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Estimating Prevalence of Diabetesand Other Chronic Diseases for Small Geographic Areas
Peter Congdon, Geography, QMUL
Major chronic diseases are leading source of morbidity and health service costs in developed societies with ageing populations
Age Effect compounded by high diabetes rate among relatively young immigrant/ethnic group populations (e.g. South Asian community in England)
Diabetes also increasing in developing societies (e.g. China)
Trends
Prevalence Trends have to be distinguished from Trends in Mortality (e.g. Important for CHD)
Diabetes relatively small as direct cause of death but important as risk factor for CHD, stroke, etc
Trends in Diabetes Prevalence: US Data shows upward trend and this also applies for England
HSE 1993 to 2003 (ages 16+) Males 3% 4.3% Females 2% 3.4%
Risk Factors for DiabetesDiabetes type 2 (adult onset) incidence varies
considerably by age, ethnic group and income group
Diabetes linked to socio-economic deprivation: diabetic patients with lower education level less likely to follow advice on lifestyle/medicines; less likely to attend their GP for a review of their condition.
HSE also shows higher prevalence for males
HSE 2004 Diabetes Rates by Ethnic Group & Age
Indirect Area Estimates Can model gradients over these demographic categories
using Health Survey for England; use logit regression to develop prevalence rate profile by age, ethnicity, and gender.
Apply prevalence rate profile to census populations disaggregated according to these categories
Census table ST101 cross-tabulates age, ethnicity and gender down to electoral ward level (approx. 8000 wards in England)
Deprivation gradient also applied. Gradient in prevalence over IMD quintiles, as ratio to average prevalence, is (0.76, 0.84, 0.91, 1.13, 1.37) for males, (0.80, 0.84, 0.93, 1.07, 1.36) for females.
Relevance of Quality Outcomes Framework (QOF Registers)
QOF Registers also supply estimates of prevalence but geographic profile limited (PCTs only, not local authorities or electoral wards - at least in terms of publicly available data)
Also subject to registration biases-work in Jrnl of Public Health (Sigfrid et al, Vol 28(3)) shows exception reporting increased for deprived practices - means prevalence gradient by deprivation flatter than should be
Compare Prevalence to Adverse Events
Thous. %Lower Limb Amputations
Ketoacidosis & Coma
Amput-ations
DKA & Coma
England 1529 3.1 3.4 27.5 13.5 9.1Highest % Prevalence Birmingham 91 4.0 2.8 32.4 7.9 8.5North East London 59 4.0 4.5 28.4 10.8 7.3North West London 60 3.4 2.0 24.0 5.9 6.9West Yorkshire 71 3.4 2.3 25.3 8.1 7.5Lowest % Prevalence Avon Gloucs Wilts 59 2.7 3.5 26.1 16.9 9.9Hampshire & IOW 48 2.7 4.8 26.2 21.4 10.0Beds & Herts 42 2.6 3.2 24.4 14.1 9.4Thames Valley 52 2.4 2.6 24.3 11.1 10.0* 2000-1 & 2001-2 (Two years)
Comparison of Adverse Outcomes to Prevalence
England and StHAs
Adverse Hospital Outcomes*
Age Standardised rates per 100,000 popn
Rates per 1000 Prevalent Popn
Prevalence (Persons, 1 &
2)
0
2
4
6
8
10
12
14
En
glan
d
Avo
n G
lou
cestershire &
Wiltsh
ire
Bed
ford
shire &
Hertfo
rdsh
ire
Birm
ing
ham
& B
lack Co
un
try
Ch
eshire &
Merseysid
e
Co
un
ty Du
rham
& T
ees Valley
Cu
mb
ria & L
ancash
ire
Do
rset & S
om
erset
Essex
Greater M
anch
ester
Ham
psh
ire & Isle O
f Wig
ht
Ken
t & M
edw
ay
Leicestersh
ire, No
rthan
ts & R
utlan
d
No
rfolk S
uffo
lk & C
amb
ridg
eshire
No
rth &
East Y
orksh
ire & N
. Lin
cs
No
rth C
entral L
on
do
n
No
rth E
ast Lo
nd
on
No
rth W
est Lo
nd
on
No
rthu
mb
erland
Tyn
e & W
ear
Sh
rop
shire &
Staffo
rdsh
ire
So
uth
East L
on
do
n
So
uth
West L
on
do
n
So
uth
West P
enin
sula
So
uth
Yo
rkshire
Su
rrey & S
ussex
Th
ames V
alley
Tren
t
West M
idlan
ds S
ou
th
West Y
orksh
ire
Prevalence % (Persons)
Diabetic Coma Rate per1000 Prevalent Cases
Highest & Lowest Ward Level% Prevalence
Ward Name LA P M FLatimer Leicester UA 7.4 8.2 6.6Spitalfields and Banglatown Tower Hamlets LB 7.3 8.6 5.9Sutton on Sea North East Lindsey CD 7.1 7.8 6.4Handsworth Birmingham MCD 6.9 7.3 6.5Sparkbrook Birmingham MCD 6.9 7.5 6.2Southall Broadway Ealing LB 6.7 7.3 6.1Small Heath Birmingham MCD 6.7 7.5 6.0Blakenhall Wolverhampton MCD 6.7 7.2 6.1West Bromwich Central Sandwell MCD 6.6 7.2 6.0Sparkhill Birmingham MCD 6.5 7.2 5.9LowestWellington Rushmoor CD 1.2 1.1 1.4Bicester South Cherwell CD 1.2 1.2 1.1South Chafford Thurrock UA 1.1 1.2 1.0Carfax Oxford CD 1.1 1.0 1.2The Lower Tarrants North Dorset CD 1.1 0.9 1.3Scotton Richmondshire CD 1.1 0.9 1.4Whitehill Pinewood East Hampshire CD 1.0 1.0 1.0Heslington York UA 1.0 0.9 1.1Tidworth Perham Down Kennet CD 0.9 0.9 1.0Hipswell Richmondshire CD 0.7 0.6 0.9
Other Applications Same principles can be applied to other major
chronic diseases (CHD, Serious Mental Illness)Potential to link prevalence estimation to
development of IMD indicator domainsPrevalence forecasts linked to mortality forecastsPrevalence forecasts linked to ethnic population
estimates & projectionsCompare indicative prevalence (indirect
approaches) with QOF registrations - assess under or over-registration