lack of social gradient in excess winter mortality in ... · n with a peak in winter and a trough...

Nordic Population Research Rau, 26 Nov 2004 - p. 1/19

Lack of Social Gradient inExcess Winter Mortality in Denmark.

A Register Based Study

Roland RauMax Planck Institute for Demographic Research

http://www.demogr.mpg.de

http://www.demogr.mpg.de

Introduction

l What is Seasonal Mortality?


l Causes for Seasonality

l The Seasonality Paradox


l Research Questions

Data & Methods

Results

Summary


Introduction

Introduction







Data & Methods

Results

Summary


What is Seasonal Mortality?

Introduction







Data & Methods

Results

Summary



n A pattern in mortality which is regular over (calendar) time

n with a peak in winter and a trough in summer.n All ages are affected.n Magnitude:

u 17 % more deaths during winter than during summer(Denmark)

u ∼ 45,000 excess winter deaths in Britain annually(mean since 1950s)

u more than 33,000 excess winter deaths in Britain annually(mean for the last 10 years)

Introduction







Data & Methods

Results

Summary



n A pattern in mortality which is regular over (calendar) timen with a peak in winter and a trough in summer.

n All ages are affected.n Magnitude:




Introduction







Data & Methods

Results

Summary



n A pattern in mortality which is regular over (calendar) timen with a peak in winter and a trough in summer.n All ages are affected.

n Magnitude:u 17 % more deaths during winter than during summer

(Denmark)u ∼ 45,000 excess winter deaths in Britain annually

(mean since 1950s)u more than 33,000 excess winter deaths in Britain annually

(mean for the last 10 years)

Introduction







Data & Methods

Results

Summary



n A pattern in mortality which is regular over (calendar) timen with a peak in winter and a trough in summer.n All ages are affected.n Magnitude:




Introduction







Data & Methods

Results

Summary


Causes for Seasonality

A Simple Chain of Causality

'

&

$

%

'

&

$

%

'

&

$

%

Climate

ColdTemperature

BiomedicalReaction to

Climate

Blood Clotting,Infections of theRespiratoryTract, etc.,

’Demographic’Reaction toBiomedical

Changes

IncreasedMortality Risk

=⇒ =⇒

Introduction







Data & Methods

Results

Summary



A Simple Chain of Causality

'

&

$

%

'

&

$

%

'

&

$

%

Climate

ColdTemperature


Climate

Blood Clotting,Infections of theRespiratoryTract, etc.,

’Demographic’Reaction toBiomedical

Changes

IncreasedMortality Risk

=⇒ =⇒

But can this explain everything?

Introduction







Data & Methods

Results

Summary


The Seasonality Paradox

Minimum Monthly Temperature (°C)

Exc

ess

Win

ter D

eath

s (%

)

05

1015

−10 −5 0 5 10 15

Austria

Belgium

Denmark

Finland

France

Hungary

Iceland

Ireland

Italy

Netherlands

Norway

Portugal

Spain

Sweden

Switzerland

United Kingdom

West Germany

Yugoslavia

Data−Source: McKee 1989, p.179

Introduction







Data & Methods

Results

Summary



A More Advanced Chain of Causality

'

&

$

%

'

&

$

%

'

&

$

%

'

&

$

%

Climate

Cold

Temperature

InterveningSocialFactors

?


Climate

Blood Clotting,

Infections of the

Respiratory,

Tract, etc.

DemographicReaction toBiomedicalChanges

Increased

Mortality Risk

=⇒ =⇒ =⇒

Introduction







Data & Methods

Results

Summary


Research Questions

What are those intervening factors?

Factor Findings fromthe Literature

Income/Wealth Not much researchEducation No research so farHousing Conditions Strong Indicator

for Excess MortalityMarital Status No research so farLiving Arrangements No research so far

Introduction

Data & Methods

l Danish Register Data

l Method

Results

Summary


Data & Methods

Introduction

Data & Methods


l Method

Results

Summary


Danish Register Data

n All People who werealive

n between Jan 1980 andDec 1998

n being 65 years or oldern ∼1.8 Mio. Individualsn broken down into

person-months lived(∼186 Mio. Person-Monthslived)

n Covariates: Wealth,Education, HousingConditions, Info onHousehold, MaritalStatus, . . .

Calendar Time

Age

1975 1980 1985 1990 1995 200060

7080

9010

011

0

Age 100

Age 65

Jan 1980 Dec 1998

Lexis−Map of Available Data

Introduction

Data & Methods


l Method

Results

Summary


Method

Logistic Regression

log

(Pit

1− Pit

)=α+ β1x1,i,t + β2x2,i,t + β3x3,i,t+

+∑

Period k

γkxk,i,t +∑

Age j

δjxj,i,t + further covariates

x1 =

{1, if current month = Dec, Jan, Feb

0, else.

x2 =

{1, if current month = Mar, Apr, May

0, else.

x3 =

{1, if current month = Sep, Oct, Nov

0, else.

Introduction

Data & Methods

Results

l Wealth

l Education

l Housing Conditions

l Marital Status

l Living Arrangements

Summary


Results

Introduction

Data & Methods

Results

l Wealth

l Education


l Marital Status


Summary


Wealth

Winter Excess Mortality, Women (RG: Summer)O

dds−

Rat

ios

0.9

11.

11.

21.

31.

4All Cause Mortality, Women

Wealth Quartile: 0%−25%Wealth Quartile: 25%−50%Wealth Quartile: 50%−75%Wealth Quartile: 75%−100%

Introduction

Data & Methods

Results

l Wealth

l Education


l Marital Status


Summary


Education

Winter Excess Mortality, Women & Men (RG: Summer)

Odd

s−R

atio

s

0.9

11.

11.

21.

31.

4

All Cause Mortality

Women Men

Education: LowEducation: MiddleEducation: High

Introduction

Data & Methods

Results

l Wealth

l Education


l Marital Status


Summary


Housing Conditions

Winter Excess Mortality, Women & Men (RG: Summer)O

dds−

Rat

ios

0.9

11.

11.

21.

31.

4All Cause Mortality

Women Men

Bad HousingGood Housing

Introduction

Data & Methods

Results

l Wealth

l Education


l Marital Status


Summary


Marital Status

Winter Excess Mortality (RG: Summer)O

dds−

Rat

ios

0.9

11.

11.

21.

31.


Women Men

WidowedDivorcedMarriedNever Married

Introduction

Data & Methods

Results

l Wealth

l Education


l Marital Status


Summary


Living Arrangements

Winter Excess Mortality, (RG: Summer)O

dds−

Rat

ios

0.9

11.

11.

21.

31.


Women Men

a) b) AloneNot Alone

Odd

s−R

atio

s

0.9

11.

11.

21.

31.

4

Ischaemic Heart Diseases

Women Men

c) d) AloneNot Alone

Odd

s−R

atio

s

0.9

11.

11.

21.

31.

4

Cerebrovascular Diseases

Women Men

e) f) AloneNot Alone

Odd

s−R

atio

s

0.9

11.

11.

21.

31.

41.

51.

61.

71.

8

Respiratory Diseases

Women Men

g) h)AloneNot Alone

Introduction

Data & Methods

Results

Summary

l Summary


Summary

Introduction

Data & Methods

Results

Summary

l Summary


Summary

Factor Findings from Our Findingsthe Literature

Income/Wealth not much research No Gradient (DK!)Education No research so far No GradientHousing Conditions Strong Indicator No Gradient (DK!)

for Excess MortalityMarital Status No research so far No GradientLiving Arrangements No research so far Risky: Living

Alone

Introduction

Data & Methods

Results

Summary

l Summary


Summary

Thanks for Your Attention!

Questions? Comments?

lack of social gradient in excess winter mortality in ... · n with a peak in winter and a trough...

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