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Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data
BACKGROUND: Social class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594287/ https://www.ncbi.nlm.nih.gov/pubmed/33115485 http://dx.doi.org/10.1186/s12939-020-01302-4 |
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author | Wami, Welcome McCartney, Gerry Bartley, Mel Buchanan, Duncan Dundas, Ruth Katikireddi, Srinivasa Vittal Mitchell, Rich Walsh, David |
author_facet | Wami, Welcome McCartney, Gerry Bartley, Mel Buchanan, Duncan Dundas, Ruth Katikireddi, Srinivasa Vittal Mitchell, Rich Walsh, David |
author_sort | Wami, Welcome |
collection | PubMed |
description | BACKGROUND: Social class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data and whether those measures were able to explain health outcomes. METHODS: Using a theoretically informed approach, we sought to map variables within the National Child Development Study (NCDS) to five different social class mechanisms: social background and early life circumstances; habitus and distinction; exploitation and domination; location within market relations; and power relations. Associations between the SF-36 physical, emotional and general health outcomes at age 50 years and the social class measures within NCDS were then assessed through separate multiple linear regression models. R(2) values were used to quantify the proportion of variance in outcomes explained by the independent variables. RESULTS: We were able to map the NCDS variables to the each of the social class mechanisms except ‘Power relations’. However, the success of the mapping varied across mechanisms. Furthermore, although relevant associations between exposures and outcomes were observed, the mapped NCDS variables explained little of the variation in health outcomes: for example, for physical functioning, the R(2) values ranged from 0.04 to 0.10 across the four mechanisms we could map. CONCLUSIONS: This study has demonstrated both the potential and the limitations of available cohort studies in measuring aspects of social class theory. The relatively small amount of variation explained in the outcome variables in this study suggests that these are imperfect measures of the different social class mechanisms. However, the study lays an important foundation for further research to understand the complex interactions, at various life stages, between different aspects of social class and subsequent health outcomes. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s12939-020-01302-4. |
format | Online Article Text |
id | pubmed-7594287 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75942872020-10-30 Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data Wami, Welcome McCartney, Gerry Bartley, Mel Buchanan, Duncan Dundas, Ruth Katikireddi, Srinivasa Vittal Mitchell, Rich Walsh, David Int J Equity Health Research BACKGROUND: Social class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data and whether those measures were able to explain health outcomes. METHODS: Using a theoretically informed approach, we sought to map variables within the National Child Development Study (NCDS) to five different social class mechanisms: social background and early life circumstances; habitus and distinction; exploitation and domination; location within market relations; and power relations. Associations between the SF-36 physical, emotional and general health outcomes at age 50 years and the social class measures within NCDS were then assessed through separate multiple linear regression models. R(2) values were used to quantify the proportion of variance in outcomes explained by the independent variables. RESULTS: We were able to map the NCDS variables to the each of the social class mechanisms except ‘Power relations’. However, the success of the mapping varied across mechanisms. Furthermore, although relevant associations between exposures and outcomes were observed, the mapped NCDS variables explained little of the variation in health outcomes: for example, for physical functioning, the R(2) values ranged from 0.04 to 0.10 across the four mechanisms we could map. CONCLUSIONS: This study has demonstrated both the potential and the limitations of available cohort studies in measuring aspects of social class theory. The relatively small amount of variation explained in the outcome variables in this study suggests that these are imperfect measures of the different social class mechanisms. However, the study lays an important foundation for further research to understand the complex interactions, at various life stages, between different aspects of social class and subsequent health outcomes. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s12939-020-01302-4. BioMed Central 2020-10-28 /pmc/articles/PMC7594287/ /pubmed/33115485 http://dx.doi.org/10.1186/s12939-020-01302-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wami, Welcome McCartney, Gerry Bartley, Mel Buchanan, Duncan Dundas, Ruth Katikireddi, Srinivasa Vittal Mitchell, Rich Walsh, David Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title | Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title_full | Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title_fullStr | Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title_full_unstemmed | Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title_short | Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data |
title_sort | theory driven analysis of social class and health outcomes using uk nationally representative longitudinal data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594287/ https://www.ncbi.nlm.nih.gov/pubmed/33115485 http://dx.doi.org/10.1186/s12939-020-01302-4 |
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