The population effect of crime and neighbourhood on physical activity: An analysis of 15 461 adults

Article (PDF Available)inJournal of Epidemiology & Community Health 61(1):34-9 · February 2007with117 Reads
DOI: 10.1136/jech.2006.048389 · Source: PubMed
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.
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
authors’ affiliations
........................
Correspondence to:
R A Harrison, Evidence for
Population Health Unit,
Epidemiology & Health
Sciences, School of
Medicine, University of
Manchester, Oxford Road,
Manchester M13 9PT, UK;
roger.harrison@manche-
ster.ac.uk
Accepted 2 June 2006
........................
I
n the UK, as many as two thirds of adults live
sedentary lives,
12
representing one of the least
physically active nations of 15 European mem-
ber states.
3
Lack of regular physical activity is
associated with marked preventable mortality and
morbidity
4
and is a public health priority. Although
efforts to increase physical activity among indivi-
duals have had some small effect,
5–7
modifying
social, economic and environmental factors may be
more successful at the population level.
6
Indeed,
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
UK
8
despite sedentary behaviour being a major
public health concern. Increasing our understand-
ing of the relationship between physical activity,
‘‘who you are’’ and ‘‘where you live’’,
9
although
challenging,
6
is 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.
2
The 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).
10
PIMs provide a population
perspective by adding incidence information to
traditional measures of risk, such as the popula-
tion attribu
risk, thus, providing information on the actual
numbers of people who are at risk from specific
exposures in a particular population to assist local
policy decisions.
11
METHODS
The study was based in two districts in northwest
England, which is divided into 44 administrative
electoral wards. Data from the 2001 national
census calculated a resident population of
567 600 adults: 94% were white people and the
population density was 1700 people per square
kilometre.
12
Methods for data collection have been
described previously.
21314
In brief, data were
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 study.
The 50-item questionnaire sought information
on general and specific health, health behaviours
and perceptions of neighbourhood. Question
constructs were taken from previous national
Abbreviation: PIM, population impact measure
34
www.jech.com
surveys.
114
The questions specific to the neighbourhood
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).
15
Townsend Scores
from 1142 census enumeration districts for the two electoral
districts in the study were assigned using the participants’
postal code.
16
Physical activity was assessed using the Godin and Shephard
instrument.
17
This 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
Analysis
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,
Texas, USA).
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 is
10
:
PIN-ER = n6I
p
6PAR
where n is the population size; I
p
is the incidence of sedentary
behaviour (physical inactivity) in the whole population; PAR is
the population attributable risk (P
e
(RR21)/1+P
e
(RR21)); P
e
is
proportion of the population who is physically inactive; RR is
relative risk.
Calculations of the population attributable risk for variables
with multiple strata were adjusted according to the methods of
Hanley.
19
RESULTS
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).
Table 1 Prevalence of physical activity by baseline characteristics
Number of
respondents*
Physically active,
% (n)
Unadjusted relative
prevalence
(95% CI)
Adjusted relative
prevalence
(95% CI)
Everyone 15 461 27.1 (4193)
Sex
Male 6 984 27.6 (1927) 1.00 1.00
Female 8 477 26.7 (2266) 0.97 (0.92 to 1.02) 0.97 (0.92 to 1.01)
Ethnicity
Non-white 689 75.9 (523) 1.00 1.00
White 14 559 27.5 (4004) 1.14 (1.00 to 1.30) 1.32 (1.16 to 1.52)
Deprivation quintiles`
1 (least deprived) 3 512 30.4 (1066) 1.00 1.00
2 3 037 28.1 (853) 0.93 (0.86 to 1.0) 0.92 (0.85 to 0.99)
3 2 726 27.8 (759) 0.92 (0.85 to 0.99) 0.90 (0.84 to 0.97)
4 2 812 26.1 (734) 0.86 (0.79 to 0.93) 0.85 (0.78 to 0.91)
5 (most deprived) 3 279 22.9 (752) 0.76 (0.70 to 0.82) 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 activity 35
www.jech.com
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
(table 3).
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
Table 2 Association of physical activity with individual perceptions of neighbourhood facilities
Variable
Number of
respondents*
Physically active,
% (n)
Unadjusted relative
prevalence
(95% CI)
Adjusted relative
prevalence
(95% CI)
How well placed for leisure facilities?
Very well 2926 30.3 ( 886) 1.00 1.00
Fairly well 3792 29.4 (1115) 0.97 (0.90 to 1.05) 0.95 (0.88 to 1.02)
Average 4212 28.6 (1203) 0.94 (0.88 to 1.01) 0.96 (0.89 to 1.03)
Not very well 2192 26.3 (576) 0.87 (0.79 to 0.95) 0.90 (0.82 to 0.98)
Badly 1493 23.0 (344) 0.76 (0.68 to 0.85) 0.86 (0.77 to 0.94)
Feel of belonging to the area?
Strongly agree 3300 26.2 (864) 1.00 1.00
Agree 5928 26.9 (1594) 1.03 (0.96 to 1.10) 0.98 (0.92 to 1.05)
Neither agree nor disagree 4069 30.3 (1232) 1.16 (1.07 to 1.25) 0.99 (0.92 to 1.06)
Disagree 1042 28.7 (299) 1.10 (0.98 to 1.23) 0.93 (0.84 to 1.04)
Strongly disagree 451 29.1 (131) 1.11 (0.95 to 1.30) 0.90 (0.77 to 1.04)
How well placed for transport?
Very well 6728 27.9 (1878) 1.00 1.00
Fairly well 4380 28.4 (1244) 1.02 (0.96 to 1.08) 0.98 (0.92 to 1.04)
Average 2668 26.9 (718) 0.96 (0.90 to 1.04) 0.95 (0.88 to 1.01)
Not very well 780 28.1 (219) 1.01 (0.89 to 1.13) 1.01 (0.90 to 1.13)
Badly 335 24.2 (81) 0.87 (0.71 to 1.05) 0.89 (0.73 to 1.08)
How well placed for general shopping?
Very well 5059 28.1 (1423) 1.00 1.00
Fairly well 4626 29.1 (1344) 1.03 (0.97 to 1.10) 1.00 (0.94 to 1.06)
Average 3633 27.3 (991) 0.97 (0.90 to 1.04) 0.95 (0.90 to 1.01)
Not very well 1183 23.9 (283) 0.85 (0.76 to 0.95) 0.93 (0.83 to 1.03)
Badly 504 24.2 (122) 0.86 (0.73 to 1.01) 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).
Table 3 Association of individual perceptions of crime and safety with physical activity
Number of
respondents*
Physically active,
% (n)
Unadjusted relative
prevalence
(95% CI)
Adjusted relative
prevalence
(95% CI)
Feel safe out in neighbourhood
During the day?
Yes 14 155 28.3 (4009) 1.00 1.00
No 758 15.8 (120) 0.55 (0.47 to 0.66) 0.70 (0.59 to 0.82)
During the night?
Yes 9 601 31.1 (2982) 1.00 1.00
No 5 305 21.6 (1148) 0.70 (0.66 to 0.74) 0.82 (0.78 to 0.88)
How much of a problem to you are any of
the following
Vandalism?
Not a problem 5 424 28.0 (1518) 1.00 1.00
Some problem 7 799 28.5 (2221) 1.01 (0.96 to 1.08) 1.05 (1.00 to 1.11)
Serious problem 1 525 25.6 (391) 0.92 (0.83 to 1.01) 1.01 (0.92 to 1.12)
Assaults or muggings?
Not a problem 10 161 28.8 (2921) 1.00 1.00
Some problem 3 817 28.3 (1079) 0.98 (0.93 to 1.04) 1.01 (0.95 to 1.07)
Serious problem 372 25.3 (94) 0.88 (0.74 to 1.05) 0.91 (0.77 to 1.08)
Speeding traffic?
Not a problem 5 491 26.8 (1474) 1.00 1.00
Some problem 6 255 29.4 (18.7) 1.09 (1.03 to 1.16) 1.08 (1.10 to 1.14)
Serious problem 2 925 28.2 (824) 1.05 (0.98 to 1.13) 1.04 (0.97 to 1.11)
Personal experience of crime in the past year?
Yes 2 649 29.6 (786) 1.09 (1.02 to 1.17) 0.97 (0.91 to 1.03)
No 12 404 27.2 (3370) 1.00 1.00
*Not all respondents answered every question.
Adjusted for age, sex, ethnicity and deprivation (Townsend Score at enumeration district).
36 Harrison, Gemmell, Heller
www.jech.com
be physically active, but this was not consistent to this being a
serious problem.
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
(table 5).
DISCUSSION
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.
2
The 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
facilities.
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
Table 4 Estimated population effect on physical activity from changing neighbourhood perceptions
Number
Number of
respondents
answering this
question
RR of being
sedentary P
e
PAR
Number of adults
in this population
Proportion
physically active
overall PIN-ER*
Feel unsafe
During the day 758 14 913 1.43 0.05 0.021 567 600 0.27 3 290
During the night 5 305 14 606 1.23 0.34 0.073 567 600 0.27 11 237
How well placed for leisure
facilities
Very well 2 926 14 615 Ref Ref Ref
Fairly well 3 792 14 615 1.05 0.26 0.01
Average 4 212 14 615 1.04 0.29 0.01
Not very well 2 192 14 615 1.11 0.15 0.02
Badly 1 493 14 615 1.16 0.10 0.02
Overall PAR 0.05 567 600 0.27 8 342
PAR, population attributable risk; P
e
, 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 = n6I
p
6PAR, where n is the population size; I
p
, the incidence of sedentary behaviour
(physical inactivity) in the whole population; PAR = (P
e
(RR21)/1+P
e
(RR21)).
Table 5 Number of people in the total population expected to become physically active if neighbourhood perceptions improved
Number of
adults in this
population
Currently
physically active
(%)*
Currently
physically active
(n) PIN-ER`
Expected to be
physically active
(n)1
Expected to be
physically active
(%)
Absolute increase in
people expected to
be physically active
(%)**
Feel safe
During the day 567 600 27.0 153 252 3 290 156 542 27.6 0.6
During the night 567 600 27.0 153 252 11 237 164 489 29.0 2.0
How well placed for
leisure facilities
Very well 567 600 27.0 153 252 8 342 161 594 28.5 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 activity 37
www.jech.com
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.
10
PIMs
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 20
In the current study, this
method has been used to estimate the effect of neighbourhood
and neighbourhood perceptions on sedentary behaviour in
adults.
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,
21
supporting 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.
22
Therefore, 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 England
23
found 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,
24
and crime was perceived
as more of a problem in socially deprived areas that also had
low levels of physical activity.
25
Similarly, 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.
26
However, in a Danish study, although participating in
sports activities was inversely related to perceptions about the
amount of police attention their neighbourhood received,
27
it
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,
23
but
supports findings in Australia
28
and the US.
29 30
Consequently,
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.
CONCLUSION
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.
Authors’ affiliations
.......................
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,
Manchester, UK
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
leisure facilities.
Policy implications
N
Making people feel safer in their neighbourhood is a key
priority to increase population levels of physical activity.
38 Harrison, Gemmell, Heller
www.jech.com
10 Heller R. Evidence for population health. Oxford: Oxford Medical Publications,
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11 Heller RF, Buchan I, Edwards R, et al. Communicating risks at the
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2002;31:872–4.
14 Office for National Statistics. Census 2001. General report for England and
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North. London: Croom Helm, 1988.
16 Adams J, Ryan V, White M. How accurate are Townsend Deprivation Scores as
predictors of self-reported health? A comparison with individual level data.
J Public Health 2004;27:101–6.
17 Godin G, Shephard R. A simple method to assess exercise behavior in the
community. Can J Appl Sports Sci 1985;10:141–6.
18 Zou G. A modified Poisson regression approach to prospective studies with
binary data. Am J Epidemiol 2004;159:702–6.
19 Hanley JA. A heuristic approach to the formulas for population attributable
fraction. J Epidemiol Community Health 2001;55:508–14.
20 Gemmell I, Heller RF, McElduff P, et al. Population impact of stricter adherence to
recommendations for pharmacological and lifestyle interventions over one year
in patients with coronary heart disease. J Epidemiol Community Health
2005;59:1041–6.
21 Hillsdon M, Thorogood M, Murphy M, et al. Can a simple measure of vigorous
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Health Nutr 2003;7:557–62.
22 Hill A, Roberts J, Ewings P, et al. Non-response bias in a lifestyle survey. J Public
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SPEAKERS CORNER...........................................................................................
Patient centredness
P
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
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.
1
However, there are difficulties
with the concept, both at the level of its definition and in its
implementation.
23
At its worst, it is simply a buzz phrase, which sounds
good and allows managers and politicians to seem to be on
the patients side. In the wider economic sphere, Zuboff
and Maxmin
4
draw attention to the fact that many organisa-
tions that claim to be ‘‘customer focused’’ actually are not.
Perhaps patient centredness is the health sectors equivalent
term.
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
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 patients illness or predicament.
5
A truly patient-centred National Helth Service would support
both sides of the professionalpatient 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; npgdavies@blueyonder.co.uk
References
1 Stewart M. Towards a global definition of patient-centred care. BMJ
2001;322:4445.
2 Elwyn G. Idealistic, impractical, impossible? Shared decision making in the real
world. Br J Gen Pract 2006;56:4034.
3 Davies P. The beleaguered consultation. Br J Gen Pract 2006;56:2269.
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.
Effect of crime and neighbourhood on physical activity 39
www.jech.com
    • "Contrary to some previous studies, which have considered other services or facilities (including proximity to schools or to work) to be more relevant for residential satisfaction (Türksever and Atalik 2001; Sirgy and Cornwell 2002), here the possibility of practising outdoor sports enhances residential satisfaction as it promotes social interaction (Oh 2003; Dassopoulos et al. 2012), which in turn increases the level of trust in social relationships and decreases feelings of insecurity (Harrison, Gemmell, and Heller 2007). Those inhabitants placing importance on city safety, neighbourly cooperation and the availability of areas for outdoor sports (node 8) with regard to residing in the respective cities report themselves to be satisfied (81%), and are predominantly young and middleaged residents, reinforcing their sense of belonging and safety (Harrison, Gemmell, and Heller 2007; Aiello, Ardone, and Scopelliti 2010). This result is in line with the finding of Santos, Martins, and Brito (2007) for Oporto that young people tend to value aspects related to leisure and tend to have a more favourable assessment of the city. "
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    [Show abstract] [Hide abstract] ABSTRACT: Cities facing a continued and prolonged process of population decline require innovative urban regeneration policies complementary to growth-oriented policies. Losing inhabitants involves a decrease in economic activity and social capital. Therefore citizens’ participation in defining policies to cope with population decline is being increasingly advocated. This research focused on four shrinking cities of Portugal to capture residents’ knowledge about the strengths and weaknesses of their city of residence as well as the policies and actions they prioritized for dealing with the population decline. The responses from 701 questionnaires show that economic revival policies as well as safety and accessibility policies were preferred. To put these policies into action, the recovery of industrial activity, the creation of business incubators, an improvement in law enforcement, and public lighting were ranked as top priorities. Rank-ordered logistic regression models were used to understand which variables influenced the residents’ rankings. We found that the evaluation of the city's characteristics impact the ranking of the policies and actions. Hence, residents show a high level of coherence when engaging in a discussion at the level of policy-making. Therefore, the findings support residents’ involvement in decision-making processes regarding urban regeneration in shrinking cities. Free download: http://www.tandfonline.com/eprint/b3ayFQbdq57cv8XEfkMJ/full
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    • "This is important to examine as research has documented that some barriers, such as safety, are more of a concern for women than for men. There is also evidence from past research that men are more likely to use walking than women323334, highlighting the importance of examining sex differences in perceived barriers to walking. Household income is defined in this study based on low-income cut-offs (LICO) as published by Statistics Canada [35]. "
    [Show abstract] [Hide abstract] ABSTRACT: This study investigates perceived barriers to walking using data collected from 179 randomly-selected adults between the ages of 18 and 92 in Hamilton, Ontario, Canada. A survey (Hamilton Active Living Study) asked questions about socio-demographics, walking, and barriers to walking. A series of binary logit models are estimated for twenty potential barriers to walking. The results demonstrate that different barriers are associated with different sub-groups of the population. Females, senior citizens, and those with a higher body mass index identify the most barriers to walking, while young adults, parents, driver's license owners, and bus pass owners identify the fewest barriers. Understanding who is affected by perceived barriers can help policy makers and health promotion agencies target sub-groups of the population in an effort to increase walking.
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