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Using Mortality to Compare the Health of Populations by James W. Vaupel Max Planck Institute for Demographic Research, Rostock, Germany, University of

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Using Mortality to Comparethe Health of Populations

by James W. Vaupel

Max Planck Institute for Demographic Research, Rostock, Germany,

University of Southern Denmark, Odense, Denmark

Mortality Past and Present: Celebrating Graunt

Gresham College, London 29 November 2012

10/33

Age

The Postponement of Senescence: Evidence from Sweden

Data Source: Calculations based on Human Mortality Database by Elisabetta Barbi and Giancarlo Camarda (unpublished)

30 40 50 60 70 80 90

0.0001

0.001

0.01

0.1

11950

1980

2010

57 6863

Swedish FemalesAge 30-90

Ris

k o

f D

eath

11/33

Age

Equivalent Age 50 Years Ago

Female Male

France Sweden

USA Japan France Sweden

USA Japan

50 42 40 44 23 44 43 44 39

60 49 52 53 43 51 53 51 50

70 59 62 63 53 59 62 60 57

80 71 72 74 67 71 73 73 70

90 83 85 85 79 84 87 85 81

Current age and age of equivalent mortality 50 years ago.

Old age and advanced old age, for France

The duration of advanced old age for females and males in various countries

Females Malese(X10)

1960

e(X10)

recent

e(X10)

1960

e(X10)

recent

UK 6.0 5.9 6.3 6.1

France 5.9 5.7 6.1 5.7

USA 6.1 5.7 6.3 5.9

Japan 6.1 5.7 6.2 6.0

Russia 6.8 6.0 7.1 6.7

Belarus 6.7 5.9 6.4 6.6

Equivalent ages from 1900 to present in France (solid) and Sweden (dashed) for q(x)=1%, e(x)=20, ecohort(x)=20.

Equivalent ages,1950 to present in Japan.q(x)=0.1% in red, e(x)=40 in blue, ec(x)=40 in purple

Equivalent ages,1950 to the present in France.

Top: q(x)=1% (red), e(x)=20 (blue) and ec(x)=20 (purple). Bottom: q(x)=0.1% and e(x)=ec(x)=40.

Equivalent ages,1950 to present for women in Japan (solid) vs. the U.S. (dashed), for q(x)=1%, e(x)=ec(x)=20

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 81 51 78

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 81 51 78

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 82 50 79

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 79 52 76

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 72 79 90 52 62 76 86

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 72 79 90 52 62 76 86

Russia 58 82 50 78

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 72 79 90 52 62 76 86

Russia 58 58 82 82 50 43 78 78

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 72 79 90 52 62 76 86

Russia 58 58 82 82 50 43 78 78

Belarus 60 86 54 82

Ages x1 and x10 for females and males in various countries

F MX1

1960

X1

recent

X10

1960

X10

recent

X1

1960

X1

recent

X10

1960

X10

recent

UK 59 67 81 88 51 59 78 85

France 59 71 81 88 51 59 78 88

USA 58 64 82 88 50 58 79 85

Japan 57 72 79 90 52 62 76 86

Russia 58 58 82 82 50 43 78 78

Belarus 60 58 86 83 54 43 82 77

Grip Strength at x1 and x10

Normalized physical weakness for females(based on grip strength)

Normalized measures of health for males and females in the EU and in the US

Comparative baseline:gauging mortality reduction

0 20 40 60 80

0.0

00

10

.00

10

.01

0.1

1

Hunter-gatherersHunter-gatherer, lowest mortality

Age

An

nu

al p

rob

ab

ility

of d

ea

th

Mostly flatish

Hunter-gatherer data: Gurven and Kaplan 2007

Siler fits

average of 5 populations of full time foragers

This average is the comparative evolutionary baseline

-lowest mortality

Comparative baseline:gauging mortality reduction

0 20 40 60 80

0.0

00

10

.00

10

.01

0.1

1

Hunter-gatherersHunter-gatherer, lowest mortalitySweden, 1750-2010, 10 yr intervals

Age

An

nu

al p

rob

ab

ility

of d

ea

th

Hunter-gatherersHunter-gatherer, lowest mortalitySweden, 1750-2010, 10 yr intervals

(Human mortality database)

Pile up-lowest mortality

How much should we expect?

Equivalent age:72 is the new 30

0 20 40 60 80 100

020

4060

8010

0

30

72

6080

15

63

30

71

Hunter-gatherer age

Equ

ival

ent a

ge

(Burger et al. 2012)

0 20 40 60 80 100

0.00

001

0.00

010.

001

0.01

0.1

1

Japan 2010Japan 1947Sweden 2010Sweden 1900Sweden 1800hunter-gathererAcculturated h-gsTrinidad slaves Wild chimpsCaptive chimps

Age

Ann

ual p

roba

bilit

y of

dea

th

Ratio improvement:Population distance > species distance

0 20 40 60 80

12

510

2050

100

200

Hunter-gatherers to Japan 2010

Wild chimps to hunter-gatherers

Hunter-gatherers to Sweden2010

1950

1900

Age

Rat

io o

f mor

talit

y ris

ks

NOTE: Human hunter-gatherers have exceptionally low mortality

Lowest mortality across the lifespan

1750 1800 1850 1900 1950 2000

Year

Min

imu

m p

rob

ab

ility

of d

ea

th a

cro

ss th

e li

fetim

e

SwedenFranceJapan

Hunter-gatherer

0.0

00

10

.00

10

.01

0.1

~6.6 million years

~150 years

1750 1800 1850 1900 1950 2000

Year

Min

imu

m p

rob

ab

ility

of d

ea

th a

cro

ss th

e li

fetim

e

SwedenFranceJapan

Hunter-gatherer

Chimpanzee

Acculturated HG

0.0

00

10

.00

10

.01

0.1

(Burger et al. 2012)

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