Transcript Measuring Burden of disease

Measuring Burden of Disease
- an essential foundation to
improve health
Prof Debbie Bradshaw
Dr Pam Groenewald
MRC Burden of Disease Research
Unit
David Bourne
UCT Department of Public Health
and Family Medicine
Outline of presentation

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
Burden of Disease Methodology

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)
YLL – years of life lost
YLD – 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
Alcohol
Blood pressure
Tobacco
Underw eight
Overw eight
Cholesterol
Low fruit and vegetable intake
Indoor smoke from solid fuel
Iron deficiency
Unsafe w ater, sanitation and hygiene
0%
2%
4%
6%
Attributable DALYs (% of total 833 million)
Source: WHO World Health Report 2002
8%
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
2000
1800
Deaths per 100 000
1600
1400
1200
1000
800
600
400
HIV/AIDS
Other Communicable/mat/peri/nutrition
Source: Bradshaw et al, 2005
Non-communicable
Injuries
South Africa
Western Cape
Northern Cape
North West
Mpumalanga
Limpopo
KwaZulu-Natal
Gauteng
Free State
0
Eastern Cape
200
Western Cape 2000 (YLLs)
HIV/AIDS
Homicide/violence
Tuberculosis
Road traffic accidents
Ischaemic heart disease
Stroke
Trachea/bronchi/lung ca
Lower respiratory infections
Suicide
Diarrhoeal diseases
Diabetes mellitus
COPD
Fires
Low birth weight
Septicaemia
Hypertensive heart disease
Breast ca
Nephritis/nephrosis
Asthma
Epilepsy
14.1
12.9
7.9
6.9
5.9
4.6
2.7
2.4
2.3
2.3
2.1
2.1
1.8
1.7
1.5
1.2
1.1
1.1
1.0
1.0
Source: Bradshaw et al, 2005
South Africa, 2000
South Africa, 2000
31.5%
Unsafe sex/STIs
8.5%
Interpersonal violence
7.0%
Alcohol harm
4.0%
Tobacco
High BMI
2.9%
Childhood and Maternal underweight
2.7%
Unsafe water sanitation and hygiene
2.6%
High blood pressure
2.4%
Diabetes
1.6%
High cholesterol
1.4%
Low fruit and vegetable intake
1.1%
Physical inactivity
1.1%
Iron deficiency anaemia
1.1%
Vitamin A deficiency
0.7%
Indoor smoke
0.4%
Lead exposure
0.4%
Urban air pollution
0.3%
Attributable DALYs (% of 16.2 million)
Source: Norman et al, 2007
Part 2
• Changing pattern of Mortality 2000 -2006
Female deaths 1998 - 2006
Females
35,000
30,000
1998
25,000
1999
2000
20,000
2001
2002
15,000
2003
2004
2005
10,000
2006
5,000
Source: Laubscher , Bradshaw, Bourne and Dorrington, 2007
95+
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
1-4
0
0
Natural causes female deaths 2000-06
KwaZulu-Natal
8000
7000
Deaths
KwaZuluNatal
9000
2000
6000
2001
5000
2002
2003
4000
2004
2005
3000
2006
2000
1000
95+
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
0
Age group
Western Cape
Western
Cape
2000
1800
1600
2000
1400
2001
Deaths
1200
2002
1000
2003
800
2004
2005
600
2006
400
200
Age group
95+
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
Source: Laubscher et al, 2007
15-19
0
Population standardised rates (25-49)
relative to 2000 National
Males
Males
3.0
2.5
Western Cape
Eastern Cape
2.0
Northern Cape
Free State
KwaZulu-Natal
1.5
North West
Gauteng
1.0
Mpumalanga
Limpopo
0.5
0.0
2000
2001
2002
2003
2004
2005
2006
Females
Females
3.0
2.5
Western Cape
Eastern Cape
2.0
Northern Cape
Free State
KwaZulu-Natal
1.5
North West
Gauteng
1.0
Mpumalanga
Limpopo
0.5
0.0
2000
Source: Laubscher et al, 2007
2001
2002
2003
2004
2005
2006
Mortality under age 5, 1997 to 2002
[unpublished StatsSA special tabulation]
number of deaths by month
14000
2002
2001
12000
2000
1999
10000
1998
1997
8000
6000
4000
2000
age in months
StataSA unpublished data
60
56
52
48
44
40
36
32
28
24
20
16
12
08
04
00
0
Correlation with Antenatal HIV prevalence
1000
800
200
400
AIDS associated
600
2-3 month peak
at age 2 -3 months
1200
AIDS associated/NonAIDS associated diseases
15
20
25
AIDS associated (Excluding perinatal) ASSA Antenatal HIV prevalence 1997-2002
Fitted values
-40
NonAIDS associated
2-3 month peak
-20
0
20
40
60
AIDS_p
15
20
25
NonAIDS associated (natural) ASSA Antenatal HIV prevalence 1997-2002
StataSA unpublished data
NonAIDSn
Fitted values
1998
1999
2000
2001
2002
2003
2004
2005
2005/6
Natural Deaths (adjusted) Western Cape Province
RR
3
2.5
2
1.5
1
0.5
0
0
1
2
3
4
5
6
age in months
7
8
9
10
11
Natural De aths (adjuste d) M pumalanga
RR
20
1998
15
1999
2000
10
2001
2002
5
2003
2004
0
0
1
2
3
4
5
6
age in m onths
7
8
9
10
11
2005
2005/
6
Cape Town City
Boland/Overberg
Medical Research Council
Rapid Mortality surveillance
Electronic records
transferred
Copies of forms
Health
Facility
Regional
Home Affairs
Office
Forms to be
checked and
archived
Doctor
Headman
Burial order
Mortuary
NIMSS collection
at sentinel sites
Inquest for
unnatural
causes
Abridged
death
certificate
UNISA/MRC Non-natural
Injury Surveillance System
(NIMSS)
Magistrate
National
Home Affairs
Office
(Population
Register)
Statistics
South Africa
Forms
transferred
Full death
certificate
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 subdistricts
– Showing changes in death rates for certain
conditions over time
Mortality profile, 2004
Boland Overberg, 2004
N = 4230
Cape Town, 2003
N = 24068
Ill defined natural
7%
Ill defined natural
13%
Injuries undetermined whether
intent or unintent
0%
Injuries undetermined whether
intent or unintent
1%
Inf/para
16%
Other Group1
2%
Intentional injuries
8%
HIV/AIDS
6%
Unintentional injuries
9%
Unintentional injuries
6%
Other Group1
2%
HIV/AIDS
10%
Other Group 2
7%
Malignant neoplasms
13%
Other Group 2
6%
Malignant neoplasms
15%
Respiratory disease
5%
Cot death
0%
Respiratory disease
5%
Intentional injuries
9%
Inf/para
11%
Diabetes mellitus
4%
Cardiovascular disease
18%
Cardiovascular disease
22%
Diabetes mellitus
5%
Leading causes of premature mortality,
Cape Town 2004
Premature mortality rates by cause group
and HIV for sub-districts, Cape Town 2004
2004
25000
YLLs per 100 000
20000
15000
10000
5000
0
Athlone
Blaauw
Central
Helder
Khay
M Plain
Nyanga
Oos
SPD
Tyg Eas
Tyg Wes
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
Age std premature mortality rate (YLL per 100 000)
for TB, HIV+TB and HIV by sub-district,
Boland Overberg 2004 - 2005
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
2004.0
2005.0
Breede River
HIV/AIDS excl TB
905.5
560.3
2004.0
2005.0
Breede Valley
1002.6
657.2
2004.0
2005.0
Witzenberg
749.1
2004.0
2005.0
Cape Agulhas
1221.8
527.1
527.1
2004.0
2005.0
Swellendam
784.6
2004.0
2005.0
Overstrand
784.6
853.1
853.1
2004.0
2005.0
Theewaterskloof
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
Trends in age-specific HIV/AIDS
rates, Cape Town 2001 - 2004
Age specific HIV death rates in males, Cape Town
Age specific HIV death rates in females, Cape
Town
200
250.0
150
200.0
150.0
100
100.0
50
50.0
0
0.0
0-4
5-14
15-24
2001
25-34
35-44
2002
45-54
2003
55-64
2004
65-74
75+
0-4
5-14
15-24
2001
25-34
35-44
2002
45-54
2003
55-64
2004
65-74
75+
Trends in age-specific homicide
rates, Cape Town 2001 - 2004
Males
350
300
Deaths per 100 000
250
200
150
100
50
0
0-4
5 to 14
15 to 24
25 to 34
35 to 44
45 to 54
55 to 64
65 to 74
75+
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
Age standardised homicide death rates (ave) by subdistrict, Cape Town 2001 – 2004
Homicide
140
120
62
100
Deaths per 100 000
69
80
60
40
21
51
24
55
71
22
29
59
17
20
20
23
32
31
15
20
14
20
17
Oos
SPD
16
21
0
Athlone
Blaauw
Central
Helder
Khay
Homicide with firearm
M Plain
Nyanga
Homicide without firearm
Tyg East Tyg Wes
Causes of mortality in infants 1 – 11 months,
Boland Overberg 2004
Boland Overberg: 1 - 11 months
N = 368
Diarrhoeal Diseases
19.6
Ill defined natural
16.0
Lower Respiratory infections
14.7
HIV/AIDS
11.1
Other unintentional injuries specified
9.0
Cot death/Sudden infant death syndrome
5.4
Short gestation and Low birth weight
4.9
Protein-energy malnutrition
3.0
Congenital abnormalities
3.0
Septicaemia
2.4
Bacterial Meningitis and meningococcaemia
1.9
RDS
1.1
Other respiratory
1.1
Road traffic
0.8
Other Infectious and parasitic diseases
0.5
Neonatal infections
0.5
0
5
10
15
Percent
20
25
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
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•
•
•
•
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City of Cape Town
Boland Overberg
Dept Home Affairs
BCG project
Mortuaries
CARe, UCT
MRC BOD and Biostatistics Units