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Alan Marshall (University of Leeds)

Using POPGROUP to develop district estimates and projections of limiting long term illness and disability. Health surveys user meeting Royal Statistical Society 5 th July 2011. Alan Marshall (University of Leeds). a.d.marshall@leeds.ac.uk. Motivation. Information gap

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Alan Marshall (University of Leeds)

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  1. Using POPGROUP to develop district estimates and projections of limiting long term illness and disability Health surveys user meeting Royal Statistical Society 5th July 2011 Alan Marshall (University of Leeds) a.d.marshall@leeds.ac.uk

  2. Motivation Information gap • Local data distinguishing disability type/severity • District disability projections not produced by statistical agencies Planning • Delivery of specialist services • Protect budgets from cuts • Evidence to restructure service provision Substantive issues • Health inequalities • Population ageing

  3. POPGROUP POPGROUP is a family of software originally developed to forecast population, households and the labour force Based on Excel Population projections - Cohort component methodology http://www.ccsr.ac.uk/popgroup/ 3

  4. POPGROUP – population projections Population Births Deaths In and out migration (UK) In and out migration (Overseas) Excel sheet containing counts (or rates) for each component in each area/social group Schedules of rates for components change over time Projections have single year of age and sex detail Pt+1 = Pt + B + D + Iuk + Ouk + Iov + Oov 4

  5. POPGROUP - Derived forecasts module • New POPGROUP development • Enables users to produce projections of any characteristic with rates that follow a strong age pattern • Households (headship rates), Labour force, LLTI, disability, use of particular services (e.g. libraries) • Product of age/sex specific rates and population projections

  6. LLTI/disability age pattern In district d, at age x and for sex s: Disabled popdxs = ratedxs * popdxs

  7. POPGROUP data modules • External data provided for all sub-national areas (e.g. agency household projections) • Select areas of interest • Replicate agency forecasts • LLTI and disability module includes: • Age and sex specific district rates of LLTI and disability (4 types and two severity levels) (2001) • 4 scenarios of differing LLTI/disability rates (2002-2033)

  8. Methodology – LLTI data • Census (2001) Limiting long term illness question • Do you have any long standing illness, health problem or disability which limits your daily activities or the work that you can do? Include problems which are due to old age. (Yes/No)

  9. Methodology – disability data • Health survey for England provides disability data • Sample size around 16,000 • Combine 2000 and 2001 Surveys - disability module (size) • Disability measured according to activities of daily living • Four disability types (mobility, personal care, hearing, sight) and two severity categories • Not available below for sub regional areas

  10. Relational models • Originally developed for estimation of mortality (schedules of survival rates) (Brass 1971) Relational models comprise: • Standard schedule of survival rates (reliable) • Relational rule • complexity of the mortality age pattern is captured in the standard schedule

  11. Methodology: Relational models of disability 2 (or 3) Parameters quantify adjustment

  12. Estimating local disability • Apply national adjustments to local LLTI schedules If two districts have the same age structure But one has higher level of LLTI (census) Then we would expect higher levels of personal care disability

  13. Methodology: projecting LLTI and disability rates • Debate – compression versus expansion of morbidity • In the UK a static assumption of LLTI is reasonable given recent trends (Jarvis 2000) • However, GHS and Census inform alternative scenarios of LLTI rates • Relational models are again useful – project forward age specific changes in LLTI • Alterative scenarios of disability rates are derived from the LLTI projections

  14. LLTI pyramid (2001 and 2021) Manchester Males Females Grey bars=2001, White bars=2021 14

  15. LLTI pyramid (2001 and 2021) Bolton Males Females Grey bars=2001, White bars=2021 15

  16. Conclusions POPGROUP LLTI and disability module – valuable resource Robust set of local disability rates Different scenarios of future LLTI and disability risk Flexibility for users to develop alternative projections Guide to relational models and other small area estimation techniques – ESDS government website 16

  17. Contacts Local Government Association - purchasing Alex Marshall alexandra.marshall@local.gov.uk Edge analytics – application, development technical support Peter Boden pete@edgeanalytics.co.uk Leeds University – methodological support Alan Marshall a.d.marshall@leeds.ac.uk

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