Declining Mortality (Increasing Lon

At What Rate?

Steve Goss and Mark Bye

Office of the Chief Actuary

Social Security Administration

Living to 100 International Symposium

Society of Actuaries

January 5, 2017
Perspective: “Aging” Not Mainly from M

Aging (change in age distribution) mainly due to drop in b

0.000.050.100.150.200.250.300.350.400.450.50

1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 20

Aged Dependency Ratio 2016 TR

Population 65+/(20-64) 

Actual and TR IntermediateTFR remain at 3.0 after 1964TFR remain at 3.3 after 1964
Various Alternative Projec

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 Techn

CBO 2013-5)

Or reflect changing conditions:

5) Improvement by cohort (UK CMI, SOA)6) Mortality rate by age, sex, cause (OCACT/

Technical Panel)
2) Extrapolation by Age and 

Example: Lee and CarterFit the average trend of a selected pFuture conditions must replicate th

past—on average

Age gradient never changesNo deceleration in mortality declin
Mortality Decline Varies Over 

Conditions: Antibiotics/economy 1936-54; Medicare/Medi

Female Historical and Projected (2014 Trustees Report) 

Annual Percent Reduction in U.S. Mortality Rates

012345

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

older

Total

Male Historical and Projected (2014 Trustees Report) 

Annual Percent Reduction in U.S. Mortality Rates

-1

012345

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

older

Total
3) Will Life Expectancy Rise Lin

Vaupel/Oeppen 2002; Best Nation

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
4) Extrapolate All Ages the S

Ignores historical age gradientResult: 

– Substantial bias for population age distribu

Thus, large bias for cost as % of payroll

– Less mortality decline at young ages raises – More mortality decline at higher ages raise
Appropriate Data: by Age Cr

Age-gradient in past reduction is clear
5) Extrapolation by Coho

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

issues

 Post-WW2 births: antibiotics young, statins la 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 conditio

are stronger—especially in the U.S.
6) Projection by Age, Sex, C

 SSA/OCACT/Trustees Reports (2015 Techni 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 20

2.79 1.22 2.14 0-14 2.77 2.74 2.72 1.58 0.63 0.61 1.06 15-49 1.07 1.06 1.05 0.97 1.61 1.27 0.05 50-64 1.34 1.34 1.34 1.17 0.92 2.11 0.91 65-84 1.06 1.06 1.05 1.09 

-0.18 1.30 -0.11 85+ 0.65 0.64 0.63 0.64 

0.51 1.78 0.48 65+ 0.88 0.86 0.85 0.89 0.75 1.59 0.48 Total 0.99 0.96 0.94 0.95 

* 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 I

Comparison of Historical, 2015 Trustees Report, and Ron Lee

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

Historical (Dec 2015 data) Ron Lee
Age-adjusted Death Rates for Heart Disease, Canc

and Unintentional Injuries: United States, 190

(courtesy Robert Anderson, NCHS)

Rate per 100,000 standard population

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

Heart disease

Cancer

Stroke

Unintentional injuries
Mortality Decline by Cause of D

Rate of change from 1979 to 2013

-4-3-2-1

01234

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

CardiovascularCancerViolenceRespiratoryOther

FEMALE

-3-2-1

01234

Under 15 15-49 50-64 

MALE
Age-Sex Extrapolation vs. Age-Sex-Cause P

Lee maintaining full age-gradient offsets lack of dece

Result: OASDI actuarial deficit unchanged using Lee e

Mortality Rate Comparison Age 0-14 Unisex

0123456

1950 1970 1990 2010 2030 2050 2070 2090

Historical 2015TR Ron Lee

Mortality Rate Comparison Age 6

 Unisex

7.5

8

8.5

9

1950 1970 1990 2010 2030 

Historical 2015TR Ron Le
2015 Technical Panel

Endorsed projections by cause with age-Suggested average age-adjusted 1% ann

of decline

– To match average rate since 1950, overall– Understood this incorporated deceleration

Chairperson Alicia Munnell, after TR 20

she was glad Trustees did not adopt the of decline
Mortality Improvement: Slow Sinc

Trustees Reports have overestimated reduction la

700750800850900950

1,0001,0501,100

1990 1995 2000 2005 2010 2015

Age-Sex-Adjusted Death Rates

(Total, All Ages)

2014TR 2015TR 2016TR Actual

4,0004,2004,4004,6004,8005,0005,2005,4005,6005,8006,000

1990 1995 2000 2005 

Age-Sex-Adjusted Death 

(Ages 65 and Older)

2014TR 2015TR 2016TR 
Developing Assumptions by C

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 medium term expectations—independen

– Trustees’ medium-term rates by cause had 

published 
Cardiovascular: JHU Less Optimist

Trustees over Age 50 for Next 30 Y

0.00.51.01.52.02.53.03.54.0

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 202010 to 202038 to 20

JHU 

0.5

JHU 

1.5 JHU 

1.6

JHU 

1.5

0.00.51.01.52.02.53.03.54.0

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 202010 to 202038 to 20

JHU 

1.1 JHU 0.6

JHU 

1.5 JHU 1.6
Respiratory: JHU More Optimistic 

Age 50, Less Optimistic over Ag

-3.0-2.0-1.0

0.01.02.03.04.0

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 t2010 t2038 t

JHU 

0.1 JHU 0.5 JHU 0.8 JHU 1.7

-3.0-2.0-1.0

0.01.02.03.04.0

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 t2010 t2038 t

JHU 

0.4 JHU 0.4 JHU 0.8 JHU 1.5
Cancer: JHU Very Similar 

to Trustees’ Expectations

-1.0-0.5

0.00.51.01.52.02.53.0

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 2010 2038 

JHU 

0.4

JHU 

0.9

JHU 

1.3 JHU 

1.8

-1.0-0.5

0.00.51.01.52.02.53.0

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 2010 2038 

JHU 

0.6

JHU 

1.2

JHU 

1.1

JHU 

1.3
How Future Conditions Might C

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 decelerat
Trends in Obesity: US 1971-20

Sam Preston 2010—must consider cumulative eff

Increasing duration of obesity for aged in futu
Death Rates Vary by Career Earnings R

Difference has increased

Female 65-69 Retired-Worker 

Relative Death Rates by AIME Quart

0

0.20.40.60.8

1

1.21.41.6

123

19920
Does Health Spending Affect Mort

Note rise, at least through 2009

0%2%4%6%8%

10%12%14%16%18%20%

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

National Health Expenditures With and Without 

Medicare and Medicaid as a Percent of GDP

NHE/GDP(NHE-Med&Med)/GDPNIPA NHE/GDP
Health Spending Cannot Continue 

at Historical Rates

Note Trustees’ deceleration

-1%

0%1%2%3%4%5%

 1970-1980 1980-2010 2010-2040 2040-2070 207

Annual Percent Change in Medicare Cost per Beneficia

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

It appears we are rectangularizing the survival cu

Survival Curve U.S. Female: Period Data

0

0.10.20.30.40.50.60.70.80.9

1

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

Survival Curve U.S. Male: Period Data

0

0.10.20.30.40.50.60.70.80.9

1

0 10 20 30 40 50 60 70 80 90 100 110
Death Rates Will Continue to D

But How Fast and for Whom

Must understand past and future conditio

– 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 

to be 19.0; actual was 19.1
For More Information...

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

 Documentation of Trustees Report data & assu

https://www.ssa.gov/oact/TR/2016/2016_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