Decomposition Tools for Health Expectancy

Wilma Nusselder

Department of Public Health

Erasmus MC

Rotterdam, The Netherlands

w.nusselder@erasmusmc.nl

Task Force on Health Expectancy, Luxembourg, June 8, 2006

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to 10 years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU database

New questions:Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to 10 years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU database

New questions:Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU database

New questions:

Is difference due to higher mortality or higher disability?

Which age groups are responsible responsible for this difference?

Step 3: to explain differences in HE between for this difference?

Which causes of death and disability are MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU database

New questions:Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU database

New questions:Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU databaseNew questions:

Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in H between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU databaseNew questions:

Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU databaseNew questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU databaseNew questions:

Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition tools

Health expectancy (HE) in the EU

Step 1: HE to describe population health:

EHEMU database

New questions:

Is this low or high relative to other MS?

Is this low or high relative to other sex/subpopulation?

Is this low or high as compared to five years ago?

Step 2: to compare HE between MS, within MS, over time

EHEMU databaseNew questions:

Is difference due to higher mortality or higher disability?

Which age groups are responsible for this difference?

Which causes of death and disability are responsible for this difference?

Step 3: to explain differences in HE between MS, within MS, over time

Decomposition toolsContribution of mortality vs. disability, age groups and causes to HE differences

Decomposition tools

• Decomposition (or partition techniques) are widely used in mortality research to decompose differences in life expectancy (LE)

• By age: additive contribution of age groups

• By cause: additive contribution of causes of death

• For HE derived with the Sullivan method decomposition tools have recently been developed (Nusselder & Looman, 2004; ******)

• By type: additive contribution of mortality and disability

• By age: additive contribution of age groups

• By cause: additive contribution of causes of death and causes of disability

Decomposition tools

• Decomposition (or partition techniques) are widely used in mortality research to decompose differences in life expectancy (LE)

- By age: additive contribution of age groups

- By cause: additive contribution of causes of death

• Decomposition tools have recently been developed (Nusselder & Looman, 2004; Andreev et al, 2003) to decompose differences in health expectancy (HE)

- By type: additive contribution of mortality and disability

- By age: additive contribution of age groups

- By cause: additive contribution of causes of death and causes of disability

Date needed for decomposition of HE

Decomposition by kind of effect & age:

• Mortality rates by age and sex

• Disability prevalence by age and sex

Decomposition by cause:

• Mortality rates by age, sex and cause of death

• Disability prevalence by age, sex and cause of disability

= Not generally available: can be derived from individual-level

survey data on age, sex, disability and chronic diseases

Two illustrations

1. Gender gap in years with disability in the Netherlands

2. SES disparities in DFLE in Belgium

3. Other possible applications:

1. Differences in HE over time

2. Differences in HE between MS

1. Decomposition of gender gap in HE (a)

Why is number of years with disability higher among women?

Total LE

DFLE LED

Men Women

59.9 65.8

51.5 51.1

8.4 14.8

Difference (men baseline)

+5.89

-0.48

+6.36

Due to: Differences in mortality Differences in disability

+5.89

…

+3.07 -3.55

+2.82 +3.55

-0.24

1. Decomposition of gender gap in HE (b)

Source : Nusselder & Looman, 2004.

Total LE

DFLE LED

Men Women

59.9 65.8

51.5 51.1

8.4 14.8

Difference (men baseline)

+5.89

-0.48

+6.36

Due to: Differences in mortality Differences in disability

+5.89

…

+3.07 -3.55

+2.82 +3.55

-0.24

1. Decomposition of gender gap in HE (c)

• Difference in years with disability: men 8.4 vs. women 14.8 yrs

Source : Nusselder & Looman, 2004.

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4

Asthma/COPD

CVD

Stroke

Diabetes mellitus

Back complaints

Arthritis

Cancer

Other diseases

Non attributable

Institutions

Mortality Disability

2. Decomposition of SES disparity in DFLE (a)

Men WomenLE DFLE LED LE DFLE LED

Low education 44.0 27.3 16.7 50.4 24.9 25.5High education 47.6 35.3 12.3 52.9 30.7 22.2

Difference (H-L) 3.6 8.0 -4.4 2.6 5.9 -3.3

Due to mortality 3.6 1.5 2.1 2.6 0.6 2.0Due to disability 0.0 6.5 -6.5 0.0 5.3 -5.3

Source : Nusselder et al, 2005.

2.Decomposition of SES disparity in DFLE (b)

Men WomenLE DFLE LED LE DFLE LED

Low education 44.0 27.3 16.7 50.4 24.9 25.5High education 47.6 35.3 12.3 52.9 30.7 22.2

Difference (H-L) 3.6 8.0 -4.4 2.6 5.9 -3.3

Due to mortality 3.6 1.5 2.1 2.6 0.6 2.0Due to disability 0.0 6.5 -6.5 0.0 5.3 -5.3

Source : Nusselder et al, 2005.

2. Decomposition of SES disparity by cause, men

Mort. Disab. TotalTotal difference in DFLE 1.5 6.5 8.0Due to Cancer 0.4 0.2 0.6 Heartdisease/stroke 0.4 1.2 1.5 asthma/COPD 0.2 1.0 1.2 Diabetes mellitus 0.0 -0.3 -0.2 Back complaints 0.0 2.1 2.1 Arthritis 0.0 1.3 1.3 Other diseases 0.5 1.9 2.4 Background 0.0 -0.9 -0.9

Source : Nusselder et al, 2005.

2. Decomposition of SES disparity by cause, men

-2

0

2

4

6

8

10

Mort. Disab. Total

Background

Other diseases

Arthritis

Back complaints

Diabetes mellitus

asthma/COPD

Heartdisease/stroke

Cancer

Source : Nusselder et al, 2005.

Mort. Disab. TotalTotal difference in DFLE 0.6 5.3 5.9Due to Cancer 0.1 0.4 0.5 Heartdisease/stroke 0.2 1.4 1.6 asthma/COPD 0.0 1.5 1.5 Diabetes mellitus 0.0 0.7 0.7 Back complaints 0.0 -0.2 -0.2 Arthritis 0.0 2.2 2.2 Other diseases 0.2 0.2 0.3 Background 0.0 -0.8 -0.8

2. Decomposition of SES disparity by cause, women

Source : Nusselder et al, 2005.

2. Decomposition of SES disparity by cause, women

-2

-1

0

1

2

3

4

5

6

7

8

Mort. Disab. Total

Background

Other diseases

Arthritis

Back complaints

Diabetes mellitus

asthma/COPD

Heartdisease/stroke

Cancer

Source : Nusselder et al, 2005.

Added value of decomposition tools

• Provides more insight into differences in health• Mortality vs. disability

• Mortality -> which age

-> which cause of death

• Disability -> which age

-> which chronic disease

* prevalence of disease

* disabling impact of disease

• Provides parsimonious summary of contribution of specific diseases to health differences

• Takes into account that contribution of disease depends on huge amount of factors (e.g., differences in prevalence, disabling impact, age distribution, mortality from the disease, age distribution of mortality from the disease, mortality from other causes)

Conclusion

• Decomposition of HE is feasible

• Decomposition of HE is useful to explain differences in HE between MS, within MS and over time

• More work is needed to make tool widely applicable:

• Publicly available program to decompose differences in HE

• Publicly available program to obtain cause-specific disability information

Thank you for your attention