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Myles Gould (UoL ) Email: m.i.gould@leeds ac.uk Twitter: @Myles_Gould_UoL

Health , Housing T enure & Entrapment 2001-2011: Does C hanging T enure and Address I mprove Health?. Myles Gould (UoL ) Email: m.i.gould@leeds ac.uk Twitter: @Myles_Gould_UoL Ian Shuttleworth (QUB ) Email: i.shuttleworth@qub.ac.uk.

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Myles Gould (UoL ) Email: m.i.gould@leeds ac.uk Twitter: @Myles_Gould_UoL

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  1. Health, Housing Tenure & Entrapment 2001-2011:Does Changing Tenure and Address Improve Health? Myles Gould (UoL) Email: m.i.gould@leeds ac.uk Twitter: @Myles_Gould_UoL Ian Shuttleworth (QUB) Email: i.shuttleworth@qub.ac.uk Presentation at British Society for Population Studies 2014 Conference Winchester, Wednesday 10th September 2014

  2. Structure • Introduction • Project Aims & Presentation objectives • Data & analytical approach • NILS Data • Population bases • Data description • Multilevel Cross-Interaction Model Results • Staying good health (2001-11) • Staying good health (2001-11) • Transitioning good to bad health (2001-11) • Transitioning bad to good health (2001-11) • Conclusions

  3. Introduction • Political & policy debates about social-rented housing focus on low spatial mobility &reduced chances of upward social mobility • Extensive literature on inter-relationships between: housing tenure, health, and wider dimensions of social wellbeing, and the measurement of these at both the individual and area level (e.g. Marmot, 2010; Macintyre et al, 2002) • Smith & Easterlow (2005) consider concepts of housing entrapment & selective placement • Are people entrapped in poor housing & health? • Are people selectively placed in tenures / spatialities in poor health?

  4. Project Aims • To explore relationships between changing health & housing tenure in Northern Ireland, 2001-2011 • To determine whether different tenure trajectoriesare associated with changes in health status e.g. movements from social rented to owner occupied housing & changing health status • To explore whether changing health status is linked to different kinds of spatial move/mobility • moves between different types of place/area (e.g. area deprivation score) • i.e. change SOA geographical area Aims 1 & 3 are todays presentation’s focus Aim 2 was considered in previous presentation (RGS-IBG, & NILS Launch event)

  5. Today’s Presentation Objectives • Explore the effects on tenure (2001) on changing health status (2001-11) • Explore the relative importance of changing address and of changing tenure on changing health status (2001-11) • Explore the importance of initial area context (multiple deprivation 2001, & change 2001-11)

  6. Data and Analytical Approach • Restricted set of variables for parsimony • Descriptive analysis different kinds of tenure/health transition in the NILS • changes in individuals’ general health 2001-2011 • Multilevel statistical modelling (individuals nested in SOAs) • Later will look at limiting long-term illness (disability) • will also compare health changes with chronic illness(es) status in 2011

  7. NILS Structure • 2001 Core NILS • ID • Health card registration • Sex & age • 2001 Census • Household data • Individual data • 2001 SOA code • 2011 Core NILS • ID • Health card registration • Sex & age • 2011 Census • Household data • Individual data • 2011 SOA code • 2001 Aggregate Census • Area statistics • 2001 SOA code • 2011 Aggregate Census • Area statistics • 2011 SOA code • 2005 Area Deprivation • (MDM) • 2001 SOA code • One in three sample of the whole N. Ireland population • Born on a selection secret birthdates • Treating as individuals, ignoring fact households might have multiple members

  8. Population Bases • Movers – changed tenure • may/may not changed home/address • &/or changed SOA • theoretically possible to only change tenure - e.g. (re)mortgage, buy from landlord • Movers changed address / SOAs • Recently been analysing this too: 4 possibilities • Changed tenure, changed address • Changed tenure, not changed address (unlikely) • Not changed tenure, changed address • Not changed tenure, not changed address

  9. Health Transitions: 2001-2011 • Health 2011: 5 categories recoded /combined to 3 to compare with 2001 • Consider model results for those cells shaded in red today

  10. Health Transitions (2001-2011) & Age (2011) • Reminds us of obvious importance of taking account of age, doing this in our statistical modelling work

  11. Variations in Average Area by Area (SOAs): 2011 • Demography varies by SOA, need to take account of this in our statistical models

  12. Modelling Approach • Restricted set of variables for parsimony • At this stage a number of logistical regression models treating response as binary outcomes • Sticking: 1. Staying Good; 2. Staying Good (2001-11) • Transitioning: 3. Good to Bad; 4. Bad to Good (2001-11) • Multilevel statistical modelling (individuals nested in SOAs) • Place difference having taken account socio-demographic characteristics • Include area effects for SOA deprivation in 2001; or ratio for change in deprivation 2001-11 • Cross-level interactions: individual/household & area effects • Area deprivation with 2001 tenure • Area deprivation with indicator for changed tenure &/or changed address

  13. Model Predictors • Having allowed for 2001 tenure [tenure change in previous analysis]… • …Also age, sex, occupational status, education level, & community background • Plus allowed for response to vary by SOA find small effect, but significant place differences

  14. Modelling probability staying in good health

  15. Cross-level interaction of individual & area effects:(Response: Staying good health) Owner Occupier Social renter Prob. Remaining in Good Health (2001-2011) Private renter SOA Multiple Deprivation (md=17.8), 2001

  16. Cross-level interaction of individual & area effects:(Response: Staying good health) Owner Occupier Prob. Remaining in Good Health (2001-2011) Private renter Social renter Ratio of SOA Deprivation 2001 compared 2011 (Area change with respect to deprivation)

  17. Cross-level interaction of individual & area effects(Response: Staying good health) Not changed tenure, not changed address Not changed tenure, changed address Prob. Remaining in Good Health (2001-2011) Changed tenure, not changed address Changed tenure, changed address SOA Multiple Deprivation (md=17.8), 2001

  18. Modelling probability staying in bad health

  19. Cross-level interaction of individual & area effects(Response: Staying bad health) Social renter Prob. Remaining in Bad Health (2001-2011) Owner Occupier Private renter SOA Multiple Deprivation (md=17.8), 2001

  20. Modelling probability changing from good to bad health

  21. Cross-level interaction of individual & area effects(Response: Transitioning good to bad health) Prob. Transitioning from Good to Bad Health (2001-2011) Private renter Social renter Owner Occupier SOA Multiple Deprivation (md=17.8), 2001

  22. Modelling probability changing from bad to good health

  23. Cross-level interaction of individual & area effects:(Response: Transitioning bad to good health) Prob. Transition from bad to good health (2001-2011) Owner Occupier Private renter Social renter SOA Multiple Deprivation (md=17.8), 2001

  24. Cross-level interaction of individual & area effects:(Response: Transitioning bad to good health) Owner Occupier Prob. Transition from bad to good health (2001-2011) Private renter Social renter Ratio of SOA Deprivation 2001 compared 2011 (Area change with respect to deprivation)

  25. Cross-level interaction of individual & area effects(Response: Transitioning bad to good health) Not changed tenure, changed address Changed tenure, changed address Prob. Transition from bad to good health (2001-2011) Not changed tenure, not changed address Changed tenure, not changed address SOA Multiple Deprivation (md=17.8), 2001

  26. Summary Results (1) • Age decreases the probability of transiting from bad to good health, and of remaining in good health in 2001-11 • Age slightly decreases the probability of remaining in good health in 2001-11, & increasing probability remaining in bad health in 2001-11 • Males less likely to stay good, more likely to transition from good to bad health (2001-11) • Catholics more likely to transition from good to bad health; & more likely stay bad health (2001-11)

  27. Summary Results (2) • Those in owner occupation are more likely to remain in good health (2001-11); ditto transition from bad-to-good health (2001-11) • Those in social renting are more likely to remain in bad health (2001-11); & generally transition from good-to-bad (2001-11) • Not changing tenure more likely to remain good health - irrespective of changing address (2001-11) • Changing tenure less likely to remain good health, & more so if have changed address (2001-11) • Probability of transitioning from bad to good highest for those both changed tenure & address, other patterns more complex depend on area deprivation

  28. Conclusions (1) • Other model results reassuring • finding similar/consistent patterns with different specifications of Y-variable (consistent, logical & plausible results) • Seeking to model considerable complexity: transitional states, compositional & contextual effects, & cross-level interactions • possible because of large & rich variable detail of NILS • We think self-reported general health is a good Census question that captures people’swell-being / happiness • but will do more investigation/work • Also need to give some more thought to harmonizing 2011 5 categories to 3 categories

  29. Conclusions (2) • Evidence of selective placement of the (un)healthy in different tenures / spatialities • Implications: tenure and spatial mobility (or its lack) linked to social residualisation • Can’t assign causality/directionality between health/tenure, or tenure/health • Requires quite different research designs (c.f. Smith & Easterlow, 2005)

  30. Future Work • Will look at limiting long-term illness (LLTI) transitions • Unified multinomial models of the different health transitions simultaneously • Will compare general health / LLTI with NI 2011 chronic illness question

  31. Acknowledgement The help provided by the staff of the Northern Ireland Longitudinal Study and the NILS Research Support Unit is acknowledged. The NILS is funded by the Health and Social Care Research and Development Division of the Public Health Agency (HSC R&D Division) and NISRA. The NILS-RSU is funded by the ESRC and the Northern Ireland Government. The authors alone are responsible for the interpretation of the data and any views or opinions presented are solely those of the author and do not necessarily represent those of NISRA/NILS. NILS-RSU Contact Details Web: http://www.qub.ac.uk/research-centres/NILSResearchSupportUnit/ Email: nils-rsu@qub.ac.uk

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