Declining Mortality (Increasing Longevity):

At What Rate?

Steve Goss and Karen Glenn

Office of the Chief Actuary

Social Security Administration

National Bureau of Economic Research

July 26, 2017
2

Perspective: “Aging” Not Mainly from Mortality

Aging (change in age distribution) mainly due to drop in birth rates
Various Alternative Projection 

Approaches Using Data

Extrapolating past trends:

1) Age setback (early method)

2) Mortality rate by age and sex (Lee/Carter)

3) Life expectancy at birth (Vaupel/Oeppen)

4) Mortality rate by trend all ages (2011 Technical Panel, 

CBO 2013-5)

Or reflect changing conditions:

5) Improvement by cohort (UK CMI, SOA)

6) Mortality rate by age, sex, cause (OCACT/TR, 2015 

Technical Panel)

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2) Extrapolation by Age and Sex

Example: Lee and Carter

Fit the average trend of a selected period

Future conditions must replicate the 

past—on average

Age gradient never changes

No deceleration in mortality decline

4
Mortality Decline Varies Over Time

Conditions: Antibiotics/economy 1936-54; Medicare/Medicaid 1968-82

Female Historical and Projected (2014 Trustees Report) 

Annual Percent Reduction in U.S. Mortality Rates

0

1

2

3

4

5

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

1900 to 1936

1936 to 1954

1954 to 1968

1968 to 1982

1982 to 2010

Male Historical and Projected (2014 Trustees Report) 

Annual Percent Reduction in U.S. Mortality Rates

-1

0

1

2

3

4

5

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

1900 to 1936

1936 to 1954

1954 to 1968

1968 to 1982

1982 to 2010 5
3) Will Life Expectancy Rise Linearly?

Vaupel/Oeppen 2002; Best Nations

Requires accelerating

rate of decline in 

mortality rates if 

retain age gradient

LE most affected by 

lowest ages—only so 

much gain possible

Most disagree

– Vallin/Meslé

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4) Extrapolate All Ages the Same

Ignores historical age gradient

Result: 

– Substantial bias for population age distribution

Thus, large bias for cost as % of payroll

– Less mortality decline at young ages raises cost

– More mortality decline at higher ages raises cost

7
Appropriate Data: by Age Critical

Age-gradient in past reduction is clear

8
5) Extrapolation by Cohort

 U.K. (& SOA-RPEC): “Phantoms never die” data 

issues

 Post-WW2 births: antibiotics young, statins later

 What does change up to age x say above age x?

Is cohort healthier at x if lower mortality up to x?

Or is cohort compromised by impaired survivors?

What does one cohort imply for the next cohort?

 Period effects from known changes in conditions 

are stronger—especially in the U.S.

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6) Projection by Age, Sex, Cause

 SSA/OCACT/Trustees Reports (2015 Technical Panel)

 Requires selecting ultimate rates of decline

 Allows change in age gradient

 Results in deceleration in mortality decline

AGE

1982-99 1999-2009 2009-13 2011-39 2011-89 2039-89 2011-39 2011-89 2039-89

2.79 1.22 2.14 0-14 2.77 2.74 2.72 1.58 1.57 1.57

0.63 0.61 1.06 15-49 1.07 1.06 1.05 0.97 0.93 0.90

1.61 1.27 0.05 50-64 1.34 1.34 1.34 1.17 1.09 1.06

0.92 2.11 0.91 65-84 1.06 1.06 1.05 1.09 0.86 0.74

-0.18 1.30 -0.11 85+ 0.65 0.64 0.63 0.64 0.53 0.48

0.51 1.78 0.48 65+ 0.88 0.86 0.85 0.89 0.71 0.61

0.75 1.59 0.48 Total 0.99 0.96 0.94 0.95 0.80 0.71

* Fit 1950-2011, using Medicare-enrollment data for 65 and over, rather than HMD data

 See Actuarial Note 158 https://www.ssa.gov/oact/NOTES/pdf_notes/note158.pdf

2015TR Intermediate

Comparison of Historical, 2015 Trustees Report, and Ron Lee* 

Average Annual Rates of Decline in Age-Sex-Adjusted Death Rates

Historical (Dec 2015 data) Ron Lee

10
Age-adjusted Death Rates for Heart Disease, Cancer, Stroke, 

and Unintentional Injuries: United States, 1900-2015

(courtesy Robert Anderson, NCHS)

Rate per 100,000 standard population

NOTE: Data prior to 1933 contain death-registration States only. Data for 2015 is provisional.

Heart disease

Cancer

Stroke

Unintentional injuries

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Mortality Decline by Cause of Death: 

Rate of change from 1979 to 2013

-4

-3

-2

-1

0

1

2

3

4

Under 15 15-49 50-64 65-84 85+

Cardiovascular

Cancer

Violence

Respiratory

Other

FEMALE

-3

-2

-1

0

1

2

3

4

Under 15 15-49 50-64 65-84 85+

MALE

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Age-Sex Extrapolation vs. Age-Sex-Cause Projection 

Lee maintaining full age-gradient offsets lack of deceleration

Result: OASDI actuarial deficit unchanged using Lee estimates

Mortality Rate Comparison Age 0-14 Unisex

0

1

2

3

4

5

6

1950 1970 1990 2010 2030 2050 2070 2090

Historical 2015TR Ron Lee

Mortality Rate Comparison Age 65+

 Unisex

7.5

8

8.5

9

1950 1970 1990 2010 2030 2050 2070 2090

Historical 2015TR Ron Lee

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2015 Technical Panel

Endorsed projections by cause with age-gradient

Suggested average age-adjusted 1% annual rate 

of decline

– To match average rate since 1950, overall

– Understood this incorporated deceleration

Chairperson Alicia Munnell, after TR 2016, said 

she was glad Trustees did not adopt the 1% rate 

of decline

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Mortality Experience: All Ages

Reductions continue to fall short of expectations

15
Mortality Experience: Ages 65 and Older

Reductions since 2009 continue to fall short of expectations

16
Mortality Experience: Ages Under 65 

Actual increase since 2010

17
Developing Assumptions by Cause

Scientific approach reflecting biology

Trustees and SSA/OCACT develop in 

consultation with other experts

Johns Hopkins recent survey of medical 

researchers and clinicians came to very similar 

medium term expectations—independently

– Trustees’ medium-term rates by cause had not been 

published 

18
Cardiovascular: JHU Less Optimistic than 

Trustees over Age 50 for Next 30 Years

19

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Cardiovascular Disease-Female

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

0.5

JHU 

1.5 JHU 

1.6

JHU 

1.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Cardiovascular Disease-Male

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

1.1 JHU 

0.6

JHU 

1.5 JHU 

1.6
Respiratory: JHU More Optimistic under 

Age 50, Less Optimistic over Age 85

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-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Respiratory-Female

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

0.1 JHU 

0.5

JHU 

0.8

JHU 

1.7

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Respiratory-Male

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

0.4 JHU 

0.4

JHU 

0.8

JHU 

1.5
Cancer: JHU Very Similar 

to Trustees’ Expectations

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-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Cancer-Female

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

0.4

JHU 

0.9

JHU 

1.3 JHU 

1.8

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Under Age 15 Ages 15 - 49 Ages 50 - 64 Ages 65 - 84 Ages 85 and

older

Total

Cancer-Male

Average Annual Percent Reduction

JHU values are for the period 2009-2040

1979 to 2010

2010 to 2038

2038 to 2088

JHU 

0.6

JHU 

1.2

JHU 

1.1

JHU 

1.3
How Future Conditions Might Change

Smoking decline for women

– Started and stopped later than men

Obesity—sedentary lifestyle

Difference by income/earnings

Health spending—must decelerate

– Advances help only if apply to all

Human limits

– Increasing understanding of deceleration

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Trends in Obesity: US 1971-2006 

Sam Preston 2010—must consider cumulative effects

Increasing duration of obesity for aged in future

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Death Rates Vary by Career Earnings Ranking 

Difference has increased

Female 65-69 Retired-Worker 

Relative Death Rates by AIME Quartile

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 2 3 4

1990

2010

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Does Health Spending Affect Mortality?

Note rise, at least through 2009

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0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

National Health Expenditures With and Without 

Medicare and Medicaid as a Percent of GDP

NHE/GDP

(NHE-Med&Med)/GDP

NIPA NHE/GDP
Health Spending Cannot Continue to Rise 

at Historical Rates

Note Trustees’ deceleration

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-1%

0%

1%

2%

3%

4%

5%

 1970-1980 1980-2010 2010-2040 2040-2070 2070-2085

Annual Percent Change in Medicare Cost per Beneficiary 

Relative to GDP per Worker: 2015 TR
Is There an Omega?

It appears we are rectangularizing the survival curve?

Survival Curve U.S. Female: Period Data

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50 60 70 80 90 100 110

1900

1925

1950

1975

2000

2013

Survival Curve U.S. Male: Period Data

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50 60 70 80 90 100 110

1900

1925

1950

1975

2000

2013

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Death Rates Will Continue to Decline: 

But How Fast and for Whom?

Must understand past and future conditions

– Persistent historical “age gradient”

– Avoid simple extrapolation of past periods

» Cannot ignore changing conditions

 “Limits” on longevity due to physiology

 Latter half of 20th century was extraordinary

» So deceleration seems likely

» Cause-specific rates allow basis for assumptions

– Results: in the 1982 TR, we projected LE65 in 2013 

to be 19.0; actual was 19.1

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For More Information...

http://www.ssa.gov/oact/

 Documentation of Trustees Report data & assumptions 

https://www.ssa.gov/oact/TR/2017/2017_LongRange_Demographic_Assumptions.pdf

 Historical and projected mortality rates

https://www.ssa.gov/oact/HistEst/DeathHome.html

 Annual Trustees Reports 

https://www.ssa.gov/oact/TR/index.html

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