Years of life lived by elderly Singaporeans with and without frailty

REVES@30University of Michigan, Ann Arbor

1st June 2018

Rahul Malhotra1, Abhijit Visaria1, Choy-Lye Chei1, Chi-Tsun Chiu2, John Carson Allen1, Stefan Ma3, Chek Hooi Wong4, Angelique Chan1, Yasuhiko Saito5, Truls Østbye1, David Bruce Matchar1

1Duke-NUS Medical School, Singapore 2Academia Sinica, Taipei, Taiwan3Ministry of Health, Singapore4Khoo Teck Puat Hospital, Singapore5Nihon University, Tokyo, Japan

Content

• Singapore

• Frailty, and the Frailty Assessment Measure (FAM)

Duration of life lived with and without frailty

Motivation

Methods

Results

Discussion

2

Singapore – Demographic Profile

3

Population, 2017: 5.61 million (Resident=3.97 million, Non-resident=1.64 million)

Populations Trend 2017, Department of Statistics Singapore, 2017

https://www.globalvillagespace.com/trump-skeptical-about-his-meeting-with-kim-jong-un/

https://www.globalvillagespace.com/no-history-will-be-made-trump-bails-out-of-the-singapore-summit/

Demographic indicators (Singapore and USA)

Singapore USA

Total Population (2015) 5.5 million 321 million

Population Density (2015) 19935 /miles2 91 / miles2

Total number of those aged 60 and above (2015) 0.7 million* 66 million

Percentage of those aged 60 and above (2015) 17.9% * 20.8%

Percentage of those aged 65 and above who live alone (2010) 17.4%* 29.3%

4

*Singapore residents

• http://www.census.gov/popclock/• https://www.statista.com/statistics/183475/united-states-population-density/• https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk• http://www.singstat.gov.sg/publications/publications-and-papers/GHS/ghs2015content• Populations Trend 2016, Department of Statistics Singapore, 2016• https://www.singstat.gov.sg/docs/default-source/default-document-library/publications/newsletter/archive/ssnmar2014.pdf• http://www.aging.ca.gov/docs/DataAndStatistics/Statistics/OtherStatistics/Profile_of_Older_Americans_2011.pdf

Speed of Ageing – USA, Japan and Singapore

0

5

10

15

20

25

30

35

40

1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Japan Singapore United States of America

Super-Aged (21%)

Aged (14%)

Ageing (7%)

Source: United Nations, Department of Economic and Social Affairs, Population Division (2015). World Population Prospects: The 2015 Revision, custom data acquired via website.

Proportion of population aged 65+

Frailty: Definition(s)

6

A clinical state in which there is an increase in an individual’s risk for developing increased dependency and/or mortality when exposed to a stressor

A dynamic state affecting an individual who experiences losses in one or more domains of human functioning (physical, psychological and social), which is caused by a range of variables, and which increases the risk of adverse health outcomes

• Morley JE, Vellas B, van Kan GA, et al. Frailty consensus: a call to action. Journal of the American Medical Directors Association 2013;14:392-7.• de Vries NM, Staal JB, van Ravensberg CD, Hobbelen JS, Olde Rikkert MG, Nijhuis-van der Sanden MW. Outcome instruments to measure frailty: a systematic review. Ageing research reviews 2011;10:104-14.

Frailty Assessment Measure (FAM)

7

ROBUST PRE-FRAIL FRAIL

< 0.38 0.38 to 0.82 > 0.82

• Body mass index* (1 item)• Hand grip strength* (1 item)• Mobility (9 items)

• Age (1 item)• Gender (1 item)• Number of chronic health conditions (1 item)

14-item measure

* measured

Content

• Singapore

• Frailty, and the Frailty Assessment Measure (FAM)

Duration of life lived with and without frailty

Motivation

Methods

Results

Discussion

8

Duration of life lived with and without frailty: Motivation

• Frailty, among the elderly, is highlighted by clinical professional bodies and health organizations as an important clinical state, calling for early detection

• The policy importance of, and clinical screening utility for, frailty, however, depend on the duration of life an average elderly lives with frailty

• Only 2 publications, from Europe, have estimated this duration• Herr et al 2017: At age 70, women spend 3.4 (19%) and 2.4 (14%) years of remaining life with frailty and

disability. Corresponding estimates for men were 1.2 (9%) and 1.2 (9%) years. Years lived with pre-frailty (7.4 [41%] for women and 6.0 [41%] for men) were greater. (Frailty based the Cardiovascular Health Study [CHS] ~ Fried construct)

• Romero-Ortuno et al 2014: In the EU27, at age 50, women spend 2.1 (6%) and 7.4 (21%) years of remaining life with frailty and severe limitations. Corresponding estimates for men were 0.8 (3%) and 5.1 (17%) years. (Frailty based the Cardiovascular Health Study [CHS] ~ Fried construct)

9

Aim and Hypothesis

Utilizing longitudinal data from a national survey of the elderly in Singapore, we aim to estimate the duration of life lived with and without frailty for elderly Singaporeans, overall and by gender

Hypothesis

At age 60 (and 70 and 80) the absolute (i.e. number of years) and relative (i.e. proportion of remaining life) duration of life lived with frailty is higher for women versus men

10

Dataset

• Panel on Health and Aging of Singaporean Elderly (PHASE)

• Nationally representative longitudinal survey of home-dwelling elderly Singaporeans (Stratified Random Sampling)

• https://www.duke-nus.edu.sg/care/dataset-codebook/

• Analytical sample: 3452 (comprising those alive and interviewed in least 2 waves, as well

as those alive and interviewed in least 1 wave and reported as Deceased when contacted for the subsequent wave)

11

Wave 1In 2009N=4990

Wave 2In 2011N=3103

(and 349 reported as Deceased)

Wave 3In 2015N=1572

(and 295 reported as Deceased)

Health states, at Waves 1, 2 and 3

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1. Robust

2. Pre-Frail

3. Frail

4. Activity of Daily Living (ADL) Limitation

5. Dead (Waves 2 and 3 only; ABSORBING State)

Frailty Assessment Measure (FAM), based on data collected in the Wave

Based on data on 7 ADLs collected in the Wave

Based on data on status (Alive / Dead) collected in the Wave, with Date of Death from administrative databases

5. Dead

1. Robust 2. Pre-frail 3. Frail 4. ADL Limitation

Potential transitions across health states, across wavesAnalysis: SPACE (Stochastic Population Analysis for Complex Events) http://sites.utexas.edu/space/

Observed transitions across health states, from preceding to subsequent wave

14

Robust to… N

Robust 1440

Pre-Frail 452

Frail 2

ADL Limitation 36

Dead 86

Pre-Frail to… N

Robust 125

Pre-Frail 1658

Frail 173

ADL Limitation 218

Dead 258

Frail to… N

Robust 0

Pre-Frail 58

Frail 109

ADL Limitation 118

Dead 92

ADL Limitation to… N

Robust 4

Pre-Frail 41

Frail 28

ADL Limitation 213

Dead 208

Total number of observed transitions

5319, comprising 3452 from Wave 1 to Wave 2, and 1867 from Wave 2 to Wave 3

15

16

Absolute duration of life lived with and without frailty, overall

17

Age State Years (95% CI)

60

Robust 12.0 (11.4 - 12.7)

Pre-Frail 8.5 (7.8 – 9.1)

Frail 1.0 (0.8 – 1.2)

ADL Limitation 2.6 (2.2 – 2.9)

Total Life Expectancy (TLE) 24.1 (23.3 - 24.9)

Singapore Life Table 2012 TLE estimate: 24.4

Age State Years (95% CI)

70

Robust 3.5 (3.2 - 3.8)

Pre-Frail 8.4 (7.9 - 8.9)

Frail 1.2 (0.9 - 1.4)

ADL Limitation 2.8 (2.4 - 3.2)

Total Life Expectancy (TLE) 15.9 (15.2-16.5)Singapore Life Table 2012 TLE estimate: 16.3

Age State Years (95% CI)

80

Robust 0.3 (0.2 – 0.3)

Pre-Frail 4.7 (4.3 – 5.1)

Frail 1.4 (1.1 – 1.7)

ADL Limitation 3.0 (2.6 – 3.5)

Total Life Expectancy (TLE) 9.4 (8.8- 10.0)Singapore Life Table 2012 TLE estimate: 9.8

Relative duration of life lived with and without frailty, overall

18

49.9

22.1

2.7

35.2

53.0

50.2

4.3

7.4

14.9

10.617.5

32.2

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Age 60 (24.1) Age 70 (15.9) Age 80 (9.4)

Prop

ortio

n of

rem

aini

ng li

fe

Robust Pre-Frail Frail ADL Limitation

Duration of life lived with and without frailty at age 60, by gender

19

Age

State MEN WOMEN Difference (Men minus Women)

Years (95% Confidence Interval)

60

Robust 13.7 (12.9 , 14.6) 10.2 (9.4 , 11.0) 3.6 (2.6, 4.7)

Pre-Frail 6.0 (5.2 , 6.8) 11.1 (10.2 , 12.0) -5.1 (-6.2 , -3.8)

Frail 0.4 (0.2 ,0.6) 1.7 (1.4 , 2.1) -1.3 (-1.7 , -0.9)

ADL Limitation 1.5 (1.0 , 2.0) 3.4 (2.9 , 4.0) -1.9 (-2.6 , -1.0)

Total Life Expectancy (TLE) 21.7 (20.6 , 22.8) 26.5 (25.3 , 27.6) -4.8 (-6.1 , -2.9)

Singapore Life Table 2012 TLE 22.5 26.1 -

63.4

38.5

27.6

42.0

2.0

6.5

7.013.0

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Men Women

Prop

ortio

n of

rem

aini

ng li

fe a

t age

60

Robust Pre-Frail

Frail ADL Limitation

Duration of life lived with and without frailty at age 70, by gender

20

Age

State MEN WOMEN Difference (Men minus Women)

Years (95% Confidence Interval)

70

Robust 5.4 (4.8, 5.9) 1.7 (1.5, 2.0) 3.6 (2.2, 4.3)

Pre-Frail 6.5 (5.7, 7.2) 10.2 (9.5, 10.9) -3.7 (-4.7 , -2.6)

Frail 0.5 (0.3, 0.8) 1.9 (1.5, 2.2) -1.3 (-1.8 , -0.9)

ADL Limitation 1.6 (1.1, 2.1) 3.8 (3.2, 4.5) -2.2 (-2.9 , -1.4)

Total Life Expectancy (TLE) 14.0 (13.1, 14.9) 17.7 (16.8, 18.5) -3.7 (-4.7 , -2.3)

Singapore Life Table 2012 TLE 14.7 17.6 -

38.4

9.8

46.2

57.7

3.9

10.7

11.521.8

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Men Women

Prop

ortio

n of

rem

aini

ng li

fe a

t age

70

Robust Pre-Frail

Frail ADL Limitation

Duration of life lived with and without frailty at age 80, by gender

21

Age

State MEN WOMEN Difference (Men minus Women)

Years (95% Confidence Interval)

80

Robust 0.5 (0.4, 0.6) 0.1 (0.0, 0.1) 0.4 (0.3, 0.6)

Pre-Frail 4.8 (4.3, 5.4) 4.7 (4.2, 5.3) 0.1 (-0.7 , 1.0)

Frail 0.7 (0.4, 1.0) 2.0 (1.6, 2.4) -1.3 (-1.8 , -0.8)

ADL Limitation 1.9 (1.4, 2.4) 3.8 (3.2, 4.4) -1.9 (-2.6 , -1.0)

Total Life Expectancy (TLE) 7.9 (7.2, 8.7) 10.6 (9.8, 11.4) -2.7 (-3.6 , -1.5)

Singapore Life Table 2012 TLE 8.7 10.4 - 6.40.6

60.8

44.5

9.0

19.1

23.8

35.8

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Men Women

Prop

ortio

n of

rem

aini

ng li

fe a

t age

80

Robust Pre-Frail

Frail ADL Limitation

Conclusions and Implications

• At age 60 (and 70 and 80), despite their higher total life expectancy, women, versus men, spend:fewer years in a robust state, and more years in the pre-frail, frail, and ADL limitation states

• Support for a priori hypothesis: Women’s disadvantage in health expectancy, often reported for disability or for ADL limitations, is also manifested in context of frailtyAlso observed in health states (robust and pre-frail) preceding frailty and ADL

limitationCalls for greater and earlier attention to women’s health

22

Conclusions and Implications

• Short absolute (1, 1.2 and 1.4 years, respectively) or relative (~4%, 7% and 15%) duration of remaining life at age 60, 70 and 80 spent in a frail state:Consistent with previous reportsQuestions the policy and clinical focusing on frailty among older adults, but suggests

that increased attention should be placed on pre-frailty

23

Limitations

• Sample size for some of the observed transitions

• 2 and 4 year interval between survey waves

• Measure used for frailty

24

Strengths

• Measure used for frailty

• Mortality assessment from administrative databases

• Singapore! Asia!

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Future work

• Strata defined by ethnicity and by educational status

• Simulated lifelines: Duration spent in a specific state

• Potential replication of analyses in other cohort studies in Singapore (and elsewhere in Asia)

• Trends (fresh cohort – THE SIGNS Study established [Wave 1 in 2016/17; Wave 2 in 2018/19; …….$])

26

27

• Ministry of Social and Family Development, Singapore. • Singapore Ministry of Health’s National Medical Research Council under its Singapore Translational Research Investigator Award as part of the project “Establishing a

Practical and Theoretical Foundation for Comprehensive and Integrated Community, Policy and Academic Efforts to Improve Dementia Care in Singapore” (NMRC-STAR-0005-2009)

• Singapore Ministry of Health’s National Medical Research Council under its Clinician Scientist – Individual Research Grant - New Investigator Grant (NMRC-CNIG-1124-2014)

• Duke-NUS Geriatric Research Fund • Funding for dynamometers was through a grant obtained by the Nihon University Population Research Institute from the “Academic Frontier” Project for Private

Universities: matching fund subsidy from MEXT (Ministry of Education, Culture, Sports, Science and Technology), 2006-2010.

Funding for Panel on Health and Ageing of Singaporean Elderly (PHASE) Waves 1, 2 and 3

• Singapore Ministry of Health’s National Medical Research Council under its Clinician Scientist – Individual Research Grant - New Investigator Grant (NMRC-CNIG-1124-2014)

• Centre for Ageing Research & Education, Duke-NUS Medical School, Singapore

Funding for Travel

Acknowledgements

THANK YOUrahul.malhotra@duke-nus.edu.sg

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29

Frailty Assessment Measure (FAM)

30

BMI: Body Mass Index; SE: Standard Error a Continuous variable***p<0.01

β coefficient (SE)

Intercept 0.37 (2.89)

Frailty variables

ln BMIa -6.75 (2.31)***

BMIa^0.5 2.79 (0.92)***

Hand Grip Strength Ranka 0.04 (0.01)***

Nagi Index Scorea^2 0.12 (0.02)***

Nagi Index Scorea^3 -0.01 (0.003)***

Number of Chronic Health Conditionsa 0.25 (0.03)***

Agea (in years) 0.07 (0.005)***

Male Sex 0.58 (0.07)***

Association with a composite adverse health outcome - death or incident limitation in ≥1 ADL or prolonged hospitalization or frequent hospitalization or frequent emergency room visits (N=4564)

Predicted probability of the composite adverse outcome based on the FAM measure logistic regression coefficients

Predicted probability of the composite adverse outcome = 𝒆𝒆𝒙𝒙

𝟏𝟏+𝒆𝒆𝒙𝒙

𝒙𝒙=�𝟎𝟎.𝟑𝟑𝟑𝟑𝟑𝟑 − 𝟔𝟔.𝟑𝟑𝟕𝟕𝟑𝟑 ln 𝑩𝑩𝑩𝑩𝑩𝑩 + 𝟐𝟐.𝟑𝟑𝟕𝟕𝟕𝟕 𝑩𝑩𝑩𝑩𝑩𝑩𝟎𝟎.𝟕𝟕 + 𝟎𝟎.𝟏𝟏𝟐𝟐𝟎𝟎 𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵 𝑩𝑩𝑰𝑰𝑰𝑰𝒆𝒆𝒙𝒙 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝒆𝒆𝟐𝟐 − 𝟎𝟎.𝟎𝟎𝟏𝟏𝟑𝟑 𝑵𝑵𝑵𝑵𝑵𝑵𝑵𝑵 𝑩𝑩𝑰𝑰𝑰𝑰𝒆𝒆𝒙𝒙 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝒆𝒆𝟑𝟑 +

31

Low risk of the composite adverse outcome or ROBUST

Moderate risk of the composite adverse outcome or PRE-FRAIL

High risk of the composite adverse outcome or FRAIL

< 0.38 0.38 to 0.82 > 0.82

43%

49%

8%

ROBUST PRE-FRAIL FRAILN=4564

Analysis: SPACE (Stochastic Population Analysis for Complex Events )

IDAge at WaveHealth State at WaveCovariate(s) value at Wave

Input Data, in long form

Imputation of data for ‘missing’

years

Annual age-specific

transition probability estimates applied to synthetic cohort of 100,000

Multinomial logistic

regression for annual

age-specific transition probability estimates

Based on preceding and subsequent wave values

Point estimates for

life expectancy and health expectancy

from the resulting

multi-state life table

200 Bootstrap Samples, and for each…..

Bootstrapped Input Data, in long form

Imputation of data for ‘missing’ years

Multinomial logistic

regression for annual age-

specific transition probability estimates

Annual age-specific

transition probability estimates applied to

synthetic cohort of 100,000

95% Confidence Intervals

around point estimates for

life expectancy and health expectancy from the

resulting multi-state life table

http://sites.utexas.edu/space/