Measuring Burden of Disease - an essential foundation to improve health Prof Debbie Bradshaw Dr Pam...

Measuring Burden of Disease - an essential foundation to improve health

Prof Debbie BradshawDr Pam GroenewaldMRC Burden of Disease

Research Unit

David BourneUCT Department of Public

Health and Family Medicine

Burden of Disease Methodology Global and national

What do we know about the burden of disease in the Western Cape? Estimates from the National Burden of Disease

Study for 2000 Trends in mortality using data from Statistics

South Africa and Home Affairs

Getting the basics right Local level mortality surveillance in Cape Town

and Boland/Overberg

Outline of presentation

Developed for the 1990 Global Burden of Disease Study by WHO and Harvard to confront data deficiencies in measuring population health to guide investment in health

Estimates levels of mortality and underlying causes of death – from multiple sources of information and derived consistent and coherent estimates using demographic techniques and statistical analysis

• Measures the fatal and non-fatal outcomes using Disability Adjusted Life Years (DALYS)

Burden of Disease Methodology

YLL – years of life lostYLD – years lived with disability

DALY = YLL + YLD

Explicit values: - age weights,- discounting, - severity weights,- expected life span

DALYs per 1000 population by region and cause, 2001

Source: Lopez et al, 2006

World Health Report 2002

Developing countries - low mortality

0% 2% 4% 6% 8%

Unsafe w ater, sanitation and hygiene

Iron deficiency

Indoor smoke from solid fuel

Low fruit and vegetable intake

Cholesterol

Overw eight

Underw eight

Tobacco

Blood pressure

Alcohol

Attributable DALYs (% of total 833 million)Source: WHO World Health Report 2002

Burden of disease estimates for South Africa?

• SA National Burden of Disease Study, 2000– Made use of the ASSA2000 model to estimate the

total number of deaths and the number due to AIDS, 1996 cause of death data for the non-AIDS causes, NIMSS injury data

– Mainly focused on mortality and premature mortality– Derived provincial and national estimates

• SA Comparative Risk Assessment, 2000– Revised the burden of disease estimates using

ASSA2002 and estimated DALYs for single causes– Made use of the WHO CRA methods and estimates

applied to South African data on prevalence of 17 selected risk factors

Age-standardised mortality rates by province, 2000

Source: Bradshaw et al, 2005

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Eas

tern

Cap

e

Fre

e S

tate

Gau

teng

Kw

aZul

u-N

atal

Lim

popo

Mpu

mal

anga

Nor

th W

est

Nor

ther

n C

ape

Wes

tern

Cap

e

Sou

th A

fric

a

Dea

ths

per

100

000

HIV/AIDS Other Communicable/mat/peri/nutrition Non-communicable Injuries

Western Cape 2000 (YLLs)

14.1

12.97.9

6.95.9

4.62.7

2.42.3

2.32.12.1

1.8

1.71.5

1.21.1

1.11.01.0

HIV/AIDS Homicide/violence

TuberculosisRoad traffic accidents

Ischaemic heart diseaseStroke

Trachea/bronchi/lung caLower respiratory infections

SuicideDiarrhoeal diseases

Diabetes mellitusCOPD

FiresLow birth weight

SepticaemiaHypertensive heart disease

Breast caNephritis/nephrosis

AsthmaEpilepsy

Source: Bradshaw et al, 2005

South Africa, 2000

Attributable DALYs (% of 16.2 million)

31.5%

8.5%

7.0%

4.0%

2.9%

2.7%

2.6%

2.4%

1.6%

1.4%

1.1%

1.1%

1.1%

0.7%

0.4%

0.4%

0.3%

Unsafe sex/STIs

Interpersonal violence

Alcohol harm

Tobacco

High BMI

Childhood and Maternal underweight

Unsafe water sanitation and hygiene

High blood pressure

Diabetes

High cholesterol

Low fruit and vegetable intake

Physical inactivity

Iron deficiency anaemia

Vitamin A deficiency

Indoor smoke

Lead exposure

Urban air pollution

South Africa, 2000

Source: Norman et al, 2007

Part 2

• Changing pattern of Mortality 2000 -2006

Female deaths 1998 - 2006Females

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

0

1-4

5-9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85-8

9

90-9

4

95+

1998

1999

2000

2001

2002

2003

2004

2005

2006

Source: Laubscher , Bradshaw, Bourne and Dorrington, 2007

Natural causes female deaths 2000-06

Western Cape

Western Cape

0

200

400

600

800

1000

1200

1400

1600

1800

200015-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85-8

9

90-9

4

95+

Age group

Death

s

2000

2001

2002

2003

2004

2005

2006

KwaZulu-Natal

KwaZulu-Natal

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

85-8

9

90-9

4

95+

Age group

Death

s

2000

2001

2002

2003

2004

2005

2006

Source: Laubscher et al, 2007

Population standardised rates (25-49) relative to 2000 National

Males

Females

Males

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2000 2001 2002 2003 2004 2005 2006

Western Cape

Eastern Cape

Northern Cape

Free State

KwaZulu-Natal

North West

Gauteng

Mpumalanga

Limpopo

Females

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2000 2001 2002 2003 2004 2005 2006

Western Cape

Eastern Cape

Northern Cape

Free State

KwaZulu-Natal

North West

Gauteng

Mpumalanga

Limpopo

Source: Laubscher et al, 2007

Mortality under age 5, 1997 to 2002 [unpublished StatsSA special tabulation]

StataSA unpublished data

0

2000

4000

6000

8000

10000

12000

14000

00 04 08 12 16 20 24 28 32 36 40 44 48 52 56 60

age in months

nu

mb

er

of

dea

ths

by

mo

nth

2002

2001

2000

1999

1998

1997

20

04

00

60

08

00

10

00

12

00

2-3

mo

nth

pe

ak

15 20 25AIDS associated (Excluding perinatal) ASSA Antenatal HIV prevalence 1997-2002

AIDS_p Fitted values

Correlation with Antenatal HIV prevalence

AIDS associated/NonAIDS associated diseases

AIDS associated

NonAIDS associated

StataSA unpublished data

-40

-20

020

4060

2-3

mon

th p

eak

15 20 25NonAIDS associated (natural) ASSA Antenatal HIV prevalence 1997-2002

NonAIDSn Fitted values

at age 2 -3 months

Natural Deaths (adjusted) Western Cape Province

0

0.5

1

1.5

2

2.5

3

0 1 2 3 4 5 6 7 8 9 10 11

age in months

1998

1999

20002001

2002

2003

20042005

2005/6

RR

Natural Deaths (adjusted) Mpumalanga

0

5

10

15

20

0 1 2 3 4 5 6 7 8 9 10 11

age in months

1998

1999

2000

2001

2002

2003

2004

2005

2005/6

RR

Doctor

Health Facility

Headman

Mortuary

MagistrateInquest for unnatural

causes

Abridged death

certificateBurial order

Full death certificate

Forms to be checked and

archived

National Home Affairs

Office(Population

Register)

Regional Home Affairs

Office

Electronic records transferred

Forms transferred

Statistics South Africa

Medical Research Council Rapid Mortality surveillance

Cape Town City Boland/Overberg

Copies of forms

UNISA/MRC Non-natural Injury Surveillance System

(NIMSS)

NIMSS collection at sentinel sites

Cause of death

statistics

Part 3

• Local area mortality – getting the basics right

Local level mortality surveillance in Cape Town

• Cape Town has a well established system for compiling death statistics which utilises the national vital registration system administered by Dept of Home Affairs

• Health section of local municipalities obtain copies of death certificates from regional Home Affairs offices

• Information on the manner of death for unnatural deaths is obtained directly from the mortuaries

• Since 2000, trained clerks code the underlying cause of death using a shortlist based upon ICD 10, developed with the MRC, and capture this information

Local level mortality surveillance in

Boland Overberg

• Since 2004, the Boland Overberg region has implemented a similar system

• Initially started at the Worcester and Caledon Home Affairs offices with the assistance of the BCG project

• Since 2006 the Paarl office has also been included

What information does this system provide?

For the first time we have a cause of death profile for the Cape Town metro, BO region and for each health sub-district

– Ranking of leading causes of premature death

– Highlighting inequities in health between sub-districts

– Showing changes in death rates for certain conditions over time

Mortality profile, 2004Boland Overberg, 2004

N = 4230

Inf/para16%

Other Group12%

HIV/AIDS6%

Malignant neoplasms13%

Diabetes mellitus4%

Cardiovascular disease18%

Respiratory disease5%

Cot death0%

Other Group 26%

Unintentional injuries9%

Intentional injuries8%

Injuries undetermined whether intent or unintent

0%

Ill defined natural13%

Cape Town, 2003N = 24068

Inf/para11%

Other Group12%

HIV/AIDS10%


Diabetes mellitus5%



Other Group 27%




1%


Boland Overberg, 2004N = 4230

Inf/para16%

Other Group12%

HIV/AIDS6%


Diabetes mellitus4%



Cot death0%

Other Group 26%




0%


Cape Town, 2003N = 24068

Inf/para11%

Other Group12%

HIV/AIDS10%


Diabetes mellitus5%



Other Group 27%




1%


Leading causes of premature mortality,

Cape Town 2004

Premature mortality rates by cause group and HIV for sub-districts, Cape

Town 2004

2004

0

5000

10000

15000

20000

25000

YL

Ls

per

100

000

III. Injuries 2266 2168 2187 3899 4954 2251 5663 3110 1743 2685 2020

II. Non-communicable diseases 7651 4061 4274 5293 7636 7417 6897 5720 4875 5918 5983

HIV/AIDS 664 1036 1540 2018 5064 973 5571 1913 824 1968 496

Comm excl HIV, mat, peri, nut 1559 1466 1738 3330 5451 1812 4427 2515 1454 2726 1843

Athlone Blaauw Central Helder Khay M Plain Nyanga Oos SPD Tyg Eas Tyg Wes

Age std premature mortality rate (YLL per 100 000) for TB, HIV+TB and HIV by sub-district,

Boland Overberg 2004 - 2005

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

HIV/AIDS excl TB 905.5 560.3 1002.6 657.2 749.1 1221.8 527.1 527.1 784.6 784.6 853.1 853.1 1361.4 1361.4

HIV/AIDS + TB 266.3 360.2 722.8 885.4 283.9 900.3 142.6 142.6 89.4 89.4 223.5 223.5 337.8 337.8

Tuberculosis 1767.1 1389.6 2104.4 2197.2 2137.6 2648.9 694.0 694.0 1140.0 1140.0 298.8 298.8 1534.0 1534.0

2004.0 2005.0 2004.0 2005.0 2004.0 2005.0 2004.0 2005.0 2004.0 2005.0 2004.0 2005.0 2004.0 2005.0

Breede River Breede Valley Witzenberg Cape Agulhas Swellendam Overstrand Theewaterskloof

Trends in age-specific HIV/AIDS rates, Cape Town

2001 - 2004

Age specific HIV death rates in males, Cape Town

0

50

100

150

200

0-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+

2001 2002 2003 2004

Age specific HIV death rates in females, Cape Town

0.0

50.0

100.0

150.0

200.0

250.0

0-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75+

2001 2002 2003 2004

Trends in age-specific homicide rates, Cape Town

2001 - 2004

Males

0

50

100

150

200

250

300

350

Dea

ths

per

100

000

2001 8 10 264 279 186 103 54 19 56

2002 7 7 311 270 173 95 75 41 91

2003 4 7 256 206 132 95 49 41 29

2004 3 5 196 176 115 79 38 16 46

0-4 5 to 14 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 65 to 74 75+

Age standardised homicide death rates (ave) by sub-district, Cape Town 2001 – 2004

Homicide

31

1520

14

59

32

71

20 17 16 21

21

20

22

55

69

24

62

51

1729 23

0

20

40

60

80

100

120

140

Athlone Blaauw Central Helder Khay M Plain Nyanga Oos SPD Tyg East Tyg Wes

Dea

ths

per

100

000

Homicide with firearm Homicide without firearm

Causes of mortality in infants 1 – 11 months, Boland Overberg 2004

Boland Overberg: 1 - 11 monthsN = 368

19.6

16.0

14.7

11.1

9.0

5.4

4.9

3.0

3.0

2.4

1.9

1.1

1.1

0.8

0.5

0.5

0 5 10 15 20 25

Diarrhoeal Diseases

Ill defined natural

Lower Respiratory infections

HIV/AIDS

Other unintentional injuries specified

Cot death/Sudden infant death syndrome

Short gestation and Low birth weight

Protein-energy malnutrition

Congenital abnormalities

Septicaemia

Bacterial Meningitis and meningococcaemia

RDS

Other respiratory

Road traffic

Other Infectious and parasitic diseases

Neonatal infections

Percent

Conclusions• Cape Town and the BOR are facing a quadruple burden of

disease: – pre-transitional diseases and poverty related conditions– emerging chronic diseases– an extremely high burden of injuries – HIV/AIDS epidemic.

• Efforts are being made to combat some of the top causes of death but these need to be expanded and strengthened– PMTCT and ARV rollout appears to have slowed down

mortality due to HIV/AIDS. – Multisectoral strategies are required to address the burden of

injuries. It is not clear what role the SAPS POSS strategy played in decrease in homicide in Cape Town; needs further investigation.

– Multisectoral approaches are needed to address the burden of other conditions: TB – housing, food security; diarrhoea – water and sanitation; NCDs – transport, safety, education etc.

• Inequities in health remain a challenge not just for poverty related conditions and injuries but also for non communicable diseases.

Institutionalising local level mortality surveillance

Developing the system – Extending to automated ICD-10 coding– Electronic mortuary surveillance– Tools for quality control– Tools for analysis– Training for death certification

Roll out surveillance to other regions in the province

Acknowledgements

• City of Cape Town • Boland Overberg• Dept Home Affairs• BCG project• Mortuaries• CARe, UCT• MRC BOD and Biostatistics Units

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