27

Linking Welfare Participation and Health Data The availability of information regarding individual TANF status will usually depend on the cooperation of local welfare agencies. However, the political sensitivity of this issue, as well as confidentiality policies, may limit access to case-level data. Although such data may be available from clinical settings or advocacy groups, these sources are not likely to provide population-based or representative study cohorts. In most situations, analyses will have to depend on direct involvement of welfare agencies or on alternative strategies that rely on proxy variables such as income, health insurance, employment, education, marital status, and age-related data to approximate TANF status. October 1999, Vol. 89, No. 10


Moving Targets, Lag, Classification, and Rare Outcomes

Heterogeneity of Welfare Effects and the Role ofHealth Providers

Changing regulations present practical difficulties in assessing health effects ofwelfare policies. The independent variable, welfare policy, varies by state (and often by county) and is subject to legislative amendment. Furthermore, there is a time lag associated with implementing programmatic change. This "moving target" nature of the TANF program greatly complicates efforts to estimate the point at which health effects might begin to be manifest. In fact, although the first bonuses to the top 5 states that reduce their out-of-wedlock birth rate will be awarded this year, experts say it is too soon for many state initiatives to have had an effect, and demonstrating a causal relationship will be problematic even when more time has lapsed.46 There may also be problems with how to classify receipt of TANF and, therefore, how to identify those families affected by policy changes. In addition, problems with classification raise important questions regarding the choice of appropriate comparison groups and controls. Many welfare beneficiaries move on and off cash assistance programs frequently, and turnover may be even more likely because of sanctions. Diversion efforts, such as one-time emergency cash payments in lieu of applying for TANF, are also under way in many states to deter individuals from applying for assistance.47 In NewYork City, a federal investigation found that the city's procedures to divert people from applying for TANF inappropriately resulted in denial of food stamps and Medicaid benefits.48 These maneuvers may effectively deter a group of people from enrolling in the TANF program, although their socioeconomic characteristics may be very similar to those who actually enroll. If cases are classified only on the basis of welfare enrollment, the full effects of these policies on poor women and children may not be captured. Reliance on data sources with proxies for welfare status may also dilute the effect. For example, an examination of birth rates among all unmarried women may obscure changes in birth patterns among the subset of umnarried women who receive TANF. Another concern in assessing the impact of welfare policy on reproductive and infant health is that many of the relevant outcomes are relatively rare. Rates of very low birthweight, prematurity, infant death, and maternal mortality, for example, are best measured in relatively large populations. Therefore, questions of statistical power invariably arise when these outcomes are assessed in populations of fewer than several thousand births.

The purpose of the PRWORA was to alter the conditions ofwelfare participation in order to reduce its use.'3 Indeed, nationwide use rates have decreased by 44% since 1993, and even more in certain states (e.g., Wisconsin has dropped 86%, from 240 000 to 34 000) and cities (e.g., New York City has decreased by more than 500 000 since 1995).849 While proponents have hailed these declines as a major success, others have noted that little is known, with the exception of short-term employment data, about the experience of families once they are off TANF.2'6'50 In the General Accounting Office report that reviewed state follow-ups of former welfare recipients, post-TANF employment rates ranged from 61% to 87% in the 7 states that had reasonably complete data. However, these rates generally did not include in the denominator recipients who had returned to welfare (the prevalence rates of such cases ranged from 19% at 3 months in Maryland to 30% at 15 months in Wisconsin), thus overestimating the rate of employment among former recipients. 6 Some recent developments include a decline in the receipt of food stamps,'0'11'51 despite increases in demand for emergency food assistance,52 and an increase in the uninsured population while Medicaid enrollment has fallen.9'53'54 While these declines have largely affected women and children, it is unknown whether pregnant women's use of previous Medicaid expansions has been similarly affected. Also of concern is that enrollment in the State Child Health Insurance Plan has been below the estimated need for health insurance among poor children, such that the president established a special outreach initiative earlier this year.55 Given these developments, it is important that evaluations look beyond broad demographic or epidemiologic trends and examine the consequences for specific subgroups. Of special interest are women with chronic illnesses, substance abuse and mental health problems, limited education and employment skills, language barriers, and chronically ill children, all ofwhom are likely to experience problems in acquiring stable employment.56'57 There is growing evidence that immigrant families have experienced particularly sharp declines in program enroll-


ment. 8,58-60

The welfare caseload in New York City, for example, has become increasingly ethnically stratified, with no change in the number of Hispanic recipients, although there has been an overall decline of 36% of cases since 1995.56 57 An ecologic analysis in New York

City revealed that use of the Special Supplemental Nutrition Program for Women, Infants, and Children had declined in neighborhoods with large numbers of immigrants.60 We speculate that this may be due to administrative confusion over eligibility criteria and immigrants' fears that receipt of public benefits will jeopardize their immigration status.61'62 It is likely, therefore, that the health consequences of recent welfare policies will be mixed. The experience of groups that depart from the mainstream could escape the notice of large-scale evaluators and policymakers. It may fall to those who provide direct services, including clinicians and social service providers, to contribute "sentinel" cases and qualitative insights regarding families who experience severe hardships. Although these insights may not involve the numbers necessary to reach statistical significance, they can identify preventable conditions or system failures. An example of such an approach is found in the examination of individual infant and maternal deaths by fetal and infant mortality review programs and maternal mortality committees. The circumstances of such deaths, while not necessarily representative, may be instructive in depicting gaps in services or the negative consequences of certain

policies. This year, for example, 2 mothers in New York City who were TANF recipients breast-fed neonates who died of apparent malnutrition.63'6" In both cases, the women had sought pediatric care but were not able to obtain it because, although eligible, they lacked Medicaid coverage for their babies. Other anecdotal accounts of welfare-towork-related child deaths have been reported in other states (A. Yowell, PhD, written communication, April 30, 1998), as have accounts of mothers having to discontinue breastfeeding their infants in order to comply with inflexible workfare schedules (J. Star, written communication, August 1998).

Extant Data Sources

National and state level. Most evaluations of welfare legislation have relied on the analysis of large, extant data sets. Data sets that are collected on a regular basis and that involve large representative samples are of special interest. National survey data can provide information on secular trends in demographic, program participation, and healthrelated outcomes. Table 2 summarizes the characteristics of some of the most relevant national data sets for analyzing welfare and health data. Several national data sets can provide geographically tagged data for analysis by state or selected localities. Census tract American Journal of Public Health 1517

Wise et al.

TABLE 2-Select National Data Sources Data Set

Design

Sample

National Health Interview Survey'

Repeated, cross-sectional household survey; latest 1996

National Survey of Family Growthb

Repeated, cross-sectional household survey; latest 1995

National Health and Nutrition Examination National Hospital Discharge Surveyd

Repeated, cross-sectional household survey; latest 1994 Repeated, cross-sectional hospital survey

Stratified, national sample; minority oversampling; special surveys of disabled (n = 106 000) Stratified, national sample of women aged 15-44 years; minority oversampling (n = 25 534) Stratified, national sample (n = 34 000)

National Longitudinal Survey of Youthe

Longitudinal survey; latest 1994

Surveyc

Continuous series panels followed for 2-4 years; latest 1996 Participationf Annual tabulation of US Natality Data Setg birth certificates; latest 1995 Annual linkage of birth US Linked Natality/ and death certificates; Infant Death Data Seth latest 1995

Census Survey of Income and Program

Demographic-Welfare Variables

Health Variables

Basic demographic, economic

Multiple health status and service use

Basic demographic, economic, AFDC; detailed marriage

Detailed fertility, contraception, pregnancy

Basic demographic

Detailed health status and service use; nutrition and lifestyle Medical diagnoses, procedures

Stratified, national sample of hospitals (n = 478 hospitals) Stratified cohort and their children (n = 8778) Multistage-stratified sample (n =5000 households) All US resident births

Minimal demographic; health insurance, Medicaid

All US resident births and infant deaths

Minimal maternal and infant

Detailed demographic and program data, AFDC

Detailed demographic, AFDC economic and program data Minimal maternal and infant demographic

demographic

Health, pregnancy, child medical and selected developmental Disability, childbearing

Infant birth characteristics; prenatal care use Infant birth characteristics and prenatal care use linked to infant mortality and cause of death

Note. AFDC = Aid to Families with Dependent Children. awww.cdc.gov/nchswww/about/nhis/nhis.htm.

bwww.cdc.gov/nchswww/about/nsfg/nsfg.htm.

cwww.cdc.gov/nchswww/products/catalogs/subject/nhanes3/nhanes.htm.

dwww.ntis.gov/fcpc/cpn8481 .htm. ewww.bIs.gov/nIsnew.htm. fwww.sipp.census.gov/sipp/sipphome.htm.

gwww.cdc.gov/nchswww/about/major/natality/natality.htm.

hwww.cdc.gov/nchswww/products/pubs.pubd/mvsr/supp/46-45/mvs46/2s.htm-

zip code information may permit ecologic estimates of a number of demographic and economic variables. Among the most useful of these data sets is the National Longitudinal Survey of Youth, which has followed a cohort of young people through their early adulthood and contains information on the personal experiences of those who have had children. Similarly useful is the US Bureau of the Census Survey of Income and Program Participation, which regularly surveys a national sample, collecting information on economic, social, and demographic changes. The Census Bureau, at the direction of Congress, is currently conducting the Survey of Program Dynamics, which will provide detailed information on welfare and employment experiences of a national sample or

of American families. The National Health Interview Survey, the National Survey of Family Growth, the National Health and Nutrition 1518

American Journal of Public Health

Examination Survey, and the Ortho Birth Control Study,65 as well as data sets based on vital

statistics, provide ongoing, health-related data that can be analyzed over time and provide a context for generating hypotheses for more specific state and local analyses. Because of the variation in state and local programs, national data sets may not provide much insight into effects at the local level. The most commonly used state-based data sources for assessing fertility, birth outcomes, and infant mortality are birth and death certificate files. Most states link birth and death certificates, although these linked data sets may lag behind the availability of individual birth or death certificate files. National linked data are available as well. Many states also routinely collect information on use and insurance coverage via Medicaid and hospital discharge data sets; these can, in turn, be linked to vital statistics files.

An important source for data on abortions is the survey of providers periodically conducted by the Alan Guttmacher Institute; these data are organized by state of occurrence rather than by residence of the

patient.31'66 This organization recently indicated that underreporting has increased in certain states, apparently because of provider fear of harassment and violence.67 The Centers for Disease Control and Prevention also collects data on abortions, obtained from state health departments.68 Although these data do not capture as many abortions as do the Alan Guttmacher Institute surveys, they include more demographic covariables (including marital status). Data on abortion can be derived as well from surveys such as the National Survey of Family Growth, the National Longitudinal Survey of Youth, and the National Health Interview Survey, although reluctance to disclose such sensi-



TABLE 3-Select State Data Sources78

Data Set

Sample

Design

DemographicWelfare Variables

Behavioral Risk Factor Surveillance System

Repeated, cross-sectional, household survey

50 states

Youth Risk Behavior Surveillance System

School-based survey

State surveys, national Basic demographic school-based survey, local student surveys More than 48 states Basic demographic and territories Approximately Basic demographic; AFDC, 20 states (expected WIC, and food stamps to expand) aggregated

Pediatric Nutrition Survey of participants in Surveillance System WIC, EPSDT, Head Start Pregnancy Risk Survey of pregnant and Assessment Monitoring postpartum women System

Health Variables

Basic demographic, insurance status

Tobacco, alcohol, obesity, nutrition, activity, screening test use, health status, insurance Tobacco, marijuana, weapons, condom use, activity, nutrition Nutrition, weight, height Prenatal care, alcohol-tobacco use, infant health care

Note. WIC = Special Supplemental Nutrition Program for Women, Infants, and Children; EPSDT = Early Periodic Screening, Diagnostic, and Treatment Program; AFDC = Aid to Families with Dependent Children.

tive information is thought to lead to serious

underreporting.69 State-based surveys, often conducted as part of national programs, may also provide useful information. The Pregnancy Risk Assessment Monitoring System, a statebased surveillance system survey that is overseen by the Centers for Disease Control and Prevention, is currently administered in approximately 20 states and is expected to expand to more states. State-specific information on maternal and infant risk indicators and public program participation is generally available. State-level data on nutrition and health-related behaviors are also available from ongoing surveys (Table 3). Specially developed data sets. The major problem inherent in using extant national or state data sets is that detailed information on both welfare and health is rarely available in the same data set. It may be useful, therefore, to develop new data sets that include both welfare and health variables. One approach is to link data sets derived from different systems (e.g., TANF participation files and Medicaid or child protective services files).70 We have found that at least 10 states have already linked TANF and child protective services cases as part of the Statewide Automated Child Welfare Information System, a state database mandated by the PRWORA.71 Federal funding has also been provided to encourage states to link multiple administrative databases and make them available for public use.4 Longitudinal cohort and case-control designs could solve the problem of using proxies for welfare status. These approaches are expensive and still vulnerable to problems associated with the study of rare outcomes and with the identification of diverted, deterred, sanctioned, and timed-out families. FurtherOctober 1999, Vol. 89, No. 10

more, these designs will probably require collaboration with state or local welfare agencies. Qualitative data sources. Important information can also be derived through qualitative analyses that examine the experiences and perceptions of people affected by welfare programs and policies.41'7273 These qualitative research methods provide insights not obtainable from large quantitative data sets. Detailed mterviews and focus groups mvolving recipients, former recipients, and those deterred could lead to the development of hypotheses for subsequent quantitative analyses. One such study was conducted with 50 families receiving TANF in the greater Philadelphia area.72 The researchers found that many of the respondents had serious health problems (33%), had children with chronic illnesses (40%), and had lost ajob because ofchild care problems (26%) or their own or their child's health problems (16%). Without such qualitative inquiries, quantitative approaches might have simply revealed a "lack of compliance with work requirements" among many of these individuals.

Conclusion There is no clearly defined, straightforward approach to assessing the potential health effects of welfare reform policies on reproductive and infant health. The pathways of effect are complex, and the necessary data are difficult to come by. In addition, by transferring so much of the development and administration of TANF to the states, the PRWORA in effect created 50 separate and constantly evolving welfare programs. This dynamic complexity presents a daunting challenge to all those committed to assessing the effects of welfare legislation on health.

The importance of the PRWORA to the social well-being of millions of American families makes its evaluation as compelling as it is difficult. In fact, national74 and state75 policymakers have proposed legislation requiring states to evaluate the impact of TANF on the well-being of current and former recipients. The federal legislation is up for reauthorization in 2002. It is essential that the consequences for health be included in the next round ofpublic debate. C]

Contributors All 3 authors participated in the design of the study, research, and writing and revision ofthe manuscript. P. Wise wrote the first draft.

Acknowledgments This research was supported in part by funding from the Ford Foundation, the General Service Foundation, the Maternal and Child Health Bureau, the Moriah Fund, the Open Society Institute, and the Peabody Foundation. We gratefully acknowledge the thoughtful suggestions provided by Hani Atrash, MD, MPH, Paula Braveman, MD, MPH, Jodie Levin-Epstein, and Roger Rochat, MD, who reviewed drafts of this article; however, the article reflects the views of the authors, and we accept full responsibility for its content. We are also grateful for the assistance of Jennifer Ellis, BA, and Lauren Smith, MD, in the research and preparation of the article.

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Chronic Disease Epidemiology and Control, 2nd edition

75. McCall H. An Update on the Evaluation ofWelfare Reform in New York State. Albany, NY: State of New York, Office of the State Comptroller; 1999. 76. Levin-Epstein J. The IRA: Individual ResponsibilityAgreements and TANF Family Life Obligations. Washington, DC: Center for Law and Social Policy; 1998. 77. What Congress Didn't Tell You: A State-by-State Guide to the Welfare Law s Hidden Reproductive Rights Agenda. New York, NY: National Organization for Women Legal Defense and Education Fund; 1998. 78. Leiwant S. Reproductive Rights and Welfare: Update on Recent Child Exclusion Developments. New York, NY: National Organization for Women Legal Defense and Education Fund; 1998. 79. SelectedActivities in Support of the National Action Agenda: Building Capacity for Maternal and Child Health. Atlanta, Ga: Centers for Disease Control and Prevention; 1999.

0/);.

Edited by Ross C. Brownson, PhD, Patrick Remington, MD, MPH, and James R. Davis

With this book, you'll learn to: o Locate critical background information for developing appropriate interventions o Master the science and practice of chronic disease control o Enhance your technical capacity for delivering effective programs o Improve your knowledge about the methods used in chronic disease epidemiology o Identify diseases and risk factors o Examine the underlying biological or physiological processes of disease o Learn about high risk populations, geographic variations, and trends o Plan, organize, and address prevention and control methods o Discover the recommendations for future research and demonstrations 546 pages * Softcover * 1998 * Stock no. 0875532373/CDAD98 $32.00 APHA Members* * $45.00 Non-members American Public Health Association * Publications Sales PO Box 753, Waldorf, MD 20604-0753. Voice: (301) 893-1894; Fax: (301) 843-0159 E-mail: TASCOl @APHA.ORG; Web: www.apha.org


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