Healthy Lifestyles Synthetic Estimates Project Shaun Scholes, Kevin Pickering and Claire Deverill.
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Transcript of Healthy Lifestyles Synthetic Estimates Project Shaun Scholes, Kevin Pickering and Claire Deverill.
Healthy Lifestyles Synthetic Estimates
Project
Shaun Scholes, Kevin Pickering and Claire Deverill
Outline of presentation
• A ‘small-area estimation problem’ with national surveys such as the Health Survey for England
• Get around this problem by statistical modelling. HSE data is used in combination with other data sources to generate estimates at fine levels of geography
• Importance of quality assurance
• Caveats when using small area estimates
Demand for local area data on health
• Health related behaviour is not uniform across England (‘place matters’)
• NatCen regularly use HSE data to produce health indicators: • England (trend tables)• Larger areas such as: GORs (Annual HSE reports); GORs,
SHAs & Counties (SHA report 2004, Compendium of Clinical Indicators, forthcoming Chief Medical Officer’s report on binge drinking)
Regional indicators using HSE data
U n ita ry A u th o rit ies
W a rds M S O A s
D is tric t s
C o u n ties
G O R s
P C O s
S H A s
E n g la nd
Small area estimation problem
• National surveys such as the HSE are not designed to provide reliable estimates at local level:• Sample sizes typically small or zero within small areas, even
after pooling years of HSE data together• Direct estimates, where we can calculate them, are
unbiased - but have low precision due to wide sampling error
• Local health surveys are an option but various problems:• Costs• Comparability across surveys
• Small area estimation techniques are an alternative
Healthy lifestyles synthetic estimates project
• Information Centre for Health and Social Care and Neighbourhood Statistics commissioned NatCen to use HSE data to produce small area estimates of:• current smoking (adults)• binge drinking (adults)• obesity (adults)• fruit & vegetables consumption (adults & children
separately)
Small area estimation methodology used by NatCen
• Use a statistical model to express the relationship between individual healthy lifestyle behaviour and area-level information
• Outputs from that model used to generate a model-based estimate for all areas
• But must be interpreted differently to direct estimates ~ estimates represent the expected prevalence for an area based on its population characteristics
IllustrationWhether an
individual currently smokes from HSE
2003-2005
Attach area-level information to HSE dataset:
Regional indicator
% 16-74 with no qualifications (Census 2001)
Statistical model run on the subset of areas covered by HSE
2003-2005
Use terms from model to obtain a predicted estimate for all small areas
Area-level characteristics and current smoking
Variable Odds ratio Standarderror
95%confidence
interval
T2 ratio
North East SHA (reference) 1North West SHA 0.92 0.076 0.79-1.09 0.92Yorkshire & The Humber SHA 0.94 0.082 0.79-1.12 0.47East Midlands SHA 0.99 0.089 0.83-1.18 0.02West Midlands SHA 0.95 0.083 0.80-1.13 0.34East of England SHA 0.95 0.085 0.80-1.13 0.35London SHA 0.89 0.086 0.74-1.08 1.35South East Coast SHA 0.97 0.092 0.81-1.17 0.09South Central SHA 0.86 0.086 0.71-1.05 2.24South West SHA 0.89 0.080 0.75-1.06 1.75% of IS claimants ‘carers and others’ 0.99 0.002 0.99-1.00 16.64% White origin 1.01 0.002 1.01-1.02 48.90% unpaid carers 0.94 0.014 0.91-0.97 17.82% highest qualification NVQ Level 1 or noqualifications (aged 16-74)
1.02 0.002 1.02-1.03 132.50
% 16+ residing as couple 0.98 0.003 0.97-0.98 84.47
Implementation
MSOA Region % 16-74with noqualifications
% 16+residingas couple
% currentsmoking
E02000984 North-West 32% 73% 13%E02001007 North-West 52% 64% 24%E02000996 North-West 61% 53% 36%
Quality assurance
• Quality of estimates crucially depend on the quality of the model
• Need for QA measures to provide evidence on plausibility of estimates• Internal checks (examine the residuals, correlation between
direct and model-based estimates)• External checks (no gold standard!)
– correlation with direct estimates from other surveys such as GHS
– correlation with local boost surveys
– correlation with Index of Multiple Deprivation 2004
Residual plot (all areas sampled)
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
0 0.1 0.2 0.3 0.4 0.5 0.6
Model-based estimates for PCS
Area
leve
l res
idua
l
Correlation with IMD 2004 (Bolton)
Rank of smoke estimates compared with rank of IMD
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
Rank of IMD 2004
Ran
k o
f M
od
elle
d E
stim
ates
Putting estimates in a contextIndicator England E02001007 E02000182
Region - North West London
Local Authority - 00BL 00AG
Survey estimate ofcurrent smoking
24.1% [23,25] - -
Model-based estimate - 23.9% [13,40] 19.5% [10,34]
Rank of MSOA on IMD - 3,965 5,009
% dwellings CTX band Aor B (<£52,000)
44% 74% 5%
% residents 16-74 withno qualifications
46% 52% 21%
% residents 16+ residingas a couple
61% 64% 45%
Estimates have health warnings
• Have to be interpreted differently ~ not estimates of actual prevalence
• Dependent upon quality of the model • Method relies on having powerful predictors of health
variations between areas. A large amount of unexplained between area variation results in wide CIs:• Can compare MSOAs against the national average• Cannot meaningfully compare MSOA X against MSOA Y as
CIs overlap
• But we stress that these estimates are not available elsewhere!