Social gaps in healthy life years across Europe Why, what and how should we measure them? Emmanuelle...

Social gaps in healthy life years across EuropeWhy, what and how should we measure them?

Emmanuelle Cambois

INED - France& the JA-EHLEIS project

Estimating social inequalities in Healthy Life Years in Belgium : Challenges and opportunities

Brussels, February 10th 2012

Health expectancies, essentials indicators for monitoring health trends:

to measure not only the average length of life but also the quality of the year lived adding health to years, not only years to life appraising the quality of life

to address crucial public health questions regarding health trends in the aging context health care needs

to address crucial social question regarding sustainability of policies ( participation in mid & late

adulthood) (un)equal chances of healthy aging across countries.

Why should we measure SES differentials in HLY across EU?

Why should we measure SES differentials in HLY across EU?

Active ageing can give the baby-boom generation and tomorrow's older adults the opportunity to:

• stay in the workforce and share their experience• keep playing an active role in society• live as healthy and fulfilling lives as possible. “Increasing by two years the healthy life years of the EU by 2020”

Monitoring inequalitiesbetween and within EU countries

2012 European year for active aging:

How should we measure SES differentials in HLY across EU?

Healthy life years “HLY” is part of the family of health expectancies indicators

HLY measures the share of the life expectancy indicators between years in “an healthy status” and years of “unhealthy status”

It allows monitoring mortality/health dynamics over time, between countries, within countries

The observed mortality and hypothetical morbidity and disability survival curves for females. United States of America,

1980. (WHO, 1984)


Health expectancy is the number of years one can

expect to live in good health, giving the social,

medical, sanitary context.

The observed mortality and hypothetical morbidity and disability survival curves for females. United States of America,

1980. (WHO, 1984)


Several methods:•Panel data allows to compute

the transition probabilities and provide multistate life tables,

•Cross-sectional data on health providing only prevalence (and not incidence or transition probabilities). Age-specific prevalence are “injected” in usual life table

There are as many health expectancies as dimensions of health, as soon as one can measure the prevalence of this dimension in the population (disease-free, good perceived health…)

Functional limitations

Sensory, motor, mental

Wood, 1975, OMS 1980, Verbrugge…

Disease, Injuries…

Restriction in Social participationDEPENDENCY

Need help for shoppingDon’t go out/get isolated

Macular degenerationCannot

drive/readDifficulties to

focus on details

Activity restrictions

Work, home, care

Environmental and individual resources allowing to cope and maintain activities


Wood, 1975, OMS 1980, Verbrugge…


Using a conceptual framework:• There are differences at the level of exposure (to diseases,

functional limitations)• There are differences in the risk that functional limitations

induce activity restrictions• It is therefore crucial

1) to provide measures at the different levels and/or 2) to refer to the level at which measures are made

Diffulties with elementary activities : ADL, IADL, work…

Difficulty for walking, hearing, bending, remembering….

Functional Limitations

(sensory, motor…)

ActivityRestrictionsActivity

Restrictions

Functional Limitations

(Sensory, motor…)

Incapacité

Diseases, Injuries…

Technical aids, home Workplace adjustment…

Human assistance, benefits pension…

Existing data and their relevance GALIHow should we measure SES differentials in HLY across EU?

Numerous calculations since the mid 1980’s:

Research network “REVES” (www.reves.net)

European programmes (www.eurohex.eu)

EURO-REVES to promote EU harmonization in health measurement

EHEMU to coordinate and interprete Euro-HLY calculations (trends and differentials)

JA EHLEIS to promote the HLY indicators and conduct advanced researches on measures and determinants


http://www.reves.net/

Wide variation in the HLY in the EU

Jagger C, Gillies C, Moscone F, et al. Inequalities in Healthy life expectancies in EU25: a cross-national meta-regression analysis. Lancet 2008;9656:2124-31.

What should we measure to account for SES differentials in HLY across EU?

What do we already know?

What about inequalities within countries?On which health/disability dimension should this apply?

Social interventions are possible triggers to reduce disparities?

Why these variations in the HLY in the EU?



By education:Bossuyt et al. 2004;Bronnum-Hansen et al. 2004Bronnum-Hansen, Baadsgaard 2008Lievre, Alley, and Crimmins 2008Matthews et al. 2009Matthews, Jagger, and Hancock 2006Minicuci and Noale 2005Pérès et al. 2005Van Oyen et al. 2005

A recent study using the European panel Majer et al. 2010

By occupational status Bronnum-Hansen 2000Melzer et al. 2000Cambois et al, 2001 and 2011

The shorter the LE, the longer the LE with disability

• Can we learn from each other?• Which disability dimension?• Can we monitor trends?



73%

10121416182022242628303234363840424446485052

Anné

es d

'esp

éran

ce d

e vi

e

LE with…LE witout

Up ClMan Wk

ADL

Men, age 35

Activitylimitations

Functionallimitations

Up ClMan Wk Up ClMan Wk Up ClMan Wk Up ClMan Wk Up ClMan Wk

Women, age 35

ADL Activity

limitationsFunctionallimitations

Example: French DFLE/HLY at age 35 by occupational class

•+7 years of ADL free LE (4 years for women)•+8 years of HLY (6 years for women)•+10 years of functional free LE (8 years for women)

•More years with disability: •+3/+7 years with functional limitations•+1/+3 years with ADL

45 46

24

3843

3

6

4135

40

32

7

9

10

13

60%

34

24

35

27

13

16

15

22


+6 years of LE +2 years of LE

47

41

5149


In the 50-65 years old span, a 9 year-slot of « healthy » life for male (and female) manual workers

Men partial DFLE (50-65 years old)

Cambois E, Laborde C, Romieu I, et al. Occupational inequalities in health expectancies in France in the early 2000s: Unequal chances of reaching and living retirement in good health. Demographic Research 2011;25:407-36.

1. Social differential in DFLE are almost twofold the LE differentials,

2. The shortest LE go along longest LE with disability Double burden of social conditions ( gender differential)

Large social disparities in the quality of the years livedSpecific damaging effect of manual activities regarding

functional limitation & impact on daily lifeSustainability of the objective of a late work/social

participation of the babyboomers?


How should we approach SES differentials in HLY across EU?

HLY is expected to be routinely produced not only for the all MS populations but also for each MS for social groups.

Major issue is the availability of the requested data to compute such indicators, more specifically regarding mortality stratified by SES

In this workpackage, we plan to produce such indicators in countries for which mortality data is available by social groups and where national computations have been performed (with national health data).

Exploring the feasability of measuring SES HLY dispartitiesacross EU27•Starting with countries in which such estimates have been produced•Assessing the availability, robustness, comparability of the requested data•Interpreting country specific situations in the light of the national situation

Objectives of the WP6


Overview of the national experience in these indicators with national data on health and disability, and to gather the available mortality data stratified by social status,

Evaluation of the comparability of the mortality data available for the countries involved : years, social status and the compatibility with the European micro data stratified by social variables (SILC, SHARE, EHIS),

Computation of HLY by SES with SILC and/or other possible HE indicators depending on the available data and to interpret and comment country specific patterns

Several steps would be followed to achieve this objective


Census of the existing data on mortality by SES in partner’s countries Are they linked data (census/survey matched with vital statitistics)? Which social criteria used (occupational status, education)? Availability (periods, level of agregation for age and SES…)? Assessment of the quality

Assessing the comparability of the SES mortality data


Using tables from other programmes (SES criteria, period…)

Methodological issues Relevant social criteria within the national context Availability of data on institutionalization by SES status Comments on limitations/scope of national studies

Centralized computation of relevant life tables (IMach?)

Methodological issues Sample size, Response rate Size of the SES groups…

Descriptive analysis Prevalence of GALI by SES Assessment of the relevance in regards of national experiences Assessment of European comparability Recommandations for HLY computation

Intermediary technical report

Analysis of the SILC data for the partners countries


Centralized computation after agreement on methods Collection of life table/raw data, Collection of information on % institutionalized

Preparation of SILC data Stratification by appropriate SES groups Collect weigthed/unweithed data for confidence intervals

Comparison of SES_HLY in the partners countries Results to be commented/circulated Assessment of the quality/relevance

Computing HLY whenever it seems possible


Social gaps in healthy life years across EuropeWhy, what and how should we measure them?

Emmanuelle Cambois

INED - France& the JA-EHLEIS project

Estimating social inequalities in Healthy Life Years in Belgium : Challenges and opportunities

Brussels, February 10th 2012

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Social gaps in healthy life years across Europe Why, what and how should we measure them? Emmanuelle...

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