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European transnational ecological deprivation index and index and participation in beast cancer screening ...
[ Pobierz całość w formacie PDF ]Preventive Medicine 63 (2014) 103
–
108
Contents lists available at
Preventive Medicine
journal homepage: www.elsevier.com/locate/ypmed
European transnational ecological deprivation index and participation in
population-based breast cancer screening programmes in France
Samiratou Ouédraogo
a
,
b
,
, Tienhan Sandrine Dabakuyo-Yonli
b
,
c
, Adrien Roussot
d
, Carole Pornet
e
,
f
,
g
,
Nathalie Sarlin
h
,PhilippeLunaud
i
,PascalDesmidt
j
, Catherine Quantin
d
,
k
, Franck Chauvin
l
,
m
,
Vincent Dancourt
k
,
n
,PatrickArveux
a
,
b
a
Breast and Gynaecologic Cancer Registry of Cote d'Or, Georges-François Leclerc Comprehensive Cancer Care Centre, 1 rue Professeur Marion, 21000 Dijon, France
b
EA 4184, Medical School, University of Burgundy, 7 boulevard Jeanne d'Arc, 21000 Dijon, France
c
Biostatistics and Quality of Life Unit, Georges-François Leclerc Comprehensive Cancer Care Centre, 1 rue du Professeur Marion, 21000 Dijon, France
d
Service de Biostatistique et d'Informatique Médicale, University Hospital of Dijon, 21000 Dijon, France
e
Department of Epidemiological Research and Evaluation, CHU de Caen, France
f
EA3936, Medical School, Université de Caen Basse-Normandie, Caen, France
g
U1086 Inserm, Cancers and Preventions, Medical School, Université de Caen Basse-Normandie, Avenue de la Côte de Nacre, 14032 Caen Cedex, France
h
Caisse Primaire d'Assurance maladie de la Côte d'Or, 8 rue du Dr Maret, 21000 Dijon, France
i
Régime Social des Indépendants de Bourgogne, 41 rue de Mulhouse, 21000 Dijon, France
j
Mutualité Sociale Agricole de Bourgogne, 14 rue Félix Trutat 21000 Dijon, France
k
Inserm U866, Medical School, University of Burgundy, 21000 Dijon, France
l
Institut de Cancérologie Lucien Neuwirth, CIC-EC 3 Inserm, IFR 143, Saint-Etienne, France
m
Université Lyon 1, CNRS UMR 5558 and Hospices Civils de Lyon, Lyon, France
n
Association pour le Dépistage des Cancers en Côte d'Or et dans la Nièvre (ADECA 21-58), 16
⁎
–
18 rue Nodot, 21000 Dijon, France
article info
abstract
Available online 15 December 2013
Background: We investigated factors explaining low breast cancer screening programme (BCSP) attendance
taking into account a European transnational ecological Deprivation Index.
Patients and methods: Data of 13,565 women aged 51
Keywords:
Breast cancer screening programmes
Screening programme attendance
Mammography screening
Prevention
Socioeconomic inequalities
European Deprivation Index
74 years old invited to attend an organised mammog-
raphy screening session between 2010 and 2011 in thirteen French departments were randomly selected. Infor-
mation on the women's participation in BCSP, their individual characteristics and the characteristics of their area
of residence were recorded and analysed in a multilevel model.
Results: Between 2010 and 2012, 7121 (52.5%) women of the studied population had their mammography
examination after they received the invitation. Women living in the most deprived neighbourhood were less
likely than those living in the most af
–
uent neighbourhood to participate in BCSP (OR 95%CI = 0.84[0.78
–
0.92]) as were those living in rural areas compared with those living in urban areas (OR 95%CI = 0.87[0.80
–
0.95]). Being self-employed (p
0.0001) or living more than 15 min away from an accredited screening centre
(p = 0.02) was also a barrier to participation in BCSP.
Conclusion: Despite the classless delivery of BCSP, inequalities in uptake remain. To take advantage of preven-
tion and to avoid exacerbating disparities in cancer mortality, BCSP should be adapted to women's personal and
contextual characteristics.
b
© 2014 Elsevier Inc. All rights reserved.
Introduction
Breast cancer (BC) is the leading cancer site and the leading cause of
death from cancer among women in Europe (
Ferlay et al., 2013
). It is
more a progressive than a systemic disease (
Tabar and Dean, 2010
)
and the progression of this disease can be slowed through early detec-
tion on mammography screening (MS) and treatment at an early
stage (
Autier, 2011; Autier et al., 2009; Ballard-Barbash et al., 1999;
Giordano et al., 2012
). Estimates of mortality reduction attributed to
screening range from 10 to 30% (
Arveux et al., 2003; Broeders et al.,
2012; Giordano et al., 2012; Peipins et al., 2011; Perry et al., 2008;
Corresponding author at: Breast and Gynaecologic Cancer Registry of Cote d'Or,
Georges-François Leclerc Comprehensive Cancer Care Centre, 1 rue Professeur Marion,
21000 Dijon, France. Fax: +33 3 80 73 77 34.
E-mail addresses:
(S. Ouédraogo),
⁎
.fr
(T.S. Dabakuyo-Yonli),
(A. Roussot),
(C. Pornet),
(N. Sarlin),
(P. Lunaud),
(P. Desmidt),
(C. Quantin),
(F. Chauvin),
(V. Dancourt),
.fr
(P. Arveux).
–
0091-7435/$
see front matter © 2014 Elsevier Inc. All rights reserved.
104
S. Ouédraogo et al. / Preventive Medicine 63 (2014) 103
108
–
Puliti and Zappa, 2012; Smith et al., 2011
). Despite controversies around
the bene
100% of new information and no new information is obtained with the increase
in the number of subjects for a certain cluster (IRIS). Then, 13,565 women were
randomly selected from the eligible population without replacement. With this
sample size, the study would have a power of 90% to detect a difference of at
least 10% on participation rates between deprived and af
t and harm of MS (
Gotzsche and Jorgensen, 2013;
Independent UK Panel on Breast Cancer Screening, 2012; Jorgensen
and Gotzsche, 2009; Jorgensen et al., 2009
), organised mammography
screening programmes (SP) have been implemented inmany countries.
According to the European recommendations, to reduce BC mortality
through MS, programmes must reach a participation rate of 70% of the
target population (
von Karsa et al., 2008
) with regular attendance to
screening (
Arveux et al., 2003; Giordano et al., 2012; Ouedraogo et al.,
2011
). In several Northern European countries, participation of around
80% has been achieved (
Hakama et al., 2008
). However, in France as in
many other European countries, the annual national participation rate
barely exceeds 50% (
European Commission and Eurostat, 2009
).
Factors explaining non-attendance in breast cancer screening (BCS)
have been examined in many previous studies (
Barr et al., 2001; Dailey
et al., 2007, 2011; Engelman et al., 2002; Esteva et al., 2008; Gonzalez
and Borrayo, 2011; Hyndman et al., 2000; Jackson et al., 2009; Kinnear
et al., 2011; Lagerlund et al., 2000; Pornet et al., 2010; von Euler-
Chelpin et al., 2008
). Neighbourhood income had been widely reported
to be an important determinant of participation in BCS programmes. In
the United Kingdom or in Canada, where the National health services
provide free BCS for all eligible women, lower uptake in more deprived
areas and in areas further away from screening locations has been re-
ported (
Kothari and Birch, 2004; Maheswaran et al., 2006
). However,
these studies performed in Anglo-Saxon countries used neighbourhood
deprivation indicators like the Townsend score (
Townsend, 1987
)
which is more appropriate for the context in these countries. Recently,
a new ecological deprivation index called the European Deprivation
Index (EDI), which is based on a European survey, has become available
(
Pornet et al., 2012
). This Index corresponds better to cultural and social
policy in European countries as a whole.
To harmonize analysis and allow the inclusion of intervention-based
studies performed elsewhere it is necessary to use transnational indica-
tors. The ultimate goal of this study was to identify barriers to participa-
tion in SP in order to implement action that could increase programme
attendance. We conducted this large study to investigate predictive fac-
tors of low participation in population-based mammography SPs in
thirteen French departments taking into account the new EDI and puta-
tive factors such as the type of health insurance plan, the travel time to
the nearest MS centre and the urban-rural status of the place of
residence.
uent IRISes (50% par-
ticipation rate in deprived IRISes and 60% participation rate in af
uent IRISes)
with an alpha risk of 0.05. This study was approved by ethics committees:
“
Comité Consultatif sur le Traitement de l'Information en matière de Recherche
dans le domaine de la Santé
”
,
“
Commission Nationale de l'Informatique et des
Libertés
”
and the Ethics Committee of Besançon Teaching Hospital.
Studied variables
Data on participation and other individual information such as the women's
age, their health insurance scheme, their address and the address of the
accredited screening centres in the department were provided by institutions
in charge of organising SPs. Lists of accredited screening facilities are provided
regularly by the French health authorities. These centres meet baseline quality
standards for equipment and professional abilities and are allowed to perform
BCS.
Age was entered as
–
74 years old). The women were insured by one of the three main health insur-
ance schemes: the general medical insurance scheme (GMIS), which insures
employees; the agricultural insurance scheme (AIS), which insures farm
workers and the self-employed insurance scheme (SEIS), which insures the
self-employed.
As women eligible for BCS programmes are aged 50
ve categories (51
–
54, 55
–
59, 60
–
64, 65
–
69 and 70
74 years old, and in our
population, about 57% were more than 60 years old and thus probably retired,
the travel time from their place of residence to the nearest accredited screening
centre by private car was considered. The travel time was calculated using
“
–
software based on a road route algorithm. Based on its distribution
and on the literature (
Evain, 2011
), the travel time to the nearest accredited
screening centre was split into two categories: living at most 15 min away or
more than 15 min away.
The French EDI, which re
MOViRIS
”
ects fundamental needs and is associatedwith ob-
jective and subjective poverty (
Pornet et al., 2012
), was calculated for each IRIS
on the basis of ten variables: variables related to households (the percentage of
households with more than one person per room, those with no central or elec-
tric heating system, those that are not owner-occupied, those with no access to
a car, thosewith six persons or more and the percentage of single-parent house-
holds) and other variables concerning the residents: the percentage of unem-
ployed people, foreign nationals, unskilled or skilled factory workers and
persons with a low level of education. Preliminary validation showed that the
French EDI presents a stronger association with two socioeconomic variables
measured at an individual level: income (p trend = 0.0059) and educational
level (p trend = 0.0070) than does the Townsend score (p trend = 0.0409
and p trend = 0.2818, respectively) (
Pornet et al., 2012
). The scores were divid-
ed into three classes according to their distribution: themost af
Methods
uent, the inter-
mediate and the most deprived class. For each IRIS, the environment (rural,
semi-urban or urban)was also provided by the French National Institute for Sta-
tistics and Economic Studies.
Study population
We examined data of women aged 51 to 74 years old invited to attend a
free-of-charge organised MS session between 2010 and 2011 in France. In
France, women aged from50 to 74 years old are eligible for the BCS programme.
Thosewho had not had theirmammography sixmonths after the
Statistical analyses
rst invitation
received a reminder. We retained data on women aged 51
74 years old to con-
sider the delay between the invitation to attend an MS session and having the
examination. The study was conducted in thirteen French departments: Côte
d'Or, Nièvre, Rhône, Ain, Loire, Haute Savoie, Ardèche, Isère, Drôme, Doubs,
Jura, Haute Saône and Territoire de Belfort. France counts 101 departments
which are territorial divisions between regions and districts. The departments
included in this study accounted for about 12% of women eligible for BCS in
France in 2010
–
Analyses were performed using STATA Data Analyses and Statistical Soft-
ware (StataCorp LP, College Station, Texas, USA). Categorical variables are
given as percentages with the percentage of missing data, while continuous var-
iables are given as means, standard deviations (SD), medians and ranges. Khi2
or Fisher's exact tests and the Mann and Whitney or Kruskal and Wallis non-
parametric tests were used for categorical and continuous variables, respective-
ly, to compare variables inwomenwho participated in organised SPs with those
in women who did not.
The effects of characteristics at the individual and area-level on participation
in population-based SPs were assessed using univariable logistic regression
models. All variables with a p
2011. The study concerned 709,764 eligible women insured
by the three main health insurance schemes and for whom addresses were
available, corresponding to 66% of the women eligible for BCS in the thirteen
departments.
Each French department is also divided into smaller geographical census
units of 1800 and 5000 inhabitants called IRIS (
–
0.20 from univariable logistic analyses were el-
igible for inclusion in the multilevel multivariable model (using the
≤
”
command in Stata 11 software). Correlations and interactions between vari-
ables in each level were tested. We also examined cross-level interactions be-
tween the effects of neighbourhood and individual factors. Multilevel
multivariable logistic regression was then performed using individual and
area level variables in the same model. All reported p-values are two sided.
The statistical signi
“
xtmelogit
“
Ilots Regroupés pour
l'Information Statistique
: Merged Islet for Statistical Information). The major
towns are divided into several IRISes and small towns form one IRIS (
Pornet
et al., 2010
). The departments included in this study comprised a total of 6806
IRISes. According to
Twisk (2006)
, the sample-size in multilevel studies can be
calculated in a
”
“
conservative
”
manner, in which the
rst individual provides
cance level was set at p
0.05.
b
S. Ouédraogo et al. / Preventive Medicine 63 (2014) 103
–
108
105
Results
Table 2
Comparison of individual and area characteristics between women who participated in an
organised breast cancer screening programme and those who did not in a sample of
women invited to attend an organised mammography screening session between 2010
and 2011 in thirteen French departments.
Characteristics of the studied population
–
74 years old invited
to attend an organised MS session between 2010 and 2011 in thirteen
French departments. A total of 7121 (52.5%) women of the sample
attended the BCS session between 2010 and 2012 after they received
the invitation. The main characteristics of the studied population
were: age 55
This study concerned 13,565 women aged 51
Variables
Non-participants
Participants
P value
N =6444 %
N =7121 %
Individual level variables
Age (year)
b
0.0001
51
–
54
1247
19.3
1228
17.2
64 years old (50.5%), covered by the GMIS (86.9%), living
in semi-urban or urban areas (69.7%) and 15 min at most from an
accredited screening centre (62.5%) (
Table 1
).
–
55
–
59
1517
23.5
1898
26.6
–
60
64
1565
24.3
1862
26.1
65
–
69
1133
17.6
1263
17.7
70
–
74
982
15.2
870
12.2
Missing
0
0.0
0
0.0
Comparison of the characteristics of women who attended organised MS
and those who did not
Health Insurance Schemes
0.0001
b
General medical insurance scheme
5529
85.8
6264
88
Agricultural insurance scheme
735
11.4
726
10.2
–
Participation in MS was greater in women aged 55
64 years old
Self-employed insurance scheme
180
2.8
131
1.8
Missing
0
0.0
0
0.0
(p
0.0001), in women living in the most af
uent areas (p
0.0001)
b
b
and in urban and semi-urban areas (p
0.0001). Womenwho attended
the screening sessions were more likely to be insured by the GMIS
(p
b
Travel time to the nearest
accredited screening
centre (min)
b
0.0001
0.0001) and to live atmore than 15 min froman accredited screen-
ing centre (p
b
b
0.0001) than were those who did not attend (
Table 2
).
≤
15
3893
60.4
4583
64.4
15
2395
37.2
2389
33.5
N
Missing
156
2.4
149
2.1
Area level variables
French European Deprivation
Index
Table 1
Characteristics of the studied population: A sample of women invited to attend an
organised mammography screening session between 2010 and 2011 in thirteen French
departments.
b
0.0001
Tertile 1 (Most af
uent)
2594
40.2
3129
43.9
Tertile 2
2030
31.5
2180
30.6
Tertile 3 (Most deprived)
1820
28.2
1812
25.4
Categorical variables
N =13,565
%
Missing
0
0.0
0
0.0
Individual level variables
Participation in organised
breast cancer screening
No
Place of residence
b
0.0001
Urban or semi-urban
4332
67.2
5117
71.9
Rural
2112
32.8
2004
28.1
6444
47.5
Missing
0
0.0
0
0.0
Yes
7121
52.5
Missing
0
0.0
Percentages may not add to 100% due to rounding.
Age (years)
51
–
54
2475
18.2
55
–
59
3415
25.2
60
–
64
3427
25.3
Predictive factors of participation in organised BCS programmes
65
–
69
2396
17.7
70
–
74
1852
13.6
Univariable logistic regression analyses showed that all individual-
level characteristics such as age (p
Missing
0
0.0
0.0001), the type of health insur-
ance scheme (p = 0.0001) and the travel time to the nearest accredited
screening centre (p
b
Health Insurance Schemes
General medical insurance scheme
11,793
86.9
Agricultural insurance scheme
1461
10.8
0.0001) and area-level variables such as the EDI
(p = 0.0006) and rurality (p
b
Self-employed insurance scheme
311
2.3
0.0001) were predictive factors for par-
ticipation in BCS programmes (
Table 3
).
Multivariable multilevel analyses con
b
Missing
0
0.0
Travel time to the nearest
accredited screening centre (min
a
)
rmed that women aged 55
–
≤
15
8476
62.5
59, 60
69 years old were more likely to attend screening
sessions. Odds ratios and 95% con
–
64 and 65
–
15
4784
35.3
N
dence intervals (OR 95% CI) were
Missing
305
2.2
1.28[1.15
1.30], respectively.
Only women insured by the SEIS were less likely than those insured
by the GMIS to attend screening sessions OR 95% CI = 0.62[0.49
–
1.42], 1.22[1.10
–
1.36] and 1.16[1.04
–
Area level variables
French European Deprivation
Index
Tertile 1 (Most af
–
0.78]. Women living in the most deprived IRISes, those living in rural
IRISes and those living at more than 15 min from an accredited screen-
ing centre were less likely to perform MS: OR 95% CI were 0.84[0.78
uent)
5723
42.2
Tertile 2
4210
31.0
Tertile 3 (Most deprived)
3632
26.8
–
Missing
0
0.0
–
–
0.92], 0.87[0.80
0.95] and 0.91[0.84
0.99], respectively (
Table 3
).
Place of residence
Urban or semi-urban
9449
69.7
Discussion
Rural
4116
30.3
Missing
0
0.0
Mean (SD
b
)
Continuous Variables
Median [Min
Max]
–
This study was conducted to investigate factors explaining atten-
dance at BCS sessions in thirteen French departments taking into ac-
count a transnational EDI. The studied population was representative
of women invited to take part in organised MS sessions in these areas
in 2010
Age (year)
61.3 (6.3)
61 [51
–
74]
Travel time to the nearest
accredited screening centre (min)
12.8 (11.3)
11 [0
–
105]
Percentages may not add to 100% due to rounding.
a
Min: Minutes.
b
SD: Standard Deviation.
–
2011 and who were af
liated to one of the three major health
insurance schemes.
106
S. Ouédraogo et al. / Preventive Medicine 63 (2014) 103
108
–
Table 3
Univariable and multivariable multilevel logistic regression analyses to determine individual and area predictors of participation in organised breast cancer screening in a sample of
women invited to attend an organised mammography screening session between 2010 and 2011 in thirteen French departments.
Variables
N = 13,565
Participation vs. non-participation in organised breast cancer screening
Univariable logistic regression analyses
Multilevel logistic regression analyses
N =13,260
OR
a
[95% CI
b
]
OR
a
[95% CI
b
]
P value
P value
Individual level variables
Age (year)
13,565
0.0001
⁎
0.0001
⁎
b
b
51
–
54
1.00
1.00
55
–
59
1.28 [1.15
–
1.42]
0.0001
1.28 [1.15
–
1.42]
0.0001
b
b
60
–
64
1.22 [1.10
–
1.35]
0.0001
1.22 [1.10
–
1.36]
0.0001
b
b
65
–
69
1.14 [1.02
–
1.28]
0.02
1.16 [1.04
–
1.30]
0.01
70
–
74
0.90 [0.80
–
1.02]
0.1
0.91 [0.80
–
1.03]
0.1
Health Insurance schemes
13,565
0.0001
⁎
0.0003
⁎
General medical insurance scheme
1.00
1.00
Agricultural insurance scheme
0.87 [0.78
–
0.97]
0.01
0.94 [0.83
–
1.05]
0.26
Self-employed insurance scheme
0.65 [0.51
–
0.82]
0.0001
0.62 [0.49
–
0.78]
0.0001
b
b
Travel time to the nearest
accredited screening centre (min)
13,260
15
1.00
1.00
≤
N
15
0.86 [0.80
–
0.93]
b
0.0001
⁎
0.91 [0.84
–
0.99]
0.02
⁎
Area level variables
French European Deprivation Index
13,565
⁎
⁎
0.0006
0.0005
Tertile 1 (Most af
uent)
1.00
1.00
Tertile 2
0.91 [0.84
–
0.99]
0.03
0.94 [0.87
–
1.02]
0.16
Tertile 3 (Most deprived)
0.85 [0.77
–
0.92]
0.0001
0.84 [0.78
–
0.92]
0.0001
b
b
Place of residence
13,565
Urban or semi-urban
1.00
1.00
–
0.89]
⁎
–
0.95]
⁎
Rural
0.82 [0.76
b
0.0001
0.87 [0.80
0.001
a
OR: Odds Ratio.
b
CI: Con
dence Interval.
⁎
Global P Value of the variable.
The results of the study show that individual characteristics like age,
the type of health insurance scheme and travel time to the nearest
mammography facility are associated with participation in BCS
programmes. Indeed, women aged 55
lack of time due to the increased professional responsibilities in this
group.
Screening increased with decreasing levels of socioeconomic depri-
vation. Women who lived in the intermediate and most af
69 years old were more likely
to attend MS sessions than were those aged 51
–
uent IRISes
–
54 years old. However,
were more likely to participate in SPs. This result con
rmed previous
there was no statistically signi
cant difference for participation be-
ndings on the topic using other deprivation indexes than the EDI
(
Dailey et al., 2007, 2011; Maheswaran et al., 2006; Pornet et al., 2010;
von Euler-Chelpin et al., 2008
).
Peek and Han (2004)
reported that vul-
nerable groups such as the poor, the elderly and minorities were often
unaware of mammography screening programmes, had misconcep-
tions regarding cancer, viewedmammography negatively and had fatal-
istic attitudes about cancer. Qualitative studies performed within
populations in socioeconomically-disadvantaged neighbourhoods
show a lack of information and/or a lack of awareness of disease preven-
tion, diagnosis and treatment. Underestimation and a lack of anticipa-
tion of risks have also been noted among these populations (
Chamot
et al., 2007; Chauvin and Parizot, 2009
).
Our results also show that women living far from an accredited
screening centre and those living in rural localities were less likely to at-
tend MS sessions. This result is in keeping with previous
tween women aged 51
–
54 and those aged 70
–
74 years old. Women
aged 51
54 years old are newly enrolled in the SP. They generally at-
tend individual mammography sessions on their own initiative or on
the advice of their family doctor before joining the organised pro-
gramme (
Hirtzlin et al., 2012
). For older women, knowledge about BC
is poor (
Grunfeld et al., 2002
), particularly knowledge about BC symp-
toms, the level of risk (
Linsell et al., 2008
) and diagnosis of the disease.
Moreover, they are uncertain about their eligibility to take part in SPs
(
Collins et al., 2010
). Until 2003, the BCS programme was limited to a
few departments in France. In 2004, the programme was extended to
all departments. Women aged over 50 years at that time (over
56 years in 2010
–
–
2011) thus became eligible for BCS in the organised
programme and attended screening sessions. This can explain the high
participation rate in SP in the intermediate age group in our study
(55
ndings from
the United Kingdom and the United States of America (
Engelman et al.,
2002; Hyndman et al., 2000; Maheswaran et al., 2006; Wang et al.,
2008
). There is a signi
69 years old). Our results are in accordance with those of
Poncet
et al. (2013)
, who reported that screening uptake was lower among
the youngest (50
–
–
54 years) and the oldest (70
–
74 years) women
cant inverse relationship between the distance
a woman must travel for screening and her likelihood of attending. How-
ever, this has a relatively minor effect on attendance rates compared
with the impact of socioeconomic factors (
Maxwell, 2000
). The reasons
why rural women are less likely than non-rural women to take advan-
tage of preventive services include greater distances to medical facilities
and lower availability of services. Moreover, there are lower education
and income levels in rural areas (
Carr et al., 1996; Coughlin et al., 2002,
2008
). Indeed, in our thirteen departments, semi-urban and urban
than in the intermediate age-group (55
69 years).
Women insured by the SEIS were less likely than those insured by
the GMIS to participate in the programme.
Pornet et al. (2013)
also re-
ported lower participation in organised colorectal screening among
women insured by agricultural and SEIS than those insured by the
GMIS.
Jensen et al. (2012)
reported that the self-employed and chief ex-
ecutives were less likely than employed women to participate in BCS.
The barrier to MS participation in self-employed women could be the
–
S. Ouédraogo et al. / Preventive Medicine 63 (2014) 103
–
108
107
areas seemed to be those with a privileged or intermediate socio-
economic status while rural areas tended to include more deprived IRIS-
es and to be located far from mammography facilities.
d'Or, Nièvre, Rhône, Ain, Loire, Haute Savoie, Ardèche, Isère,
Drôme, Doubs, Jura, Haute Saône and Territoire de Belfort.
Conclusion
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