Transcript European Conference of Public Health Observatories Parallel Workshop Diabetes Workshop: Modelling Diabetes Prevalence 8th July 2004 Professor Brian Ferguson – Director, YHPHO Dr Nita Forouhi –

European Conference of Public Health Observatories
Parallel Workshop
Diabetes Workshop:
Modelling Diabetes Prevalence
8th July 2004
Professor Brian Ferguson – Director, YHPHO
Dr Nita Forouhi – Specialist Registrar in Public Health Medicine, Brent PCT
Mr David Merrick – Public Health Information Specialist, YHPHO
Aims of the Session
• Provide latest data on diabetes prevalence and
forecasts
• Outline the various data sources and models used
for estimating diabetes prevalence
• Introduce the PBS diabetes population prevalence
model
• Provide opportunity for discussion about the
model
Session Plan
• Introduction
• Estimating the burden of diabetes
• Modelling diabetes
• The PBS Model
• Q&A Session
• Next steps
Diabetes – YHPHO lead role
• Local reference group
• Development of PBS diabetes population
prevalence model
• National Diabetes Support Team
• DH Public Health Division
• Phase II of the prevalence model
• Economics of diabetes
• Further work on modelling impact of obesity
Diabetes – YHPHO lead role
• Local reference group
• Development of PBS diabetes population
prevalence model
• National Diabetes Support Team
• DH Public Health Division
• Phase II of the prevalence model
• Economics of diabetes
• Further work on modelling impact of obesity
Diabetes reference group
“A source of informal advice and a ‘sounding board’ for
YHPHO in developing its diabetes lead role”
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•
•
Diabetes UK
local GP
local hospital diabetologist
SHA lead
PCT DPH
academic input
UK Context
• National Service Framework
• New GMS contract
– Report and verify patients with diabetes
– Compare expected prevalence with reported/recorded
prevalence
• 2001 Census
• National Diabetes Support Team
Diabetes – A global epidemic
• Estimated worldwide prevalence – 2.8% in 2000
• Increasing to 4.4% by 2030
• Total number of people with diabetes increasing from 171
million to 366 million
• Greatest burden in developing world
• Increasing population aged >65 years
‘“Diabetes epidemic” will continue even if levels of obesity
remain constant – i.e. underestimate’
(Source: Wild et al, 2004)
Trends in obesity
• Proxied by BMI
• International Obesity Task Force
– expect c.14,000 children to be currently diagnosed with Type 2
diabetes in the UK
– >20,000 children with glucose intolerance
– largely a ‘hidden problem’
• Trend in both UK and USA is linear
• Estimated cost of obesity in England in 1998 was
£2.6bn (both direct & indirect costs)
• Medical expenses attributed to overweight and
obesity accounted for 9.1% of total medical
expenditures in the USA in 1998
Impact of diabetes
• reduced life expectancy (e.g. up to 10 years in
people with Type 2)
• mortality rates from CHD up to five times higher
• leading cause of renal failure
• leading cause of blindness in people of working
age
• additional risks in pregnancy
Cost implications
• Significant personal costs: direct plus lost earnings
• Around 5% of total NHS resources are used for the care of
people with diabetes
• People with diabetes are twice as likely to be admitted to
hospital (and likely to have LOS twice the average)
• 1 in 20 people with diabetes incurs social services costs
(average annual cost in 1999 was £2,450)
• Estimates of health care costs of complications:
– e.g. amputation £8,459 (95% CI £5,295-£13,200)
– non-fatal MI £4,070 (95% CI £3,580-£4,722)
– blindness in one eye £872 (95% CI £526-£1,299)
[Clarke et al. (2003); results from UK Prospective Diabetes
Study]
Key Questions
• What is the total population prevalence of
diabetes in the UK?
• How complete are diabetes registers in primary
care?
• How does diabetes prevalence vary across the
UK?
• How will local prevalence patterns change in the
future?
European Conference of Public Health Observatories
Parallel Workshop
Estimating the burden of
diabetes
Dr Nita Forouhi
Specialist Registrar in Public Health Medicine, Brent PCT
Goals – general overview
• Understanding diabetes
• Epidemiology of diabetes
• Estimating the burden of diabetes
• The PBS Model
• Uses of the model
Diabetes – the condition
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•
•
•
What is it?
How is it caused?
Who gets it?
Risk factors
What is diabetes?
• A condition in which the amount of glucose
(sugar) in the blood is too high because the body
cannot use it properly
• This happens because the body does not produce
or properly use insulin, which is needed to convert
sugar and starchy foods from the diet into energy
needed for daily life
Types of diabetes
•
Type 1 (5-10%) – sudden
onset absolute deficiency in
insulin. Usually affects
younger age group (not
always)
•
Type 2 (90 - 95%) – gradual
onset of relative insulin
insensitivity. Usually older age
group (not always)
•
Pre-diabetes – T2DM
Impaired glucose tolerance
May remain undiagnosed for years;
risk of complications same as for
T2DM
Diagnosis of diabetes
Symptoms
• Thirst
• Passing lots of urine
• Malaise
• Infections (thrush)
• Weight loss
BUT – many years of pre-diabetes
(type 2) before these symptoms
appear!
Biochemical tests
•
•
•
Random plasma glucose
Fasting plasma glucose
Oral glucose tolerance test – 2h
glucose
WHO criteria
ADA criteria
Why is diabetes so important?
The burden to patients, carers, NHS
– Complications
•
•
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•
Cardiovascular
Eyes
Renal - Hypertension, renal failure
Feet
Skin, infections, sexual, psycho-sexual, depression
Quality of life
Premature mortality
– Cost
DIABETES NSF
Diabetic complications
Epidemiology of diabetes
• Prevalence worldwide is increasing*
• 2.8% in 2000; 4.4% in 2030 worldwide
• 171 million in 2000; 366 million in 2030
• Greatest rise in developing world
• Prevalence in England
• 1.4 million people, HSE ’98/99
• 2-3% of England population
• “Missing million” campaign
• Prevalence in your area? PCT/LA
*Wild S et al; Diabetes Care, May 2004. Vol 24, pg 1047-53
Epidemiology of diabetes – Risk
factors
• Increasing age
• Ethnic origin
• Obesity
Physical (in)activity
Diet (calorie intake)
• Family history
• Social deprivation
• Maternal/foetal factors
GENES OR ENVIRONMENT?
Why do we need to know diabetes
prevalence?
Diabetes NSF
• Standards – Dec 01
• Delivery Strategy – Jan 03
• Service provision, monitor outcomes, identify individuals at
high risk of diabetes
• Establish diabetes registers
• Offer retinal screening to 100% of diabetic population by
year 2007 (80% by 2006)
New GMS contract
•
•
Report and verify patients with diabetes
Compare expected prevalence with reported/recorded prevalence
Do we know our diabetes prevalence?
ENGLAND
Prevalence by age/sex/ethnicity
Prevalence (%) of self-reported diabetes
Health survey for England 1999
Prevalence rate (%)
HSE-Diabetes prevalence: Men
HSE- Diabetes prevalence: Women
50
White
40
Black-C
30
Indian
20
Pakistani
Bangladesh
10
Chinese
0
16-34
35-54
Age group
55+
16-34
35-54
Age group
55+
Do we know our diabetes
prevalence?
What is the prevalence
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•
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•
•
In a health sector (StHA level)?
In a PCT?
In a ward?
In a practice?
In a geographic area – eg London?
Estimating prevalence - Where do we
start?
Sources of information on prevalence in a
PCT – e.g. Brent
• Primary care register 
• Chronic disease management payment 
• Hospital attendance, other clinics, retinal screening
database 
• Ask each practice 
• Audit 
• Capture-recapture 
Epidemiological prevalence
modelling - principles
•National surveys/databases
– Known diabetes
eg: HSE’99, GPRD (Key health statistics), MSGP-4, Oxford & Poole, DARTS, others
•Research studies
– known and undiagnosed disease
Apply reference prevalence rates by age, sex, ethnic
group to local population (by age, sex, ethnic group)
Diabetes Models in England
• Trent Model
– Total & diagnosed/undiagnosed population prevalence
– Dr Elizabeth Goyder, ScHARR; linked with NSF
• Brent Model
– Total & diagnosed/undiagnosed population prevalence
– Dr Nita Forouhi, Brent PCT; used in London + other places
• NCASP Model
– Statistical model derived using data from practice-based diabetic
registers (with registered diagnosed cases); variables regressed: age,
sex, ethnicity if over 35yr, area deprivation score, “register”
– NCASP/QUIDS team ; http://www.nhsia.nhs.uk/ncasp
• e-diabetes Model
– Internet-based "tool" for PCTs to evaluate local diabetes services; uses
an earlier version of the NCASP model (the QUIDS model)
The PBS Model
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Aims
Development of the Model
Assumptions in the Model
Potential uses
The PBS Model
Aims - The PBS approach
• To provide population estimates of total diabetes diagnosed and as-yet undiagnosed diabetes, to support
NSF
• Provide estimates for
–
–
–
–
–
England
GOR
StHA
PCT
LA
• Provide user-defined option at ward/practice/other level
The PBS Model
Development of the model
• Review the literature on total prevalence; choose
most appropriate epidemiological studies
• Build on Trent/Brent Models
• Use epidemiological, public health, statistical and
analytical skills to develop the model
Prevalence of diabetes
U.K. Research studies (known+new DM) - OGTT
Setting
Age
Prevalence % (Age standardised)
European
S. Asian
Af/Caribbean
Coventry ’91
20+
3.2 – 4.7
11.2 – 12.4
-
Southall ’91
40 – 69
2.3 – 4.8
16.1 – 19.9
14.6
Brent ’93
40 – 64
4.0 – 6.5
-
12.9 – 17.7
Wandsworth ‘97
40 – 59
5–7
20 – 25
15 – 18
Newcastle ‘98
25 – 74
7.1
21.4
-
Manchester ‘01
35 – 79
8.1 – 22.7
15.7 – 48.1
15.7 – 29.5
Ethnic differentials in diabetes
Prevalence of known+new diabetes
Coventry
Study 1991
Age
Prevalence
Men
Prevalence
Women
European
S.Asian
European
S.Asian
25 - 34
0.5%
2.5%
0.5%
1.5%
35 - 44
3.5%
12.5%
6.0%
9.5%
60 - 79
6.5%
25.5%
8.0%
20.0%
The PBS Model – Step “A”
To a given resident population (ONS census 2001), apply the following rates:
Age/sex/ethnicity specific
Age/sex/ethnicity specific
prevalence rates for T2DM
prevalence rates for T2DM
from Coventry Study
from Brent Study (European
(European White and South
White and Black African-
Asian men & women)
Caribbean men & women)
Derive a ratio for excess risk in Black
A/C compared to European White
population
Apply this ratio to the age/sex specific
European White population of Coventry
study
Age/sex specific prevalence rates for type 1 diabetes (capturerecapture technique, nearly 0.5 million men & women in Wales)
PBS Model – Reference rates for Step “A”
T2DM rate (%)-Men
Age
White
0-4
0
5- 9
0
10-14
0
15-19
0
20-24
0
25-29
0
30-39
0
40-49
2.5
50-59
3.6
60-69
8.6
70-79
9.4
80+
7.3
S.Asian Other
0
0
0
0
0
0
0
0
0.9
0
0.9
0
4
0
11.2
2.5
18.5
3.6
24.6
8.6
34.3
9.4
35
7.3
Black
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.1
6.9
18.0
19.7
15.3
T2DM rate (%)-Women
White
S.Asian Other
0
0
0
0
0
0
0
0
0
0
0
0
0.3
0.7
0.3
0.3
0.7
0.3
0
3
0
2.9
7
2.9
5.1
18
5.1
10.3
30
10.3
17.4
24
17.4
17.2
19
17.2
Black
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10.7
32.8
22.4
37.9
37.5
T1DM rate (%)
Age
Male
0-4
0.01
5- 9
0.10
10-14
0.31
15-19
0.34
20-24
0.31
25-29
0.49
30-39
0.69
40-49
0.63
50-59
0.48
60-69
0.30
70-79
0.14
80+
0.05
Female
0.04
0.06
0.27
0.43
0.33
0.42
0.48
0.38
0.28
0.14
0.11
0.12
The PBS Model – Step “B”
Adjust the model for “time” and “place”
Time
• Reference studies
>decade old
• Obesity increase in last
decade in England
• Diabetes prevalence
increase in England
Place
Coventry study representative of England?
• Foleshill ward – one of
most deprived wards in
England
• Higher levels of obesity
(?physical inactivity) &
diabetes prevalence, than
England – especially women
Obesity – what is it?
• Body mass index = BMI
• An index derived by the formula [Weight in kg / (height)2 in
metres]
• Not very good for defining fat levels in an individual, but very
good for monitoring trends over time, and across populations –
thus a very important public health statistic
WHO definitions
Normal weight
Overweight
Obese
BMI<25 kg/m2
BMI 25 – 30 kg/m2
BMI >30 kg/m2
Obesity – what is it?
•
Other measures of obesity are percentage body fat and central obesity –
waist circumference or waist/hip ratio
•
Ethnic differences in obesity – BMI cut off points adopted by WHO may not
apply uniformly across different populations
» South Asians have higher central adiposity for a given level of BMI
compared with European Whites
» While cut-off of 30 kg/m2 defines obesity in European groups, a cut-off of
27.5 may be equivalent in South Asians in defining associated risks
•
Despite its limitations, BMI remains the most robust marker of obesity that
is available
Trend in obesity in USA – 1990/2001
Obesity: What is the fuss about?
Crude mortality associated with obesity
Obesity: what is the fuss about?
The PBS Model
Adjusting for obesity trends over “time”
Linear trend in obesity and overweight between
1991 and 2002 – HSE data on BMI over time
•
Use linear regression to estimate BMI in 1986-89 (Coventry study) and
2001
•
Define risk association between BMI category & diabetes prevalence
(NHANES-III study, USA, JAMA 1999, Must A et al)
•
Derive BMI-index by applying increased risk for diabetes by BMI-category.
Ratio between 2001 and ’86-’89 gives “uplift” factor for increased diabetes
prevalence since Coventry Study
The PBS Model
Adjusting for “place” differences between Coventry & all
England
Obtain detailed data on prevalence of
obesity/overweight/normal-weight in Coventry (authors) vs all
England (HSE)
Compare rates of obesity/overwt/normal-wt
Derive an index to calculate an “adjustment” factor for what the
diabetes prevalence would have been in Coventry, if the
distribution of BMI had been similar to England
Model assumptions
Type 2 diabetes
1.White and other ethnic groups, including the Chinese population are assumed to have the same
prevalence as the Coventry “White” population
2.All “Black” ethnic groups , including “Black-other”are assumed to have same rates as the Black
African and Caribbean populations in the Brent study
3.Indians, Pakistanis, Bangladeshis and “other” Asian groups are assumed to have the same rate as
the Coventry “South Asian” population
4.Type 2 prevalence rates have been adjusted for changes in prevalence over time and differences
between Coventry and England assuming changes in prevalence in all ethnic groups are predicted by
the overall population trend in BMI
5.Levels of obesity (using BMI) in all areas are assumed to be the same as England as a whole in
2001
Type 1 diabetes : Prevalence rates are assumed to be the same in all ethnic groups and to not vary
significantly with time or place
Census Population estimates reflect accurately the “true” denominator population – could
under or overestimate
The PBS Model
Potential uses – phase 1
– Estimate total diabetes prevalence (T2DM / T1DM)
– Compare expected prevalence between populations
– Assess relative completeness of primary care diabetes registers
– Assess completeness of case finding (proportion of all cases
diagnosed)
– Compare complication rates or admission rates after adjustment for
variation in expected prevalence
– Compare service provision with population need
– Tackle health inequalities – age/sex/ethnic
– Use for LDP (PCT Local Delivery Plan)
– Planning services
– Commissioning
– Apply to ward level / practice level
– Others
PBS model
PCT perspective - Brent
England
Brent
Total n
2.2 million
14,739
%
4.41%
5.6%
Male
3.61%
5.13%
Female
5.17%
6.03%
<30y
0.33%
0.43%
30-59y
3.37%
5.91%
60+y
13.92%
19.05%
Europ White
4.29%
3.95%
S. Asian
6.63%
8.29%
Black A/C
5.67%
6.45%
Other
2.13%
2.29%
Age
Extensions of the model
Practice (GP) prevalence – support n-GMS
Warnings!
– Model estimates may be different from the actual number of expected
cases, particularly at practice level
– Model estimates less precise as denominator population numbers get
smaller
Reasons why
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Practice ethnicity
Local determinants of prevalence
Random variation
Resident vs registered populations
Proportion of undiagnosed cases/screening practice
Diagnostic criteria
Others!
Practice pilot in NW-London
The Model
Limitations
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Lifestyle (obesity, physical inactivity, smoking)
Social factors (deprivation, SES)
ONS Resident population vs GP registered population
Likely Underestimate
Point estimates only
No future prevalence estimates (incidence/outmigration/deaths)
• Assumptions about Chinese and “other” ethnic groups –
lack of robust data
The Model
Strengths
• Robust – local population structure by age, sex, ethnic subgroups
• Overall prevalence plus breakdown by age groups, sex,
ethnic group
• Shows up “hidden” differences due to confounding variables
• Model can be modified & updated & extended
• Compares well/better(!) with other models
• Quality assurance
Public Health message
•Obesity prevalence is increasing
•Diabetes prevalence is increasing
European Conference of Public Health Observatories
Parallel Workshop
The PBS Diabetes Population
Prevalence model
Mr David Merrick
Public Health Information Specialist, YHPHO
Model Definition
Diabetes Prevalence
(Age, Sex, Ethnic-group strata)
=
Diabetes %
estimate from
literature
England, GORs, SHAs, PCTs, LAs
*
2001 Census
population
Type 1 prevalence rates
Clwyd, Wales 1998 (Harvey et al)
•
Derived from white population of 418,200 - Clwyd, Wales
•
Assumes same age/sex specific rates for all ethnic groups
Type 1 diabetes prevalence
Clwyd, Wales 1998 (Harvey et al)
Male
Female
0.8
0.7
Percentage
0.6
0.5
0.4
0.3
0.2
0.1
0
0-4
5- 9
10-14
15-19
20-24
25-29
30-39
40-49
50-59
60-69
70-79
80+
Type 2 prevalence rates
Coventry 1986-89 (Simmons et al)/Brent 1991 (Chaturvedi et al)
Type 2 diabetes prevalence
Male
Female
40
35
25
20
15
10
5
White/Other
Black
Asian
80+
70-79
60-69
50-59
40-49
30-39
25-29
20-24
80+
70-79
60-69
50-59
40-49
30-39
25-29
20-24
80+
70-79
60-69
50-59
40-49
30-39
25-29
0
20-24
Percentage
30
T2DM % - ‘Time’ and ‘Place’ adjustment
• Adjustment for ‘Time’
Trends in obesity and diabetes from Health Survey for
England suggest that 1986-89 rates may be an
underestimate of Type 2 prevalence in 2001 so we need to
upwardly adjust them.
• Adjustment for ‘Place’
Foleshill was a very deprived ward with higher levels of
obesity than England during the late eighties. Rates of
T2DM from Foleshill may be high and unrepresentative of
England, so we need to adjust them downwards.
How do we estimate change in T2 diabetes
prevalence, 1986-89 vs 2001?
HSE diabetes prevalence data
• Self-reported ‘T1+T2 diagnosed’ not ‘T2 diag+undiag’
• Poor data, only 6 observations, ‘noisy’ series
• Need another method
Diabetes %, England ages 16+ years, Linear extrapolation
7
6
Men
Women
Linear (Men)
Linear (Women)
Percent
5
y = 0.1579x + 0.3019
R2 = 0.7353
4
3
2
y = 0.029x + 1.8676
R2 = 0.0494
1
Source: Health Survey for England
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
0
How do we estimate change in T2 diabetes
prevalence, 1986-89 vs 2001?
• Diabetes Index
Product of relative risk of diabetes and % England
population in BMI groups.
• Relative risk of diabetes by BMI group
3rd National Health & Nutrition Examination Survey
(NHANES III) 1988-94. 16,884 adults aged 25+. JAMA
1999, Must et al
• % England population by BMI group
Health Surveys for England 1991-2002
Relative risk of diabetes by BMI group
•
Must A. ‘The disease burden associated with overweight and obesity’.
JAMA 1999.
3rd National Health & Nutrition Examination Survey (NHANES III) 1988-94.
16,884 adults aged 25+, Ethnic mix 50+% Mex. Hispanic/Black
Relative risk of Type 2 diabetes by WHO BMI category
8
Diabetes relative risk
7
6
5
4
3
2
1
0
<25
25-29
30-34
Men
Soure: JAMA 1999, Must et al
35-39
40+
<25
25-29
30-34
Women
35-39
40+
% England population by BMI group
Continuous smooth time series of BMI from HSE
Reliable (measurements taken by health professional)
BMI distribution in Men aged 16+ years, England
100%
2
2
2
2
2
3
3
3
2
3
4
4
10
10
11
11
13
14
13
14
15
17
17
17
80%
BMI 40+
40
43
BMI 35-39
44
44
60%
44
45
45
46
44
45
BMI 30-34
47
43
BMI 25-29
BMI<25
39
38
37
37
35
32
35
2001
2002
41
2000
42
1999
42
1998
45
1997
48
20%
1996
40%
Source: Health Survey for England - 1991-2002
1995
1994
1993
1992
0%
1991
•
•
T2 DM prevalence rates - ‘Time’ adjustment
Diabetes Index - Linear Extrapolation
Men aged 16+ years, England 1986-2002
300
Diabetes Index
250
200
150
100
y = 4.1077x + 177.54
R2 = 0.9849
50
‘Time’
adjustment
=
Diabetes Index [2001]
Average Diabetes Index [1986, 87, 88, 89]
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
0
T2DM adjustment for ‘Place’
‘Place’ =
adjustment
Diabetes Index [Foleshill - Whites]
Diabetes Index [England 1991 HSE]
T2 DM prevalence rates
‘Time’ & ‘Place adjustment
• ‘Time’ adjustment
Males
129.2%
Females
123.1%
• ‘Place’ adjustment
Males
93%
Females
86.6%
PBS model Type 2 diabetes rates
Adjusted for ‘Time’ & ‘Place’
PBS model Type 2 diabetes prevalence % rates
Male
Female
Age
White/Other
Black
Asian
White/Other
Black
Asian
0-19
0.0
0.0
0.0
0.0
0.0
0.0
20-24
0.0
0.0
1.1
0.3
0.0
0.7
25-29
0.0
0.0
1.1
0.3
0.0
0.7
30-39
0.0
0.0
4.8
0.0
0.0
3.1
40-49
3.0
6.1
13.5
3.1
11.4
7.5
50-59
4.3
8.3
22.2
5.4
35.0
19.0
60-69
10.3
21.6
29.6
11.0
23.9
31.9
70-79
11.3
23.7
41.2
18.6
40.4
25.5
80+
8.8
18.4
42.1
18.3
40.0
20.5
Geographic adjustment for Obesity?
• No direct adjustment for geographic variations in Obesity
• Adjustment for geographic variations in Sex, Age and
Ethnicity
Therefore indirect adjustment for some geographic variation
in obesity
• May underestimate in areas with low ethnicity & high
deprivation/obesity
• Need an adjustment for obesity that is independent of
age/sex/ethnicity, so we don’t over-adjust.
• Phase II enhancement?
Suggestions welcome (e.g. NatCen Synthetic Estimation)
Demonstration
• Downloadable from website www.yhpho.org.uk
with supporting documentation (12 July 2004)
• 2.3Mb unzipped / 0.7Mb zipped
• Developed in Excel (Windows 2000)
• User-friendly front end – navigation buttons
• User guide within the model
Key Findings – What does the model
show?
• PBS model estimates total persons with diabetes,
ie diagnosed + undiagnosed prevalence
England
•
•
•
•
2.1M (almost 1 in 20) people with diabetes
Women 1.3M (5.17%) vs Men 0.86M (3.6%)
<30yrs = 0.33% vs 60+yrs = 13.9%
Asian (6.6%)>Black (5.7%)>White (4.3%)
Key Findings – What does the model
show?
PBS model T1 + T2 diabetes % prevalence rates
Diagnosed + undiagnosed
16
14
10
8
13.9
6
4
2
4.4
3.6
5.2
0.3
4.3
3.4
5.7
6.6
2.1
Other
Asian
Black
White
60+ yrs
30-59 yrs
0-29 yrs
Female
Male
0
Persons
Percentage (%)
12
Key Findings – What does the model
show? – Regional level
PBS model T1 + T2 diabetes % prevalence rates
Diagnosed + undiagnosed
4.70
4.50
4.65
4.40
South East
4.37
4.37
East
4.33
4.36
London
4.33
4.36
North East
4.30
Yorkshire
& Humber
4.55
North West
4.43
South
West
West
Midlands
4.20
East
Midlands
Percentage (%)
4.60
Key Findings – What does the model
show? – Regional level
• South West highest
Oldest population (24% aged 60+ yrs)
• West Midlands second highest
High (9.3%) Black/Asian population
• London average
Highest (23%) Black/Asian population but
Youngest population (16.4% 60+yrs)
Key Findings
Top 10 Local authorities
Local Authority
Christchurch
Rother
West Somerset
East Devon
Tendring
North Norfolk
Arun
Harrow
East Dorset
Brent
T1+T2
diabetes
prevalence
6.2
6.1
5.9
5.9
5.7
5.7
5.7
5.7
5.7
5.6
% aged 60+
years
%
Black/Asian
36.0
34.9
33.4
33.3
32.5
32.1
31.8
19.0
31.6
15.7
0.4
0.6
0.3
0.2
0.5
0.3
0.7
35.8
0.3
47.6
• LAs that have high rates because of their high % B/A,
also have more established elderly B/A populations
Key Findings – What does the model
show? – Local authorities
•Strength
association %
elderly vs diabetes
PBS model T1+T2 diabetes % vs % population aged 60+
Local authority areas of England
6.5
6.0
•Outlier from
association have
high % black/asian
Percentage (%)
5.5
5.0
4.5
Black/Asian % > 90th percentile
4.0
Black/Asian% < 90th percentile
3.5
3.0
10
15
20
25
30
% population aged 60+ years
35
40
European Conference of Public Health Observatories
Parallel Workshop
Discussion
European Conference of Public Health Observatories
Parallel Workshop
Next Steps
Professor Brian Ferguson
Director, YHPHO
Dissemination/release schedule
• Model Launch – 12/07/04
• Phase 2 – Autumn 2004
– Further methodological developments?
– Projected diabetes prevalence
• PBS Paper/Report – findings/methodology –
Autumn 2004
Extensions of the model
Next steps
– Project prevalence over next 10-20 years
• Include obesity trends in model
– Model in social deprivation/lifestyle factors
– Apply at ward level systematically
– Age standardised prevalence rates
– Spatial maps
– “sky is the limit” but it is a model!
Summary
•
•
Estimating population prevalence – diagnosed PLUS
undiagnosed diabetes
PBS model adjusted for local age/ethnicity and
gender
Also includes obesity – (at national level)
•
•
Female overall prevalence higher than male
Age key factor affecting overall prevalence
•
PBS Phase 2 to model projected changes in diabetes
prevalence
•
Contact Details
Yorkshire and Humber Public Health Observatory
01904 724588
http://www.yhpho.org.uk
[email protected]