The population effect of crime and neighbourhood on physical activity: an analysis of 15,461 adults.
ABSTRACT Area-based interventions offer the potential to increase physical activity for many sedentary people in countries such as the UK. Evidence on the effect of individual and area/neighbourhood influences on physical activity is in its infancy, and despite its value to policy makers a population focus is rarely used. Data from a population-based health and lifestyle survey of adults in northwest England were used to analyse associations between individual and neighbourhood perceptions and physical activity. The population effect of eliminating a risk factor was expressed as a likely effect on population levels of physical activity. Of the 15,461 responders, 21,923 (27.1%) were physically active. Neighbourhood perceptions of leisure facilities were associated with physical activity, but no association was found for sense of belonging, public transport or shopping facilities. People who felt safe in their neighbourhood were more likely to be physically active, but no associations were found for vandalism, assaults, muggings or experience of crime. The number of physically active people would increase by 3290 if feelings of "unsafe" during the day were removed, and by 11,237 if feelings of "unsafe" during the night were removed. An additional 8342 people would be physically active if everyone believed that they were "very well placed for leisure facilities". Feeling safe had the potential largest effect on population levels of physical activity. Strategies to increase physical activity in the population need to consider the wider determinants of health-related behaviour, including fear of crime and safety.
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ABSTRACT: activity, obesity and wellbeing relation to neighbourhood satisfaction, physical Recreational values of the natural environment in http://jech.bmj.com/cgi/content/full/62/4/e2 Updated information and services can be found at: These include: References http://jech.bmj.com/cgi/content/full/62/4/e2#BIBL This article cites 35 articles, 5 of which can be accessed free at: Rapid responses http://jech.bmj.com/cgi/eletter-submit/62/4/e2 You can respond to this article at: service Email alerting the top right corner of the article Receive free email alerts when new articles cite this article -sign up in the box at Notes http://journals.bmj.com/cgi/reprintform To order reprints of this article go to: http://journals.bmj.com/subscriptions/ go to: Journal of Epidemiology and Community Health To subscribe to onJournal of epidemiology and community health 04/2008; 62(e2):1-7. · 3.04 Impact Factor
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ABSTRACT: Hypotheses on the relationship between neighborhood perception and obesity (as measured by body mass index) seem to generally posit that a positive neighborhood perception may be related with behaviors that positively moderate body weight.The Journal of frailty & aging. 01/2012; 1(4):152-161.
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ABSTRACT: We examined the relationship between neighborhood environment (e.g., objective neighborhood socioeconomic status [SES] and subjective neighborhood perceptions) and waist-hip ratio (WHR) or central obesity using logistic regression and content analysis of respondents’ narratives on housing unfair treatment in the YES Health pilot study. Multivariate results showed significant relationships between low SES White, low SES Black, and middle SES Black versus middle SES White neighborhoods and total-sample and women's obesity, in almost all neighborhood perception models. Significant relationships included: disliking neighborhood and total-sample obesity; neighborhood informal monitoring/surveillance and total-sample and women's obesity; social participation and total-sample and women's obesity; and perceptions of families and total-sample and women's obesity. Qualitative results partially corroborate our quantitative results that low SES neighborhood adults were more likely to experience neighborhood disorders and safety issues. Our findings highlight examining objective and subjective neighborhood environments related to central obesity, suggesting specific health targets for neighborhood intervention programs.Journal of Social Issues 06/2014; 70(2). · 1.96 Impact Factor
EVIDENCE BASED PUBLIC HEALTH POLICY AND PRACTICE
The population effect of crime and neighbourhood on physical
activity: an analysis of 15 461 adults
Roger A Harrison, Islay Gemmell, Richard F Heller
............................................................... ............................................................... .....
J Epidemiol Community Health 2007;61:34–39. doi: 10.1136/jech.2006.048389
Area-based interventions offer the potential to increase physical
activity for many sedentary people in countries such as the UK.
Evidence on the effect of individual and area/neighbourhood
influences on physical activity is in its infancy, and despite its
value to policy makers a population focus is rarely used. Data
from a population-based health and lifestyle survey of adults in
northwest England were used to analyse associations between
individual and neighbourhood perceptions and physical
activity. The population effect of eliminating a risk factor was
expressed as a likely effect on population levels of physical
activity. Of the 15 461 responders, 21 923 (27.1%) were
physically active. Neighbourhood perceptions of leisure
facilities were associated with physical activity, but no
association was found for sense of belonging, public transport
or shopping facilities. People who felt safe in their
neighbourhood were more likely to be physically active, but no
associations were found for vandalism, assaults, muggings or
experience of crime. The number of physically active people
would increase by 3290 if feelings of ‘‘unsafe’’ during the day
were removed, and by 11 237 if feelings of ‘‘unsafe’’ during
the night were removed. An additional 8342 people would be
physically active if everyone believed that they were ‘‘very well
placed for leisure facilities’’. Feeling safe had the potential
largest effect on population levels of physical activity. Strategies
to increase physical activity in the population need to consider
the wider determinants of health-related behaviour, including
fear of crime and safety.
See end of article for
R A Harrison, Evidence for
Population Health Unit,
Epidemiology & Health
Sciences, School of
Medicine, University of
Manchester, Oxford Road,
Manchester M13 9PT, UK;
Accepted 2 June 2006
ber states.3Lack of regular physical activity is
associated with marked preventable mortality and
morbidity4and is a public health priority. Although
efforts to increase physical activity among indivi-
duals have had some small effect,5–7modifying
social, economic and environmental factors may be
more successful at the population level.6Indeed,
evidence is emerging that contextual or area-level
factors, including transport systems, land use mix,
population density and leisure opportunities, are
related to population levels of physical activity.7–10
However, few studies have examined this in the
UK8despite sedentary behaviour being a major
public health concern. Increasing our understand-
ing of the relationship between physical activity,
n the UK, as many as two thirds of adults live
sedentary lives,1 2representing one of the least
physically active nations of 15 European mem-
‘‘who you are’’ and ‘‘where you live’’,9although
challenging,6is essential to inform the develop-
ment of interventions to seriously reduce the
number of people living mainly sedentary lives.
In the general population, regular physical
activity is more likely among men, younger adults,
people with other healthy lifestyle behaviours (eg,
non-smoking, greater intake of fruit and vegeta-
bles), those reporting good general health and no
history of chronic disease.2The aim of the current
study was to examine neighbourhood influences
on physical activity and to quantify this in terms of
the population effect using population impact
measures (PIMs).10PIMs provide a population
perspective by adding incidence information to
traditional measures of risk, such as the popula-
risk, thus, providing information on the actual
numbers of people who are at risk from specific
exposures in a particular population to assist local
The study was based in two districts in northwest
England, which is divided into 44 administrative
electoral wards. Data from the 2001 national
567 600 adults: 94% were white people and the
population density was 1700 people per square
kilometre.12Methods for data collection have been
described previously.2 13 14
collected using a postal self-completion question-
naire as part of a population-based health and
lifestyle survey in 2001. The sampling frame was
all resident adults on the general practitioner
register and systematic sampling was used to
select a 5% sample. The postal questionnaire was
sent with a covering letter and a business pre-paid
return envelope. Non-responders were sent a
reminder postcard 10 days later. After another
10 days, persistent non-responders were sent a
reminder letter with another copy of the survey
and a return envelope. The questionnaire included
an introduction in Gujarati and Urdu, the main
second languages spoken in the area, with
information on the local health translation ser-
vices. A favourable opinion was received from the
local research ethics committees before starting
The 50-item questionnaire sought information
on general and specific health, health behaviours
and perceptionsof neighbourhood.
constructs were taken from previous national
In brief, data were
Abbreviation: PIM, population impact measure
asked respondents about the following: the extent that
they felt they belonged to that area (strongly agree to
strongly disagree); how well placed their home was for
public transport, general shopping and leisure facilities (very
well placed to badly placed); in their neighbourhood how
much of a problem was vandalism; assaults and muggings;
speeding traffic; and whether they had been the subject of
personal crime in the past year. They were also asked whether
they felt safe ‘‘out and about’’ in their neighbourhood during
the day and during the night. Multiple deprivation was
measured using the Townsend Index, which is constructed on
four census variables (unemployment, overcrowding, non-car
ownership and non-home ownership).15Townsend Scores
from 1142 census enumeration districts for the two electoral
districts in the study were assigned using the participants’
Physical activity was assessed using the Godin and Shephard
instrument.17This is valid for use in epidemiological studies and
discriminates between adults participating in different amounts
and types of physical activity. Participants were asked to record
how many times in the past week they had engaged in light,
moderate or vigorous activity for a session lasting at least
15 min. Examples of moderate physical activity included brisk
walking, table tennis, easy cycling, golf, dancing and cleaning
windows; vigorous activity included running, football, cardio-
vascular gym workouts and aerobics. In the current analysis,
physically active was defined as participating in at least five
sessions per week of moderate or vigorous physical activity,
with each session lasting at least 15 min.17
The questions specific to the neighbourhood
Individual associations with physical activity and neighbour-
hood factors were expressed as relative differences (prevalence
rate ratios) using a modified Poisson regression approach.18
This involves fitting a generalised linear model to the data with
a log link and a Poisson error term. The outcome variable in
these models was being physically active, and the predictor
variables were the health and lifestyle behaviours. The robust
variance estimator was used to adjust for misspecification of
the error term. The analyses controlled for the potential
confounding effects of age, sex, ethnicity and deprivation.
Data were analysed Stata V.8.2 (StataCorp, College Station,
The population effect of eliminating a risk factor was
calculated when the relative risk was statistically significant.
The calculation excluded a time element, given the cross-
sectional nature of our data. Its formula is10:
where n is the population size; Ipis the incidence of sedentary
behaviour (physical inactivity) in the whole population; PAR is
the population attributable risk (Pe(RR21)/1+Pe(RR21)); Peis
proportion of the population who is physically inactive; RR is
Calculations of the population attributable risk for variables
with multiple strata were adjusted according to the methods of
In June 2001, 70.1% of the sample returned a useable
questionnaire (15 461/21 923). Their mean age was 49.8
(standard deviation (SD) 17.6) years, 45.2% (6986) were men
and 95.5% (14 765) described themselves as Caucasians. The
mean age of responders was 8.3 years more than that of non-
responders. No other information on non-responders was
available for comparisons. In all, 27.1% (4193/15 461) of
responders defined themselves as being physically active. The
mean age of physically active respondents was 10 years lesser
than those not defined as being physically active (42.5 v
52.5 years, p=0.001).
We found no differences in the proportion of men and
women who were defined as physically active (27.6% v 26.7%),
but those described as Caucasians compared with non-
Caucasians had a higher relative prevalence of physical activity
(1.32, 95% confidence interval (CI) 1.16 to 1.52). For depriva-
tion, a graded relationship was observed, with the prevalence of
physical activity reducing across each of the deprivation
quintiles (table 1).
Looking at neighbourhood factors, a graded relationship was
observed between how well people thought their neighbour-
hood was for leisure facilities and the prevalence of being
physically active (table 2).
We found no association between physical activity and sense
of ‘‘belonging’’ to their neighbourhood, how well placed they
believed their neighbourhood was for public transport and for
general shopping (table 2).
Prevalence of physical activity by baseline characteristics
Everyone 15 46127.1 (4193)——
0.97 (0.92 to 1.02)
0.97 (0.92 to 1.01)
1.14 (1.00 to 1.30)
1.32 (1.16 to 1.52)14 559
1 (least deprived)
5 (most deprived)
0.93 (0.86 to 1.0)
0.92 (0.85 to 0.99)
0.86 (0.79 to 0.93)
0.76 (0.70 to 0.82)
0.92 (0.85 to 0.99)
0.90 (0.84 to 0.97)
0.85 (0.78 to 0.91)
0.77 (0.72 to 0.84)
*Not all respondents answered every question.
?Adjusted for all variables in the table.
`Townsend Score at enumeration level as a proxy for individual deprivation.
Effect of crime and neighbourhood on physical activity35
People who felt unsafe out and about in their neighbourhood
during the day (relative prevalence 0.70, 95% CI 0.59 to 0.82)
and during the night (relative prevalence 0.82, 95% CI 0.78 to
0.88) were significantly less likely to be defined as physically
active compared with those who felt safe during these times
We observed no association for physical activity and people
stating that vandalism, and assaults or muggings were a
problem in their neighbourhood, also not among people who
had or not been victims of personal crime during the past year.
People who thought that there was some problem with
speeding traffic in their neighbourhood were more likely to
Association of physical activity with individual perceptions of neighbourhood facilities
How well placed for leisure facilities?
Not very well
30.3 ( 886)
0.97 (0.90 to 1.05)
0.94 (0.88 to 1.01)
0.87 (0.79 to 0.95)
0.76 (0.68 to 0.85)
0.95 (0.88 to 1.02)
0.96 (0.89 to 1.03)
0.90 (0.82 to 0.98)
0.86 (0.77 to 0.94)
Feel of belonging to the area?
Neither agree nor disagree
1.03 (0.96 to 1.10)
1.16 (1.07 to 1.25)
1.10 (0.98 to 1.23)
1.11 (0.95 to 1.30)
0.98 (0.92 to 1.05)
0.99 (0.92 to 1.06)
0.93 (0.84 to 1.04)
0.90 (0.77 to 1.04)
How well placed for transport?
Not very well
1.02 (0.96 to 1.08)
0.96 (0.90 to 1.04)
1.01 (0.89 to 1.13)
0.87 (0.71 to 1.05)
0.98 (0.92 to 1.04)
0.95 (0.88 to 1.01)
1.01 (0.90 to 1.13)
0.89 (0.73 to 1.08)
How well placed for general shopping?
Not very well
1.03 (0.97 to 1.10)
0.97 (0.90 to 1.04)
0.85 (0.76 to 0.95)
0.86 (0.73 to 1.01)
1.00 (0.94 to 1.06)
0.95 (0.90 to 1.01)
0.93 (0.83 to 1.03)
1.00 (0.86 to 1.17)
*Not all respondents answered every question.
?Adjusted for age, sex, ethnicity and deprivation (Townsend Score at enumeration district).
Association of individual perceptions of crime and safety with physical activity
Feel safe out in neighbourhood
During the day?
During the night?
0.55 (0.47 to 0.66)
0.70 (0.59 to 0.82)
0.70 (0.66 to 0.74)
0.82 (0.78 to 0.88)
How much of a problem to you are any of
Not a problem
Assaults or muggings?
Not a problem
Not a problem
1.01 (0.96 to 1.08)
0.92 (0.83 to 1.01)
1.05 (1.00 to 1.11)
1.01 (0.92 to 1.12)
0.98 (0.93 to 1.04)
0.88 (0.74 to 1.05)
1.01 (0.95 to 1.07)
0.91 (0.77 to 1.08)
1.09 (1.03 to 1.16)
1.05 (0.98 to 1.13)
1.08 (1.10 to 1.14)
1.04 (0.97 to 1.11)
Personal experience of crime in the past year?
1.09 (1.02 to 1.17)
0.97 (0.91 to 1.03)
*Not all respondents answered every question.
?Adjusted for age, sex, ethnicity and deprivation (Townsend Score at enumeration district).
36 Harrison, Gemmell, Heller
be physically active, but this was not consistent to this being a
Table 4 shows the population effect of eliminating statisti-
cally significant risk factors for sedentary behaviour.
The data suggest that the number of physically active people
would increase by 3290 if feelings of being unsafe during the
day were removed, and by 11 237 if feelings of being unsafe
during the night were removed. An additional 8342 people
would be physically active if everyone believed that they were
‘‘very well placed for leisure facilities’’. In absolute terms, this
would be expected to increase the current level of physical
activity in the population by 0.6%, 2.0% and 1.5%, respectively
Our work represents one of the most comprehensive assess-
ments of individual and contextual associations with physical
activity among adults in the UK general population. We have
previously confirmed low levels of physical activity among
several adults, which decreased with advancing age and by
socioeconomic deprivation.2The focus of the current investiga-
tion was to examine the association of physical activity with
contextual factors, based on the notion that both individual
and contextual factors can influence physical activity. We
found that individual perceptions of how well placed their
neighbourhood was for leisure facilities were considerably
associated with physical activity. The fact that this increased
across each response category adds strength to this dose–
response association. We also found that feeling safe in the
neighbourhood during the day or during the night was
positively associated with physical activity. Our approach of
applying population effect measures suggested that the greatest
increase in physical activity would be achieved in the
population if everyone was made to feel safe during the night,
with only a small effect if everyone was made to feel that their
neighbourhood was well placed for leisure facilities. Therefore,
if we are to increase population levels of physical activity,
increasing feelings of safety seems to be a greater priority than
improving perceptions regarding the provision of leisure
In our study, we failed to find any consistent association
between physical activity and sense of belonging to the
neighbourhood or perceptions about transport or shopping
facilities, or problems in the neighbourhood from unsociable
and criminal behaviours. Perhaps these did not differ suffi-
ciently across the study setting to influence physical activity or
among this population these factors may have had little effect
on this behaviour.
The strengths of our study are its population focus, a large
sample size with good response rates and data on a wide range
Estimated population effect on physical activity from changing neighbourhood perceptions
RR of being
Number of adults
in this population
During the day
During the night
758 14 913
11 237 5 305
How well placed for leisure
Not very well
Overall PAR 0.05567 6000.278 342
PAR, population attributable risk; Pe, proportion of the population who is physically inactive, PIN-ER, population effect of eliminating a risk factor.
*The number of people expected to become physically active if everyone in this population felt safe during the day, or felt safe during the night, or thought their
neighbourhood was very well placed for leisure facilities, calculated as PIN-ER=n6Ip6PAR, where n is the population size; Ip, the incidence of sedentary behaviour
(physical inactivity) in the whole population; PAR=(Pe(RR21)/1+Pe(RR21)).
Number of people in the total population expected to become physically active if neighbourhood perceptions improved
adults in this
Expected to be
Expected to be
Absolute increase in
people expected to
be physically active
During the day
During the night
How well placed for
Very well567 60027.0 153 252 8 342161 59428.5 1.5
PIN-ER, population effect of eliminating a risk factor.
*Observed in the survey.
?Calculated as number of adults in the population6(percentage of adults physically active/100).
`From table 4.
1Number of adults physically active+PIN-ER.
?Expected number in the population to be physically active as a proportion of total population.
**Difference between expected percentage of the population to be physically active and percentage of the population currently physically active.
Effect of crime and neighbourhood on physical activity37
of possible effects on physical activity. The survey included
validated questions and reflected those used in national surveys
and surveillance systems. We also adjusted for the potential
confounding effects of area deprivation, using the participants’
postcode linked to deprivation data at an enumeration level.
Although this method has been found to be an effective method
to examine the effect of individual deprivation on health,16
some misclassification may have taken place.
PIMs are a recently described addition to other measures of
population effect, such as population attributable risk.10PIMs
add information on incidence to estimate the number of people
in a total population who may benefit (or be at risk) from an
intervention. As such, they provide a population perspective to
inform local policy decisions.16 20In the current study, this
method has been used to estimate the effect of neighbourhood
and neighbourhood perceptions on sedentary behaviour in
Our study relied on self-reported measures, which may be
subject to measurement error, and our control for confounders
was limited to the data originally collected. Simple methods for
assessing physical activity have been found to reliably predict
outcomes such as mortality,21supporting their wide application
in epidemiological studies. Response bias is a known problem
in population studies and just ,30% of those in the original
sample did not return a useable questionnaire. A previous study
found that non-responders were less likely to be physically
active compared with responders.22Therefore, the true pre-
valence of sedentary behaviour in the population studied might
be more than what we observed.
The main weakness of our cross-sectional study is that a
cause–effect relationship between the factors we examined and
their effect on physical activity cannot be assumed. We have
been careful to use the term ‘‘association’’ rather than
‘‘relationship’’. Therefore, our calculation of the population
effect of eliminating a risk factor, which assumes a cause–effect
relationship, needs to be interpreted with caution. We make no
claim here that making people feel safe in their neighbourhood
would, in itself, increase the number of people who would be
physically active. Rather, we have applied PIMs to highlight the
potential effect of changes in particular neighbourhood factors
on physical activity, and state that intervention studies are the
only sure way to examine their effect. However, in practice,
given the paucity of community-based evaluations, policy
makers often rely on cause–effect relationships to be assumed
to some degree. We have merely applied a population
perspective to such interpretation.
Few studies have previously examined the influence of
feelings of safety on physical activity, particularly in the UK. A
small cross-sectional study in England23found that women
were more likely to walk at least 15 min a week if they felt safe
during the day. In the US, perceptions of safety for walking
were associated with actual walking,24and crime was perceived
as more of a problem in socially deprived areas that also had
low levels of physical activity.25Similarly, Americans who
perceived their neighbourhood as less than extremely safe were
more than twice as likely to have no leisuretime physical
activity, and those who considered it to be not at all safe were
nearly three times as likely to have no leisuretime physical
activity.26However, in a Danish study, although participating in
sports activities was inversely related to perceptions about the
amount of police attention their neighbourhood received,27it
was not found to influence walking and cycling activities.
Evidence on the possible role of perceptions relating to the
location of leisure facilities and physical activity is conflicting.
Our own findings support an independent association of
perceived access to recreational facilities and physical activity,
although its population effect was much less than for feelings
of safety. This differs to the earlier study in England,23but
supports findings in Australia28and the US.29 30Consequently,
we argue the urgent need to carry out prospective studies in the
UK, which, wherever possible, will make full use of the many
‘‘natural experiments’’ around the country to obtain reliable
evidence on the effect of contextual changes on population
levels of physical activity.
Our study suggests that feeling unsafe in the neighbourhood is
as much of a barrier to physical activity as how well people
thought their home was for access to leisure facilities. As such,
strategies to increase physical activity need to emphasise the
perceived effect of feeling safe among the local population.
Encouraging people to spend more time walking for leisure and
commuting purposes seems to be a sensible approach to
incorporate physical activity within activities of daily living.
For this to become a reality, we need to start by ensuring that
people feel safe out and about in their neighbourhood.
R A Harrison, Bolton Primary Care Trust, Bolton, UK
I Gemmell, R F Heller, Evidence for Population Health Unit, Epidemiology &
Health Sciences, School of Medicine, University of Manchester,
Competing interests: None declared.
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What this paper adds
N Few studies have considered the wider determinants of
health on levels of physical activity in the population.
N Feeling safe in the home and out and about in the
neighbourhood may have as large an effect on popula-
tion levels of physical activity as factors such as access to
N Making people feel safer in their neighbourhood is a key
priority to increase population levels of physical activity.
38Harrison, Gemmell, Heller
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to engage with patients as equal partners at a deep level that
includes understanding both their illness and what it will mean
for patients in their life context.1However, there are difficulties
with the concept, both at the level of its definition and in its
At its worst, it is simply a buzz phrase, which sounds
good and allows managers and politicians to seem to be on
the patient’s side. In the wider economic sphere, Zuboff
and Maxmin4draw attention to the fact that many organisa-
tions that claim to be ‘‘customer focused’’ actually are not.
Perhaps patient centredness is the health sector’s equivalent
It is not always clear at what level patient centredness should
apply. Is it at the level of individual doctors and patients? Is it at
the level of the whole system? The idea that a healthcare system
that has to provide care to millions of patients can be focused
on one individual patient is clearly impossible.
It is far from clear that the health service should be entirely
patient centred. The health service must exist to meet the needs
of patients (if it does not do this, it has no function). The health
service cannot conceivably meet the needs of patients solely by
focusing on them.
Indeed, a one-sided approach focused solely on patients risks
alienating health professionals by playing down the importance
of their professional knowledge and skill. The knowledge of
atient centredness is one of the current buzz phrases in the
British National Health Service. At its best, the term
expresses a great aspiration, a wish for health professionals
medicine, and related professions, is entirely patient centred in
that it is all ultimately derived from the study of patients. It has
only one purpose, which is to help patients, and it is only
brought to fruition when this goal is achieved.
The argument should not be about patient or professional
centredness. The key unit of medicine is the professional–
patient dyad, the interaction in which hopefully the profes-
sional and the patient come to a useful shared understanding of
the patient’s illness or predicament.5
A truly patient-centred National Helth Service would support
both sides of the professional–patient dyad appropriately, and
would not look to champion one against the other. It would be
a shame if the ideal of patient centredness was lost to one-sided
interpretations of the term.
Correspondence to: Peter G Davies, Keighley Road Surgery, Illingworth,
Halifax HX2 9LL, UK; firstname.lastname@example.org
1 Stewart M. Towards a global definition of patient-centred care. BMJ
2 Elwyn G. Idealistic, impractical, impossible? Shared decision making in the real
world. Br J Gen Pract 2006;56:403–4.
3 Davies P. The beleaguered consultation. Br J Gen Pract 2006;56:226–9.
4 Zuboff S, Maxmin J. The support economy. New York: Penguin Books, 2002.
5 Neighbour R. The inner consultation 2nd edn. Oxford: Radcliffe Medical 2000.
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