Skip to main content

The effects of food stamp receipt on weight gained by expectant mothers

Abstract

With over 66% of Americans overweight, expectant mothers are unusual because they are encouraged to gain weight while pregnant. Food stamp receipt (FSR) may facilitate recommended weight gain by providing resources for food and nutrition. I examine the effects of FSR on the amount of weight gained by low-income expectant mothers using NLSY79 data. Results indicate FSR decreases the probability gaining insufficient weight but does not exacerbate the probability of gaining too much weight. Examining the effects of FSR on pregnancy weight gain is important because low birth weight is more likely when expectant mothers gain insufficient weight.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Notes

  1. See Devaney and Fraker (1989), Fraker (1990), and Fraker et al. (1995).

  2. See Basiotis et al. (1998), Rose et al. (1997), and Wilde et al. (1999).

  3. However, Kaushal (2007) concludes that the FSP does not have statistically significant effects on obesity.

  4. The CDC consider adults to be underweight if their body mass index (BMI) is less than 18.5, normal weight if their BMI is 18.5 to 25, overweight if their BMI is 25 to 30, and obese if their BMI is 30 or more (CDC 2006a). BMI is defined as weight in kilograms divided by height in meters squared (CDC 2006b).

  5. However, these pregnancy weight gain recommendations, derived by the Institute of Medicine in 1990, define underweight pre-pregnancy as a BMI less than 19.8, normal pre-pregnancy weight as a BMI of 19.8 to 26.0, overweight as a BMI of 26.1 to 29.0, and obese as a BMI of 29.0 or higher.

  6. Traditionally, to be eligible for food stamp benefits, a household must have gross monthly income less than a household size-specific amount (130% of the federal poverty line), though the gross income test is disregarded if the household contains an elderly (aged 60 and over) or disabled member. The household must also have net monthly income less than a household size-specific amount (100% of the federal poverty level). Furthermore, a household must have assets whose value is less than a specified amount (historically $2,000). This amount is not specific to household size, but the amount is higher ($3,000) if the household contains an elderly or a disabled member.

  7. Relatedly, 30% to 40% of expectant mothers do not gain an amount of weight that falls within recommended ranges, gaining either an insufficient amount of weight or too much weight (Abrams et al. 2000; Hickey 2000).

  8. Limiting the sample in this way follows much of the welfare literature (for example, see Hurst and Ziliak 2006; Sullivan 2006).

  9. Some disagree that pregnancy weight gain significantly affects these measures (Johnson and Yancey 1996; Stephansson et al. 2001).

  10. Almond et al. (2011) examine the effects of the FSP on birth weight and the probability of low birth weight. They conclude that food stamps significantly increase birth weight (and decrease the prevalence of low birth weight) but do not significantly affect neonatal mortality. Somewhat differently, Currie and Cole (1991) find no significant effects of the FSP on birth weight, and Currie and Moretti (2008) find that food stamps reduce birth weight.

  11. Further, some have found that gaining an excessive amount of weight while pregnant has adverse effects on infant and maternal health and increases the probability of cesarean delivery (Cogswell et al. 1995; Johnson et al. 1992; Johnson and Yancey 1996; Rosenberg et al. 2005; Young and Woodmansee 2002).

  12. Results are broadly similar when I instead define low-income as being at or below either 100%, 150%, or 200% of the poverty line.

  13. The NLSY79 measures of weight are self-reported. Unfortunately, self-reported weight potentially is measured with error. Cawley (2004), using National Health and Nutrition Examination Survey (NHANES)—NHANESIII (1988–1994) data, predicts actual weight using self-reported weight for NLSY79 respondents. I am unable to adjust my NLSY79 data for reporting inaccuracies with NHANES data because NHANES does not collect information on actual and reported pregnancy weight gain. Regardless, measurement error in weight gain may be less of an issue than measurement error in self-reported weight if individuals conceal their true weight but have little incentive to report inaccurately their change in weight during pregnancy.

  14. There are 560 mothers. One observation is provided by 436 mothers, 100 mothers provide two observations, 23 mothers provide three, and 1 mother provides 4.

  15. However, the CDC’s method for classifying weight in those under age 21 is through age- and gender-specific BMI growth charts, which are categories not consistent with CDC’s categories for recommended pregnancy weight gain. For consistency across respondents, I use the BMI cutoffs described earlier for all respondents.

  16. The sizable proportion underweight is at least partially due to these women being relatively young (with an average age of 21.6). For example, 33.9% of expectant mothers in my sample who give birth in 1979, 1980, 1981, or 1982 are underweight compared to 6.8% of expectant mothers in my sample who give birth in 1993 through 2002. Furthermore, the definition of underweight for pregnant women is relatively liberal: recall that the CDC’s definition of underweight for pregnant women is a BMI less than 19.8 instead of a BMI less than 18.5 for others.

  17. Food Stamp Program participation may be misreported, with empirical evidence indicating that errors of omission are substantially more prevalent than errors of commission (Bitler et al. 2003; Bollinger and David 1997). Bollinger and David (1997, 2001, 2005) show that survey respondents seem to be predisposed to provide either accurate or inaccurate food stamp information and that reporting errors are less likely to be due to difficulty recalling whether participation occurred in a specific month. While I do not address misreporting empirically, I acknowledge that reporting errors may lead to puzzling results: for example, some researchers (e.g., Wilde and Nord 2005) find that food stamps seem to be correlated with adverse health and nutritional outcomes such as food insecurity. However, Gundersen and Kreider (2008) show that in the presence of food stamp reporting errors, we cannot necessarily conclude that food stamps and food insecurity are positively associated, although this association could be due to measurement error with food insecurity as well (Gundersen 2008; Gundersen and Kreider 2009).

  18. See Hamilton and Rossi (2002) and Burstein et al. (2005) for more on potential bias in food assistance research.

  19. I jointly model other types of welfare receipt (e.g., WIC and AFDC/TANF welfare receipt) when included as covariates in the weight equation.

  20. This routine is performed in FORTRAN using analytic first derivatives to obtain maximum likelihood estimates. Identification is achieved by setting the first mass point equal to zero and the second mass point equal to one for each factor. The additional mass points and the probability weights are restricted to lie between zero and one, but the factor loadings are allowed to take any value.

  21. Furthermore, a regression-discontinuity approach based on income eligibility would require inclusion of those with gross income above the food stamp eligibility threshold, and these expectant mothers may be systemically different.

  22. I adjust my standard errors to account for state-specific correlation because the instruments are state-level indicators.

  23. The instruments were added to the pregnancy weight gain equation simultaneously, treating food stamp receipt as exogenous with identification based solely on functional form. Formally, testing exclusion restrictions requires over identification with at least one valid instrument, although empirical studies often use the type of informal test employed here.

  24. Marginal effects are calculated at the covariate sample means.

  25. Kramer (1987a, b) suggests that fetal growth is easier to manipulate than gestational length.

  26. Results are also statistically insignificant when I adjust initial BMI for reporting error using the approach of Cawley (2004), described above, and then split the sample using adjusted pre-pregnancy BMI.

  27. Several of the covariates (the state and year dummy variables) are not identified and must be dropped from the models in specifications 1 and 2 due to reduced sample sizes.

  28. Shared instruments may operate on food stamps and WIC receipt the same way, essentially making their fitted values highly collinear and reducing the precision of their estimated effects.

  29. In addition, several of the covariates (state dummy variables, for example) are dropped from the model because they are not identified in the smaller sample.

  30. As for WIC receipt, in this specification, I estimate an additional equation for welfare receipt. The instruments that identify welfare receipt are: a pre-welfare reform dummy variable that equals one if a state waiver is in force either terminating or reducing benefits due to time limits, changing work exemption policies, changing sanctions for violations, increasing earned income disregards, or changing family cap rules (see Crouse 1999); the state monthly maximum AFDC/TANF benefit level for a family of four; the state time limit during which recipients may receive TANF benefits (months of allowable lifetime receipt); whether household benefits are capped for births occurring during participation spells (family caps); child age (in months) for which caregivers are exempt from work requirements; state sanctions for program violations (whether the most severe sanction is full or permanent instead of partial and temporary); state earned income exemptions (flat dollar amounts and percentages of earnings disregarded from benefits calculation for the first month with earnings); and state asset limits, including variables characterizing the extent to which vehicles are counted as assets. Information required to create these variables is obtained from a report on state AFDC/TANF policies by Crouse (1999) and from the Urban Institute’s online Welfare Rules Database (Urban Institute 2005). I add the state welfare program characteristics to the food stamp and WIC equations because those eligible for TANF benefits are automatically eligible for food stamps and WIC benefits.

  31. A literature review by Rush et al. (1980) suggests nutrition during the third trimester is most important.

  32. Actually, providing food stamps to expectant mothers in my sample would only decrease the probability of gaining an insufficient amount of weight by 6 percentage points if none of the low-income expectant mothers were receiving food stamps initially. Since about 48% receive food stamps, providing such benefits to the 52% who were not receiving food stamps initially would decrease the probability of gaining an insufficient amount of weight in my sample by about half of 6 percentage points. However, to determine the marginal effect of providing food stamps to every expectant mother in my sample (versus no food stamp receipt), my calculations assume the probability of gaining an insufficient amount of weight decreases by the full 6 percentage points.

  33. Similarly, many studies, which are summarized by a GAO report (1992), find that WIC reduces low birth weight, though this conclusion has been challenged recently by some who contend that much of this effect appears to operate through preterm birth but that it is unlikely WIC would affect gestation length (Joyce et al. 2005).

  34. Food stamp recipients in my sample receive roughly $200.00 a month on average in food stamp benefits.

References

  • Abrams BF, Selvin S (1995) Maternal weight gain pattern and birth weight. Obstet Gynecol 86(2):163–169

    Article  Google Scholar 

  • Abrams B, Altman SL, Pickett KE (2000) Pregnancy weight gain: still controversial. Am J Clin Nutr 71(5):1233S–1241S

    Google Scholar 

  • Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki C (eds) 2nd international symposium on information theory. Akademiai Kiado, Budapest, pp 267–281

    Google Scholar 

  • Akin JS, Guilkey DK, Popkin BM, Smith KM (1985) The impact of federal transfer programs on the nutrient intake of elderly individuals. J Hum Resour 20(3):383–404

    Article  Google Scholar 

  • Almond D, Hoynes HW, Schanzenbach DW (2011) Inside the war on poverty: the impact of food stamps on birth outcomes. Rev Econ Stat 93(2):387–403

    Article  Google Scholar 

  • Basiotis P, Kramer-LeBlanc CS, Kennedy ET (1998) Maintaining nutrition security and diet quality: the role of the food stamp program and WIC. Fam Econ Nutr Rev 11(1–2):4–16

    Google Scholar 

  • Baum CL (2007) The effects of race, ethnicity, and age on obesity. J Popul Econ 20(3):687–705

    Article  Google Scholar 

  • Baum CL (2011) The effects of food stamps on obesity. South Econ J 77(3):623–651

    Article  Google Scholar 

  • Bitler M, Currie J, Scholz JK (2003) WIC eligibility and participation. J Hum Resour 38(S):1139–1179

    Article  Google Scholar 

  • Blau DM (1994) Labor force dynamics of older men. Econometrica 62(1):117–156

    Article  Google Scholar 

  • Blau DM, Hagy A (1998) The demand for quality in child care. J Polit Econ 106(1):104–146

    Article  Google Scholar 

  • Bollinger CR, David M (1997) Modeling discrete choice with response error: food stamp participation. J Am Stat Assoc 92(439):827–835

    Google Scholar 

  • Bollinger CR, David M (2001) Estimation with response error and nonresponse: food-stamp participation in the SIPP. J Bus Econ Stat 19(2):129–141

    Article  Google Scholar 

  • Bollinger CR, David M (2005) I didn’t tell, and i won’t tell: dynamic response error in the SIPP. J Appl Econ 20(4):563–569

    Article  Google Scholar 

  • Burstein NR, Hamilton WL, Fox MK, Price C, Battaglia M (2005) Assessing the food security and diet quality impacts of FNS program participation. United States Department of Agriculture, Economic Research Service, Supplemental Nutrition Assistance Program Studies, Washington

    Google Scholar 

  • Butte NF, Ellis KJ, Wong WW, Hopkinson JM, Smith EO (2003) Composition of gestational weight gain impacts maternal fact retention and infant birth weight. Am J Obstet Gynecol 189(5):1423–1432

    Article  Google Scholar 

  • Caulfield LE, Stolzfus RJ, Witter FR (1998) Implications of the institute of medicine weight gain recommendations for preventing adverse pregnancy outcomes in black and white women. Am J Public Health 88(8):1168–1174

    Article  Google Scholar 

  • Cawley J (2004) The impact of obesity on wages. J Hum Resour 39(2):451–474

    Article  Google Scholar 

  • Centers for Disease Control and Prevention (CDC) (2006a) Overweight and obesity: defining overweight and obesity. Centers for Disease Control and Prevention, Department of Health and Human Services, Washington. http://www.cdc.gov/nccdphp/dnpa/obesity/defining.htm

    Google Scholar 

  • Centers for Disease Control and Prevention (CDC) (2006b) BMI—body mass index: home. Centers for Disease Control and Prevention, Department of Health and Human Services, Washington. http://www.cdc.gov/nccdphp/dnpa/bmi/index.htm

    Google Scholar 

  • Centers for Disease Control and Prevention (CDC) (2006c) Birth outcome and risk factor analysis. Centers for Disease Control and Prevention, Department of Health and Human Services, Washington. http://www.cdc.gov/pednss/how_to/read_a_data_table/prevalence_tables/birth_outcome.htm

    Google Scholar 

  • Chen Z, Yen ST, Eastwood DB (2005) Effects of food stamp participation on body weight and obesity. Am J Agric Econ 87(5):1167–1173

    Article  Google Scholar 

  • Chomitz VR, Cheung LWY, Lieberman E (1995) The role of lifestyle in preventing low birth weight. Future Child 5(1):121–138

    Article  Google Scholar 

  • Cogswell ME, Serdula MK, Hungerford DW, Yip R (1995) Gestational weight gain among average-weight and overweight women—what is excessive? Am J Obstet Gynecol 172(2):705–712

    Article  Google Scholar 

  • Costa DL (2004) Race and pregnancy outcomes in the twentieth century: a long-term comparison. J Econ Hist 64(4):1056–1086

    Article  Google Scholar 

  • Crouse G (1999) State implementation of major changes to welfare policies, 1992–1998. Research Report. Assistant Secretary for Planning and Evaluation, US Department of Health and Human Services, Washington DC

  • Currie J, Cole N (1991) Does participation in transfer programs during pregnancy improve birth weight? National Bureau of Economic Research, Cambridge, Number 13987

    Google Scholar 

  • Currie J, Moretti E (2008) Did the introduction of food stamps affect birth outcomes in California? In: Schoeni R, House J, Kaplan G, Pollack H (eds) Making Americans healthier: social and economic policy as health policy. Russell Sage Foundation, New York, pp 122–142

    Google Scholar 

  • Devaney B, Fraker T (1989) The effect of food stamps on food expenditures: an assessment of findings from the Nationwide Food Consumption Survey. Am J Agric Econ 71(1):99–104

    Article  Google Scholar 

  • Devaney B, Moffitt R (1991) Dietary effects of the food stamp program. Am J Agric Econ 73(1):202–211

    Article  Google Scholar 

  • Ehrenberg HM, Dierker L, Milluzzi C, Mercer BM (2003) Low maternal weight, failure to thrive in pregnancy, and adverse pregnancy outcomes. Am J Obstet Gynecol 189(6):1726–1730

    Article  Google Scholar 

  • Flegal KM, Carroll MD, Ogden CL, Johnson CL (2002) Prevalence and trends in obesity among US adults, 1999–2000. J Am Med Assoc 288(14):1723–1727

    Article  Google Scholar 

  • Flegal KM, Graubard BI, Williamson DF, Gail MH (2005) Excess deaths associated with underweight, overweight, and obesity. J Am Med Assoc 293(15):1861–1867

    Article  Google Scholar 

  • Fraker TM (1990) The effects of food stamps on food consumption: a review of the literature. Food and Nutrition Service, Alexandria

    Google Scholar 

  • Fraker TM, Martini AP, Ohls JC (1995) The effect of food stamp cashout on food expenditures. J Hum Resour 30(4):633–649

    Article  Google Scholar 

  • Gabor V, Botsko C (1998) State food stamp policy choices under welfare reform: findings of 1997 50-state survey. United States Department of Agriculture, Washington

    Google Scholar 

  • General Accounting Office (GAO) (1992) Early intervention: federal investments like WIC can produce savings. General Accounting Office, Washington

    Google Scholar 

  • Gibson D (2003) Food stamp program participation is positively related to obesity in low income women. J Nutr 133(7):2225–2231

    Google Scholar 

  • Gritz RM (1987) An empirical analysis of the effect of training programs on employment. Dissertation, Stanford University, Stanford, CA

  • Gritz RM (1993) The impact of training on the frequency and duration of employment. J Econom 57(1–3):21–51

    Article  Google Scholar 

  • Gundersen C (2008) Measuring the extent, depth, and severity of food insecurity: an application to American Indians in the USA. J Popul Econ 21(1):191–215

    Article  Google Scholar 

  • Gundersen C, Kreider B (2008) Food stamps and food insecurity: what can be learned in the presence of nonclassical measurement error? J Hum Resour 43(2):352–382

    Google Scholar 

  • Gundersen C, Kreider B (2009) Bounding the effects of food insecurity on children’s health outcomes. J Health Econ 28(5):971–983

    Article  Google Scholar 

  • Gunderson EP, Abrams BF (2000) Epidemiology of gestational weight gain and body weight changes after pregnancy. Epidemiol Rev 22(2):261–274

    Article  Google Scholar 

  • Gunderson EP, Abrams BF, Selvin S (2000) The relative importance of gestational weight gain and maternal characteristics associated with the risk of becoming overweight after pregnancy. Int J Obes 24(12):1660–1668

    Article  Google Scholar 

  • Ham JC, LaLonde RJ (1996) The effect of sample selection and initial conditions in duration models: evidence from experimental data on training. Econometrica 64(1):175–205

    Article  Google Scholar 

  • Hamilton WL, Rossi PH (2002) The effects of food assistance and nutrition programs on nutrition and health. United States Department of Agriculture, Economic Research Service, Food Assistance and Nutrition Research Report Number 19-1, Washington, DC

  • Heckman JJ, Singer B (1984) A method for minimizing the distributional assumptions in econometric models for duration data. Econometrica 52(2):271–320

    Article  Google Scholar 

  • Heckman JJ, Walker JR (1990) The relationship between wages and income and the timing and spacing of births: evidence from Swedish longitudinal data. Econometrica 58(6):1411–1441

    Article  Google Scholar 

  • Hediger ML, Scholl TO, Belsky DH, Ances IG, Salmon RW (1989) Patterns of weight gain in adolescent pregnancy: effects on birth weight and pre-term delivery. Obstet Gynecol 74(1):6–12

    Google Scholar 

  • Hickey CA (2000) Sociocultural and behavioral influences on weight gain during pregnancy. Am J Clin Nutr 71(supplement):1364–1370

    Google Scholar 

  • Hickey CA, Cliver SP, McNeal SF, Hoffman HJ, Goldenberg RL (1995) Prenatal weight gain patterns and spontaneous preterm birth among non-obese black and white women. Obstet Gynecol 85(6):909–914

    Article  Google Scholar 

  • Hickey CA, Cliver SP, McNeal SF, Hoffman HJ, Goldenberg RL (1996) Prenatal weight gain patterns and birth weight among non-obese black and white women. Obstet Gynecol 88(4):490–496

    Article  Google Scholar 

  • Hotz VJ, Xu LC, Tienda M, Ahituv A (2002) Are there returns to the wages of young men from working while in school? Rev Econ Stat 84(2):221–236

    Article  Google Scholar 

  • Hurst E, Ziliak JP (2006) Do welfare asset limits affect household saving? Evidence from welfare reform. J Hum Resour 41(4):46–71

    Google Scholar 

  • Institute of Medicine (1985) Preventing low birth weight. National Academy Press, Washington

    Google Scholar 

  • Institute of Medicine (1990) Nutrition during pregnancy. National Academy Press, Washington

    Google Scholar 

  • Johnson JWC, Yancey MK (1996) A critique of the new recommendations for weight gain in pregnancy. Am J Obstet Gynecol 174(1):254–258

    Article  Google Scholar 

  • Johnson JWC, Longmate JA, Frentzen B (1992) Excessive maternal weight and pregnancy outcome. Am J Obstet Gynecol 167(1):353–372

    Google Scholar 

  • Joyce T, Gibson D, Colman S (2005) The changing association between prenatal participation in WIC and birth outcomes in New York City. J Policy Anal Manage 24(4):661–685

    Article  Google Scholar 

  • Kabbani NS, Wilde PE (2003) Short recertification periods in the US food stamp program. J Hum Resour 83(5):1112–1138

    Article  Google Scholar 

  • Kaushal N (2007) Do food stamps cause obesity? Evidence from immigrant experience. J Health Econ 26(5):968–991

    Article  Google Scholar 

  • Kiely JL, Susser M (1992) Preterm birth, intrauterine growth retardation, and perinatal mortality. Am J Public Health 82(3):343–345

    Article  Google Scholar 

  • Kline J, Stein Z, Susser M (1989) Conception to birth: epidemiology of prenatal development. Oxford University Press, New York

    Google Scholar 

  • Knaus J (2003) Food stamp program state options report. United States Department of Agriculture, Food and Nutrition Service, Washington

    Google Scholar 

  • Koops BL, Morgan LJ, Battaglia FC (1982) Neonatal mortality risk in relation to birth weight and gestational age: update. J Pediatr 101(6):969–977

    Article  Google Scholar 

  • Kramer MS (1987a) Intrauterine growth and gestational determinants. Pediatrics 80(4):502–511

    Google Scholar 

  • Kramer MS (1987b) Determinants of low birth weight: methodological assessment and meta-analysis. Bull W H O 65(5):633–737

    Google Scholar 

  • Kramer MS, Coates AL, Michoud MC, Dagenais S, Hamilton EF, Papageorgiou A (1995) Maternal anthropometry and idiopathic preterm labor. Obstet Gynecol 86(5):744–748

    Article  Google Scholar 

  • Marsoosi V, Jamal A, Eslamian L (2004) Pre-pregnancy weight, low pregnancy weight gain, and preterm delivery. Int J Gynaecol Obstet 87(1):36–37

    Article  Google Scholar 

  • McCormick MC (1985) The contribution of low birth weight to infant mortality and childhood mortality. New Engl J Med 312(2):82–90

    Article  Google Scholar 

  • Meyerhoefer CD, Pylypchuk Y (2008) Does participation in the Food stamp program increase the prevalence of obesity and health care spending? Am J Agric Econ 90(2):287–305

    Article  Google Scholar 

  • Mokdad AH (2005) Correction: actual causes of death in the United States, 2000. J Am Med Assoc 293(3):293

    Article  Google Scholar 

  • Mokdad HA, Marks JS, Stroup DF, Gerberding JL (2004) Actual causes of death in the United States, 2000. J Am Med Assoc 291(10):1238–1245

    Article  Google Scholar 

  • Mroz TA (1999) Discrete factor approximations in simultaneous equation models: estimating the impact of a dummy endogenous variable on a continuous outcome. J Econom 92(2):233–274

    Article  Google Scholar 

  • Mroz TA, Savage TH (2006) The long-term effects of youth unemployment. J Hum Resour 41(2):259–293

    Google Scholar 

  • Mucscati S, Donald-Grey K, Koski K (1996) Timing of weight gain during pregnancy: promoting fetal growth and minimizing maternal weight retention. Int J Obes 20(6):526–532

    Google Scholar 

  • National Governors Association (2011) Maternal and child health (MCH) update. Research Reports from Various Years. National Governors Association, NGA Center for Best Practices, Washington. http://www.nga.org/portal/site/nga/menuitem.9123e83a1f6786440ddcbeeb501010a0/?vgnextoid=3ee2303cb0b32010VgnVCM1000001a01010aRCRD&vgnextchannel=4b18f074f0d9ff00VgnVCM1000001a01010aRCRD

  • Ogden CL, Flegal KM, Carroll MD, Johnson CL (2002) Prevalence and trends in overweight among US children and adolescents, 1999–2000. J Am Med Assoc 288(14):1728–1732

    Article  Google Scholar 

  • Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM (2006) Prevalence of overweight and obesity in the United States, 1999–2004. J Am Med Assoc 295(13):1549–1555

    Article  Google Scholar 

  • Pitt M (1997) Estimating the determinants of child health when fertility and mortality are selective. J Hum Resour 32(1):129–158

    Article  Google Scholar 

  • Rooney BL, Schauberger CW (2002) Excess pregnancy weight gain and long-term obesity: one decade later. Obstet Gynecol 100(2):245–253

    Article  Google Scholar 

  • Rose D, Habicht JP, Devaney B (1997) Household participation in the food stamp and WIC programs increases the nutrient intakes of preschool children. J Nutr 128(3):548–55

    Google Scholar 

  • Rosenberg TJ, Garbers S, Lipkind H, Chiasson MA (2005) Maternal obesity and diabetes as risk factors for adverse pregnancy outcomes: differences among 4 racial/ethnic groups. Am J Public Health 95(9):1545–1551

    Article  Google Scholar 

  • Rush D, Stein Z, Susser M (1980) Diet in pregnancy: a randomized controlled trial of nutritional supplements. Alan R. Liss, Inc., New York

    Google Scholar 

  • Schieve LA, Cogswell ME, Scanlon KS (1998) An empiric evaluation of the institute of medicine’s pregnancy weight gain guidelines by race. Obstet Gynecol 91(6):878–884

    Article  Google Scholar 

  • Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica 65(3):557–586

    Article  Google Scholar 

  • Stephansson O, Dickman PW, Johansson A, Cnattingius S (2001) Maternal weight, pregnancy weight gain, and the risk of antepartum stillbirth. Am J Obstet Gynecol 184(3):463–469

    Article  Google Scholar 

  • Sullivan JX (2006) Welfare reform, saving, and vehicle ownership: do asset limits and vehicle exemptions matter? J Hum Resour 41(1):72–105

    Google Scholar 

  • Super D, Dean S (2001) New state options to improve the food stamp vehicle rule. Center on Budget and Policy Priorities, Washington. http://www.cbpp.org/1-16-01fs.htm

    Google Scholar 

  • Tekin E (2007a) Childcare subsidies, wages, and employment of single mothers. J Hum Resour 42(2):453–487

    Google Scholar 

  • Tekin E (2007b) Single mothers working at night: standard work and child care subsidies. Econ Inq 45(2):233–250

    Article  Google Scholar 

  • Thorsdottir I, Torfadottir JE, Birgisdottir BE, Geirsson RT (2002) Weight gain in women of normal weight before pregnancy: complications in pregnancy or delivery and birth outcome. Obstet Gynecol 99(5):799–807

    Article  Google Scholar 

  • United States Department of Health and Human Services (2000) Healthy people 2010: understanding and improving health. US Department of Health and Human Services, Washington

    Google Scholar 

  • Urban Institute (2005) The welfare rules database. Urban Institute, Washington. http://www.urban.org/content/Research/Databases/Databases.htm

    Google Scholar 

  • Wilde PE, Nord M (2005) The effect of food stamps on food security: a panel data approach. Rev Agric Econ 27(3):425–432

    Article  Google Scholar 

  • Wilde PE, McNamara PE, Ranney CK (1999) The effect of income and food programs on dietary quality: a seemingly unrelated regression analysis with error components. Am J Agric Econ 81(4):959–971

    Article  Google Scholar 

  • Young TK, Woodmansee B (2002) Factors that are associated with cesarean delivery in a large private practice: the importance of prepregnancy body mass index and weight gain. Am J Obstet Gynecol 187(2):312–320

    Article  Google Scholar 

  • Ziliak JP, Gundersen C, Figlio DN (2003) Food stamp caseloads over the business cycle. South Econ J 69(4):903–919

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Charles L. Baum.

Additional information

Responsible editor: Erdal Tekin

This project was supported with a grant from the University of Wisconsin’s Institute for Research on Poverty (UW-IRP) through the U.S. Department of Agriculture. The opinions and conclusions expressed are solely those of the author and should not be construed as representing the opinions or policy of the UW-IRP or any agency of the federal government. I thank two referees for helpful comments and suggestions.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

(PDF 365 KB)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Baum, C.L. The effects of food stamp receipt on weight gained by expectant mothers. J Popul Econ 25, 1307–1340 (2012). https://doi.org/10.1007/s00148-011-0391-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00148-011-0391-7

Keywords

  • Weight gain
  • Obesity
  • Mothers

JEL CLassification

  • J1
  • J18
  • J13