Journal of Child and Family Studies

, Volume 28, Issue 3, pp 753–764 | Cite as

Beyond Income: Expanding our Empirical Toolkit to Better Predict Caregiver Well-Being

  • Eliana Hurwich-ReissEmail author
  • Sarah Enos Watamura
  • C. Cybele Raver
  • The BTS Consortium PI’s
Original Paper



Despite growing concern that income alone does not capture how low-income families are managing financially, it continues to be one of the most commonly used indicators of socioeconomic status and is routinely used as a qualifying factor for government assistance programs. Income can be difficult to measure accurately and alone may not be the best predictor of caregiver well-being, in particular among ethnically diverse families. A more nuanced understanding may be critical for identifying families in need of services and supporting success after enrollment in need-based programming. Thus, the current study investigated the relationship between traditional (low income, low education, unemployment), and less traditional (economic pressure, economic hardship, perceived social status, crowding) socioeconomic indicators and caregiver well-being (caregiver depressive symptoms, anxiety, dysfunction in the parent-child relationship) using data from a multisite study.


Participants were 978 racially/ethnically diverse caregivers (97% female) of young children enrolled in Early Head Start programming from six sites across the United States.


Exploratory factor analyses resulted in a three-factor model, capturing demographic risk, resource strain, and perceived social status. The Resource Strain factor was most strongly associated with greater caregiver depressive and anxiety symptoms, and dysfunction in the parent-child relationship. Further, hierarchical regression models revealed up to a four-fold increase in variance explained when adding economic strain along with traditional variables to models predicting caregiver well-being.


Results support the need to supplement traditional economic measurement when supporting families experiencing low income and for measuring poverty among ethnically diverse families.


Low-income families Economic strain Caregiver mental-health Children in poverty Income 


BTS Consortium PIs

Lisa Berlin3, Clancy Blair2, John N. Constantino4, Rena A. Hallam5, Myae Han5, Jason T. Hustedt5, Brenda Jones Harden3, Michelle Sarche6, and Jennifer A. Vu5.

Author Contributions

E.H.R. led analyses, design, execution, and writing of the manuscript. S.E.W. contributed to the conceptualization of the study design and collaborated with the design, analyses and writing of the manuscript. C.C.R. contributed to the conceptualization of the study design and collaborated with the design and writing of the manuscript. BTS Consortium PIs contributed to conceptualization of the question, study design, and collaborated in writing and editing of the final manuscript.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

Ethical Approval

This study was funded by grants from the Administration for Children and Families to the University of Denver (90YR0056), the University of Colorado-Denver (90YR0058), New York University (90YR0057), Washington University in St. Louis (90YR0054), the University of Delaware (90YR0055), and the University of Maryland School of Social Work (90YR0059). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study. The authors have no conflict of interests related to this publication. The authors’ work in the conceptualization, design, and drafting of this paper was supported by cooperative agreements from the Administration for Children and Families to the University of Denver (90YR0056), the University of Colorado-Denver (90YR0058), the New York University (90YR0057), Washington University in St. Louis (90YR0054), the University of Delaware (90YR0055), and the University of Maryland School of Social Work (90YR0059).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of DenverDenverUSA
  2. 2.New York UniversityNew YorkUSA

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