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Measuring the “Sandwich”: Care for Children and Adults in the American Time Use Survey 2003–2012

While the economic burden of simultaneously caring for young and old family members is widely recognized, it has yet to be accurately measured. Yet, such assessments are relevant both to public policies providing support to family caregivers and to private insurance markets for long-term care. This...

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Detalles Bibliográficos
Autor principal: Suh, Jooyeoun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883270/
https://www.ncbi.nlm.nih.gov/pubmed/27279726
http://dx.doi.org/10.1007/s10834-016-9483-6
Descripción
Sumario:While the economic burden of simultaneously caring for young and old family members is widely recognized, it has yet to be accurately measured. Yet, such assessments are relevant both to public policies providing support to family caregivers and to private insurance markets for long-term care. This descriptive study presents a new method to address this problem: the construction of a crosswalk between time-use diaries and other types of surveys using lists of activities of daily living (ADLs) and instrumental activities of daily living (IADLs) for which assistance is required. Analysis of pooled data from American time use survey 2003–2012 provides some quantitative indicators, but understates the temporal burden of care and fails to distinguish types of care that involve personal interaction from those that do not. A crosswalk of time-use survey categories with the list-based approach typically applied in public health surveys clearly demonstrates the importance of clear definitions and also offers more precise measures. Depending on how sandwich caregiving was defined, the temporal burden for caregiving ranged from 11.2 to 60 h per week, clustering at around 20 h per week for most cases. This result demonstrates the magnitude of sandwich care demands and also underscores the need for improved care survey design. As shown in this study, such efforts should take into account the implications of disaggregating data by gender and age, and definitional variations that characterize existing datasets.