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Happiness, Socioeconomic Status, and Family Functioning in South African Households: a Structural Equation Modelling Approach

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Abstract

This paper examines how SES relates to individual happiness, while also controlling for family functioning; the latter measured by the Family Attachment and Changeability Index 8 (FACI8). An individual-, household-, and subjective SES index are developed via multiple correspondence analyses (MCA). Using data from the 2012 South African Social Attitudes Survey (SASAS), the paper employs structural equation modelling (SEM) to explore the relationship between happiness, SES, and family functioning. Multiple-group SEM (MGSEM) is employed to examine the association between happiness and family functioning across quartiles of the three SES indices. The results reveal that higher SES is significantly related to greater happiness, with the role of household- and subjective SES being stronger than individual SES. Furthermore, improved levels of family changeability are positively associated with happiness, whereas there is no relationship between happiness and family attachment. Overall, levels of family changeability and individual happiness are likely to benefit from improvements in socioeconomic status.

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Notes

  1. Although quintiles are often used in applied work, this paper uses quartiles instead. This choice was driven by preliminary analyses that highlighted potential issues in employing quintiles when examining the SES indices, in particular due to the strong relationship between SES and race in South Africa. As an example, it is often the case that the lowest quintiles were made up of only Black and Coloured respondents, whereas the highest quintiles consist mainly of White and Indian respondents. To allow for more meaningful analyses and a more even sample size distribution across SES categories, quartiles were more appropriate. Even when using quartiles, though, race had to be excluded from the multiple-group models, as discussed in "Data Analysis" section. This was because only one White person and no Indian/Asian persons fell into the first two SES quartiles, with the majority in the bottom two quartiles being Black and Coloured individuals. Thus, in some instances the bottom two quartiles represent only certain racial groups. The lack of observations in the White- and Indian/Asian samples in the bottom two quartiles also complicated model convergence.

  2. The SEM results are also reported in Table format since the graphical results are too cluttered.

  3. The MGSEM analyses exclude race as covariate based on the skewed distribution of SES across South Africa’s racial groups. For example, in some cases only one White person and no Indian/Asian persons fell into the first two SES quartiles, with the majority in the bottom two quartiles being Black, followed by Coloured individuals. This implies that in some instances the bottom two quartiles represent only certain racial groups. The lack of observations in the White- and Indian/Asian samples in the bottom two quartiles complicated model convergence.

  4. Although the S-B scaled χ 2 difference test (Satorra and Bentler 1994) is generally preferable, the software used in the analysis does not currently allow for estimation of the S-B χ 2 in the examination of group constraints. Thus, the MGSEM analyses employ the default maximum likelihood χ 2 difference test statistic. Although this statistic does not correct for non-normality, its maximum likelihood estimates are nevertheless relatively robust even in the presence of non-normality (Acock 2013).

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Acknowledgements

We thank seminar participants at the University of Johannesburg as well as two anonymous referees for helpful comments and suggestions on a previous version of this paper. This research was supported by Rhodes University (Grants PGSD05/2015, PGSD07/2015, and RC2017). We also thank Ben Roberts at the Human Sciences Research Council (HSRC) for providing access to the data used in this paper.

Funding

This research was funded by Rhodes University (Grants PGSD05/2015, PGSD07/2015, and RC2017).

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Authors and Affiliations

  1. Department of Economics and Economic History, Rhodes University, P.O. Box 94, Grahamstown, 6140, South Africa

    Ferdi Botha

  2. Faculty of Social Sciences, University of Antwerp, Antwerp, Belgium

    Ferdi Botha

  3. Department of Sociology, University of Antwerp, Antwerp, Belgium

    Edwin Wouters

  4. Population Health, Health Systems and Innovation Research Unit, Human Sciences Research Council (HSRC), Pretoria, South Africa

    Frikkie Booysen

  5. Department of Economics, University of the Free State, Bloemfontein, South Africa

    Frikkie Booysen

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  1. Ferdi Botha
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Appendix

Appendix

Table 12 Components of SES indices
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Table 13 Summary statistics and MCA weights of SES index components
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Table 14 Family attachment and changeability (FACI8) item averages
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Table 15 Goodness-of-fit results for SES group CFA models
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Table 16 Measurement invariance results
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Botha, F., Wouters, E. & Booysen, F. Happiness, Socioeconomic Status, and Family Functioning in South African Households: a Structural Equation Modelling Approach. Applied Research Quality Life 13, 947–989 (2018). https://doi.org/10.1007/s11482-017-9568-x

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