abstract: 'Health inequalities continue to grow despite continuous policy

  intervention. Work, one domain of health inequalities, is often included

  as a component of social class rather than as a determinant in its own

  right. Many social class classifications are derived from occupation

  types, but there are other components within them that mean they may not

  be useful as proxies for occupation. This paper develops the exposome, a

  life-course exposure model developed by Wild (2005), into the worksome,

  allowing for the explicit consideration of both physical and

  psychosocial exposures and effects derived from work and working

  conditions. The interactions between and within temporal and

  geographical scales are strongly emphasised, and the interwoven nature

  of both psycho social and physical exposures is highlighted. Individuals

  within an occupational type can be both affected by and effect upon

  occupation level characteristics and health measures. By using the

  worksome, occupation types are separated from value-laden social

  classifications. This paper will empirically examine whether occupation

  better predicts health measures from the European Working Conditions

  Survey (EWCS). Logistic regression models using Bayesian MCMC estimation

  were run for each classification system, for each health measure. Health

  measures included, for example, whether the respondent felt their work

  affected their health, their self-rated health, pain in upper or lower

  limbs, and headaches. Using the Deviance Information Criterion (DIC), a

  measure of predictive accuracy penalised for model complexity, the

  models were assessed against one another. The DIC shows empirically

  which classification system is most suitable for use in modelling. The

  2-digit International Standard Classification of Occupations showed the

  best predictive accuracy for all measures. Therefore, examining the

  relationship between health and work should be done with classifications

  specific to occupation or industry rather than socio-economic class

  classifications. This justifies the worksome, allowing for a conceptual

  framework to link many forms of work-health research.'
affiliation: 'Eyles, E (Corresponding Author), Univ Bristol, Sch Geog Sci, Univ Rd,
  Bristol BS8 1SS, Avon, England.

  Eyles, Emily; Manley, David; Jones, Kelvyn, Univ Bristol, Sch Geog Sci, Univ Rd,
  Bristol BS8 1SS, Avon, England.'
author: Eyles, Emily and Manley, David and Jones, Kelvyn
author-email: ee15592@bristol.ac.uk
author_list:
- family: Eyles
  given: Emily
- family: Manley
  given: David
- family: Jones
  given: Kelvyn
da: '2023-09-28'
doi: 10.1016/j.socscimed.2018.09.020
eissn: 1873-5347
files: []
issn: 0277-9536
journal: SOCIAL SCIENCE \& MEDICINE
keywords: 'Occupational health; Classifications; Class; Work; Worksome; Exposome;

  Social exposure'
keywords-plus: 'SELF-RATED HEALTH; SOCIOECONOMIC-STATUS; PRECARIOUS EMPLOYMENT;

  ENVIRONMENTAL EXPOSURE; WORKING HOURS; EXPOSOME; INEQUALITIES;

  CHALLENGE; MORTALITY; SCIENCE'
language: English
month: APR
note: '17th International Medical Geography Symposium (IMGS), Angers, FRANCE,

  JUL 02-07, 2017'
number: SI
number-of-cited-references: '63'
orcid-numbers: 'Jones, Kelvyn/0000-0001-8398-2190

  Jones, Kelvyn/0000-0001-8398-2190

  Eyles, Emily/0000-0002-2695-7172'
pages: 56-62
papis_id: a084e0cd6f0b9ea8363f8f68581c3084
ref: Eyles2019occupiedclassificati
researcherid-numbers: 'Jones, Kelvyn/ABE-8689-2020

  Jones, Kelvyn/A-3939-2011

  '
times-cited: '15'
title: 'Occupied with classification: Which occupational classification scheme better
  predicts health outcomes?'
type: Article; Proceedings Paper
unique-id: WOS:000466260800006
usage-count-last-180-days: '1'
usage-count-since-2013: '15'
volume: '227'
web-of-science-categories: 'Public, Environmental \& Occupational Health; Social Sciences,

  Biomedical'
year: '2019'