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NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
University of Oxford Examination Schools
Monday 9 and Tuesday 10 December 2013
NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
Parallel Session D Workshop
12.00-13.15
NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
NPRI: Natural experiments:
success and challenges
Gavin Malloch, Annie Anderson,
Frank Kee and Chris Owen
Annie S. Anderson, A.Craigie, S. Caswell, M. Macleod
The BeWEL team Centre for Research into Cancer Prevention and
Screening
University of Dundee
The impact of a weight loss
programme (BeWEL) initiated
through a national colorectal cancer
screening programme
• Prof Annie Anderson (PI)
• Prof Robert Steele
• Dr Shaun Treweek
• Prof Jill Belch
• Dr Fergus Daly
University of Dundee
• Prof Jane Wardle
University College London
• Prof Anne Ludbrook
University of Aberdeen
• Dr Martine Stead
University of Stirling
• Dr Alison Kirk
University of Strathclyde
National Prevention Research
Initiative (MRC)
• Joyce Thompson
• Jackie Rodger
NHS Tayside
• Tayside
• Prof Robert Steele
• Ayrshire & Arran
• Mr Robert Diament
• Forth Valley
• Mr Wilson Hendry
• Greater Glasgow and Clyde
• Mr Derek Gillon
NHS Site Collaborators
Preventability estimates (PAF%) for cancers
of the colon and rectum (UK) (WCRF, 2013)
and Parkin (2011)
Exposure WCRF PAF%
Parkin PAF%
Foods containing Fibre 12 12
Red meat 5 21 (combined)
Processed meat 10
Alcoholic drinks 7 12
Physical Activity 12 3
Body Fatness 14 13
Total estimate 47 48
Does weight loss reduce
incidence of CRC?
Changing Cancer Risk Byers & Sedjo (2011) Diabetes Obes Metab
Dietary RCT’s Site Populati
on
Body
weight
loss
Cancer
risk
reduction
Sjostrom et al
(2009)
All sites Women
Men
31.9%
19.3%
42%
3%
Adams et al (2009) All sites Women
Men
31.0% 24%
2%
Christou et al (2008) All sites Men &
Women
31.9% 78%
Bariatric Surgery Cohorts
Observational data suggest wt decreases incidence in CRC in men (Rapp et al. 2008)
The effect of Body Weight Reduction on
the incidence of Colorectal adenoma
Subjects Adenoma Incidence %
Weight gain/maintenance 2418 413 17.1 **
Weight loss 150 14 9.3
Total 2568 427 16.6
** p<0.01
Incidence after 1 year according to weight change:
Yamaji et al, (2008) Am J Gastroenterol (103) 2061-2067
Scottish Bowel Screening Programme
Colonoscopy
Removing the adenoma removes the immediate risk of disease
The underlying factors which might influence the development of adenoma remain
Study design
3.5 year study (start 1st Feb 2010)
Two-arm multi-centre RCT
Hospital setting across 4 sites
n=316 randomised (158 / group):
– 12 month BeWEL intervention
– Usual care
6 months 24 months 6 months
Pre-trial development
Recruitment, data collection & intervention
implementation
Final data collection, analysis &
interpretation
Formative research
Using the teachable moment…..
Patients need to
– Be aware of the risk factors for adenoma
– Be able to relate these to personal behaviours
– To have a shared and accepted understanding of lifestyle and CRC
Importance of consultant endorsement
Baseline assessments
Randomisation
Intervention Group Comparison Group
12 month follow up
Exit interview
Full invitation from research nurse:
Sent within next 2 weeks
3 month follow up
Colonoscopy results sent by post
+ “Teaser Letter” from consultant endorsing study
Study
Procedures
BeWEL
12-month
programme
Outcome measures
• Change in body weight (not adenoma recurrence)
Primary outcome
• Change in:
• Waist circumference
• Cardiovascular risk factors (BP, lipids)
• Metabolic risk factors (glucose, HbA1c, insulin)
• Dietary intake (DINE)
• Physical activity (Accelerometry)
• Self assessed general health (SFQ12)
• Self-efficacy
• Programme acceptability to participants and staff
• Intervention cost
Secondary outcomes
Intervention design
Based on Diabetes Prevention Programme:
Target 7% weight loss:
• -600 kcal/day deficit diet
• Red and processed meat portions (animal fats)
• Alcohol
• Portion sizes
• Increase wholegrains, vegetables and fruit
• Increased mod / vig activity to 150 mins / week
Intervention delivery
• Combine knowledge, motivation and
• Behavioural techniques
• Motivational interviewing
• Goal setting
• Implementation intentions
• Self monitoring and feedback
• Re-enforcement
Behavioural and Re-enforcement techniques
for promoting change weight management
Self monitoring record book Body weight scales
Remind about 12 month goal, self monitoring records,
telephone calls and visits
Demonstrate and also
discuss body fat Explain recording and reporting
Inclusion criteria
Colorectal adenoma detected following
national FOBT screening
Age 50 to 74 (screening age in Scotland)
BMI >25 kg/m2
NO known cancer, insulin dependent DM
or pregnancy
Dose
All face to face contacts in months 1 to 3
– Delivered by Lifestyle counsellor
Foster immediate changes
Take 3 months to establish initial changes and build on
Monthly Telephone contacts thereafter
Baseline 12 months 3 months
Face-to-face
consultations
9 telephone consultations
BeWEL Recruitment – people are interested in
lifestyle intervention
Adults screened positive for adenoma aged 50 to 74 years
(n=997)
Responded ‘No’ n= 345 (35%)
Did not respond n=160 (16%)
Responded ‘Yes’ n=492 (49%) Changed mind
n=42 (9%)
Ineligible
1. BMI <25kg/m2 n=108(22%)
2. ‘Yes’ ineligible as reply
received after study closing
to recruitment n=13(3%)
Randomised n=329
BeWEL Retention – people stay with the
lifestyle intervention (91% follow up) for 12m
Allocated to intervention (n=163) Allocated to control (n=166)
3 month follow-up (n=153) 3 month follow-up (n=161)
12 month loss to
follow-up (n=9) 12 month loss to
follow-up (n=15)
12 month follow-up
(n=148) 91%
12 month follow-up
(n=157) 95%
Baseline and Clinical Characteristics at Randomisation
Intervention
(n=163)
Control
(n=166)
All
(n=329)
Age (years)
Range
63.5 7.0
50 – 75
63.6 6.7
50 – 75
63.6 6.8
50 – 75
Male gender 120 (73.6%) 123 (74.1%) 243 (73.9%)
Employment status
Retired
Employed full-time
Employed part-time
Unemployed
Other
90 (55.2%)
45 (27.6%)
18 (11.0%)
2 (1.2%)
8 (4.9%)
97 (58.4%)
41 (24.7%)
14 (8.4%)
10 (6.0%)
4 (2.4%)
187 (56.8%)
86 (26.1%)
32 (9.7%)
12 (3.6%)
12 (3.6%)
SIMD* (quintiles)
1 (most deprived)
2
3
4
5 (least deprived)
25 (15.3%)
33 (20.2%)
26 (16.0%)
39 (23.9%)
40 (24.5%)
29 (17.5%)
28 (16.9%)
33 (19.9%)
45 (27.1%)
31 (18.7%)
54 (16.4%)
61 (18.5%)
59 (17.9%)
84 (25.5%)
71 (21.6%)
Data are mean ± SD or number (%) unless stated otherwise. *Scottish Index of Multiple Deprivation
Primary Outcome
Intervention
Group
Control Group
P
n Mean ± SD n Mean ± SD
Bodyweight (kg)
Baseline 163 90.2± 14.9 166 88.4± 14.3
<0.0001 12 months 148 87.2± 15.7 157 88.1± 14.2
Difference 148 -3.50 ± 4.9 157 -0.78 ± 3.8
Weight loss (%) 12 months 148 -3.92 ± 5.4 157 -0.83 ± 4.1 <0.001
Waist
Circumference (cm)
Baseline 163 104.7 ± 10.9
166 103.9 ± 10.9
<0.0001
12 months 145 100.2 ± 12.0 157 102.1 ± 11.1
Difference 145 -4.91 ± 5.4 157 -2.16 ± 4.4
Changes in anthropometric measures from
baseline at 12 months by treatment group
Body Weight Reduction
% achieving 5% body weight loss
– Significantly higher in the intervention group
than the control group (36% vs. 12%)
% achieving 7% body weight loss
– Also higher in the intervention group (22% vs.
9%)
Weight change in intervention
and control groups at 12 months
Secondary Outcomes
Intervention
Group
Control Group
P
n Mean ± SD n Mean ± SD
Glucose
(mmol/l)
Baseline 142 6.11± 2.0 149 6.12± 1.9
0.05 12 months 125 5.68± 1.4 132 6.08± 1.7
Difference 125 -0.27± 1.9 132 -0.07± 1.0
Insulin
(mmol/l)
Baseline 104 11.12± 8.3 110 10.17± 8.8
0.82 12 months 74 12.77± 11.1 79 13.48± 10.2
Difference 66 2.77± 9.00 73 2.58± 7.1
HbA1c (%)
Baseline 149 6.02± 1.2 151 6.03± 1.2
0.06 12 months 120 5.84± 0.8 129 6.03± 1.0
Difference 120 -0.13± 0.9 129 -0.02± 0.6
Glucose metabolism biomarkers
Intervention
Group
Control Group
P
n Mean± SD n Mean± SD
Fat
consumption
score*
Baseline 163 30± 10.6 166 32± 10.6
<0.0001 12 months 146 24± 7.4 156 28±10.3
Difference 146 -7.3± 10.2 156 -3.8± 8.0
Fruit and
vegetable
(p/day)
Baseline 163 4± 2.2 166 4± 2.2
0.0004 12 months 148 5± 2.4 157 4± 2.4
Difference 148 0.6± 2.3 157 0.0± 2.1
Changes in dietary intake
*Based on intakes of foods which contribute substantially to fat intake i.e. dairy
foods, meat, processed meat, fish, fried foods, sweet and savoury snacks and fat
spreads. . A score of less than 30 is equivalent to around 83g fat (estimate 35% of total energy intake for an average woman).
Intervention Group Control Group
P n Mean± SD n Mean± SD
Daily average
time spent
active (mins)
Baseline 156 82± 62.3 157 79± 55.9
0.02 12 months 140 89± 65.3 148 74± 62.0
Difference 140 6.23± 60.1 148 -5.53± 40.0
Daily average
time spent in
moderate
activity (mins)
Baseline 153 81± 58.0 153 77± 53.7
0.05 12 months 137 86± 63.4 144 73± 60.7
Difference 137 6.27± 54.5 144 -3.67± 38.5
Daily average
step count
Baseline 156 8429± 3995 157 7734± 3538
0.03 12 months 140 8697± 4404 148 7460± 3873
Difference 140 239.6± 3118.3 148 -310.2± 2263.6
Changes in Physical Activity
Participant experience
spoke highly of the study + counselling staff
feeling of being understood as an individual
(encouraging and maintaining involvement)
several felt they would not have engaged so
well in a group setting
motivations varied: small "scare“/ adenoma
+ other triggers/ “if not now, when”?
successful weight loss - sustained
commitment/strategies to deal with relapse
triggers.
Conclusions
There is interest in lifestyle change in people
with CRC adenomas
Study participants show commitment to lifestyle
change over a 12 month period
Study participants respond favourably to lifestyle
interventions
Considerable potential for disease risk reduction
in older adults
Colorectal cancer screening and prevention
programme?
NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
• The Connswater Community Greenway
• The elements of the evaluation
• The best laid plans.....
• The importance of theory and the challenges for analysis
• Collateral KE benefits of PARC
The PARC Study: a case study of a natural experiment
Health • 5 wards within the top 10% most disadvantaged
Education • 7 wards within the top 10% most disadvantaged
Environment • 3 of the 10 most deprived living environments in
NI
Employment • 5 wards within the top 20% most disadvantaged
• Before and after household survey (1200x2)
• Regional comparison survey (SportNI)
• Network and social capital analysis
• Process evaluation
• Economic and behavioural economics analysis
• Built environment
• Primary care based exercise referral
• Walking schemes and other community - led physical activity initiatives
• Employer and school based initiatives
• “Loyalty schemes”
What makes complex public health interventions complex ?
Questions to ask about evaluability
• CMO configurations/ “realist evaluation”
• Testing theories rather than interventions
• Seeing the “big picture”
• How will an evaluation affect policy?
• What are the plausible sizes and distribution of hypothesized impacts?
• How will the findings add value to the evidence?
• Is it practical within the time available ?
An ecological model of 4 domains of physical activity.
Sallis J F et al. Circulation 2012;125:729-737 Copyright © American Heart Association
`
Preliminary analysis of PARC Survey
• Structural Equation Model based on hypothesised pathways from socio-ecological model (Mplus)
• Tested a series of relationships through which environmental (objective and subjective), social and individual factors potentially interact to influence PA
• Perceived environment factors (attractiveness and supportive infrastructure) predict overall and travel related PA; but not recreational PA
• Perceived social support for PA moderates this relationship
• Suggests possible pathway between the built environment and PA
The importance of theory - added value from concept mapping-
Benches, lighting
•Quality of surface •Signage
Somewhere to go
Green space Graffiti, Noise
•Stamina •Mastery
Social capital Dog ownership Police presence
The importance of theory - added value from concept mapping in PARC-
Index of Activities: 1 = Being out and
about,
2= Being Active.
Index of Facilitators: 3=Physical
Infrastructure, 4 = Good weather, 5= Other
People, 6 = Being Safe, 7 = Greenery and
Open Space, 8 = Organizational
Infrastructure.
Index of Inhibitors: 9 = Current demands
of work and daily life, 10 = Vandalism &
Anti-social behaviour, 11 = Territoriality, 12
= Bad Weather, 13 = Urban Infrastructure.
The importance of theory
• Are there any unblocked back-door paths from exposure to outcome?
• Are mediators themselves “confounded” ?
• Are any associations induced by selection bias?
• Perfectly even distributions of causal factors do not prevent confounding
• Confounding without confounders
• DAG may not always correctly identify the presence of confounding
The importance of theory Manski’s typology
• effects of aggregate outcomes at the group-level on individual-level outcomes (“endogenous” effects)
• contextual effects of group composition
• environmental effects.
Infectious disease Social capital/norms
Challenges for “experiments” on Nature and Neighbourhoods
• Spatial resolution and boundary issues
• Synergies between physical and social environments
• Individual-level variables may simultaneously be confounders and mediators
• Migration and selection
Where’s the evidence ?
“The highway from one merchant town to another shall be cleared so that no cover for malefactors should be allowed for a width of two hundred feet on either side; landlords who do not effect this clearance will be answerable for robberies committed in consequence of their default, and in case of murder they will be in the king’s mercy”.
17 June 1239 – 7 July 1307) Statute of Winchester, 1285
• Even RCTs need mechanistic insights
• eg to help with the interpretation of external validity
– distinguishing behavioural effect modification from biological effect modification”
• Methodology has a rather weak influence on research use by policy makers;
• We need to consider information needs and intended use of new information
– only then consider added value in the context of precision, bias and generalisability
• Be honest in considering how ambiguous results will be used in decision making
Existing research on walkability
• mostly from US and Australia • different urban form
• cultural and demographic differences
• subjective versus objective measures
• data availability
• Most indices based on • Residential density
• Land use mix
• Street connectivity
• Retail area ratio
Special thanks to
• Dr Mark Tully
• Dr Ruth Hunter
• Prof Geraint Ellis
• Prof Margaret Cupples; Prof Lindsay Prior
• Dr Mary Dallat; Prof George Hutchinson;
• Dr Michael Donnelly, Dr Helen McEneney, Mike Stevenson
• CCG Team
THANKYOU
NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
Natural experiments:
success and challenges
Operational experiences
from ENABLE London
Christopher Owen
Population Health Research Centre,
St George’s, University of London, UK
Will moving into social and intermediate
housing in the East Village increase
family physical activity levels?
Christopher Owen, Bina Ram, Billie Giles-Corti †, Ashley Cooper ‡, Anne Ellaway §, Alicja Rudnicka, Peter Whincup, Derek Cook Population Health Research Centre, St George’s,
University of London, UK
† McCaughey Centre, University of Melbourne, Australia
‡ Department of Exercise, Nutrition & Health Sciences, University of Bristol, UK
§ MRC Social and Public Health Unit, Glasgow, UK
Objectives
What is ENABLE London?
Progress to date
Recruitment rates
Data collected
Questionnaire, activity / GPS data
Challenges ahead
Decisions made / to be made
Future work
How to increase physical activity
- evidence to date Interventions to increase physical activity
levels
have shown limited effects
poorly maintained in the longer-term
The built environment may be key constraint limited evidence on the effect of the built
environment on physical activity
Need for studies examining impact of
marked changes in the built environment on
physical activity levels (‘natural experiment’)
ENABLE London aims
Do families moving to East Village show a
sustained change in PA levels compared
with non-movers?
Is the change in PA attributable to use of
elements of the local built environment?
What factors influence the change in PA
levels? (e.g., age, gender, social factors)
Do other health indicators (e.g., body fat
levels) change – if so, does this reflect
changes in physical activity?
1200 families
recruited from EV
applications
600 families
(1 adult, 1 child)
1200 subjects
East Village
600 families
(1 adult, 1 child)
1200 subjects
Living elsewhere
420 adults
(320 children)
420 adults
(320 children)
1 YEAR FOLLOW-UP
Evaluating the impact of the EV development
Control families matched to those moving into the Village
Powered to detect
500 step difference
5% daily steps
AF
TE
R M
OV
E
BE
FO
RE
MO
VE
Types of East Village housing
East Village
housing (E20)
N=2818 units
Social Housing
Intermediate Rent
Shared Ownership
Shared Equity
N=675
(290 3+beds,
49 2 beds)
N=704
(356 IMR,
269 SO, 79 SE)
TRIATHLON HOMES
Private Rent
N=1439
All owned by
QDD
QDD
Target recruitment
January 2013 January 2014
600 Social
Households
600 Intermediate
Households
300 Social
EV households
300 households
elsewhere
300 Intermediate
EV households
300 households
elsewhere
Social housing recruitment
634 interviewed
at East Thames
321 (80%) agreed
to participate:-
272 (85%) seen
49 (15%) pending
426 (67%)
forms received
105 (20%) refusals
23 snowballs:-
7 refusals
16 seen
598 school
questionnaires:
90 (15%) forms:-
32 refusals
52 seen
6 pending
539 forms:
144 (27%) refusals
340 (63%) seen
55 (10%) pending
Opportunities to recruit
634 interviewed
at East Thames
215 to be
allocated by
mid-November
460 allocated EV
social housing
Snowballs may
yield 10% 395 social
households so far
need to recruit
205 more
Control
East
Village
School
recruitment
could be
maximised but
select group
Social housing recruitment
Control
0
100
200
300
400
500
600
700
Target
Forms Received
Recruited
Visits Completed
OR
Intermediate progress
Intermediate recruitment
96/150 Triathlon
EV Intermediate
homes allocated
44 (77%) agreed
to participate:-
38 (86%) seen
6 (14%) pending
57 (59%)
forms received
13 (23%) refusals
7 snowballs:-
0 refusals
7 seen 64 forms:
13 (20%) refusals
45 (70%) seen
6 (9%) pending
Less suited to
school
recruitment?
Intermediate recruitment
0
100
200
300
400
500
600
700
Target
Forms Received
Recruited
Visits Completed
East Village not fully open
Access / move postponed
Recruitment process for EV Intermediate (IMR, SO, SE) homes
Step 1
• Eligible
• Online application
Step 2 • Financial assessment
Step 3 • Invited to Interview
Step 4
• Accommodation offered
• Deposit paid (circa £15K+)
Further
recruitment
opportunities,
especially
for controls
Current
recruitment
Phase 1
N=150
Phase 2
N=200
Phase 3
N=200
Phase 4
N=150
Questionnaire sources
ENABLE London
Census 2011
HSE 1995, 2004
General Household
Survey 1994
SURESTART
EQ-5D, 2009
NEWS, IPAQ
RESIDE, TREK,
HABITAT
CHASE & NOVEL Qs
Item Main / partner / adult Parent Child
Demographics
Household
Qualifications
Employment
Travel to work / study
Household income
General health
Health outcomes
Satisfaction scores
Smoking / drinking
Local neighbourhood
Activities / IPAQ
Cost of activities
Attitudes to exercise
TV & computers
Eating / sleeping
Maximum items 219 / 174 20 52
Median duration (mins) 49 / 38 / 26 Included with main 19
17.8
36.3
21.4
14.9
9.5
0
10
20
30
40
50
Pe
rce
nt
(%)
1 2 3 4 5
Enjoy living in area
39.4
48.7
5.73.9
2.3
0
10
20
30
40
50
1 2 3 4 5
Good local transport
16.0
35.8
21.118.8
8.2
0
10
20
30
40
50
1 2 3 4 5
Good leisure services
10.6
20.1
25.8
31.7
11.9
0
10
20
30
40
50
1 2 3 4 5
Problems due to vandalism
5.2
36.9
19.6
26.0
12.4
0
10
20
30
40
50
Pe
rce
nt
(%)
1 2 3 4 5
Area free from litter
11.9
28.125.826.5
7.7
0
10
20
30
40
50
1 2 3 4 5
Too much traffic
8.8
28.6
22.2
27.6
12.9
0
10
20
30
40
50
1 2 3 4 5
Area attractive to look at
12.1
39.2
21.9
17.3
9.5
0
10
20
30
40
50
1 2 3 4 5
Enjoy walking in area
1: Strongly agree, 2: Agree, 3: Neither agree or disagree, 4: Disagree, 5: Strongly disagree
Missing data: 0 out of 388 records
Actigraph data
From 480 individuals
312 (65%) have good Actigraph data
Defined as 4 days at 540 mins
Re-testing 10% with borderline data
Defined as at least 3 to <4 days at 540
mins
Of 20 re-issued, 8/16 good data
GPS data
Preliminary analyses on small sample
73% of Actigraph wear time matches
GPS data
26% of GPS data was outdoors
Data cleaned by applying criterion of
60 minutes of zero values, allowing for
2 minute blips
Wear time is the amount of valid
accelerometer data after this
Points to consider
Electronic surveys
Third party recruitment
Delay in East Village opening
Social housing recruitment on target
Numbers from intermediate housing will
increase
Staffing issues
Future funding: extension, further work
http://www.enable.sgul.ac.uk/
National Prevention
Research Initiative
NPRI
UK Society for Behavioural Medicine 9th Annual Scientific Meeting
“Behavioural Medicine: From Laboratory to Policy”
