Longer Life, Better Health?

Transcription

1 Longer Life, Better Health? Trends in health expectancy in New Zealand,

2 Reproduction of material Material in this report may be reproduced and published, provided that it does not purport to be published under government authority and that acknowledgement is made of this source. Citation Ministry of Health and Statistics New Zealand (2009). Longer life, better health? Trends in health expectancy in New Zealand Wellington: Statistics New Zealand Published in July 2009 by Statistics New Zealand Tatauranga Aotearoa Wellington, New Zealand ISBN (online)

3 Foreword Our health system aims, above all else, to improve the health of our population. So to manage this complex system effectively and efficiently, we need to be able to measure population health. Health expectancy a generalisation of life expectancy to include nonfatal as well as fatal health outcomes provides just such a metric. Health expectancy, in the form of independent life expectancy (the expectation of life free of functional limitation requiring assistance), has been used by the Ministry of Health as a summary measure of the performance of our health system for some years. Since 2003, this metric has served as the peak health indicator in documents such as the Ministry s Statement of Intent and its Health and Independence Report, as well as the Ministry of Social Development s overarching Social Report. Yet opportunities remain for wider application of health expectancy indicators within the health policy space, and methods for constructing these indicators are not yet fully standardised. Accordingly, in 2008 the Ministry of Health and Statistics New Zealand produced a joint discussion paper Health Expectancy: Toward Tier 1 Official Statistic Status, to seek advice on this issue. We are grateful to all those individuals and organisations who responded to this discussion paper with useful suggestions and constructive criticism. Based on this consultation, the Ministry and Statistics NZ have now produced the current report Longer Life, Better Health? Trends in health expectancy in New Zealand, This report sets out standard definitions and methods for health expectancy indicators, and makes recommendations as to the appropriate indicator for most health policy applications. The report also provides final estimates for health expectancy over the past decade. While it is pleasing to note that all health expectancy indicators have improved, some expansion of morbidity has also occurred. This has clear implications for health policy, especially in the context of an ageing population. This report will now provide a key input into Statistics NZ s formal process for conferring Tier 1 official statistic status on health expectancy as a headline health indicator. Whatever the outcome of this process, this report will help policy makers, planners, and funders in the health sector make better use of these indicators for the assessment and management of health system performance and so contribute to better informed health policy, wiser investment decisions, and consequently better health for us all. Stephen McKernan Director-General of Health Geoff Bascand Government Statistician 3

4 Acknowledgements This report was written by Martin Tobias, Li-Chia Yeh and Stephen Salzano (Ministry of Health) and Conal Smith, Jade Pinkerton and Barb Lash (Statistics NZ). The authors gratefully acknowledge valuable input from peer reviewers of this report and respondents to the discussion paper this report is based on. 4

5 Contents Foreword... 3 Acknowledgements... 4 Contents... 5 Executive summary... 6 Introduction... 6 Data sources and methods... 6 Findings... 7 Discussion... 8 Recommendations... 9 Introduction Why measure and monitor health expectancy? What to measure? A taxonomy of health expectancies Health state expectancies Health-adjusted life expectancy Data sources and methods Mortality Non-fatal health states Populations Estimation of health expectancies Health expectancy in Total population Mäori and non-mäori comparison Trends in health expectancy, Evidence for compression or expansion of morbidity Discussion Strengths and limitations of health expectancy as an indicator Choice of health expectancy indicator Recommendations References Appendix Method for calculating health expectancies using Sullivan s observed prevalence approach Appendix Summary of feedback from consultation on discussion document

6 Executive summary Introduction To monitor and improve the performance of the health system as a whole, we need a summary measure of population health one that integrates both fatal (quantity of life) and non-fatal (quality of life) outcomes. Health expectancy a generalisation of life expectancy to include time lived in different non-fatal health states defined by level of functioning provides just such a measure. Two types of health expectancy indicators can be distinguished: health state expectancies health adjusted life expectancy. Health state expectancies use defined functional limitation thresholds to categorise personyears into different health states. Based on data collected in Statistics NZ s post-censal disability survey (as well as mortality and population data), three health state expectancies may be defined: limitation-free life expectancy (LFLE) the number of years expected to be lived free of any functional limitation independent life expectancy (ILE) the number of years expected to be lived free of functional limitation needing assistance active life expectancy (ALE) the number of years expected to be lived free of functional limitation needing daily assistance. Health adjusted life expectancy (or healthy life expectancy, HLE) is based on continuous weighting of non-fatal health states relative to full health, rather than categorical functional limitation thresholds. So HLE can be defined as the equivalent number of years of full health that a person can expect to live. Independent life expectancy has been used as the peak health indicator in the Ministry of Health s Statement of Intent and Health and Independence Report, and The Social Report (Ministry of Social Development). However, understanding of these indicators is limited and methods for their calculation have not been fully standardised. This led to a joint project between the Ministry of Health and Statistics NZ to seek advice on these issues. A discussion paper was produced and used as the basis for wide consultation in late The current report builds on this consultation to: set out standard definitions and methods for health expectancy indicator construction provide final estimates for health expectancies in 2006, and trends from 1996 to 2006 make recommendations for the choice of health expectancy indicators, and the reporting, international benchmarking, and evaluation of the use and usefulness of these indicators support consideration of Tier 1 official statistic status for the health expectancy metric. Data sources and methods Abridged life tables for , and were provided by Statistics NZ. Estimates of the prevalence of non-fatal health states stratified by level of functional limitation, age, sex, and (2006 only) Mäori-non-Māori ethnicity, were extracted from the corresponding post-censal disability surveys fielded by Statistics NZ. 6

7 Health expectancies were calculated by the standard method recommended by the International Network for Health Expectancy (REVES). Findings Because ILE is recommended as the health expectancy indicator of choice for most policy purposes (see Recommendations below), only findings for LE and ILE are summarised here. Over the past decade, life expectancy at birth for New Zealand males increased steadily, and at a faster rate than for females, increasing from 74.4 years in 1996 to 78.0 years in 2006 a gain of 3.6 years. The corresponding increase for females was 2.6 years, from 79.6 years in 1996 to 82.2 years in So the gender gap in life expectancy decreased from 5.2 years to 4.2 years over the decade. Independent life expectancy at birth increased from 64.8 years to 67.4 years over the decade for males, an increase of 2.6 years. So 72 percent (2.6 / 3.6) of the life years gained by males were lived in good health (ie independently). The corresponding increase for females was 1.7 years, from 67.5 years in 1996 to 69.2 years in So 65 percent (1.7 / 2.6) of the life years gained by females were lived in good health. While independent life expectancy increased, and at least two thirds of the years of life gained were years of good health, morbidity still expanded (because life expectancy increased even faster). Years lived in poor health (defined as states of dependency) increased by 1.0 years (or 1.3 percent of life expectancy) for males and 0.9 years (or 1.1 percent of life expectancy) for females. The surveys used to estimate prevalence of functional limitation by support need level were insufficiently powered statistically to permit analysis of health expectancy trends by ethnicity. However, estimates were produced for Mäori and non-māori in The current gap in life expectancy at birth (pooling genders) is 8.3 years and the corresponding gap in independent life expectancy is 6.5 years. Thus Mäori can expect to live shorter lives and fewer years independently than non-māori. However, Mäori can also expect to live fewer years dependently (9.7 years versus 11.8 years), and the lifetime proportion lived independently is approximately the same for both ethnic groups (around 86 percent). This analysis of trends and inequalities in health and life expectancy in New Zealand from 1996 to 2006 illustrates the potential value of such information for health policy. That both LE and ILE have increased substantively over the decade indicates good health system performance, although benchmarking internationally would be necessary to contextualise this finding. However, unacceptable inequality remains between Mäori and non-māori ethnic groups (although this gap narrowed over the decade, at least for life expectancy). Also, while over two thirds of the survival gain experienced by the population as a whole were years of good health, time spent in dependent health states ( morbidity ) also expanded. This suggests that increased investment in long-term but low fatality conditions may be needed to manage this growing burden. To make such reprioritisation decisions will require drilling down (to the extent possible) from the summary health expectancy indicator to identify the specific health conditions and interventions that will yield the best value for money. Ongoing monitoring of health expectancy will then evaluate the extent to which compression of morbidity has been achieved over the longer term. This is a goal of critical importance for sustainability of the health system as the structural ageing of the population accelerates over the next 20 years. 7

8 Discussion Strengths and weaknesses The strengths of the health expectancy metric as a whole-of-system outcome indicator are its robustness, transparency, comprehensiveness, and low cost. Limitations include: reliance on functional limitation as the measure of non-fatal health states limited ability to drill down to specific subsystem components or decompose estimates for subnational regions or population groups difficulties in attribution of changes in these measures to changes in health care subsystem performance potential confusion between functional limitation as a health outcome and disability as a minority rights issue. Choice of indicator Health state expectancies have two major disadvantages: the health of the population cannot be summarised in a single number (instead, three are required if the indicators discussed here are used), and measurement is susceptible to drift in the threshold used to define the indicators (eg daily versus non-daily dependency). On the other hand, a set of health state expectancies provides more information than a single health-adjusted life expectancy indicator. HLE (as a health-adjusted life expectancy indicator) overcomes these limitations, but introduces new ones namely, the validity of the preference weights (health state values) for the non-fatal health states, and the more complex interpretation of the indicator as a transformation rather than a decomposition of life expectancy. Also, the preference weights are liable to be misunderstood as valuations of people s lives. If only a single indicator is to be selected for reasons of policy focus and ease of use then ILE may be the best choice. Firstly, ILE does not require valuation of non-fatal health states. Secondly, the functional limitation threshold used in the construction of ILE dependency is both stable and meaningful in a policy sense. Finally, as a decomposition rather than a transformation of LE, the LE-ILE difference and the ILE:LE ratio are directly interpretable. Whichever health expectancy indicator (or set of indicators) is chosen, they need to form part of a balanced scorecard. Summary measures of population health such as health expectancy should be seen as only one input into evidence-informed health policy, and need to be supported by more detailed cause- and service-specific indicators. Nevertheless, this metric can provide a powerful assessment of overall health system performance and may be particularly valuable now, as we enter an era of rapid structural ageing of the population. 8

9 Recommendations 1. Health expectancy should continue to be monitored as the peak health system outcome indicator, and reported in the Health and Independence Report (Ministry of Health), The Social Report (Ministry of Social Development) and similar publications. 2. Only a single health expectancy indicator should be routinely reported and monitored: independent life expectancy (ILE). 3. This indicator (ILE) should be considered for Tier 1 status 1 as part of New Zealand s official statistics. 4. ILE should be monitored and reported five-yearly, in the second year following each Census of Population and Dwellings. 5. Estimates should be produced (nationally) for both the total New Zealand and Mäori populations. 6. The sources of data should continue to be the official life tables and the post-censal disability survey (or equivalent survey), both provided by Statistics NZ. 7. Production of the ILE estimates from these data, using standard methods (ie those set out in Appendix 1 of this report) as per the requirements for Tier 1 statistics, and the reporting and interpretation of these estimates, should be the responsibility of the Ministry of Health. 8. The Ministry of Health and Statistics NZ and should undertake further joint work to develop methods for producing: projections of ILE subnational estimates of ILE (ie regional, ethnic, socio-economic group) improved ILE estimates and projections for Mäori. 9. Use and usefulness of ILE as a summary measure of population health, to inform the Ministry of Health s long-term planning as well as broader social policy, should be periodically evaluated. 10. New Zealand, through the Ministry of Health, should participate actively in attempts by the International Network on Health Expectancy (REVES) and other international organisations to improve the cross-country comparability and international benchmarking of health expectancy estimates. 1 The intent of introducing the concept of Tier 1 statistics is to ensure that the important statistics that departments use to advise and inform Ministers, and which are of broad public interest, are of a consistently high quality and integrity. 9

10 Introduction Why measure and monitor health expectancy? The health policy debate in New Zealand, as in other countries, has traditionally emphasised measures of population health based on mortality (including standardised mortality ratios, years of life lost, and life expectancy). This emphasis has been at the expense of more broadly based population health measures that take into account non-fatal as well as fatal health outcomes. To some extent this situation reflects the longstanding availability of reliable, complete and comparable mortality records. Yet reliance on mortality as the sole population health outcome worthy of measurement can seriously distort public health policy and bias resource allocation in ways that may well be sub-optimal from a societal perspective. Such a limited view of population health is no longer necessary with the availability of valid and reliable survey instruments to measure non-fatal health states (World Health Organization 2002). The International Classification of Functioning (ICF) (World Health Organization 2001) defines non-fatal health states by level of functioning across a range of health domains (including vision, hearing, communication, cognition, affect, pain, mobility and dexterity) and health-related domains (including self-care, instrumental routines, and social functioning). Survey data describing the distribution of the population by level of functioning (ie across a set of non-fatal health states) can be combined with mortality data (in the form of a life table) to produce a summary measure of population health: one that extends the range of our understanding from life expectancy to health expectancy (Murray et al 2002). Health expectancy indicators have the potential to transform the health policy debate in the developed world from a narrow preoccupation with the extension of life to a broader concern with population health gain (World Health Organization 1997, Romieu and Robine 1997). Such measures are particularly useful for monitoring the health of ageing populations and can help guide resource allocation decisions. These measures can also serve to bring equity objectives whether between generations, genders, social classes, ethnic groups or regions more sharply into focus. Monitoring population health (in terms of both level and distribution) is essential for assessing the performance of the health system. As a summary measure of population health that integrates both fatal and non-fatal health outcomes, health expectancy plays a crucial role in this process by providing an overall outcome measure of system performance. Indeed, the health expectancy metric reflects the performance not only of the health sector itself, but of all sectors whose actions contribute substantively to population health outcomes. Therefore, policymakers, advisors and researchers across the social policy spectrum may find this indicator useful when reflecting on their own contribution potential or realised to the achievement of population health gain and the reduction of health inequalities. Given this capability, health expectancy has been accepted by the Ministry of Health as a key whole-of-system outcome indicator, much as has been the case in the US (Molla et al 2001), the European Union (European Health Expectancy Monitoring Unit 2007) and (to a lesser extent) the UK (Parliamentary Office of Science and Technology 2006). Since 2003, the Ministry of Health has reported on health expectancy (in the form of independent life expectancy) as a headline health indicator in both the Statement of Intent (Ministry of Health 2003b et seq) and the Health and Independence Report (Ministry of Health 2003a et seq). Also since 2003, independent life expectancy has been reported as the peak health 10

11 indicator in the 'Health' chapter of The Social Report (Ministry of Social Development 2003 et seq). These reports employ a pyramidal health indicator framework, with health expectancy forming the peak of the pyramid (figure 1). At the next level, this integrated measure of health is decomposed into its two components life expectancy and level of functioning, aggregating fatal and non-fatal health outcomes respectively. The following level in turn decomposes each of these major outcome categories into their major direct causes (diseases and injuries). The next level attributes these proximal causes to biological and behavioural risk and protective factors. The foundation of the pyramid is made up of the distal social, cultural and environmental determinants of health. Figure 1 Health Indicator Logic Beyond its use as a key outcome indicator, the health expectancy construct has also been applied, for example, in the long-term forecasting of public health expenditure (Tobias et al 2004, 2009). Research on social inequalities in health expectancy and on compression of morbidity in New Zealand has also been carried out by Davis and colleagues (Davis et al 1999, Graham et al 2004). What to measure? A taxonomy of health expectancies Definition of health expectancies The health expectancies reported in New Zealand are based (along with mortality and population data) on self-reported level of functioning in a range of health and health-related domains. These include the core domains identified in the World Health Organization s International Classification of Functioning (ICF) (Tobias and Blakey 2007). Population estimates and mortality data are obtained from Statistics NZ s official statistics system. The data source for level of functioning has been the post-censal disability surveys 11

12 fielded by Statistics NZ in 1996, 2001 and Respondents in these surveys were asked whether they experienced any difficulty and/or needed any assistance with various dimensions of functioning, or with performing specified everyday activities, because of a long-term condition or health problem. For children under 15 years (reported via proxy), a broader definition was used which also included specific chronic conditions and education support needs. Domains of functioning included in the surveys were: sensory (hearing, seeing) communication (speaking, making self understood by others) cognition (learning, remembering, intellectual functioning) affect (emotional and psychological functioning) physical mobility agility and dexterity self-care usual everyday activities (instrumental routines) socialising (mixing with others). Respondents who indicated that they experienced difficulty or needed help with any of the itemised functions or activities were considered to have a functional limitation. The limitation had to be for a minimum of six months (or be expected to last for that time) and not be eliminated through the use of simple corrective devices like eye glasses. Classification of health expectancies Two types of health expectancy indicators can be constructed from such data: health state expectancies and health-adjusted life expectancy. Health state expectancies Health state expectancies are calculated using defined functional limitation thresholds to categorise individuals into different health states. Three health state expectancies are reported here. To construct these indicators, the threshold for functional limitation was set at dependency: the need for assistance (from another person or a complex assistive device) with everyday routines, either intermittently or continuously. Specifically, participants in the post-censal disability surveys who acknowledged functional limitation(s) were classified into three support need levels: level 1 (low) no need for assistance level 2 (moderate) assistance needed, but only intermittently level 3 (high) assistance needed on a daily basis. Based on this framework, three health state expectancies can be identified: limitation-free life expectancy (LFLE), independent life expectancy (ILE), and active life expectancy (ALE) (box 1 and figure 1). Note that health state expectancies represent a decomposition of life expectancy, so that the sum of the time spent in the different health states equals life expectancy (at birth or any other age). 12

13 Box 1 Health State Expectancies Limitation-free life expectancy is the number of years, on average, that a person can expect to live free of any functional limitation. Independent life expectancy is the number of years, on average, that a person can expect to live independently that is, free of functional limitation needing assistance (whether intermittently or on a daily basis). Active life expectancy is the number of years, on average, that a person can expect to live free of functional limitation needing daily assistance. Figure 2 A Conceptual Model of Health State Expectancies Level of support need No functional limitation Limitation-free life expectancy Independent life expectancy Level 1 Level 2 Level 3 Functional limitation not requiring assistance Functional limitation requiring non-daily assistance Functional limitation requiring daily assistance Active life expectancy Life expectancy Health-adjusted life expectancy Health-adjusted life expectancy (or healthy life expectancy, HLE) is based on continuous weighting of non-fatal health states, rather than on categorical functional limitation thresholds (as in health state expectancies). The health states are weighted relative to the state of full health (weight = 1). Therefore, HLE can be seen as a transformation of life expectancy (rather than as a decomposition of it), and has the advantage over health state expectancies that only a single indicator is 13

14 needed to describe the health status of the whole population. HLE may be defined as follows in Box 2. Box 2 Healthy Life Expectancy Healthy life expectancy (or health-adjusted life expectancy) is the equivalent number of years of full health, on average, that a person can expect to live. The health state weights required for construction of HLE can be derived in two ways: through a health state valuation survey, in which the preferences of the population for time spent in the different component health states (relative to full health) are elicited by arbitrary assignment of weights. In the absence of New Zealand health state valuation data, the latter method has been used in this report, with equidistant weights of 0.75, 0.5 and 0.25 being assigned to the three levels of functioning defined by the component health state expectancies (figure 3). Figure 3 A Conceptual Model of Healthy Life Expectancy No functional limitation Functional limitation not requiring assistance Functional limitation requiring non-daily assistance Life expectancy Functional limitation requiring daily assistance Health state weights 14

15 Although the weights have been chosen for their mathematical properties rather than to represent New Zealanders preferences for different states of health, the rank order of the weights is likely to be the same. Given consistent rank ordering, HLE is not very sensitive to the exact weights used, depending more on their relative sizes. Furthermore, the use of arbitrary weights still allows estimation of trends in HLE, provided the weights are not changed over time. Alternatively, the arbitrary weights could be replaced in future by weights from a New Zealand health state valuation survey, and the historical estimates recalculated using these weights. The weights chosen are reasonably similar to those derived from a Dutch health state valuation exercise (Stouthard et al 1997) and to those employed in the WHO s Global Burden of Disease Study (Mathers et al 2002). From figures 2 and 3, it can be seen that the relationship between HLE, LE, and the health state expectancies is given by: HLE = LFLE (ILE LFLE) (ALE ILE) (LE ALE) The variance of healthy life expectancy is given by: Var(HLE) = x [Var(LFLE) + Var(ILE) + Var(ALE) + Var(LE)] 15

16 Data sources and methods Mortality Abridged life tables for , and for the total population and the Mäori and non-māori populations (by sex) were provided by Statistics NZ. Mäori mortality rates for and were corrected for numerator-denominator bias using New Zealand Census Mortality Study adjustors (Blakely et al 2007). Although adjustors are not yet available for , these have been close to 1.0 for all age groups since , so non-adjustment of the estimates should have little (if any) effect. Non-fatal health states Estimates of the prevalence of different health states, defined by level of functional limitation, by sex, Mäori-non-Māori ethnicity and 10-year age group, were derived from the 1996, 2001 and 2006 post-censal Household Disability Surveys and companion surveys of residential facilities fielded by Statistics NZ. The household and institutional surveys were designed to allow pooling of data so that the distribution of the whole population across the set of health states could be estimated. Populations Population denominators were the respective censal populations. The total ethnic group concept of ethnicity was used. Ethnic analysis had to be restricted to Mäori and non-māori, because of the small numbers of Pacific and Asian respondents in the surveys. Estimation of health expectancies Abridged life tables incorporating non-fatal health state distributions were constructed for each sex by ethnic group for each period using the observed prevalence method (Sullivan 1971). To do this, the empirical health state prevalence estimates by 10-year age group were first smoothed using kernel smoothing (Wand and Jones 1994) to obtain estimates by five-year age group. Confidence intervals around the health expectancy estimates were calculated using standard formulae (see Appendix 1). HLE was calculated from the component health state expectancies using the formula given on page 15. More detail on the method for calculating health expectancies is provided in the REVES manual (Jagger 2006). 16

17 Health expectancy in 2006 Total population Health state expectancies The expectations of life in 2006, with and without different levels of functional limitation, at different ages (selected to represent the beginning of each stage of the lifecycle) are summarised in table 1. Table 1 Expectation of Life With and Without Functional Limitation (Years) By gender, level of functional limitation, and lifecycle stage 2006 Male Female Exact age Limitation-free (LFLE) Independent (ILE) Active (ALE) Limited (LE LFLE) Dependent (LE ILE) Severely dependent (LE ALE) LE Ratios (%) LFLE/LE ILE/LE ALE/LE LE = life expectancy Limitation-free life expectancy Approximately 78 percent of life expectancy at birth in 2006 is expected to be lived free from functional limitation (any level). This is 61.1 out of 78.0 years (78.3 percent) for males and 64.4 out of 82.2 years (78.4 percent) for females. Note that from age 65 onwards, only half the remaining years of life are expected to be spent free of functional limitation 49.6 percent for males and 49.1 percent for females. Females enjoy a longer life expectancy than males (by 4.2 years in 2006). Females can in fact expect to live 3.3 years longer than males free of any functional limitation, and 0.9 years longer limited. These estimates are consistent with estimates for previous years (1996, 2001), which found that females can expect to live longer than males both limitation-free and limited. 17

18 Independent life expectancy About 85 percent of life expectancy at birth is expected to be free from functional limitation requiring assistance (dependency) in This is 67.4 out of 78.0 years (86.4 percent) for males and 69.2 out of 82.2 years (84.2 percent) for females. Even at age 65, over half of remaining life expectancy will be lived independently (both sexes): 62.4 percent for males and 57.9 percent for females. Females enjoy a longer expectation of independent life than males 69.2 versus 67.4 years in 2006, a difference of 1.8 years (versus 4.2 years for total life expectancy). However, females can also expect to live longer in a dependent state 13.0 versus 10.6 years, a difference of 2.4 years. That is, out of the 4.2 year female life expectancy advantage in 2006, 1.8 years (43 percent) are years of good health and 2.4 years (57 percent) are years of poor health. Active life expectancy Over 95 percent of life expectancy at birth in 2006 is expected to be lived free from functional limitation requiring daily assistance 74.8 out of 78.0 years (95.9 percent) for males and 78.4 out of 82.2 years (95.5 percent) for females. So males can expect, on average, to live for 3.2 years needing daily assistance with self-care, whereas females can expect 3.7 years in this health state. Healthy life expectancy Health adjusted life expectancy at selected ages is tabulated below (table 2). Note that differences between LE and HLE, and the ratio of HLE to LE, are also shown even though some authorities regard such calculations as inappropriate, seeing that HLE is a transformation, not strictly speaking a decomposition, of LE. Table 2 Healthy Life Expectancy at Selected Ages (Years) By gender 2006 Male Female Exact age HLE LE Diff % Table 2 shows that in 2006 males could expect to live 70.3 healthy-year equivalents from birth, while females could expect 73.5 a difference (favouring females) of 3.2 years. This represents a loss corresponding to 7.7 and 8.7 life years for males and females respectively, as a result of time spent in states of being other than full health. In both genders this loss is equivalent to approximately 10 percent of life expectancy at birth. Interestingly, the health advantage of females as estimated using this metric is 3.2 years of healthy life, exactly one year less than the 4.2-year difference in total life years in

19 Note that healthy-year equivalents as defined using the HLE metric are not the same as limitation-free years as defined using LFLE. So, for example, males aged 65 years in 2006 can expect 18.0 more years of life (on average), 13.4 more healthy-year equivalents, and 8.9 more years free of any functional limitation. Precision of the estimates The precision of health expectancy estimates is limited mainly by the sampling error in the survey used to estimate the distribution of the population across the set of non-fatal health states included in the metric (table 3). Table 3 Standard Errors and 95 Percent Confidence Intervals (Years) Life and health expectancies 2006 SE LCI UCI LFLEo male female ILEo male female ALEo male female HLEo male female LEo male female Table 3 shows that, given the current survey, the precision is likely to be adequate for most purposes. For example, the width of the confidence interval for health expectancies at birth is generally about one year or less (compared with approximately 0.3 years for life expectancy). This should be sufficient to detect any epidemiologically meaningful change in health expectancy over a five year period. Mäori and non-mäori comparison Health expectancy estimates for Mäori and non-mäori were produced in the same way as described above for the total New Zealand population. Only the key results are shown below, for expectancies at birth only (table 4 and figure 4). Note that estimates could not be produced for the ethnic minorities (Pacific and Asian ethnic groups) because of severe imprecision in the age-specific functional limitation rates. That is, the post-censal Disability Survey is not powered sufficiently to produce estimates for these ethnic groups. 19

20 Table 4 Life and Health Expectancies at Birth (Years) Mäori and non-mäori populations 2006 LFLEo %LE ILEo %LE ALEo %LE HLEo LEo Males Non-Mäori 62.3 (78.9) 68.8 (87.2) 76.1 (96.3) Mäori 56.8 (80.7) 62.0 (88.2) 67.6 (96.1) Difference Females Non-Mäori 65.7 (79.2) 70.4 (84.9) 79.5 (95.8) Mäori 58.7 (78.2) 64.2 (85.6) 72.2 (96.2) Difference Figure 4 Health and Life Expectancies by Sex Mäori and Non-Mäori Years of life Males Mäori Non-Mäori HLE0 ALE0 ILE0 LFLE0 LE0 Life expectancy Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE = limitation-free life expectancy; LE = life expectancy. 20

21 Females Years of life Mäori Non-Mäori HLE ALE ILE LFLE LE Life expectancy Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE = limitation-free life expectancy; LE = life expectancy. Table 4 and figure 4 shows that Mäori life expectancy at birth is now approximately 70.4 years for males and 75.1 years for females, a gender gap of 4.7 years. About 79 percent is lived free of any functional limitation (corresponding to 56.8 years for males and 58.7 years for females), while approximately 87 percent is lived independently (corresponding to 62.0 years for males and 64.2 years for females). At present, Mäori males and females can expect to live 64.2 and 67.6 healthy-year equivalents, respectively. Table 4 also shows that Mäori life expectancy at birth is now approximately 8.3 years less than non-mäori (pooling genders), reflecting substantial improvement in survival for Mäori in recent years, although the difference remains unacceptably large. Inequalities in health expectancies are generally smaller than those in life expectancy on an absolute scale, but similar on a relative scale. This finding reflects the complex interaction between survival and functional limitation that determines health expectancy. Thus while Mäori health and life expectancies are uniformly lower than non-māori, the ratios of health to life expectancies for each ethnic group are similar. Note that the confidence intervals for the health expectancy estimates are (unsurprisingly) wider for Mäori than non-mäori (table 5). They are generally about twice as wide (that is, health expectancy confidence intervals are typically ~2 years for Mäori compared to ~1 year for non-mäori). This should be borne in mind when interpreting the results. 21

22 Table 5 Standard Errors and 95 Percent Confidence Intervals (Years) Life and health expectancies by ethnicity 2006 SE LCI UCI LFLEo Mäori male female Non-Mäori male female ILEo Mäori male female Non-Mäori male female ALEo Mäori male female Non-Mäori male female HLEo Mäori male female Non-Mäori male female LEo Mäori male female Non-Mäori male female

23 Trends in health expectancy, In principle, health expectancy estimates for 1996, 2001 and 2006 should be comparable, as all are based on the same data definitions, methods and data sources (Statistics NZ abridged life tables and the post-censal disability survey). However, minor variations in definitions, methods, survey questionnaires and fielding did occur, which have reduced data comparability especially for the 2006 survey versus the earlier surveys. Also, the uncertainty (imprecision) in the health expectancy estimates needs to be borne in mind when interpreting the trends (95 percent confidence intervals are not shown in the table for clarity, but can be seen on the figure). With these caveats, trends in the key indicators (health expectancies at birth) are shown below (table 6 and figure 5). As we have only three time points, formal statistical tests for trend have not been done. Table 6 Health Expectancies at Birth (Years) By period Male Female Change Male Female HLE (4.6%) 2.3 (3.2%) ALE (3.7%) 2.5 (3.3%) ILE (4.2%) 1.7 (2.5%) LFLE (5.7%) 3.9 (6.4%) LE (4.8%) 2.6 (3.3%) Notes: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE = limitation-free life expectancy; LE = life expectancy. Figure 5 New Zealand Health and Life Expectancies at Birth by Sex 1996, 2001 and Males Years of life HLE 0 ALE0 ILE0 LFLE0 LE0 Life expectancy Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE = limitation-free life expectancy; LE = life expectancy. 23

24 Females Years of life HLE 0 ALE0 ILE0 LFLE0 LE0 Life expectancy Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE = limitation-free life expectancy; LE = life expectancy. Trends in HLE, ALE and ILE appear consistent over time for females (but less so for males). Among females, LE at birth increased by 1.5 years from 1996 to 2001 and 1.1 years from 2001 to ILE increased less but in a similar pattern, by 1.0 years from 1996 to 2001 and 0.7 years from 2001 to By contrast, LFLE was almost stable from 1996 to 2001 (increasing by only 0.5 years), then increased implausibly by 3.5 years from 2001 to Among males, LE increased faster than among females, by 1.9 years from 1996 to 2001 and 1.7 years from 2001 to However, both LFLE and ILE show atypical trends among males, remaining stable from 1996 to 2001 while increasing rapidly by 3.2 and 2.6 years respectively from 2001 to These discontinuities in the time series for LFLE (both sexes) and, to a lesser extent, ILE (males only) reflect a similar discontinuity in the disability survey time series. This suggests that a change occurred between 2001 and 2006 in people s perceptions of, or propensity to report, mild to moderate levels of functional limitation (Statistics NZ has ruled out statistical artefact as a likely explanation). This discontinuity is less evident for level 3 functional limitation so the other HSE trends, and the HLE trend, are likely to be more robust. Most probably the estimated trends in HSEs and HLE from 2001 to 2006 represent a combination of real change and artefact and these trends should therefore be interpreted cautiously. Note that trends for Mäori are even less reliable, given the wide confidence intervals around the HSE and HLE estimates for Mäori in 1996 and 2001 (arising from the corresponding disability surveys). So trends are presented here for the all-new Zealand population only. Evidence for compression or expansion of morbidity Depending on the relative rates of change in health expectancy and life expectancy, morbidity (the burden of non-fatal health outcomes) may become compressed, stay in dynamic equilibrium, or expand. Which trajectory is followed is a question of major health policy significance, especially in the context of an ageing population. The trajectory of population health may be defined on an absolute or relative scale. For example, a decrease in the number of years lived with dependency (ie in health states characterised by level 2 or 3 functional limitation) would constitute evidence of compression in an absolute sense. Similarly, a decrease in the proportion (percentage) of the lifetime spent in such health states would constitute evidence of compression in a relative sense. 24

25 The findings for the past decade are summarised below (figure 6). However, these findings should be interpreted cautiously in view of concerns regarding the comparability of the 2006 survey to the earlier surveys (described above). Figure Years Lived in Different Health States In years and as a percentage of life expectancy 1996 and 2006 Years lived % 10.6% 9.3% 9.9% 9.5% 8.8% 8.1% 5.8% 4.6% 4.5% 4.1% 3.1% level 1 level 2 level 3 level 1 level 2 level 3 Support need level Male Female Note: Y axis shows years lived in each health state; percentage above bars shows proportion of life expectancy lived in each health state. The trajectory varies depending on the non-fatal health states included in the metric. For females, level 1 morbidity (functional limitation) compressed on both absolute and relative scales, while level 2 morbidity expanded and level 3 morbidity remained stable (dynamic equilibrium). For males, level 1 morbidity again compressed, as for females. However, level 2 morbidity remained stable, while level 3 morbidity expanded. Using dependency (ie level 2 + level 3 functional limitation) as the threshold for inclusion of non-fatal health states in the indicator, morbidity expanded for both genders on both absolute and relative scales: by 1.0 years or 1.3 percent of life expectancy for males and 0.9 years or 1.1 percent of life expectancy for females. Although these expansions appear similar, note that the male expansion was comprised of level 3 health states while the female expansion involved mainly level 2 health states. Again, however, the caveat stated above regarding unexplained discontinuities in the post-censal survey time series should be borne in mind. Conclusions Over the past decade, life expectancy at birth for New Zealand males increased steadily, and at a faster rate than for females, increasing from 74.4 years in 1996 to 78.0 years in 2006 a gain of 3.6 years. The corresponding increase for females was 2.6 years, from 79.6 years in 1996 to 82.2 years in So the gender gap in life expectancy decreased from 5.2 years to 4.2 years over the decade. Independent life expectancy at birth increased from 64.8 years to 67.4 years over the decade for males, an increase of 2.6 years. So 72 percent (2.6 / 3.6) of the life years gained by males were lived in good health (ie independently). The corresponding increase for females was 1.7 years, from 67.5 years in 1996 to 69.2 years in So 65 percent (1.7 / 2.6) of the life years gained by females were lived in good health. While independent life expectancy increased, and at least two thirds of the years of life gained were years of good 25

26 health, morbidity still expanded (because life expectancy increased even faster). Years lived in poor health (defined as states of dependency) increased by 1.0 years (or 1.3 percent of life expectancy) for males and 0.9 years (or 1.1 percent of life expectancy) for females. However, the reliability of these estimates is limited, for reasons stated above. The surveys used to estimate prevalence of functional limitation by support need level were insufficiently powered statistically to permit analysis of health expectancy trends by ethnicity. However, estimates were produced for Mäori and non-māori in The current gap in life expectancy at birth (pooling genders) is 8.3 years and the corresponding gap in independent life expectancy is 6.5 years. Thus Mäori can expect to live shorter lives and fewer years independently than non-māori. However, Mäori can also expect to live fewer years dependently (9.7 years versus 11.8 years), and the lifetime proportion lived independently is approximately the same for both ethnic groups (~86 percent). This analysis of trends and inequalities in health and life expectancy in New Zealand from 1996 to 2006 illustrates the potential value of such information for health policy. That both LE and ILE have increased substantively over the decade indicates good health system performance, although benchmarking internationally would be necessary to contextualise this finding. However, unacceptable inequality remains between Mäori and non-māori ethnic groups (although this gap narrowed over the decade, at least for life expectancy). Also, while over two thirds of the survival gain experienced by the population as a whole were years of good health, time spent in dependent health states ( morbidity ) also expanded. This suggests that increased investment in mental health and other long-term but low-fatality conditions may be needed to manage this growing burden. To make such reprioritisation decisions will require drilling down (to the extent possible) from the summary health expectancy indicator to identify the specific health conditions and interventions that will yield the best value for money. Ongoing monitoring of health expectancy will then enable us to evaluate the extent to which compression of morbidity has been achieved over the longer term a goal of critical importance for sustainability of the health system as the structural ageing of the population accelerates over the next 20 years. 26

27 Discussion Strengths and limitations of health expectancy as an indicator Strengths New Zealand is fortunate in having both high quality vital statistics (based on a five-yearly population census and full registration of deaths) and a population-based, post-censal disability survey (covering people of all ages living in both private dwellings and in residential institutions). Thus the necessary information infrastructure to measure and regularly monitor health expectancy already exists, and the additional cost of combining mortality and functional limitation rates to generate these metrics is negligible. Measurement and monitoring of population health (level and distribution) is an essential ingredient of national health system performance assessment, and health expectancy is perhaps better suited to this task than any other available (or even theoretical) measure (WHO 2000). An international network, the International Health Expectancy Network (known by its French acronym REVES), has been operating for almost quarter of a century. It has achieved some success in standardising definitions and methods so that international comparability of health expectancy estimates is slowly improving. More and more countries and intergovernmental organisations (eg the EU) are using these measures as headline (summary) indicators of health system performance. Yet these indicators are still subject to a number of technical and conceptual challenges as outlined below. Limitations Measurement of non-fatal health states Measurement of non-fatal health states depends on serial surveys of the population, currently the post-censal disability survey fielded by Statistics NZ. Based on a recent consultation on the future of this survey carried out by Statistics NZ, sustainability of the necessary health state data seems assured either through continuance of this survey or inclusion of suitable items in the General Social Survey. Similar data could also be derived from the New Zealand Health Survey operated by the Ministry of Health. Equivalence of the data that could be collected in these surveys to that collected via the existing post-censal disability survey would need to be demonstrated (especially with regard to health state prevalence estimates disaggregated by support need level). Valuation of health states For estimation of health adjusted life expectancy (HLE), non-fatal health states must not only be described but also valued. The lack of preference weights for New Zealand is clearly a limitation in this regard, forcing us to rely on weights chosen for their mathematical properties (ie equidistant weights) rather than weights reflecting New Zealanders preferences for being in different health states. If HLE is to be used as an outcome indicator, a process to generate and regularly (say 10-yearly) update preference-based weights would be needed. This could involve a general population survey or a panel approach (eg focus groups of health workers, patients, family members, and/or politicians) (Stouthard et al 2000). However, whether HLE should be included at all in the indicator set is problematic, as discussed below. 27