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EMPLOYMENT STATUS AND HEALTH TRAJECTORIES

EMPLOYMENT STATUS AND HEALTH TRAJECTORIES. Gopalakrishnan Netuveli Imperial College London 1 Jan 2007 – 31 March 2008. Employment and health.

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EMPLOYMENT STATUS AND HEALTH TRAJECTORIES

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  1. EMPLOYMENT STATUS AND HEALTH TRAJECTORIES Gopalakrishnan Netuveli Imperial College London 1 Jan 2007 – 31 March 2008 Leeds, 18 March 2008

  2. Employment and health • “… there is a strong theoretical case, supported by a great deal of background evidence, that work and paid employment are generally beneficial for physical and mental health and well-being.” Waddel and Burton, 2006. • Debate: selection vs. causation • “…there is a strong case for all health strategies to consider employment as an outcome, where appropriate. There is also a strong case for employment policy to evaluate the health impact of all its relevant interventions.” McLean et al. 2005

  3. Problem with the direction of causation Employment and health may mutually influence each other and the direction of causation might depend on context and contingency. This makes the relationship between employment and health complex. Data form that might capture context and contingency is longitudinal trajectories. Study of trajectories might help to understand part of this complexity

  4. Objective • To explore trajectories of health and employment in a sample of BHPS Data: 2852 subjects between 16 and 50 years in 1991 who were employed and reported no health problems and self-rated health as good or better Employment trajectory: 1 =(self) employed; 0=Else Health trajectory: 1 = Good or better SRH; 0=Else W9 & 14 excluded > SRH question different

  5. Methods • Summarising trajectories: are there classes of trajectories? Latent Class Growth Analysis W1 W14 1 13 1 0 S I Age C Sex

  6. Methods • Comparing employment and health trajectories within individuals: are trajectories of health and employment similar?

  7. Measuring similarity: requirements Both trajectories coded similarly Same number of states in each point of each trajectory The states coded similarly have the same relative position in the vector of states for each trajectory Present study:

  8. Methods contd… Common distance measures of similarity: Euclidean, Hamming, Levenshtein Present study: a new approach using Kolmogorov-Smirnov D – statistic D-statistics is the maximum distance between the cumulative fractile/percentile distribution of the two trajectories. A significant test for the H0:D=0 can be done (if necessary exact test accounting for small number of points) The individual P-values can be combined using meta-analysis, even adjusting for co-variates using meta-regression It is also possible to identify which distribution ‘dominates’ Applications used: Mplus, STATA

  9. Results Distribution of the sample according to W1 age and sex

  10. Results Distribution according to W1 social class

  11. Employment trajectories Latent Class Growth Analysis of employment trajectory identified 7 classes. Classification forced to stop at 7 when number of people in any class fell below 5% *AUC Average proportion of person-time in employment

  12. Employment trajectories

  13. Age and sex distribution of employment trajectories

  14. Social class distribution of employment trajectories by sex

  15. Propensity to different types of employment trajectories Narrative description of a multinomial logistic regression:

  16. Health trajectories LCGA identified 6 classes. Classification stopped when there was no significant statistical difference between six and seven class solutions *AUC Average proportion of person-time in employment

  17. Cross-tabulation of health and employment trajectories Chi-square= 3994; df=30 p-value: <0.0001 Pivotal cells contributing to greatest to chi-square Correlation between trajectories: 0.8

  18. Are the health and employment trajectories within indivuals similar?

  19. Meta-analysis of p-values: full and subgroups

  20. Distribution of Employment and health trajectories in men, non-manual, 41-50 years Pearson chi2(12) = 32.3433 Pr = 0.001

  21. Average D according to employment and health latent classes Emboldened: significant p-value after synthesis

  22. Conclusions Are there classes of trajectories? YES Are trajectories of health and employment similar? YES for the majority (80%) Selection or causation? Weak evidence (if any) for causation

  23. Acknowledgements ESRC and UPTAP programme Professor David Blane, ICL Professor Mel Bartley, UCL Professor Richard Wiggins, IOE Members of Q3 seminar group, Imperial College London

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