121 lines
3.8 KiB
YAML
121 lines
3.8 KiB
YAML
abstract: 'Health inequalities continue to grow despite continuous policy
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intervention. Work, one domain of health inequalities, is often included
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as a component of social class rather than as a determinant in its own
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right. Many social class classifications are derived from occupation
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types, but there are other components within them that mean they may not
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be useful as proxies for occupation. This paper develops the exposome, a
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life-course exposure model developed by Wild (2005), into the worksome,
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allowing for the explicit consideration of both physical and
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psychosocial exposures and effects derived from work and working
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conditions. The interactions between and within temporal and
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geographical scales are strongly emphasised, and the interwoven nature
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of both psycho social and physical exposures is highlighted. Individuals
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within an occupational type can be both affected by and effect upon
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occupation level characteristics and health measures. By using the
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worksome, occupation types are separated from value-laden social
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classifications. This paper will empirically examine whether occupation
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better predicts health measures from the European Working Conditions
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Survey (EWCS). Logistic regression models using Bayesian MCMC estimation
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were run for each classification system, for each health measure. Health
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measures included, for example, whether the respondent felt their work
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affected their health, their self-rated health, pain in upper or lower
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limbs, and headaches. Using the Deviance Information Criterion (DIC), a
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measure of predictive accuracy penalised for model complexity, the
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models were assessed against one another. The DIC shows empirically
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which classification system is most suitable for use in modelling. The
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2-digit International Standard Classification of Occupations showed the
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best predictive accuracy for all measures. Therefore, examining the
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relationship between health and work should be done with classifications
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specific to occupation or industry rather than socio-economic class
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classifications. This justifies the worksome, allowing for a conceptual
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framework to link many forms of work-health research.'
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affiliation: 'Eyles, E (Corresponding Author), Univ Bristol, Sch Geog Sci, Univ Rd,
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Bristol BS8 1SS, Avon, England.
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Eyles, Emily; Manley, David; Jones, Kelvyn, Univ Bristol, Sch Geog Sci, Univ Rd,
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Bristol BS8 1SS, Avon, England.'
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author: Eyles, Emily and Manley, David and Jones, Kelvyn
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author-email: ee15592@bristol.ac.uk
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author_list:
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- family: Eyles
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given: Emily
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- family: Manley
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given: David
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- family: Jones
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given: Kelvyn
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da: '2023-09-28'
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doi: 10.1016/j.socscimed.2018.09.020
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eissn: 1873-5347
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files: []
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issn: 0277-9536
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journal: SOCIAL SCIENCE \& MEDICINE
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keywords: 'Occupational health; Classifications; Class; Work; Worksome; Exposome;
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Social exposure'
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keywords-plus: 'SELF-RATED HEALTH; SOCIOECONOMIC-STATUS; PRECARIOUS EMPLOYMENT;
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ENVIRONMENTAL EXPOSURE; WORKING HOURS; EXPOSOME; INEQUALITIES;
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CHALLENGE; MORTALITY; SCIENCE'
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language: English
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month: APR
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note: '17th International Medical Geography Symposium (IMGS), Angers, FRANCE,
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JUL 02-07, 2017'
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number: SI
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number-of-cited-references: '63'
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orcid-numbers: 'Jones, Kelvyn/0000-0001-8398-2190
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Jones, Kelvyn/0000-0001-8398-2190
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Eyles, Emily/0000-0002-2695-7172'
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pages: 56-62
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papis_id: a084e0cd6f0b9ea8363f8f68581c3084
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ref: Eyles2019occupiedclassificati
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researcherid-numbers: 'Jones, Kelvyn/ABE-8689-2020
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Jones, Kelvyn/A-3939-2011
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'
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times-cited: '15'
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title: 'Occupied with classification: Which occupational classification scheme better
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predicts health outcomes?'
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type: article
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unique-id: WOS:000466260800006
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usage-count-last-180-days: '1'
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usage-count-since-2013: '15'
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volume: '227'
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web-of-science-categories: 'Public, Environmental \& Occupational Health; Social Sciences,
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Biomedical'
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year: '2019'
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