Estimating social inequalities in Healthy Life Years in Belgium Estimating social inequalities in HLE: Challenges and opportunities 10 February, 2012 Rana.

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Presentation transcript:

Estimating social inequalities in Healthy Life Years in Belgium Estimating social inequalities in HLE: Challenges and opportunities 10 February, 2012 Rana Charafeddine Scientific Institute of Public Health

Outline 1. Background 2. Mortality follow up of survey data 3. Policy recommendations

1. Background

Social inequalities in HLY in Belgium  Inequalities in HLY are not static over time  In the last decade, HLY have evolved differently according to the educational level. This generated an increase in the gap between educational groups (Van Oyen et al., 2011)  For instance, the difference in HLY at 25 years among the highest and lowest educated men was 17.0 years in 1997 and became 18.6 in 2004  Among women, this difference was 11.4 in 1997 and became 18.2 in 2004

Educational inequalities in HLY among women at age 25, Belgium Ref: Van Oyen et al. ( 2011), Eur J of Public Health Education Diff.. Higher education Higher secondary Lower secondary Primary education No diploma Total

Estimation of HLY by SES  Prevalence of health status by SES  Disability indicator  Survey data (e.g. HIS, SILC)  Mortality rate by SES  Numerator: number of deaths by education  Denominator: number of person years by education  Mortality follow up of census using a unique identifier  Linked approach: golden standard  Alternative for the census?

Project: HEALTHY LIFE EXP  Funded by the Belgian Science Policy in the context of the AGORA program  Proposed by the Federal Public Service Social Security  Institutions involved:  ISP (Herman Van Oyen, Rana Charafeddine, Stefaan Demarest)  VUB (Patrick Deboosere, Sylvie Gadeyne)  Started in January 2010 until June 2011

Objectives  To explore different possible methods as alternative to the census to be used in Belgium to estimate and update HLY by SES.  Method I: involves the use of mortality rates by SES generated from two different cross-sectional datasets.  Method II: involves the use of linked record studies other than the census such as surveys.

2. Mortality follow up of survey data

Evaluation of surveys as data sources to estimate HLY by SES  Surveys considered: HIS, LFS, SHARE, SILC  Criteria of evaluation  Indicators availability: Health and SES  Mortality follow up  Representativity of the sample  Survey design aspects (sample size, response rate, periodicity)  Final Choice: HIS (2001) and SILC (2004)  Follow up mortality of these surveys

Data  Mortality follow up :  6 years for HIS, 5 years for SILC  HIS: individuals initially, matched  SILC: individuals initially, matched  SES variable  HIS: Highest educational level in the household  SILC: Highest individual educational level  Health outcome  Global Activity Limitation Indicator (GALI) “For at least the last 6 months, have you been limited because of a health problem in activities people usually do?”

Estimation of HLY  Sullivan method: based on cross sectional data  Method of choice for estimating HE due to its simplicity, relative accuracy and ease of interpretation  HLY will be estimated with their standard errors  SES Inequalities is studied in both surveys by comparing the lowest versus the highest educational category using the z-statistics

Mortality by SES among women in HIS 2001 and SILC 2004 Education HISSILC N%N% Higher education Higher secondary Lower secondary Primary education Total

Prevalence of disability by SES among women in HIS 2001 and SILC 2004 Education HIS % SILC % Higher education Higher secondary Lower secondary Primary education Total

HLY and years of disability among women aged 25 years

HLY and years of disability among women aged 65 years

Inequalities in HLY among women by age and survey Survey Primary education Tertiary education Difference in HLY p HIS-25 years <0.01 HIS-65 years <0.01 SILC-25 years <0.01 SILC-65 years <0.20

Comparison HIS and SILC  Comparable mortality rates by educational level in HIS and SILC  Disability rates are systematically higher in the SILC compared to the HIS  Systematically HLY are higher in the HIS  Significant inequalities are found in both surveys  At older ages, educational inequalities are significant in the HIS but not in the SILC

3. Recommendations

Conclusion  The golden standard for estimating mortality by SES (and subsequently HLY) is through census linkage with National Register  In the absence of the census:  Linked approach using surveys is a possible alternative  Selection bias  Comparison with the 3 years mortality follow up of census 2001

Life expectancy among women aged 25 years, census, HIS, SILC Education Census 2001 HIS 2001 SILC 2004 Higher education Higher secondary Lower secondary Primary education No diploma

Recommendations for the use of survey follow up (1)  A choice has to be made concerning the survey to use  As we got comparable variances using the HIS and SILC, the choice should not be based on statistical stability but on other criteria (e.g. regional estimates, yearly estimates)  Estimates are not interchangeable between HIS and SILC  To monitor HLY by SES in Belgium we recommend the use of the SILC as it is yearly and it is used at the European level

Recommendations for the use of survey follow up (2)  Use of educational level as the SES stratification variable  Use of the Global Activity Limitation Indicator (GALI) to estimate the disability free life expectancy  Use of the Sullivan method  Calculate the variances with the estimates  More practical information for the estimation (statistical programs, request for the privacy commission) are found in the final report

Thank you for your attention