mortality and causes of death in the city of zurich · mortality and causes of death ... statistik...

Mortality and Causes of Death in the City of Zurich Cornelia Schwierz, Judith Riegelnig and Klemens Rosin Statistik Stadt Zürich Acknowledgements: Valentina Lapteva and Olivier Bachem ETH Zurich http://www.r-project.org/

Statistik Stadt Zürich 16-18.10.2013 Schweizer Statistiktage, Basel

Outline

1. Facts on Mortality in Zurich 2. Modelling Mortality 3. Causes of Death 4. Other Effects on Mortality

Creative commons, withcreative.com

Motivation: Population Scenarios

Basis for • City administration • City planning • Schools, child care • Public transport • Health care • Homes for the elderly • … Requirement: scenarios at district level, age-specific

Stadt Zürich Statistik Stadt Zürich

Projections 2013-2025

Population (t) = Population (t-1) + births - deaths + immigration - emigration

Model Part: Demography


Calculate deaths in model as deaths = mortality rate * population Motivation: Desire to model mortality rates accurately, e.g. for cohorts 65+ or 80+

Motivation: Population Scenarios

+/- naturalisation +/- relocation within city


1. Mortality in Zurich

Mortality Rates, Zurich 1900-2011


---- deaths per 1000 inhabitants

---- Percentage (%) of inhabitants over 60 years

Age Pyramid 2012


Female Male

Age

Mortality: Age and Sex

Mortality rate Deaths per year


Male Female

Male Female

Age Age

Mortality: Age and Sex

Log(mortality rate) Deaths per year


Male Female

Male Female

Age Age


2. MODELS FOR PREDICTION a. Simple Approach b. Systematic Comparison

Age-specific Mortality Rates over Time

Simplest model: continue the trend into the future. Specific assumptions (e.g., infants) are possible.

Mortality rate (log10)

Systematic Model Comparison Valentina Lapteva and Olivier Bachem

Goal Compare different methods for predicting mortality rates

and evaluate the quality of the predictions.


Model criteria • Robustness of parameter estimates and forecasts • Plausibility of forecasts • Implementation and parsimony (as simple as possible)

Analysis

1. Consider three parametric models

2. Estimate the model parameters with the data for the years 1994 to 2008

3. Forecast the mortality rates for the years 2009 to 2011 4. Compare the different mortality models using

performance measures


The Models


where

(i.e. APC model)

The parametric models for the mortality rate m(t,x) are of the form:

Prediction for 2011


Performance Measures


Three performance measures investigated: • Discrepancy of predicted and observed values

• Log-Likelihood of the fitted model

• Number of parameters

Comparison of Results


Female

Male


3. CAUSES OF DEATH

Main Causes of Death in the City of Zurich


Female

Male

Age

Age

All others External causes (accidents, murder); without drugs and suicide Suicide

Respiratory system Dementia Cancer

Circulatory diseases and diseases of the heart

Temporal Trends


Dea

ths

per 1

000

inha

bita

nts

45-to-64 years 65-to-84 years 85 years and above

Female Male

Circulatory diseases

Cancer

Cancer Types


Females Males

Digestive system Lungs, larynx, trachea Genitals (prostate, breast)

Urinary system

Lymph system

Other types

Aids


Female Male

Deaths

Suicides


Females Males

Poison

Falls

Poison

Firearms

Strangulation

(31 cases)

(78 cases)

(67 cases) Strangulation

(164 cases)

(236 cases)

(240 cases)


4. OTHER EFFECTS ON MORTALITY not implemented in mortality model

Marital Status and Mortality


Mor

talit

y ra

te (p

er 1

000)

Females Males Divorced Unmarried Married Widowed

Age

Mortality and Taxed Income / Property


Mor

talit

y ra

te (p

er 1

000)

Females (married) Males (married)

Age

Property in 1000 CHF

Mortality Rate: Sex and Nationality


female

male

Swiss German, Austrian European (other)

Other

Age

Log(

mor

talit

y ra

te)

Seasonal Effect and Age


Deaths per Month (2003-2012)

Meteorology, People aged 80+


Monthly mean Temp (°C) deat

hs p

er 1

000

inha

bita

nts

Multiple linear regression Winter min Temp + windchill Summer Temp span + humidity

R2 ~ 30%

Summary


Modelling: − Lee-Carter and APC models seem feasible. − Performance comparable to simple linear trend. Mortality: Life expectancy increases. − Current median age at death 86 years (f) and 81

years (m). − Decreasing trends in mortality for circulatory diseases

and cancer. Causes of Death: − Interpretation of causes difficult (data quality,

multimortality,...). − What will affect future mortality?

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References


1) «Sterben in Zürich» 2) «Bevölkerungsszenarien Stadt Zürich» 3) Statistical Models

http://www.stadt-zuerich.ch/statistik

http://www.stadt-zuerich.ch/statistik�


THANK YOU FOR YOUR ATTENTION

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