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European Socio-Economic Classification: A Validation Exercise

European Socio-Economic Classification: A Validation Exercise. Figen Deviren Office for National Statistics. Introduction. The UK context Creating E-SeC Validation Using the Labour Force Survey Results Conclusions. The UK context. Deriving NS-SeC. Deriving NS-SeC.

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European Socio-Economic Classification: A Validation Exercise

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  1. European Socio-Economic Classification: A Validation Exercise Figen Deviren Office for National Statistics

  2. Introduction • The UK context • Creating E-SeC • Validation • Using the Labour Force Survey • Results • Conclusions

  3. The UK context

  4. Deriving NS-SeC Deriving NS-SeC Questions asked about occupation Questions asked about occupation SOC 2000 SOC 2000 Questions about Employment status Questions about Employment status Questions on Size of organisation Questions on Size of organisation Self-employed Supervisor NS-SeC NS-SeC

  5. Deriving E-SeC Deriving E-SeC SOC 2000 SOC 2000 ISCO-88 ISCO-88 Employment status Employment status Supervisory responsibilities Supervisory responsibilities Working alone Working alone Size of organisation E-SeC E-SeC

  6. Validation For our purposes validation meant Will E-SeC provide a representative picture of the UK that is comparable to the one provided using the NS-SeC? Does E-SeC have a similar predictive power to that of NS-SeC?

  7. Choice of survey • The Labour Force Survey • Sample size, 72,500 of working age (men aged 16 - 64, women aged 16 - 59) • Recent quarterly data – Autumn 2005 • Available at both individual and household levels • Relevant questions

  8. Comparison of E-SeC and UK NS-SeC (reduced categories) Source: Labour Force Survey, Autumn 2005

  9. Case comparability Case comparability No agreement Agree at 7 categories Agree at 3 categories Source: Labour Force Survey, Autumn 2005

  10. A Comparison of E-SEC and NS-SEC for males Lower sales, service and technical Source: Labour Force Survey, Autumn 2005

  11. A Comparison of E-SEC and NS-SEC for females Source: Labour Force Survey, Autumn 2005

  12. European Socio-Economic Classification by sex Source: Labour Force Survey Autumn 2005

  13. Lower managers, professionals, higher supervisory and technicians: E-SeC and NS-SeC by age and sex. Source: Labour Force Survey, Autumn 2005

  14. Routine occupations:E-SeC and NS-SeC by age and sex Source: Labour Force Survey, Autumn 2005

  15. Comparison of E-SeC and NS-SeC at household level Source: Labour Force Survey, Autumn 2005

  16. European Socio-Economic Classification by sex of household reference person Source: Labour Force Survey, Autumn 2005

  17. Predictive power • NS-SeC is accepted as a predictor of ill-health • Linear regression – binary outcome yes/no • Choice of variables • Significance of classifications

  18. Chronic morbidity for males (individual level) Source: Labour Force Survey, Autumn 2005

  19. Chronic morbidity for females(individual level) Source: Labour Force Survey, Autumn 2005

  20. Predictive power – Individual level Results of the regression analysis containing age, ethnicity and educational attainment

  21. Predictive power – Household level

  22. Conclusions • The picture of the UK using E-SeC is broadly similar to that obtained when using NS-SeC • Differences observed between the two classifications for lower managers/professionals and routine occupations by age and sex • E-SeC is comparable to NS-SeC when used as a predictor of chronic morbidity. • More validation needed?

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