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. 2019 Jan 1;74(1):148-159.
doi: 10.1093/geronb/gby025.

A Conceptual Matrix of the Temporal and Spatial Dimensions of Socioeconomic Status and Their Relationship with Health

Ben Lennox Kail  1 , Amy Spring  1 , Matt Gayman  1
Affiliations

A Conceptual Matrix of the Temporal and Spatial Dimensions of Socioeconomic Status and Their Relationship with Health

Ben Lennox Kail et al. J Gerontol B Psychol Sci Soc Sci. .

Abstract

Objectives: In this study, we (a) draw on fundamental cause theory, the life course perspective, and neighborhood effects to develop conceptual matrix of socioeconomic status (SES) by temporal and spatial dimensions in order to highlight the multidimensional ways in which SES relates to general health, and then (b) assess the multidimensional ways in which income (as a measure of SES) is related to disability in adulthood.

Methods: Data from the Panel Study of Income Dynamics were linked with Census data to assess (a) which temporal and spatial dimensions of income were associated with disability in adulthood, and (b) whether the various components of income interact with each other when predicting disability.

Results: Negative binomial regression results indicated both 1970 and 2013 household income were associated with lower levels of disabilities in adulthood, as was 2013 neighborhood-level income, but 1970 neighborhood-level income was not associated with disability in adulthood. Further, 4 of the 6 possible interactions between the multiple dimensions of income were associated with significant reductions in adult disability.

Discussion: These findings provide several important empirical insights, but also help inform a framework for thinking about the multidimensional ways in which SES relates to health.

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Figures

Figure 1.
Figure 1.
Conceptual matrix of SES by temporal and spatial dimensions. NOTE: The examples of SES (i.e., income) in the grey boxes are just that: examples that fit within the typology defined by the matrix. These particular examples were selected because they are the variables used in the present study. We believe this matrix would be useful for studying other forms of SES as well (e.g., parental education and individual education along the temporal dimension, or city income per capita and state income per capita along the spatial level).
See this image and copyright information in PMC

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