d is a b il it y
a n d
r e h a b i l i t a t i o n , 1999 ; v o l . 21, n o . 5} 6, 211 ± 221
Gains in health expectancy from the elimination
of diseases among older people
COLIN D. MATHERS*
Australian Institute of Health and Welfare, GPO Box 570, Canberra, ACT 2601, Australia
Abstract
Purpose : This paper examines a health expectancy based
approach to obtaining disease-speci® c measures of the contributionof health problems to loss of healthy life among older
people. Health expectancies combine mortality and morbidity
into a single population health measure. The objectives of this
study are to evaluate the usefulness of potential gains in health
expectancies as a measure of health impact of various chronic
diseases and injury among older people and to examine
whether elimination of speci® c diseases and injuries leads to a
compression or expansion of morbidity. Results are presented
for Australians aged 65 years and over in 1993.
Results: The results highlight the importance of the chronic
non-fatal diseases such as osteoarthritis and eyesight and
hearing problems as causes of disability and handicap in older
people. Elimination of such diseases results in an increase in
healthy years of life while total life expectancy remains
unchanged, leading to an absolute compression of morbidity.
At the other extreme, elimination of highly fatal diseases such
as cancer can result not only in an increase in healthy years but
an even larger increase in years with disability, resulting in a
relative expansion of morbidity.
Introduction
In developed countries with high life expectancies,
such as Australia and the USA, death rates are
continuing to fall, particularly at older ages and disability
resulting from chronic illnesses among older people is
becoming an increasingly important focus for health
interventions. Three major hypotheses have been advanced for the evolution of population health in low
mortality countries. According to the expansion of
morbidity hypothesis, the decline in mortality is accompanied by an increase in chronic illness and
disability, particularly at older ages. " ± $ The second
hypothesis, compression of morbidity, was ® rst proposed
by Fries% , & who suggested that adult life expectancy is
approaching its biological limit, so that, if the incidence
of incapacitating disease can be postponed to later ages,
then morbidity will be compressed into a shorter period
* e-mail: colin.mathers!
aihw.gov.au
of life. The third hypothesis was proposed by Manton,’
who suggested that the decline in mortality may be due
partly to decreased fatality rates, but at the same time the
incidence and progression of chronic diseases may be
decreasing, leading to a dynamic equilibrium.
Health expectancy indices that combine mortality and
morbidity into a single composite indicator are a very
attractive tool for monitoring long-term trends in the
evolution of population health and for addressing the
question of compression or expansion of morbidity. The
® rst example of such an indicator was published in a
1969 report of the US Department of Health Education
and Welfare,( which contained preliminary estimates of
Disability-free Life Expectancy (DFLE), calculated using
a method devised by Sullivan.) Since the early 1980s,
Sullivan’ s method has been used to calculate disabilityfree, handicap-free life expectancy and other forms of
health expectancy for a large number of countries.* , " !
As well as being useful for monitoring long-term
trends in the evolution of population health," " health
expectancies can be used to analyse the relative contributions of various diseases and injury to the overall
expectation of years lived in various states of ill health
and disability. This can assist in identifying the major
causes of loss of health and in evaluating the potential
for health gain. There is particular need for summary
measures which combine the impact of mortality and
morbidity since the loss of health due to the non-fatal
disabling consequences of disease and injury is of
increasing relative importance and public concern in low
mortality populations. The size of health problems is
also an input (together with information on the eŒectiveness or cost-eŒectiveness of potential interventions) to
assist in setting priorities for health service interventions,
public health programmes and for research and development.
This paper examines a health expectancy based
approach to obtaining disease-speci® c measures of the
contribution of health problems to loss of healthy life
among older people. It involves estimating the eŒect on
health expectancy or health-adjusted life expectancy of
Disability and Rehabilitation ISSN 0963-8288 print} ISSN 1464-5165 online ’ 1999 Taylor & Francis Ltd
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C. D. Mathers
variations in the incidence, prevalence and mortality
rates for speci® c diseases.
Colvez and Blanchet" # proposed in 1983 that potential
gains in life expectancy free of disability resulting from
the elimination of disability and deaths from a particular
cause were a useful tool for health planning. This
approach has since been used for the Australian
population" $ and the Dutch population." % The key to
these methods is to estimate the contribution of speci® c
diseases or disease groups to the prevalence of disability.
The `elimination’ of a disease then reduces the prevalence
of disability and mortality rates, resulting in an increase
in disability-free or health-adjusted life expectancy.
The primary objective of this study is to evaluate the
usefulness of potential gains in health expectancies for
measuring the health impact of various chronic diseases
and injury among older people using 1993 data for
Australia. An additional objective is to examine whether
elimination of speci® c diseases and injuries leads to a
compression or expansion of morbidity.
Data and methods
d a t a
Population data on the prevalence of disability among
the Australian population were obtained from the 1993
survey of disability, ageing and carers conducted by the
Australian Bureau of Statistics." & This population sample
survey included a household sample of 17 800 private
dwellings (approximately 42 000 persons or 0.25 % of the
total Australian population living in households) and a
sample of 700 health establishments (approximately 4800
persons or 2.9 % of the total population of health
establishments).
A person was de® ned as having a disability if they had
one or more of 12 screening conditions which had lasted
or was likely to last for 6 months or more. These
conditions include a range of disabilities, several impairments and one handicap, as de® ned in the WHO
International Classi® cation of Impairments, Disabilities,
and Handicaps framework," ’ and should perhaps be
viewed as de® ning a wider population likely to contain
those persons with a disability.
The survey de® ned a handicapped person as `a
disabled person aged ® ve years or over who was further
identi® ed as being limited to some degree in his} her
ability to perform tasks in relation to one or more of the
following ® ve areas : self care, mobility, verbal communication, schooling, and} or employment ’ . Severity of
handicap for persons aged ® ve years or over was assessed,
for self-care, mobility, and verbal communication, as
follows.
212
(1) Profound handicap Ð personal help or supervision always required and the person is unable to
perform one or more of the tasks.
(2) Severe handicap Ð the person is unable to perform one or more of the tasks and personal help or
supervision sometimes required.
(3) Moderate handicap Ð no personal help or supervision required, but the person has di culty in
performing one or more of the tasks.
(4) Mild handicap Ð no personal help or supervision
required and no di culty in performing the tasks,
but the person uses an aid, or has di culty
walking 200 metres or up and down stairs.
All disabled children under the age of 5 years were
regarded as being handicapped; the severity of their
handicap was not assessed.
m e t h o d s
Disability-free life expectancy and the expectation of
life with various levels of handicap severity were
calculated using Sullivan’ s method." (
In order to estimate gains in disability-free or
handicap-free life expectancy resulting from the elimination of a disease or disease group, it was necessary to
obtain estimates of the prevalence of disability and
handicap attributable to the disease group. The 1993
survey contained two questions which were used to map
disability to disease. These related to (a) the main
disabling condition and (b) the cause of the main
disabling condition. The main disabling condition was
de® ned as the health condition (disease or impairment)
that caused the most problems in terms of activity
restriction. If only one condition was reported, it was
considered the main disabling condition. The responses
to this question were coded to categories based on a
condensed three-digit classi® cation of the International
Classi® cation of Diseases version 9 (ICD-9), but codes
were also included for a range of impairments such as
brain injury, blindness, amputated leg, joint problem and
speech problems.
Respondents were also asked the cause of the main
disabling condition Ð and could specify a range of
responses including
E
E
E
E
E
E
accident} injury
working conditions
disease} illness} hereditary (around 30 disease categories coded)
war
old age
present at birth
Gains in health expectancy from disease elimination
other
don’ t know
E
E
Preliminary analysis of the survey data indicated that
where a person gave a disease as their main disabling
condition (e.g. arthritis, angina) they were likely to give
a `determinant of disease ’ answer to the cause of
condition question (such as stress or old age). Where a
person gave an impairment as an answer (such as brain
injury, blindness or amputation), they were likely to give
a disease or injury as the answer to the cause of condition
(e.g. AIDS, diabetes). Injury and perinatal conditions
were only coded as responses to the cause question, and
were not available as categories for the principal
condition question.
Some of the people who speci® ed a disease (such as
cancer or heart disease) in response to the principal
condition question also speci® ed a disease or injury in
response to the cause question. For example, some
respondents specifying cancer as the principal condition
reported that it was caused by heart disease or motor
vehicle accidents.
For each major disease category, experts were consulted to determine which main disabling conditions
could reasonably be associated causally with diseases or
injuries in that group. This advice was used to screen
disease responses to the cause question to identify the
small number of cases where the response was not
appropriate. Disabled people were then assigned to main
health problem categories as follows:
(1) For the 65 % of disabled people who speci® ed a
health condition as main disabling condition and a
determinant as underlying cause, the main health
problem was de® ned to be the speci® ed main
disabling condition.
(2) The 2 % of disabled people whose main disabling
condition was a catch-all category (disability not
elsewhere classi® ed, not stated, or unknown) and
who did not specify a disease or injury as the cause
of the main disabling condition were assumed to
have underlying causes distributed in the same
proportions as people who did specify a disease or
injury as underlying cause.
(3) For the 29 % of disabled people who speci® ed an
`appropriate ’ disease} injury category as the cause
of the main disabling condition, this was de® ned as
the main health problem.
(4) For the 4 % of disabled people whose main
disabling condition was an impairment or disease
and an `inappropriate’ disease} injury category
was speci® ed as the cause, it was assumed that the
main health problems were distributed in the same
proportions as for other people with that impairment} disease.
The main health problem categories were grouped into
84 detailed disease and injury categories and into major
disease categories de® ned by the chapters of the ICD-9.
For older people particularly, there may be comorbidity
where several conditions act together to cause disability.
The approach taken in this study has been to attribute all
of a person’ s disability to the main health problem (as
derived from respondents ’ self-reports) and to assume
that elimination of the main health problem will result in
elimination of the disability. There will be some persons
for whom this will result in an overestimate of the health
gain, since other conditions will cause residual disability.
For others, this approach will underestimate health gain,
since the health problem may be causing a proportion of
their disability, even if it is not the main cause of
disability. The eŒects of comorbidity thus operate in
both directions and the overall bias in estimated gain in
health expectancy is unlikely to be very large.
The eŒect on health expectancies of eliminating a
disease or injury was calculated assuming independence
among causes of death and disability as follows:
(1) Cause-deleted probabilities of dying were estimated with cause-elimination life tables assuming
independent causes of death." ) Cause elimination
was carried out for all age groups, including the
® nal open-ended age group.
(2) Cause-deleted disability and handicap prevalences
were calculated directly from the survey estimates
by subtracting the cause-speci® c disability and
handicap prevalences from the total prevalences.
(3) Cause-deleted health expectancies were calculated
by Sullivan’ s method using the cause-deleted
prevalences in the cause-elimination life tables.
Note that this method involves the hypothetical complete
elimination of the disease or injury at all ages. Estimation
of the change in a health expectancy due to elimination
of a disease in a speci® c age range would require
information on the duration or age of onset of the
disability, since the disability may be the result of a
disease or injury which occurred many years before (or
prior to birth). Such information is only available in the
Australian survey for injuries, but is in principle
measurable in population surveys.
Estimation of the change in health expectancy due to
partial elimination of a disease (for example, that part
which is considered preventable or which is amenable to
cost-eŒective intervention) is in principle quite straightforward." )
213
C. D. Mathers
Table 1
Preference weights used for handicap severity states
Handicap severity
Weight
Disabled not handicapped
Mild or not determined
Moderate
Severe
Profound
0.98
0.90
0.75
0.50
0.25
For the purposes of exploring the usefulness of
estimated gains in health expectancies due to disease
elimination as a measure of the health impact of diseases,
a set of hypothetical weights has been used in this paper
to construct severity-weighted disability prevalence estimates and health-adjusted life expectancies. Preferencebased weights for health states are usually derived from
economic utility theory or from psychometric traditions.
While there are a number of methods that have been
proposed for eliciting health state preferences, most
provide values as a number in the range 0 to 1, anchored
in death at 0 and perfect health at 1. Such values can be
interpreted as specifying the number of years of good
health equivalent to 1 year in the health state.
The survey allows disability to be classi® ed into ® ve
levels of severity (based on the severity of handicap
associated with the disability). These ® ve levels are
shown in table 1. The severity weights shown in this table
were chosen to be as consistent as possible with the order
of magnitudes of the weights used in the Global Burden
of Disease study. " * They were also chosen to satisfy the
criteria speci® ed by Nord,# ! who gave guidelines for the
appropriate preference weight ranges that could be
associated with health states de® ned in terms of handicap
severity.
These weights can be interpreted as specifying the
number of years of good health equivalent to 1 year with
disability at each severity level. For example, the weight
of 0.75 for mild handicap in table 1 implies that 1 year
with moderate handicap is valued equally with 0.75 years
of good health, or equivalently, that 1 year with mild
handicap corresponds to a `loss ’ of one quarter of a
year’ s good health. The health-adjusted life expectancy
(HALE) is thus an estimate of the average expected years
of good health corresponding to the total life expectancy.
Gains in HALE for Australians aged 65 were
calculated for the elimination of speci® c diseases and
injuries at sub-chapter level of ICD-9 using the detailed
disease categories coded in the survey data. However, the
ABS survey did not contain detailed classi® cations for
injury or cancer. The severity-weighted prevalence of
disability due to speci® c cancers was estimated from the
total prevalence for all sites by assuming that the ratio of
214
severity-weighted prevalence to number of deaths for
each age-sex group was proportional to the ratio of years
of life lost due to disability to numbers of death for the
same age-sex groups in established market economies as
estimated in the Global Burden of Disease study." *
Information on place of injury was used to identify
road tra c accidents and the underlying cause category
of `war ’ to identify injury due to war. For other injuries,
the total severity-weighted prevalence was apportioned
to speci® c external causes at sub-chapter level of ICD-9
using data from the Global Burden of Disease study as for
cancers.
Results
Table 2 shows the prevalence of disability and
handicap by severity level and by main health problem
classi® ed by chapter of ICD-9 for men and women aged
65 years and over in Australia in 1993. Diseases in the
chapters relating to complications of pregnancy and
perinatal problems were not associated with measurable
disability among older people and have been excluded
from the table. The leading causes of disability in older
Australians are musculoskeletal diseases in women
(attributable disability prevalence 18 %) and central
nervous system and sense organ disorders in men
(disability prevalence 13 %). Cardiovascular diseases and
injury are other major causes of disability among older
people, accounting for a disability prevalence of around
10 % among men and 9 % and 5 % respectively among
women. If senile psychoses and Alzheimer’ s disease are
combined, they rank second after osteoarthritis as a
cause of disability among older Australians.
Table 3 shows the leading 25 health problems at subchapter level of ICD-9 in terms of the proportion of
severity-weighted disability prevalence which they account for among older Australians. The leading health
problem is osteoarthritis, accounting for 11 % of severityweighted disability among men and 22 % among women.
This is followed by falls, senile psychoses and arterial
and vascular disease.
Total life expectancy at age 65 was 15.7 years for
Australian men and 19.5 years for Australian women in
1993. Disability-free life expectancy at age 65 was 6.5
years for men and 9.1 years for women (table 4). The
diŒerence between these two sets of ® gures is the
expectation at birth of years of disability: 9.2 years for
men and 10.4 years for women. In other words, for both
men and women aged 65 years, less than 50 % of their
remaining life will be lived without disability on average,
if death rates and disability prevalence rates at all ages
remain constant at their 1993 levels respectively. Of the
Gains in health expectancy from disease elimination
Table 2
1993
Estimated prevalence (per cent) of disability and handicap by severity, main health problem and sex, Australians aged 65 years and over,
Handicap
Main health problem*
Severe and
profound
Moderate
Mild or not
determined
Disabled but not
handicapped
Total
disabled
Men
Infectious and parasitic diseases
Neoplasms
Endocrine} nutritional} metabolic disorders
Blood disorders
Mental disorders
Nervous system} sense organ disorders
Circulatory system disorders
Respiratory system disorders
Digestive system disorders
Genitourinary system disorders
Skin and subcutaneous tissue disorders
Musculoskeletal disorders
Congenital anomalies
Symptoms, signs and ill-de® ned conditions
Injury and poisoning
All causes
0.2
0.3
0.1
0.0
1.5
2.3
3.0
1.0
0.2
0.1
0.1
2.2
0.1
0.0
1.7
12.8
0.1
0.3
0.4
0.0
0.2
0.9
1.4
1.2
0.2
0.1
0.1
2.7
0.1
0.0
2.4
10.1
0.0
0.5
0.9
0.1
0.3
5.9
5.4
2.0
0.6
0.0
0.2
4.5
0.1
0.0
3.8
24.2
0.1
0.3
0.5
0.0
0.1
3.8
1.3
0.6
0.5
0.1
0.0
1.8
0.1
0.0
1.8
10.9
0.4
1.5
2.0
0.1
2.1
12.8
11.0
4.7
1.5
0.2
0.3
11.2
0.4
0.0
9.6
58.1
Women
Infectious and parasitic diseases
Neoplasms
Endocrine} nutritional} metabolic disorders
Blood disorders
Mental disorders
Nervous system} sense organ disorders
Circulatory system disorders
Respiratory system disorders
Digestive system disorders
Genitourinary system disorders
Skin and subcutaneous tissue disorders
Musculoskeletal disorders
Congenital anomalies
Symptoms, signs and ill-de® ned conditions
Injury and poisoning
All causes
0.2
0.4
0.6
0.0
2.5
3.7
3.6
1.1
0.2
0.2
0.1
6.0
0.2
0.0
1.9
20.8
0.0
0.2
0.3
0.0
0.2
1.0
1.6
0.4
0.2
0.3
0.0
4.0
0.0
0.1
0.9
9.3
0.1
0.2
0.6
0.1
0.7
4.2
2.7
0.7
0.2
0.0
0.1
6.6
0.5
0.1
1.7
18.4
0.0
0.1
0.2
0.1
0.5
1.5
0.9
0.3
0.1
0.0
0.0
1.4
0.2
0.1
0.5
5.7
0.4
0.9
1.7
0.2
3.8
10.3
8.8
2.5
0.8
0.6
0.2
18.0
0.9
0.2
5.0
54.26
* Disease groups de® ned by chapters of ICD-9.
years of disability, 7.3 are years of handicap and 2.4 are
years of severe or profound handicap for men.
Women experience more years of handicap from age
65 (9.2) and 4.7 of these are years of severe handicap,
almost double that for men. Although total life expectancies of females signi® cantly exceed those of males
at all ages, the sex diŒerentials for health expectancies
are much lower and decrease more rapidly with age. Life
expectancy free of severe handicap is only 1.5 years
greater for women than men at age 65. Health-adjusted
life expectancy (HALE) at age 65 years is 13.3 years for
men and 15.5 years for women, but HALE is a higher
proportion of total life expectancy for men (at 85 %)
than for women (at 80 %).
Table 5 shows the changes in HALE resulting from the
elimination in turn of each of the major disease groups.
The baseline life expectancy and HALE of the population
(with no disease elimination) are presented for comparison. Elimination of circulatory system disorders
leads to the greatest gain in healthy years among both
men and women, followed by neoplasms for men and
musculoskeletal disorders for women. Figure 1 illustrates
these potential gains in HALE for men and women aged
65 years.
For disease groups, such as musculoskeletal conditions
and mental disorders, which cause signi® cant disability
but little mortality, there are small gains in life
expectancy but large gains in HALE oŒset by com215
C. D. Mathers
Table 3 Proportion of severity-weighted disability attributable to speci® c health problems, top 25 main health problems for men and women aged
65 years and over, Australia, 1993
% of severity-weighted disability
prevalence attributable to problem
Main health problem
Men
Women
Persons
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
11.1
7.4
5.2
11.3
5.7
5.9
3.2
2.8
3.4
4.0
5.4
6.1
2.4
1.6
3.1
0.5
1.4
1.8
1.1
1.7
0.2
1.0
0.1
0.5
0.5
21.8
6.7
7.1
2.6
5.3
4.3
3.9
3.8
3.4
2.8
1.4
0.4
2.5
3.0
1.8
2.3
2.4
2.8
1.5
0.7
1.5
1.0
1.2
0.7
0.6
17.8
6.9
6.4
5.9
5.4
4.9
3.6
3.4
3.4
3.3
2.9
2.5
2.4
2.4
2.3
2.1
2.0
1.9
1.4
1.1
1.0
1.0
0.8
0.6
0.6
Osteoarthritis
Falls
Senile psychoses
Arterial and vascular diseases
Cerebrovascular disease (stroke)
Hearing loss and ear disorders
Eye disorders other than glaucoma and cataract
Alzheimers disease and other degenerative conditions of CNS
Hypertensive disease
Ischaemic heart disease
Chronic obstructive pulmonary disease
War
Asthma
Diabetes
Parkinson’s disease
Osteopathies and deformities
Road tra c accidents
Rheumatoid arthritis and rheumatism (excluding back disorders)
Depression and stress
Back disorders
Glaucoma
Psychoses (apart from senile psychoses)
Cataract
Cardiomyopathy and other in¯ ammatory heart diseases
Colon and rectum cancers
Table 4
Health expectancies (years) and health expectancy (HE) as a percentage of total life expectancy (LE) at age 65, by sex, Australia 1993
HE (years)
Expectation of life at 65 years
With profound handicap
With severe handicap
With moderate handicap
With mild handicap*
With disability, but not handicapped
Free of disability
Health-adjusted life expectancy at age 65
Total life expectancy at age 65 (LE)
HE} LE (%)
Males
Females
Males
Females
1.72
0.64
1.62
3.34
1.90
6.51
13.33
15.73
3.72
0.94
1.64
2.90
1.19
9.09
15.50
19.48
12.7
4.1
10.3
21.2
12.1
41.4
84.8
100.0
19.1
4.8
8.4
14.9
6.1
46.7
79.7
100.0
* Includes handicap where severity not determined.
parable reductions in lost years of good health. Elimination of these disease groups results in absolute
compression of morbidity, where the `lost’ years of good
health (total life expectancy minus HALE) decrease.
Where the `lost ’ years of good health increase, but
HALE also increases, this is referred to as a `relative
compression of morbidity ’ ." % , # " In this case, HALE
increases as a proportion of total life expectancy,
216
although there is also an increase in the `lost ’ years of
good health. Relative compression of morbidity occurs
for elimination of endocrine, nutritional and metabolic
disorders, respiratory disorders and digestive disorders
in men but only for neoplasms in women (table 5).
Relative expansion of morbidity occurs when HALE
and `lost ’ years of good health both increase, but HALE
as a proportion of total life expectancy decreases. For
Gains in health expectancy from disease elimination
Table 5 Baseline and change in life expectancy and health adjusted life expectancy (HALE), at age 65, due to elimination of disease and injury
groups, Australia 1993
Men
Aged 65 years
At baseline
Infectious and parasitic diseases
Neoplasms
Endocrine} nutritional} metabolic disorders
Blood disorders
Mental disorders
Nervous system} sense organ disorders
Circulatory system disorders
Respiratory system disorders
Digestive system disorders
Genitourinary system disorders
Skin and subcutaneous tissue disorders
Musculoskeletal disorders
Congenital anomalies
Injury and poisoning
Figure 1
Women
LE
(yrs)
HALE
(yrs)
15.72
0.06
2.40
0.20
0.02
0.10
0.16
5.35
0.80
0.21
0.12
0.01
0.03
0.01
0.15
13.33
0.08
1.83
0.19
0.02
0.29
0.58
4.42
0.77
0.19
0.09
0.02
0.51
0.01
0.45
2
2
2
2
HALE} LE
(%)
84.80
0.18
1.15
0.15
0.01
1.30
2.76
0.58
0.56
0.09
0.06
0.05
3.04
0.03
2.08
LE
(yrs)
HALE
(yrs)
HALE} LE
(%)
19.49
0.02
1.07
0.13
0.01
0.06
0.08
2.11
0.30
0.11
0.07
0.00
0.03
0.00
0.05
15.50
0.03
0.91
0.21
0.01
0.48
0.83
2.32
0.41
0.13
0.10
0.01
1.34
0.02
0.40
79.53
0.07
0.29
0.55
0.02
2.23
3.90
3.00
0.87
0.22
0.23
0.05
6.72
0.10
1.83
Change in health-adjusted life expectancy at age 65 years due to elimination of diseases and injuries, at ICD-9 chapter level, Australia 1993.
217
C. D. Mathers
Table 6
1993
Change in life expectancyand health adjusted life expectancy (HALE) at age 65, due to elimination of speci® c diseases and injuries, Australia
Men aged 65 years
1 Ischaemic heart disease
2 Cerebrovascular disease
3 Arterial and vascular disease
4 Chronic obstructive pulmonary disease
5 Lung cancer
6 Senile psychoses, Alzheimer’s disease
7 Prostate cancer
8 Osteoarthritis
9 Colon and rectum cancers
10 Diabetes
11 Hearing loss} ear disorders
12 War
13 Hypertensive disease
14 Parkinson’s disease
15 Lymphomas and multiple myeloma
16 Falls
17 Eye disorders (including glaucoma, cataract)
18 Asthma
19 Stomach cancer
20 Pancreas cancer
21 Nephritis} nephrosis
22 Road tra c accidents
23 Bladder cancer
24 Melanoma and other skin cancers
25 Cardiomyopathy and other in¯ ammatory heart diseases
Women aged 65 years
1 Ischaemic heart disease
2 Osteoarthritis
3 Cerebrovascular disease
4 Senile psychoses, Alzheimer’s disease
5 Other arterial and vascular diseases
6 Eye disorders (including glaucoma, cataract)
7 Chronic obstructive pulmonary disease
8 Diabetes
9 Falls
10 Hearing loss} ear disorders
11 Hypertensive disease
12 Colon and rectum cancers
13 Lung cancer
14 Breast cancer
15 Asthma
16 Rheumatoid arthritis and rheumatism (excluding back problems)
17 Road tra c accidents
18 Parkinson’s disease
19 Osteopathies and deformities
20 Lymphomas and multiple myeloma
21 Depression} stress
22 Ovary cancer
23 Pancreas cancer
24 Nephritis} nephrosis
25 Cardiomyopathy and other in¯ ammatory heart diseases
218
LE
(yrs)
HALE
(yrs)
HALE} LE
(%)
2.56
0.72
0.59
0.54
0.56
0.15
0.39
0.01
0.28
0.16
0.00
0.00
0.06
0.06
0.12
0.05
0.01
0.03
0.10
0.09
0.09
0.03
0.08
0.08
0.06
1.93
0.65
0.52
0.51
0.43
0.31
0.29
0.28
0.22
0.15
0.14
0.14
0.13
0.12
0.09
0.09
0.09
0.07
0.07
0.07
0.06
0.06
0.06
0.06
0.06
2
1.08
0.00
0.49
0.09
0.28
0.00
0.18
0.10
0.02
0.00
0.04
0.16
0.17
0.14
0.03
0.01
0.01
0.02
0.00
0.07
0.00
0.06
0.06
0.05
0.02
0.92
0.85
0.57
0.50
0.30
0.25
0.19
0.18
0.18
0.16
0.15
0.15
0.14
0.13
0.11
0.11
0.09
0.09
0.09
0.06
0.05
0.05
0.05
0.05
0.04
2
2
2
2
2
2
2
2
2
1.35
0.23
0.09
0.36
0.27
1.75
0.20
1.75
0.12
0.09
0.90
0.85
0.47
0.44
0.08
0.30
0.35
0.29
0.06
0.05
0.10
0.22
0.03
0.05
0.04
0.28
4.38
0.90
2.40
0.41
1.12
0.23
0.53
0.85
0.81
0.61
0.09
0.03
0.08
0.43
0.49
0.43
0.38
0.43
0.00
0.29
0.00
0.00
0.03
0.12
Gains in health expectancy from disease elimination
disease groups which cause relatively little prevalent
disability but considerable mortality, such as neoplasms,
there are signi® cant gains in life expectancy with and
without disability as those persons whose deaths are
averted live longer lives and experience disability from
other causes. For men, but not women, this results in a
relative expansion of morbidity for elimination of
neoplasms, circulatory system disorders and genitourinary conditions. There is no disease group whose
elimination results in a relative expansion of morbidity
among older women.
Table 6 shows the changes in HALE at age 65 and the
change in HALE as a percentage of total life expectancy
resulting from the elimination of speci® c diseases and
injuries. The top 25 diseases and injuries for men and
women are separately ranked in descending order of
HALE increase. Elimination of ischaemic heart disease
leads to the greatest gain in HALE for both men and
women (1.9 years and 1.1 years respectively), followed by
cerebrovascular disease and other vascular diseases for
men and osteoarthritis and cerebrovascular disease for
women. Elimination of osteoarthritis and senile dementias lead to the greatest increase in HALE as a per cent
of total life expectancy for both men and women aged 65
years.
Discussion
The primary aim of this study was to evaluate the
usefulness of potential gains in health expectancies due
to disease elimination as a summary measure of the
mortality and morbidity impacts of various chronic
diseases and injury among older people. The main
limitation of this approach is the problem of mapping
disability to diseases and injuries.
A signi® cant proportion of respondents state that they
do not know the main cause of their disability, and
others undoubtedly give incorrect answers. Additionally,
this approach does not take into account comorbidity
situations, where disability is the result of the interaction
of a number of health problems. For older people
particularly, a number of diseases and impairments may
act together to cause activity limitations. As discussed
above, the approach taken in this study was to attribute
all of a person’ s disability to the main health problem,
and this may lead to either some overestimation or
underestimation of the gain in health expectancy due to
elimination of a particular disease. Nusselder and coauthors" % addressed this issue using a multivariate
modelling approach to estimate the proportion of
disability prevalence associated with each of a number of
chronic diseases. This approach holds considerable
promise not only for addressing the issue of comorbidity
but also in analysing the contribution to disability of
other causes such as aged frailty and risk factors. To
date, it has not been not feasible to carry out such an
analysis of the Australian survey data, as the public
release unit record survey data do not include su cient
information on health conditions.
It is also important to note that analysis of gains in
disability-free life expectancy, such as those carried out
previously, " $ , " % can give a considerably diŒerent picture
to that based on health-adjusted life expectancy (see
table 5). Those diseases which result in relatively more
disability at the lower end of the severity scale will rank
more highly in terms of gains in disability-free life
expectancy, which weights all disability equally, than in
terms of gains in health-adjusted life expectancy.
This paper has presented results in terms of the
absolute change in HALE (measured in years of life)
resulting from complete elimination of a disease or
injury. A related approach has been suggested by Hill et
al.# # based on a generalization of the concept of entropy
or elasticity of life expectancy. This is de® ned as the
marginal change in life expectancy that results from a
small (say 1 %) decrease in mortality rates at all ages. Hill
et al. have derived formulae for the entropy of diseasefree life expectancies with respect to changes in the
incidence rates of the disease (which is assumed irreversible) and have given an example for dementia in
Canada. Their approach does not provide a set of
disease-speci® c elasticities for overall disability-free life
expectancy and also does not include the eŒect of
simultaneous change in disease-speci® c mortality on the
health expectancy. In this regard, it follows an approach
similar to that of Colvez and Blanchet," # who presented
the ® rst calculations of the potential gain in disabilityfree life expectancy from disease elimination in terms of
separate estimates of the eŒects of mortality reduction
and disability reduction.
In practice, the elimination of almost any disease or
injury group will result in small changes in overall
disability prevalence and mortality rates unless a very
broad disease group is under consideration. Thus the
cause-deleted approach discussed in this paper essentially
provides estimates of the disease-speci® c entropies of
health expectancies, if the gains are expressed in relative
terms (as a percentage of the baseline health expectancy)
rather than absolute terms (years).
Such entropies must be interpreted as the long-term
consequences of the complete elimination of diseases,
both in terms of mortality risk and disability risk. In
general, there is little empirical evidence relating to the
219
C. D. Mathers
case-fatality rates for people with diŒerent severity levels
of disability caused by a disease. Analysis of the longterm eŒects of partial elimination of disease, through a
particular primary prevention programme for example,
would ideally require information on the way in which
that intervention alters the incidence, non-fatal disabling
consequences, and corresponding case-fatality rates. It
should be noted that the use of the prevalence-based
Sullivan’ s method for estimation of health expectancies
in this paper restricts the method to analysis of the longterm equilibrium consequences of disease elimination.
Sullivan’ s method is not appropriate for modelling
dynamic changes due to disease elimination, since it
takes a long time for the age-speci® c prevalence of
disability to reach the equilibrium values corresponding
to the changed incidence rates. # $
These results highlight the importance of the chronic
non-fatal diseases such as osteoarthritis and eyesight and
hearing problems as causes of disability and handicap in
older people. Elimination of such diseases results in an
increase in healthy years of life while total life expectancy
remains unchanged, leading to an absolute compression
of morbidity. At the other extreme, elimination of highly
fatal diseases such as cancer results not only in an
increase in health-adjusted life expectancy but an even
larger increase in total life expectancy and, for older men
in Australia, this results in a relative expansion of
morbidity. For other diseases, such as cardiovascular
diseases, which cause substantial mortality and disability,
the eŒect of the elimination depends on the relative
contributions of mortality decline and morbidity decline,
but often leads to a relative compression of morbidity in
older Australians.
take account more appropriately of the eŒects of
comorbidity and to develop empirical methods for
de® ning, measuring and valuing disability states according to severity. Survey data such as that collected in
Canada for use with the Torrance utility index# % would
allow the latter issue to be addressed.
The results presented in this paper are based on
disability data which relate to chronic disability (lasting
6 months or more) and do not include the burden of
disease resulting from short-term illnesses which can
result in severe disability for short periods (e.g. colds, ¯ u,
injury, etc.). This could be addressed in principle using
Australian health survey data on short-term disability.
Gains in health-adjusted life expectancy due to
elimination of diseases directly identify whether compression or expansion of morbidity is likely to occur. For
older Australian men, elimination of neoplasms, circulatory system disorders and genitourinary conditions
results in a relative expansion of morbidity, whereas
relative or absolute compression occurs for all disease
group elimination for older Australian women.
If health interventions for older people are preferentially targeted at lethal diseases, this is likely to lead to
an increase in years spent with disability. To ensure that
health resources are optimally directed to increasing
healthy years of life, it will be important to devote
resources to the identi® cation and modi® cation of the
determinants of non-fatal disabling diseases among older
people, as well as to research aimed at preventing fatal
diseases. Potential gains in health-adjusted life expectancy due to disease elimination oŒer a useful tool to
assist in setting priorities for health research and
interventions for older people.
Conclusions
References
Measures of disease impact among older people are of
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This paper has demonstrated the potential usefulness
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expectation of years lived in various states of ill health
and disability and to evaluate the likely eŒects of health
interventions on the healthfulness of life as well as the
length of life. For further development of this approach,
it will be important to develop multivariate techniques to
220
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