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Measuring Material Hardship among the US Population of Women with Disabilities Using Latent Class Analysis

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Abstract

We use data from the 2002 wave of the National Survey of America’s Families to develop and validate discrete measures of material hardship that can be used to examine the difficulties that vulnerable populations such as people with disabilities have in making ends meet. Using latent class analysis, we estimate two measurement models: multidimensional and omnibus. The multidimensional model provides separate estimates for food, medical, and housing and utilities hardship. The omnibus model is a single model of 11 hardship indicators. Results show three distinct classes of food hardship, three classes of medical hardship, and two classes of housing/utilities hardship. The omnibus model reveals eight classes. Both the multidimensional and omnibus models are largely invariant between women with disabilities and women without disabilities, indicating that valid comparisons can be made between these populations using these classes of hardship. These classes can be utilized in further research on the hardship of women with disabilities to inform the development of policies targeted to alleviate the specific forms of hardship experienced by disabled women.

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References

  • Abi-Habib, N., Safir, A., & Triplett, T. (2004). NSAF public use file user’s guide. Report no. 11 in the 2002 national survey of America’s families methodology series, Washington, DC: Urban Institute. http://www.urban.org/url.cfm?ID=900760.

  • Aday, L. A., & Andersen, R. M. (1981). Equity of access to medical care: A conceptual and empirical overview. Medical Care, 19(Suppl), 4–27. doi:10.1097/00005650-198112001-00004.

    Article  Google Scholar 

  • Aday, L. A., & Andersen, R. M. (1984). The national profile of access to medical care: Where do we stand? American Journal of Public Health, 74, 1331–1339. doi:10.2105/AJPH.74.12.1331.

    Article  Google Scholar 

  • Ashiabi, G. S., & O’Neal, K. K. (2007). Children’s health status: Examining the associations among income poverty, material hardship, and parental factors. PLoS ONE, 2(9), e940. doi:10.1371/journal.pone.0000940.

    Article  Google Scholar 

  • Atkinson, A. B., & Bourguignon, F. (1982). The comparison of multi-dimensioned distributions of economic status. The Review of Economic Studies, 49(2), 183–201. doi:10.2307/2297269.

    Article  Google Scholar 

  • Ayala, L., & Navarro, C. (2004). Multidimensional indices of housing deprivation with application to Spain, working papers 12-04. Instituto de Estudios Fiscales.

  • Bachman, H. J., & Chase-Lansdale, P. L. (2005). Custodial grandmothers’ physical, mental, and economic well-being: Comparisons of primary caregivers from low-income neighborhoods. Family Relations, 54(4), 475–487. doi:10.1111/j.1741-3729.2005.00334.x.

    Article  Google Scholar 

  • Bauman, K. J. (1998). Direct measures of poverty as indicators of economic need: Evidence from the survey of income and program participation. Washington, DC: U. S. Census Bureau.

    Google Scholar 

  • Bauman, K. J. (1999). Shifting family definitions: The effect of cohabitation and other nonfamily household relationships on measures of poverty. Demography, 36(3), 315–325. doi:10.2307/2648055.

    Article  Google Scholar 

  • Bauman, K. J. (2000). Measurement of material well-being in the survey of income and program participation. Washington, DC: U. S. Census Bureau.

    Google Scholar 

  • Bauman, K. J. (2002). Welfare, work, and material hardship in single parent and other households. Journal of Poverty, 6, 21–40. doi:10.1300/J134v06n01_02.

    Article  Google Scholar 

  • Beresford, P. (1996). Poverty and disabled people: Challenging dominant debates and policies. Disability & Society, 11(4), 553–567. doi:10.1080/09687599627598.

    Article  Google Scholar 

  • Beverly, S. G. (2000). Using measures of material hardship to assess well-being. Focus (San Francisco, Calif.), 21(2), 65–69.

    Google Scholar 

  • Beverly, S. G. (2001). Material hardship in the United States: Evidence from the survey of income and program participation. Social Work Research, 25(3), 143–151.

    Google Scholar 

  • Bourguignon, F., & Chakravarty, S. R. (2003). The measurement of multidimensional poverty. The Journal of Economic Inequality, 1, 25–49. doi:10.1023/A:1023913831342.

    Article  Google Scholar 

  • Boushey, H., Brocht, C., Gundersen, B., & Bernstein, J. (2001). Hardship in America: The real story of working families. Washington, DC: Economic Policy Institute.

    Google Scholar 

  • Boushey, H., & Gundersen, B. (2001). When working just isn’t enough: Measuring hardships faced by families after moving from welfare to work. Washington, DC: Economic Policy Institute.

    Google Scholar 

  • Cancian, M., & Meyer, D. R. (2004). Alternative measures of economic success among TANF participants: Avoiding poverty, hardship, and dependence on public assistance. Journal of Policy Analysis and Management, 23(3), 531–548. doi:10.1002/pam.20025.

    Article  Google Scholar 

  • Carle, A. C., Bauman, K. J., & Short, K. (2008). Assessing the measurement and structure of material hardship in the United States. Social Indicators Research. Retrieved September 20, 2008, from http://www.springerlink.com.libproxy.lib.unc.edu/content/650u514ppm80h635/fulltext.html.

  • Charles, K. K., Danziger, S., Pounder, L., & Schoeni, R. F. (2006). Consumption, income, and well-being among the mature population. Ann Arbor, MI: National Poverty Center.

    Google Scholar 

  • Chen, F. F., Sousa, K. H., & West, S. G. (2005). Testing measurement invariance of second-order factor models. Structural Equation Modeling, 12, 471–492. doi:10.1207/s15328007sem1203_7.

    Article  Google Scholar 

  • Claessens, S. (2006). Access to financial services: A review of the issues and public policy objectives. The World Bank Research Observer, 21(2), 207–240. doi:10.1093/wbro/lkl004.

    Article  Google Scholar 

  • Corcoran, M. E., Helfin, C. M., & Siefert, K. (1999). Food insufficiency and material hardship in post-TANF welfare families. Ohio State Law Journal, 60, 1395–1422.

    Google Scholar 

  • Danziger, S., Corcoran, M., Danziger, S., & Heflin, C. M. (2000). Work, income, and material hardship after welfare reform. The Journal of Consumer Affairs, 34(1), 6–30.

    Article  Google Scholar 

  • Danziger, S., Heflin, C. M., Corcoran, M. E., Oltmans, E., & Wang, H.-C. (2002). Does it pay to move from welfare to work? Journal of Policy Analysis and Management, 21(4), 671–692. doi:10.1002/pam.10080.

    Article  Google Scholar 

  • Desai, M., & Shah, A. (1988). An econometric approach to the measurement of poverty. Oxford Economic Papers, 40, 505–522.

    Google Scholar 

  • Dewilde, C. (2004). The multidimensional measurement of poverty in Belgium and Britain: A categorical approach. Social Indicators Research, 68(3), 331–369. doi:10.1023/B:SOCI.0000033578.81639.89.

    Article  Google Scholar 

  • Duclos, J. Y., Sahn, D. E., & Younger, S. D. (2006). Robust multidimensional poverty comparisons. The Economic Journal, 116, 943–968. doi:10.1111/j.1468-0297.2006.01118.x.

    Article  Google Scholar 

  • Edin, K., & Lein, L. (1997). Making ends meet: How single mothers survive from welfare and low-wage work. New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Ehrle, J., & Moore, K. (1999). Benchmarking child and family well-being measures in the national survey of America’s families. Washington, DC: Urban Institute. Retrieved August 18, 2007, from http://www.urban.org/UploadedPDF/Methodology_6.pdf.

  • Eid, M., Langeheine, R., & Diener, E. (2003). Comparing typological structures across cultures by multigroup latent class analysis: A primer. Journal of Cross-Cultural Psychology, 34(2), 195–210. doi:10.1177/0022022102250427.

    Article  Google Scholar 

  • Gassman-Pines, A., & Yoshikawa, H. (2006). Five-year effects of an anti-poverty program on marriage among never-married mothers. Journal of Policy Analysis and Management, 25(1), 11–30. doi:10.1002/pam.20154.

    Article  Google Scholar 

  • Gershoff, E. T., Aber, J. L., Raver, C. C., & Lennon, M. C. (2007). Income is not enough: Incorporating material hardship into models of income associations with parenting and child development. Child Development, 78(1), 70–95. doi:10.1111/j.1467-8624.2007.00986.x.

    Article  Google Scholar 

  • Giesbrecht, L. H., Kulp, D. W., & Starer, A. W. (1996). Estimating coverage bias in RDD samples with Current Population Survey data. In proceedings of the survey research methods section (pp. 503–508). Boston: American Statistical Association.

    Google Scholar 

  • Grinstein-Weiss, M., & Sherraden, M. (2006). Racial differences in performances in a matched savings program. Journal of Income Distribution, 13(3–4), 98–111.

    Google Scholar 

  • Haveman, R., Holden, K., Wolfe, B., Smith, P., & Wilson, K. (2000). The changing economic status of disabled women: 1982–1991. In D. S. Salkever & A. Sorkin (Eds.), The economics of disability (pp. 51–80). Stamford, CT: JAI Press.

    Chapter  Google Scholar 

  • Heflin, C. M. (2006). Dynamics of material hardship in women’s employment study. The Social Service Review, 80(3), 377–397. doi:10.1086/505289.

    Article  Google Scholar 

  • Hunter, T., & Santhiveeran, J. (2005). Experiences of material hardships among TANF leavers. Journal of Family Social Work, 9(1), 1–16. doi:10.1300/J039v09n01_01.

    Article  Google Scholar 

  • Iceland, J., & Bauman, K. J. (2007). Income poverty and material hardship: How strong is the association? The Journal of Socio-Economics, 36, 376–396.

    Article  Google Scholar 

  • Judkins, D., Brick, M. J., Broene, P., Ferraro, D., & Strickler, T. (2000). 1999 NSAF sample design: Report no. 2. Washington, DC: The Urban Institute Press.

    Google Scholar 

  • Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2007). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling: A Multidisciplinary Journal, 14, 671–694.

    Google Scholar 

  • Layte, R., Maitre, B., Nolan, B., & Whelan, C. T. (2000). Persistent and consistent poverty: An analysis of the first two waves of the ECHP. European panal analysis group working paper 11.

  • Lee, B. J., Slack, K. S., & Lewis, D. A. (2004). Are welfare sanctions working as intended? Welfare receipt, work activity, and material hardship among TANF-recipient families. Social Service Review, 78(3), 370–403.

    Article  Google Scholar 

  • Lerman, R. I. (2002a). How do marriage, cohabitation, and single parenthood affect the material hardship of families with children?. Washington, DC: Urban Institute.

    Google Scholar 

  • Lerman, R. I. (2002b). Impacts of marital status and parental presence on the material hardship of families with children. Washington, DC: Urban Institute.

    Google Scholar 

  • Loken, E. (2004). Using latent class analysis to model temperament types. Multivariate Behavioral Research, 39(4), 625–652. doi:10.1207/s15327906mbr3904_3.

    Article  Google Scholar 

  • Long, S. K. (2003). Hardship among the uninsured: Choosing among food, housing and health insurance (new federalism, series B, B-54) (pp. 1–7). Washington, DC: Urban Institute.

    Google Scholar 

  • Lovell, V., & Oh, G.-T. (2005). Women’s job loss and material hardship. Journal of Women, Politics & Policy, 3/4, 169–183. doi:10.1300/J501v27n03_12.

    Google Scholar 

  • Lubke, G. H., Dolan, C. V., & Neale, M. C. (2004). Implications of absence of measurement invariance for detecting sex limitation and genotype by environment interaction. Twin Research, 7, 292–298. doi:10.1375/136905204774200578.

    Article  Google Scholar 

  • Mayer, S. E., & Jencks, C. (1989). Poverty and the distribution of material hardship. The Journal of Human Resources, 24(1), 88–113. doi:10.2307/145934.

    Article  Google Scholar 

  • McCutcheon, A. L., & Hagenaars, J. A. (1997). Comparative social research with multi-sample latent class analysis in comparative social research. In J. Rost & R. Langeheine (Eds.), Applications of latent trait and latent class models in the social sciences (pp. 266–277). Münster, Germany: Waxmann.

    Google Scholar 

  • Meyer, M. K., & Lee, J. M. (2003). Working but poor: How are families faring? Children and Youth Services Review, 25(3), 177–201. doi:10.1016/S0190-7409(03)00002-1.

    Article  Google Scholar 

  • Millsap, R. E., & Kwok, O. (2004). Evaluating the impact of partial factorial invariance on selection in two populations. Psychological Methods, 9, 93–115. doi:10.1037/1082-989X.9.1.93.

    Article  Google Scholar 

  • Mirowsky, J., & Ross, C. E. (1999). Economic hardship across the life course. American Sociological Review, 64(4), 548–569. doi:10.2307/2657255.

    Article  Google Scholar 

  • Muthén, B. O., & Muthén, L. (2004). Mplus user’s guide. Los Angeles: Muthén & Muthén.

    Google Scholar 

  • Nolan, B., & Whelan, C. T. (1996). Measuring poverty using income and deprivation indicators: Alternative approaches. Journal of European Social Policy, 6(3), 225–240. doi:10.1177/095892879600600304.

    Article  Google Scholar 

  • Norris, J., Scott, R., Speiglman, R., & Green, R. S. (2003). Homelessness, hunger, and material hardship among those who lost SSI. Contemporary Drug Problems, 30(1–2), 241–273.

    Google Scholar 

  • Nylund, K. L., Asparouhov, T., & Muthén, B. (2007). Deciding on the number of classes inlatent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14, 535–569.

    Google Scholar 

  • Ouellette, T., Burstein, N., Long, D., & Beecroft, E. (2004). Measures of material hardship: Final report. Washington, DC: U. S. Department of Health & Human Services, Office of the Assistant Secretary for Planning and Evaluation.

  • Parish, S. L., Rose, R. A., Andrews, M. E., Grinstein-Weiss, M., & Richman, E. L. (2008). Material hardship among U. S. families raising children with disabilities. Exceptional Children, 75(1), 71–92.

    Google Scholar 

  • Parish, S. L., Rose, R. A., & Andrews, M. E. (2009). Income poverty and material hardship among U. S. women with disabilities. The Social Service Review (in press).

  • Perez-Mayo, J. (2005). Identifying deprivation profiles in Spain: A new approach. Applied Economics, 37(8), 943–955. doi:10.1080/00036840500060972.

    Article  Google Scholar 

  • Rector, R. E., Johnson, K. A., & Youssef, S. E. (1999). The extent of material hardship and poverty in the United States. Review of Social Economy, 57(3), 351–387. doi:10.1080/00346769900000007.

    Article  Google Scholar 

  • Reichman, N. E., Teitler, J. O., & Curtis, M. A. (2005). TANF sanctioning and hardship. The Social Service Review, 79(2), 215–236. doi:10.1086/428918.

    Article  Google Scholar 

  • Reichman, N. E., Teitler, J. O., Garfinkel, I., & Garcia, S. (2004). Variations in maternal and child well-being among financially eligible mothers by TANF participation status. Eastern Economic Journal, 30(1), 101–118.

    Google Scholar 

  • Renwick, T. J., & Bergmann, B. R. (1993). A budget-based definition of poverty, with an application to single-parent families. The Journal of Human Resources, 28(1), 1–24. doi:10.2307/146086.

    Article  Google Scholar 

  • Safir, A., Scheuren, F., & Wang, K. (2000). Survey methods and data reliability, 1997 and 1999. Prepared for the Urban Institute. http://www.urban.org/url.cfm?ID=310567.

  • Schafer, J. L. (1997). Analysis of incomplete multivariate data. Boca Raton, FL: Chapman Hall/CRC.

    Google Scholar 

  • Sen, A. K. (1999). Development as freedom. New York, NY: Knopf.

    Google Scholar 

  • She, P., & Livermore, G. A. (2007). Material hardship, poverty, and disability among working-age adults. Social Science Quarterly, 88(4), 970–989. doi:10.1111/j.1540-6237.2007.00513.x.

    Article  Google Scholar 

  • Short, K. (2005). Material and financial hardship and income-based poverty measures. Journal of Social Policy, 34(1), 21–38. doi:10.1017/S0047279404008244.

    Article  Google Scholar 

  • Short, K., & Shea, M. (1995). Beyond poverty, extended measures of well-being: 1992. Current population reports, P70–50RV. Washington, DC: U. S. Census Bureau.

    Google Scholar 

  • Steinmetz, E. (2006). Americans with disabilities: 2002. Current population reports P70–107, –32. Washington, DC: U. S. Census Bureau.

    Google Scholar 

  • Sullivan, J. X., Turner, L., & Danziger, S. (2008). The relationship between income and material hardship. Journal of Policy Analysis and Management, 27(1), 63–81. doi:10.1002/pam.20307.

    Article  Google Scholar 

  • Teitler, J. O., Reichman, N. E., & Nepomnyaschy, L. (2004). Sources of support, child care, and hardship among unwed mothers, 1999–2001. The Social Service Review, 78(1), 125–148. doi:10.1086/380770.

    Article  Google Scholar 

  • Townsend, P. (1979). Poverty in the United Kingdom. London, Middlesex: Allan Lane.

    Google Scholar 

  • Tsonaka, R., & Moustaki, I. (2007). Parameter constraints in generalized linear latent variable models. Computational Statistics & Data Analysis, 51(9), 4164–4177. doi:10.1016/j.csda.2006.04.023.

    Article  Google Scholar 

  • Tsui, K. (1999). Multidimensional inequality and multidimensional generalized entropy measures: An axiomatic derivation. Social Choice and Welfare, 16, 145–157.

    Article  Google Scholar 

  • van de Vijver, F., & Leung, K. (1996). Methods and data analysis of comparative research. In J. W. Berry, Y. H. Poortinga, & J. Pandey (Eds.), Handbook of cross-cultural psychology (2nd ed., Vol. 1, pp. 257–300). Chicago, IL: Allyn & Bacon.

    Google Scholar 

  • van de Vijver, F., & Leung, K. (1997). Methods and data analysis for cross-cultural research. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4–70.

    Article  Google Scholar 

  • Wang, Q. (2005). Disability and american families: 2000. U. S. Bureau of Census, census 2000 special reports. Washington, D.C.: U. S. Department of Commerce.

  • Warren, P., & Cunningham, P. (2003, June). 2002 National Survey of America's Families telephone survey methods. http://www.urban.org/UploadedPDF/900693_2002_Methodology_9.pdf. Accessed 3 Apr 2008.

  • Yoo, J., Slack, K. S., & Holl, J. (2008). Material hardship and the physical health of school-aged children in low-income households. American Journal of Public Health, 98, First Look. Retrieved October 8, 2008, from http://www.ajph.org/cgi/reprint/AJPH.2007.119776v1.

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  1. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Roderick A. Rose, Susan L. Parish & Joan P. Yoo

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  1. Roderick A. Rose
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Correspondence to Susan L. Parish.

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Rose, R.A., Parish, S.L. & Yoo, J.P. Measuring Material Hardship among the US Population of Women with Disabilities Using Latent Class Analysis. Soc Indic Res 94, 391–415 (2009). https://doi.org/10.1007/s11205-008-9428-z

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