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The European Journal of Public Health logoLink to The European Journal of Public Health
. 2016 May 11;26(6):1069–1074. doi: 10.1093/eurpub/ckw066

Trends in health expectancies among the oldest old in Sweden, 1992–2011

Louise Sundberg 1,✉, Neda Agahi 1, Johan Fritzell 1, Stefan Fors 1
PMCID: PMC6080840  PMID: 27175003

Abstract

Background: Information on the extent to which older people’s increasing life expectancy is characterized by good or poor health is important for policy and fiscal planning. This study explores trends in health expectancies among the oldest old in Sweden from 1992 to 2011. Methods: Cross-sectional health expectancy estimates at age 77 were obtained for 1992, 2002, 2004 and 2011 by Sullivan’s method. Health expectancy was assessed by severe disability, mild disability and mobility problems. Changes in health expectancies were decomposed into the contributions attributed to changes of mortality rates, and changes in disability and mobility prevalence. Mortality data were obtained from Statistics Sweden and prevalence data from two nationally representative surveys, the Swedish Panel Study of Living Conditions of the Oldest Old and the Survey of Health, Ageing and Retirement in Europe. Results: Years free from severe disability, mild disability and mobility problems increased in both men and women. Decomposition analysis indicates that the increase was mainly driven by the change in health status rather than change in mortality. In relation to total life expectancy, the general patterns suggest that women had a compression of health problems and men an expansion. Conclusion: Men’s life expectancy increased more than women’s; however, the increased life expectancy among men was mainly characterized by disability and mobility problems. The results suggest that the gender gap in health expectancy is decreasing.

Introduction

Current increases in life expectancy are mainly the result of declining late-life mortality, hence a crucial question is whether these declines are associated with increases or decreases of health problems.1 To assess if increasing life expectancy is accompanied by years with or without health problems, both mortality and health needs to be addressed.2 Health expectancy is a population health metric that accounts for both. It divides remaining life expectancy, at a given age, into years of good and bad health. By comparing the total increase in life expectancy with the change in health expectancy, we can also test the hypotheses of compression or expansion of morbidity.3,4 Compression suggests that the period of poor health at the end of life is shortened5 and expansion suggests that the period of poor health is prolonged.6 Absolute compression occurs when age-specific morbidity rates decline at a faster rate than age-specific mortality rates, and absolute expansion occurs when age-specific mortality rates decline at a faster rate than age-specific morbidity rates. Relative compression, on the other hand, occurs when the proportion of remaining life expectancy with good health increases. Correspondingly, relative expansion occurs when the proportion of remaining life expectancy with health problems increases.7

To date, the results of studies on health expectancy trends vary substantially by country, period and type of health indicator.4,8 Internationally there is large variation between countries.9,10 Studies from the USA have indicated expansion of morbidity at age 65 between 1998 and 2008 when measured by disease and mobility functioning,11 but also compression at age 70 between 1984 and 2000 when measured by disability.12 Similarly, studies for countries within the European Union show contradictive results, with indication of expansion of disability,13,14 while results from national studies point towards compression.7,15,16 In the Nordic countries, studies from Denmark indicate an overall compression of disability,17,18 and similar results have been reported in Norway.19 Eurostat’s estimations suggest that there was a compression of activity limitation at age 65 in Sweden between 1997 and 2013.20 Similar results were found in a recent Swedish study that estimated activity limitations and self-rated health in 65-year-olds between 1980 and 2010.21 However, other studies have found that there was no change in the proportion of life that could be expected to be lived with disability between 1990 and 2010, and no gender difference either; both Swedish men and women aged 50 could expect to live 20% of their remaining life with disability.9 Most other studies indicate that although women live longer than men on average, they will spend a longer period of their remaining life expectancy with health problems.22 This is also known as the male-female health-survival paradox22 and it is present in all health expectancy studies regardless of the health indicator used.8 Although consistent evidence suggests that the gender gap in life expectancy is diminishing,23,24 less is known about the gender gap in health expectancy.25,26

To assess health expectancy in the oldest old population is important for social, fiscal and policy planning, especially since the need for long-term care increases with age.8 Yet few studies have assessed health expectancy among the oldest old, the age group that will increase the most the decades ahead,27 and the age group that requires the most long-term care. In addition, many studies exclude individuals living in care facilities,8 thus disregarding a group with high burden of disability28 and with high societal costs.29 Sweden has several nationally representative surveys of the older population that assess health over extended periods of time and include both proxy interviews and individuals in care facilities, factors of great importance to achieving representative results.30

The main aim of this article was to explore whether the oldest old population in Sweden experienced a compression or expansion of morbidity, measured as disability and mobility problems, during the period between 1992 and 2011.

Methods

Data

Health data were obtained from The Swedish Panel Study of Living Conditions of the Oldest Old (SWEOLD)31 for 1992, 2002, 2004 and 2011 and from The Survey of Health, Ageing and Retirement in Europe (SHARE)32 for 2004 and 2011. Age- and sex- specific death rates were obtained from Statistics Sweden’s online database 27 for the same years. The combined study sample from SWEOLD and SHARE consisted of 3656 individuals aged 77–102. The use of health data from two nationally representative surveys served to provide strength to the findings.

SWEOLD is an ongoing survey of a random sample of the Swedish population aged 77 and above. We use data from four waves conducted in 1992, 2002, 2004 and 2011. Most interviews have been conducted face to face, except in 2004, when most were conducted via telephone. To reduce non-response, postal questionnaires were used for 1.2% of the interviews in 2004 and for 6.2% in 2011. The response rate has been high, varying between 84.4% and 95.4%. SWEOLD includes both community dwelling people and people living in care facilities. When the older people are unable to respond, proxy interviews are conducted.31 In 2011, an additional random sample of 85- to 99-year-olds was included to increase the precision of measurements in the oldest age groups. In the analyses, selection weights have been applied to adjust for this additional sample.31

SHARE is a multi-national survey of people aged 50 and above in twenty European countries and Israel. In this study, we used Swedish data from survey wave 1, conducted in 2004, and survey wave 4, conducted in 2011. Swedish SHARE data are based on a random sample of the Swedish population. The sample is drawn at the household level; in 2004 the household response rate was 46.9%, and 84.6% of all eligible household members participated. Response rates for 2011 are not yet available. SHARE also includes proxy interviews and individuals living in care facilities.32,33 Calibrated weights have been applied in SHARE to mitigate the impact of nonresponse and sample attrition on the estimates.34

Outcomes

Severe disability was measured by five items of personal activities of daily living. We created an index based on the Katz scale.35 The index for SWEOLD was based on the self-reported ability to independently eat, dress, get in and out of bed, go to the toilet and wash hair. The index for SHARE was based on the self-reported ability to independently eat, dress, get in and out of bed, go to the toilet and take a bath/shower. If the person was unable to perform any of the tasks independently, he or she was categorized as having severe disability.

Mild disability was measured by an index based on a person’s self-reported ability to independently perform two instrumental activities of daily living (iADL): shopping and preparing meals.29 A person was regarded as having mild disability if he or she could not perform one or both of the two activities independently. In SWEOLD, people living in care facilities were not asked iADL questions. Because people who are granted such accommodations in Sweden are generally in very poor health and have substantial functional disabilities,28,36 we categorized all people living in care facilities as having iADL disability (weighted N = 303).

Mobility problems were measured by two items: ability to walk and to climb stairs. In SWEOLD, respondents were asked if they could walk 100 m fairly briskly and walk up and down stairs without difficulty. In SHARE, respondents were asked if, because of health problems, they had problems walking 100 m and walking up a flight of stairs without resting. If a person answered that he or she was unable to perform one or both of the mobility items, he or she was classified as having mobility problems.

Statistical analyses

The Sullivan method was used to estimate remaining life expectancies with- and without health problems at age 77.14 Age-, gender- and period-specific prevalence of severe disability, mild disability and mobility problems was incorporated into standard period life tables. In a second step, we decomposed the change of life expectancies with good health between different survey years by the contribution attributable to mortality change and the contribution attributable to changes in the prevalence of disabilities and mobility problems.37 SWEOLD data were used to estimate the trend in health expectancy between 1992 and 2011, and SHARE data to estimate this trend between 2004 and 2011. Microsoft Excel was used for life table analysis and decomposition analysis. STATA SE12 was used to obtain morbidity prevalence, tests for statistical significance and 95% confidence intervals (CIs).

Results

Table 1 presents the sample characteristics from each survey and each year. Table 2 shows changes in estimated health expectancies between 1992 and 2011. Table 3 presents the results of t-tests for changes in health expectancies together with the results from the decomposition analyses. Figure 1 shows the estimated proportion of remaining life expectancy without the three different health problems.

Table 1.

Descriptive characteristics of the study samples

SHARE SWEOLD
2004 2011 1992 2002 2004 2011
N = 489 N = 457 N = 537 N = 621 N = 648 N = 904
Age range 77–102 77–99 77–98 77–99 77–100 77–101
Mean age 82.3 83.5 82.4 83.3 83.3 83.4
Men 36.7 38.9 39.2 40.7 39.0 37.9
Proxy interviews 14.4 9.0 15.0 19.8 21.5 20.9
pADL disability 25.9 23.0 26.9 30.6 26.5 24.7
iADL disability 23.1 22.0 36.9 37.1 34.2 36.2
Mobility problems 29.1 29.0 46.1 58.7 55.0 54.0
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Weighted proportions.

Table 2.

Remaining life expectancy at age 77 and estimated remaining life expectancy with and without severe disability, with and without mild disability, and with and without mobility problems

LE without severe disability LE with severe disability LE without mild disability LE with mild disability LE without mobility problems LE with mobility problems
Sex Year LE Years (95% CI) Years (95% CI) Years (95% CI) Years (95% CI) Years (95% CI) Years (95% CI)
SWEOLD Men 1992 8.2 6.7 (6.3–7.1) 1.5 (1.1–1.9) 5.2 (4.7–5.7) 3.0 (2.5–3.4) 5.0 (4.5–5.5) 3.2 (2.7–3.7)
2002 8.9 6.9 (6.4–7.3) 2.0 (1.5–2.4) 5.9 (5.3–6.4) 3.0 (2.5–3.5) 4.5 (4.0–5.1) 4.3 (3.8–4.9)
2004 9.3 7.4 (7.0–7.9) 1.9 (1.4–2.4) 6.2 (5.6–6.7) 3.1 (2.6–3.7) 5.2 (4.6–5.8) 4.1 (3.5–4.7)
2011 9.9 7.8 (7.2–8.3) 2.1 (1.6–2.6) 6.5 (5.9–7.0) 3.4 (2.9–3.9) 5.5 (4.9–6.1) 4.4 (3.8–5.0)
Women 1992 10.7 6.9 (6.4–7.4) 3.8 (3.2–4.3) 6.4 (5.8–7.0) 4.3 (3.7–4.9) 5.0 (4.5–5.5) 5.7 (5.2–6.2)
2002 10.8 7.0 (6.5–7.5) 3.8 (3.4–4.4) 6.7 (6.2–7.2) 4.1 (3.6–4.7) 3.8 (3.3–4.4) 7.0 (6.5–7.6)
2004 11.4 7.9 (7.4–8.4) 3.5 (3.0–4.1) 7.4 (6.9–7.9) 4.0 (3.5–4.5) 4.4 (3.9–5.0) 7.0 (6.4–7.5)
2011 11.8 8.5 (8.0–9.0) 3.3 (2.8–3.8) 7.3 (6.8–7.8) 4.5 (4.0–5.0) 4.7 (4.2–5.3) 7.1 (6.5–7.6)
SHARE Men 2004 9.3 7.5 (7.0–8.0) 1.9 (1.4–2.4) 7.8 (7.3–8.3) 1.6 (1.1–2.0) 7.4 (6.9–7.9) 1.9 (1.4–2.4)
2011 9.9 7.6 (7.0–8.1) 2.3 (1.7–2.9) 7.9 (7.3–8.5) 2.0 (1.5–2.5) 7.7 (7.2–8.3) 2.2 (1.6–2.7)
Women 2004 11.4 7.9 (7.3–8.6) 3.5 (2.8–4.1) 8.1 (7.4–8.8) 3.3 (2.7–4.0) 7.4 (6.7–8.1) 4.1 (3.3–4.8)
2011 11.8 9.2 (8.5–9.8) 2.6 (2.0–3.3) 9.1 (8.5–9.8) 2.7 (2.0–3.3) 7.9 (7.1–8.6) 3.9 (3.2–4.7)
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LE, life expectancy. Stratified by survey (SWEOLD, SHARE), sex and survey year (1992, 2002, 2004, 2011).

Table 3.

T-test for change between survey years in years of remaining life expectancy with and without severe disability, with and without mild disability, and with and without mobility problems

Men Women
SWEOLD SHARE SWEOLD SHARE
LE with 1992– 2002 1992– 2004 1992– 2011 2004– 2011 2004– 2011 1992– 2002 1992– 2004 1992– 2011 2004– 2011 2004– 2011
Severe disability With problems 0.46* 0.39 0.62* 0.23 0.47 0.09 −0.21 −0.49 −0.27 −0.84*
Without problems 0.19 0.74** 1.08** 0.33 0.09 0.09 0.96** 1.62** 0.66* 1.23**
Mortality effect 0.29 0.07 0.14 0.05 0.35 0.03 −0.57 −1.03 −0.44 −1.00
Disability effect −0.10 0.67 0.94 0.28 −0.25 0.06 1.53 2.66 1.10 2.24
Mild disability With problems 0.01 0.19 0.44 0.25 0.45 −0.14 −0.30 0.22 0.52 −0.65
Without problems 0.64* 0.95** 1.26** 0.31 0.11 0.31 1.05** 0.92** −0.13 1.04**
Mortality effect −0.30 −0.38 −0.42 0.29 0.45 −0.20 −0.70 −0.38 0.21 0.23
Disability effect 0.94 1.32 1.67 0.02 −0.34 0.52 1.74 1.30 −0.34 0.81
Mobility problems With problems 1.15** 0.96** 1.22** 0.27 0.25 1.33** 1.28** 1.36** 0.25 −0.12
Without problems −0.49 0.18 0.47 0.29 0.31 −1.15** −0.54 −0.23 0.31 0.51*
Mortality effect 0.82 0.35 0.30 −0.04 0.11 1.24 0.82 0.66 −0.18 −0.29
Disability effect −1.31 −0.17 0.17 0.34 0.20 −2.39 −1.36 −0.89 0.49 0.80
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LE, life expectancy. Decomposition of mortality effect and disability/mobility effect for the change in life expectancy without disability/mobility problems.

* Statistically significant P<0.10, ** P<0.05.

Figure 1.

Figure 1

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Estimated proportions of remaining life expectancy to be lived without severe disability; estimated proportions of remaining life expectancy to be lived without mild disability; estimated proportions of remaining life expectancy to be lived without mobility problems

As seen in table 1, more proxy interviews were conducted in SWEOLD than in SHARE, especially evident in 2011. The proportion of participants who reported severe disability was fairly similar between the surveys, but a larger proportion of SWEOLD than SHARE participants reported mild disability and mobility problems.

Health expectancies

Between 1992 and 2011, remaining life expectancy at age 77 increased by 1.7 years for men (from 8.2 to 9.9 years) and by 1.1 years for women (from 10.7 to 11.8 years).

Life expectancy without severe disability

The results derived from SWEOLD indicated that between 1992 and 2011, life expectancy without severe disability increased by 1.1 years for men (P<0.05) and 1.6 years for women (P<0.05) (table 3), suggesting that women, but not men, experienced an absolute compression of severe disability during the period. However, the proportion of remaining life expectancy without severe disability decreased in men, whereas it increased in women. A similar pattern was observed between 2004 and 2011, when most of the increase in life expectancy consisted of years without severe disability. In men it increased by 0.4 years, and in women, 0.6 years, thus an absolute compression of severe disability was observed among women during this period. The proportion of time lived without severe disability remained rather stable among men, and increased slightly among women.

The results of SHARE showed that years without severe disability increased by 0.1 years for men and 1.3 years for women (P<0.05) between 2004 and 2011, thus an absolute compression of severe disability among women. In men, the proportion of time lived without severe disability decreased in relation to total life expectancy; in women this proportion decreased.

Life expectancy without mild disability

Between 1992 and 2011, the estimates derived from SWEOLD showed an increase of years without mild disability: 1.3 years in men (P<0.05) and 0.9 years in women (P<0.05). Hence, the proportion of time lived without mild disability remained stable in both men and women. Between 2004 and 2011, a somewhat different pattern was observed. Years lived without mild disability increased by 0.3 years in men and decreased by 0.1 years in women, for women this resulted in an absolute expansion of mild disability. Thus between 1992 and 2004, the proportion of time lived without mild disability remained stable in men but decreased slightly in women.

The results of SHARE showed that between 2004 and 2011, years without mild disability increased by 0.1 years in men and 1.0 years in women (P<0.05). For women this corresponds to an absolute compression of mild disability. In relation to total life expectancy, the proportion of time without mild disability decreased in men and increased in women.

Life expectancy without mobility problems

The results of SWEOLD showed that between 1992 and 2011, life expectancy without mobility problems increased by 0.5 years in men and decreased by 0.2 years in women. Hence, most of the increased life expectancy was spent with mobility problems, it increased by 1.2 years in men (P<0.05) and 1.4 years in women (P<0.05). For women this corresponds to an absolute expansion of morbidity problems. Hence the proportion of time without mobility problems decreased in both men and women. Between 2004 and 2011, life expectancy without mobility problems increased by 0.3 years in both men and women. In relation to total life expectancy, the proportion of time without mobility problems remained rather stable in both men and women.

The estimates calculated on the basis of SHARE data indicated that between 2004 and 2011, years without problems increased by 0.3 years in men and 0.5 years in women. In relation to total life expectancy, the proportion of time spent without mobility problems remained rather stable in both men and women.

Decomposition of observed trends

The increase in life expectancy without health problems was predominantly driven by changes in the prevalence of disabilities. Between 1992 and 2011, the increase of years without severe disability, and without mild disability, was mainly driven by disability effects for both men and women. For life expectancy without mobility problems, the mortality effect had a greater impact in both sexes.

Between 2004 and 2011, the increase of years without severe disability was mostly driven by disability effects, except for men in the SHARE sample where mortality effects had a greater impact. Increases of years without mild disability were mainly driven by mortality effects, except for women in the SHARE sample. For years without mobility problems, mobility effect had a greater impact, except for males in the SHARE sample.

Discussion

This study explored trends in health expectancy at age 77 in the Swedish population between 1992 and 2011. We used two surveys based on random samples of older adults in Sweden, SWEOLD and SHARE. The results suggest that the estimates vary depending, sex and observation year, with a general pattern of relative expansion of poor health among men and a relative compression among women. Because of the initial gender differences in health and life expectancy, these opposing patterns of change resulted in a decrease in the male-female differences in life expectancy and health expectancy during the study period. The decomposition analysis indicates that the increase of years without health problems was predominantly driven by change in the prevalence, rather than mortality, especially among women.

Although overall patterns were similar in both sets of data, the prevalence of mild disability and of mobility problems differed between the two datasets. Thus, the estimations of health expectancies also differed. The prevalence of mild disability and of mobility problems was substantially higher in the SWEOLD survey than in the SHARE survey. At this point, we cannot explain these discrepancies, but some survey differences are notable. In SWEOLD, participants who lived in care facilities were not asked questions about iADL, and we classified them as having mild disabilities in the analysis. It is thus possible that the iADL problems were overestimated in the analyses. Similarly, the wording of the questions about mobility problems differed somewhat between the two surveys, which could partly explain the difference in reported mobility problems. In addition, there were substantial differences in the response rates of the surveys; SWEOLD had much lower non-response rates than SHARE, and the participants who declined to participate in SHARE might share certain characteristics that influence the result.

In addition to the discrepancies between the surveys, other limitations should be taken into consideration when interpreting the results. Both SWEOLD and SHARE have relatively small sample sizes, and the health outcomes are self-assessed which could introduce bias. Furthermore, the Sullivan method, which we used to calculate health expectancies, does not include transitions between health states, which could generate an overestimation of health problems in the population.4 However, recovery from disability decreases with increasing age,12 and the estimates made using the Sullivan method have proven reliable as long as prevalence is regular and smooth over time.3,38,39 Hence, it is unlikely that this potential overestimation substantially biased the results.

The strengths of the study include the use of two national datasets, both based on random samples of the general population and both of which included both proxy interviews and people living in care facilities, which limit the risk of underestimating health problems in the older population.30 Moreover, the outcomes were assessed in the same manner in all survey waves, which is important for accuracy in comparability.8

The results of cross-sectional studies on health expectancy diverge; some studies have found a compression17,19 and others an expansion of morbidity.13 While trend of declining gender differences in life expectancy are well documented and has been observed in several countries,23,24 less is known about the development of gender differences in health expectancy over time.22 Our results suggest that the development of health expectancy differs by gender. Because the health of women improved more than the health of men, while the mortality of men improved more than the mortality of women, gender differences in health expectancy decreased during the study period.

The overall change in survival during the study period can partly be attributed to reductions in deaths due to cardiovascular disease, and these reductions have had a greater impact on male mortality.40 This is in line with the results from this study, where the increase in life expectancy was greater among men, but at the cost of slightly worsening health. A plausible hypothesis is that the decrease in mortality from cardiovascular disease has left men increasingly exposed to disabling chronic diseases and conditions.

Acknowledgement

This work was supported by the Swedish Research Council for Health, Working Life and Welfare [grant number 2012-1704 and 2011-1330], and from NordForsk [grant number 74637, Social Inequalities in Ageing].

Funding

The study received financial support from the Swedish Research Council for Health, Working Life and Welfare [grant number 2012-1704 and 2011-1330], and from NordForsk [grant number 74637, Social Inequalities in Ageing]. These analyses used data from SHARE wave 4 release 1.1.1, as of 28 March 2013 (DOI: 10.6103/SHARE.w4.111) and SHARE waves 1 and 2 release 2.6.0, as of November 29th 2013 (DOIs: 10.6103/SHARE.w1.260 and 10.6103/SHARE.w2.260). SHARE data collection has been primarily funded by the European Commission’s fifth Framework Programme (project QLK6-CT-2001-00360 in the thematic programme Quality of Life), the sixth Framework Programme (projects SHARE-I3, RII-CT-2006-062193, COMPARE, CIT5- CT-2005-028857, and SHARELIFE, CIT4-CT-2006-028812) and through the seventh Framework Programme (SHARE-PREP, No. 211909, SHARE-LEAP, No. 227822 and SHARE M4, No. 261982). Additional funding from the U.S. National Institute on Aging (U01 AG09740-13S2, P01 AG005842, P01 AG08291, P30 AG12815, R21 AG025169, Y1-AG-4553-01, IAG BSR06-11 and OGHA 04-064) and the German Ministry of Education and Research as well as from various national sources is gratefully acknowledged (see www.share-project.org for a full list of funding institutions). This study was conducted while the corresponding author was affiliated with the Swedish National Graduate School for Competitive Science on Ageing and Health (SWEAH), which is funded by the Swedish Research Council.

Conflicts of interest: None declared.

Key points

  • Remaining health expectancy varied by sex, health indicator and time period.

  • Results suggest a general pattern of relative expansion of health problems among men and relative compression of health problems among women between 1992 and 2011

  • The male-female gap in health expectancies decreased between 1992 and 2011.

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