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All content in this area was uploaded by Daniele Masala on Oct 25, 2017
Content may be subject to copyright.
European Journal of Public Health, 1–7
ßThe Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
doi:10.1093/eurpub/ckx183
.........................................................................................................
Health related quality of life and physical activity in
prison: a multicenter observational study in Italy
Alice Mannocci
1
, Daniele Mipatrini
1
, Valeria D’Egidio
1
, Jenny Rizzo
1
, Sara Meggiolaro
1
,
Alberto Firenze
2
, Giovanni Boccia
3
, Omar E. Santangelo
2
, Paolo Villari
1
, Giuseppe La Torre
1
,
Daniele Masala
4
1 Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
2 Department of Sciences for Health Promotion and Mother and Child Care ‘Giuseppe D’Alessandro’, University of
Palermo, Palermo, Italy
3 Department of Medicine, Surgery and Dentistry ‘Scuola Medica Salernitana’, University of Salerno, Salerno, Italy
4 Department of Human, Social and Health Sciences, University of Cassino and Southern Lazio, Casssino, Italy
Correspondence: Alice Mannocci, Department of Public Health and Infectious Diseases, Sapienza University of Rome,
Piazzale Aldo Moro 5, 00185 Rome, Italy, Tel: +390649694308, Fax: +39 06 4991 4653, e-mail: alice.mannocci@uniroma1.it
Background: Inmates have a poorer health status than the general population. The physical activity is well know
that improve the wellness of the people. This multicentric cross-sectional study aimed to assess the relationship
between Quality of Life (QoL) and physical activity levels among Italian prisoners. Methods: Inmates from eight
prisons compiled a questionnaire. The Metabolic Equivalent of Task (MET) was used to measure inmates’ weekly
physical activity levels (MATwk). Their QoL was measured using two components of Short Form with 12 items
(SF12): MCS (mental score) and PCS (physical score). Results: A total of 636 questionnaires were compiled. High
level of MET was significantly (P<0.05) associated with both PCS (OR = 1.02) and MCS (OR = 1.03). The correlations
between PCS, MCS vs. METwk scores were respectively significant: r= 0.17 and r= 0.10, P< 0.05. The number of
years of detention was associated to higher MET (OR = 1.04 P< 0.05). The presence of Physical Exercise Areas (PEAs)
within Jails did not improve the QoL level. Conclusions: Jails may not seem like the ideal place to fight sedentary
behavior, but, in any case, health promotion can occur within its walls. The heterogeneity of Italian jails, and
particularly relative PEAs therein (areas had different characteristics between jails), suggests that such spaces
should be regulated or well defined. Furthermore, the implement of training schedules could be done in a
standardized way. Despite this heterogeneity both the physical and mental components of inmates’ quality of
life were associated to a high level of physical activity.
.........................................................................................................
Introduction
Prisoners usually have a poorer health status than the general
population.
1
Penal institutions are generally sickness-prone
places, and are often overcrowded.
2
One aspect that afflicts peni-
tentiary inmates is that they are at greater risk of unhealthy
behaviors such as smoking, drug abuse, inactivity and irregular
diet, factors that often lead to the development of a high rate of
acute and chronic physiological and psychological disease. In
particular, incarceration has been associated with sedentary
habits, a known risk factor for diabetes mellitus, heart disease
and other chronic disabilities.
3
The impact of the institution
itself can contribute to an unhealthy living condition,
4
but it can
also promote redemption.
1
Concerning physical inactivity, it is now known that there is a
connection between physical exercise and Health Related Quality of
Life (HRQoL) in the general population. Exercise impacts not just
physical mobility but its lack can also favor mental and sensory
impairment.
5
Aerobic activities such as brisk walking, cycling, or
even walking around the house or yard reduce the risks of
developing coronary heart disease, hypertension, colon cancer and
diabetes.
6
This association has also been seen in detention environ-
ments,
7–9
and two Italian studies suggest that physical activity in the
prison population increases psychological wellbeing and reduces
depression levels.
10,11
The aim of this investigation was to extend a previous pilot
study
11
in order to confirm the correlation seen between HRQoL
levels and high levels of physical activity.
Methods
Participants
Participation was voluntary. All apparently healthy prisoners were
invited to participate. The study excluded prisoners who had special
regimes that did not permit them to have received outside visits, as
outlined under the Italian law (as follows):
– regimens provided for by article 41bis/2O.P. (crimes of mafia,
terrorism, exploitation of prostitution, criminal association);
– justice collaborators assigned to high security sections.
Materials and procedure
A cross-sectional design was adopted, and the STrengthening the
Reporting of Observational studies in Epidemiology (STROBE)
statement was applied to perform the study.
12
The research protocol was approved by the ethical committee of
Sapienza University of Rome.
This multicenter study was carried out in eight Italian prisons.
The penitentiaries were selected on an opportunistic basis, and by
consequence located in cities easily accessible by at least two re-
searchers. In particular, three of them were houses of imprisonment.
The other five were ‘Casa Circondariale’, which are detention homes
where detainees await judgment or the inmates sentenced to a term
of less than 5 years (figure 1).
Prison directors were contacted by the researchers and the aim of
the study was explained. The educational and legal officers within
jails were involved to support the researchers in the administration
of the questionnaires with the aim of minimizing missing or
inadequate answers. The questionnaire administration was
conducted in small groups of about 25 inmates, an short introduc-
tion was given on the aims of the project and the importance of their
participation. The study was conducted between September and
December 2015.
The questionnaire
The questionnaire consisted of three sections: International Physical
Activity Questionnaire (IPAQ),
13,14
QoL assessment using the Short
Form 12 questionnaire (SF12)
15,16
and a demographic section.
The IPAQ questionnaire investigates the time spent carrying out
vigorous and moderate intensity physical activity, walking and
sitting. Total minutes per week was calculated by adding vigorous,
moderate and walking activity, but only reasonable total sum were
included in the analysis, which means the total minutes per week
greater than 7980 (>19 h per day for week), or inferior than 420 min
per week (<1 h per day per week) were excluded from the analysis.
The Metabolic Equivalent of Task minutes per week (MET-min/
wk) was calculated. The MET is a physiological measure expressing
the energy expenditure of physical activities, and it is established that
the basal metabolic rate is typically 1.0 MET.
17
The following formulas were computed:
18
Walking MET-min/wk =3.3
walking minutes
walking days
Moderate MET-min/wk =4.0
moderate-intensity activity mi-
nutes
moderate days
Vigorous MET-min/wk =8.0
vigorous-intensity activity mi-
nutes
vigorous-intensity days
Total MET-min/wk= Walking MET-min/wk + Moderate MET-
min/wk + Vigorous MET-min/wk
For each individual, the recorded activities were converted into
MET-min/wk and then classified in three level of physical activity:
13
– <3000 low;
– 3000–5999 moderate;
–6000 high.
The SF12, with 12 questions, is a shorter adaptation of the Short
Form Health Survey-36 (SF36). It is a measure of perceived health
(HRQoL) that describes the domains of general physical and mental
health status. Physical and Mental Composite Scales (PCS and MCS)
are derived from an algorithm that combines the answers of the
questions: the interpretation is that high scores correspond to high
levels of health (range is: 0–100).
16
The sociodemographic/anthropometric variables included in the
questionnaires were: gender, age (years), nationality (Italian vs. non-
Italian), civil status, educational level (illiterate, primary education,
high school diploma, bachelor degree or third level education),
children (yes/no), professional activity pre-reclusion, years of
detention, smoking habits (yes/no), weight (kg) and Body Mass
Index (BMI) (pre and post detection).
The outcomes examined were: PCS, MCS and MET-min/wk
(METwk).
Statistical analysis
Descriptive statistics such as frequencies and percentages were
reported for included qualitative variables, and recoded into
dummies if needed. Continuous variables were described as mean,
median, range, Standard Deviation (SD). For both types of variables,
missing data were reported.
A univariate analysis was carried out for which the Kolmogorv-
Smirnov Normality test was preliminarily applied. The test was then
used to evaluate the mean difference between PCS or MCS, and
METwk. The following statistical tests were used: Kruskall-Wallis
and Mann–Whitney tests for non- normal distributions, and
ANOVA and Student’s t-test for independent samples for normal
ones.
The correlation between continuous variables was evaluated using
Spearman’s coefficient. To evaluate the possible association between
categorical covariates, the Chi-square test, or Fisher’s Exact test
whenever the sample size were rather small, was used.
Multivariate linear regression models were performed to study the
relationship between quantitative outcomes; a multivariate logistic
regression model was calculated for dichotomous outcomes ‘MET-
high’: METwk was categorized into a two classes <6000 METwk = 0
and 6000 METwk = 1 in order to face with the possibility that
maximum likelihood estimation of the logistic model suffers from
small-sample bias. And the degree of bias is strongly dependent on
the number of events in the less frequent of the two categories.
The inclusion of covariates within the model was decided on the
basis of the univariate analysis: P< 0.3.
N. inmates with missing and/or
unreasonable values for IPAQ or
SF12 quesonnaires (N=238)
•Eboli=15
•Pagliarelli=90
•Rebibbia=46
•Regina Coeli=16
•San Viore=117
PATECIPANTS of THE
STUDY(N=636)
•Eboli=32
•Pagliarelli=197
•Rebibbia=109
•Regina Coeli=77
•San Viore=267
TOTAL INMATES
•Eboli (male prison)a=32
•Pagliarelli (male and female
prison)b=1185
•Rebibbia (male and female
prison)a=608
•Regina Coeli (male
prison)b=806
•San Viore (male and female
prison)b=971
N. inmates included in
the analysis for QoL
and IPAQ (N=398)
•Eboli=17
•Pagliarelli=107
•Rebibbia=63
•Regina Coeli=61
•San Viore=150
Figure 1 Flow-chart of inmates participating in the study and included in the analysis, divided by prisons (male and female structures were
considered as the same jail)
2of7 European Journal of Public Health
A Stepwise backward elimination procedure of non-significant
variables (probability of entry P< 0.05) was subsequently used to
generate a minimal model. The goodness of fit for the linear
model was assessed with R
2
and the logistic model with Hosmer
and Lemeshow‘s test.
Significance threshold was set at P< 0.05 (two-tailed) for all
analyses.
The statistical analysis was carried out using Statistical Package for
Social Science software (SPSS), version 21.0.
Results
Out of a possible 3602 prisoners from the eight jails approached. 636
were contacted to participate in the survey (18%).
The involved sample showed differences of composition in
comparison to the total number of the prisoners in terms of
gender and nationality (P< 0.05): 16% of the total males and 33%
of total females were assessed; 21% of Italian inmates and 16% of the
foreigners participated. There was no difference by age distributions
between sample and population (data not showed) (P> 0.05).
The missing data did not present significant differences by edu-
cational level (P= 0.210). On the other hand, a significant difference
with nationality was found: Italian inmates had a higher risk of
missing the IPAQ items (P= 0.015; OR = 1.55) (data not showed).
The inmates that participated in the study are shown in figure 1,
which also illustrates the number of prisoners taken into consider-
ation for the MET and QoL analysis (N= 398).
The socio-demographic, anthropometric and attitudinal charac-
teristics of the sample are described in table 1. Missing data for each
variable are also reported. The mean age of inmates was 38.6 years
(SD = 12.5; min = 18; max = 77), 498 were males (78.3%) and 397
were Italian (37.6%). The mean METwk was 8991.4 with
SD = 6597.3 (min = 1386; max = 43 146), but 196 values were
deemed as missing or unreasonable. Five of the eight jails (70%),
corresponding to 87.7% of the prisoners, had at least one physical
activity infrastructure or Physical Exercise areas (PEAs) (such as an
outdoor fitness area or vegetable plot or soccer camp or volleyball
camp).
The SF12 items and PCS and MCS summary scores are presented
in table 1.
The mean PCS was 48.4 (SD = 9.5; 95%CI: 43.9–49.3), whereas
the mean MCS was 39.3 (SD = 13; 95%CI: 34.8–40.2), respectively.
In comparison, the mean PCS is close to the average value for the
Italian general population (PCS = 48.6; 95%CI: 46.6–49.0), and the
MCS is significantly lower (MCS = 49.9; 95%CI: 47.4–50.4).
16
The
comparison of the prevalence in the sample of inmates and in Italian
general adult population that meets recommended physical activity
levels, shows that the two populations are similar, 63% (95%CI:
57.8–67.4) vs. 67%, respectively.
19,20
Table 1 Descriptive characteristics of the inmates studied
Qualitative variables N% Missing
Gender Male 498 78.3 0
Female 138 21.7
Civil status Married 287 48.0 38
Single 177 22.4
Divorced/separated/widower 134 29.6
Having sons Yes 397 64.4 0
No 219 35.6
Educational level Illiterate/primary school 124 20.4 29
Middle school 307 50.6
High school/university 176 28.9
Working position before detention Unemployed 90 17.0 108
Employed 438 83.0
Nationality Italian 397 37.6 0
Non Italian 239 62.4
Continent Europe 498 80.9 21
Non-European 117 18.3
Smoker Yes 439 70.2 11
No 186 29.8
Number of cigarettes No smoker 173 28.3 26
1–10 128 20.9
11–20 209 34.2
>21 100 16.3
Presence of Physical Exercise area Yes 558 87.7 0
No 78 12.3
MET week groups Low (<3000) 68 15.5 196
Middle (3000–5999) 122 27.7
High (6000) 250 56.8
Prison San Vittore 221 34.7 0
Palermo 197 31.
Regina Coeli 77 12.1
Rebibbia 109 17.1
Eboli 32 5.0
Continuous variables Median min max mean SD Missing
Age 37.0 18.0 77.0 38.6 12.5 8
Years of detention 2.2 0.0 33.0 4.4 5.7 23
BMI at the beginning of detention 25.3 16.1 82.2 26.3 5.8 82
BMI at the time of the study 25.3 15.6 49.4 25.9 4.5 22
MET week
a
6966.3 1386.0 43 146.0 8991.4 6597.3 196
a
PCS 50.4 15.5 67.0 48.4 9.5 69
MCS 37.7 10.3 68.9 39.3 13.0 69
a: 99 were missing and 97 unreasonable values.
Health related quality of life and physical activity in prison 3of7
The univariate analyses of PCS, MCS, METwk and MET-high are
shown in Supplementary files. In particular having single civil status,
no sons, Italian nationality, European continent origin, high METwk
score and no presence of PEAs were all significantly associated with
high values of PCS (P= 0.001, P< 0.001, P< 0.001, P= 0.023,
P< 0.001 and P= 0.002, respectively). Having Italian nationality,
European continent origin, lower number of cigarettes smoked
and belonging to the high METwk group were associated to high
MCS score (P= 0.001, P= 0.031, P= 0.022, P< 0.001, respectively).
Moreover, METwk score was associated to gender (P= 0.006).
The correlation analysis (Supplementary files) shows significant
direct associations between METwk and both PCS (r=0.165;
P= 0.001) and MCS (r= 0.099; P= 0.048). Furthermore PCS was
inversely associated with age (r= –0.231; P< 0.001), BMI at the
beginning of the detention (r= –0.109; P= 0.015), current BMI
(r= –0.106; P= 0.013) and years of detention (r=–0.136;
P= 0.001); MCS was directly associated with age (r= 0.075;
P= 0.045), current BMI (r=0.100; P= 0.019) and years of
detention (r=0.076; P= 0.076).
The first multivariate linear model studied PCS outcome (table 2).
The covariates associated to lower PCS score were: being divorced,
separated or a widower vs. being single (b= –0.12; P= 0.01), years of
detention (b= –0.14; P=0.007), being detained in Palermo vs. San
Vittore (b= –0.12, P< 0.02), BMI at the time of the study (b=–0.12;
P= 0.01) and age (b= –0.12; P= 0.03). The ones associated to higher
PCS scores were: MCS (b= 0.01, P= 0.04) and Regina Coeli prison
(b= 0.10, P= 0.05).
In the second model, the covariates were directly associated to
MCS were: a total MET above 6000 (b= 0.18; P< 0.001) and age
(b= 0.11; P= 0.03); whereas an inverse association was seen if:
inmates were non Italian (b= –0.17; P< 0.001), smokers of more
than 20 cigarettes (b= –0.14; P< 0.001) and Pagliarelli Jail vs. San
Vittore Jail (b= –0.10, P= 0.035) (table 2).
In the third model, the outcome studied was METwk. It was
directly associated to PCS (b= 0.15; P= 0.003) (table 2).
The R
2
ranged from 0.171–0.035 in the three models.
The table 3 shows the characteristics of the logistic regression
model for MET-high outcome. The model suggested that the prob-
ability of having a higher MET score increased if inmates were: male
(OR = 0.53, CI95%: 0.33–0.87); non Italian (OR = 1.78; CI95%:
1.14–2.78); older (see age: OR = 0.98, CI95%: 0.96–1); with many
years of detention (OR = 1.04; CI95%: 1.00–1.09); and high PCS and
MCS scores (respectively: OR = 1.02, CI95%: 1.00–1.05 and
OR = 1.03, CI95%: 1.0–1.05).
Discussion
This investigation extends a previous pilot study
11
and strengthens
the association found between the HRQoL and level of physical
activity. More precisely it suggests that a consistent weekly level of
physical movement (>600 METwk) is associated with a higher level
of both mental and physical health components of the QoL scale.
Furthermore, the study identifies an association between these
two components of the QoL too i.e. an increase of the physical
Table 2 Multivariate linear regression models of the impact of demographic, anthropometric, jail characteristics on the Quality of Life and
METwk
Covariates PCS MCS METwk
B
b
PB
b
PB
b
P
Gender Male
a
/female –0.02 0.668 –0.124 0.011 –0.10 0.060
Civil status Single
a
c
Married –0.003 0.964 –0.03 0.688
Divorced/separated/widower –0.12
0.012
–0.05 0.402
Educational level Illiterate/primary school
a
Middle school 0.02 0.779 0.02 0.740 0.03 0.565
High school/university 0.05 0.297 –0.06 0.212 0.05 0.504
Number of cigarettes daily No smoker
a
1–10 –0.04 0.455 0.01 0.807 0.06 0.275
11–20 –0.03 0.488 –0.05 0.344 0.02 0.68
>20 –0.05 0.405 –0.14
0.002
0.05 0.360
Children No
a
/yes –0.034 0.573 c c
Nationality Italian
a
/non Italian 0.09 0.091 –0.17
0.001
c
Continent European
a
/Non European –0.06 0.410 0.04 0.531 c
Physical exercise areas No
a
/yes 0.04 0.909 –0.51 0.111 c
METwk groups Low <3000
a
d
Middle 3000–5999 0.02 0.717 0.09 0.113
High > =6000 0.07 0.149 0.18
<0.001
Jail San Vittore
a
(Milan)
Pagliarelli (Palermo) –0.12
0.023
0.04 0.479 –0.03 0.553
Regina Coeli (Rome) 0.10
0.047
–0.10
0.035
0.03 0.55
Rebibbia (Rome) –0.07 0.208 –0.005 0.925 –0.03 0.599
Eboli (Salerno) 0.009 0.860 0.03 0.503 0.06 0.279
Years of detention –0.14
0.007
–0.06 0.287 c
BMI at the beginning of the detention –0.05 0.439 c c
BMI at the time of the study –0.12
0.014
0.05 0.304 –0.04 0.448
Age (years) –0.12
0.030
0.11
0.021
0.00 0.95
PCS d 0.10
0.052
0.15
0.003
MCS 0.010
0.04
d 0.05 0.335
R
2
(Goodness of fit) 0.171 0.115 0.035
a: Reference group.
b: Standardized coefficients.
c: Not included according to the univariate analysis.
d: The model considered this variable as outcome.
:P< 0.05
4of7 European Journal of Public Health
wellbeing appears to be linked in some way to an increase in mental
wellbeing.
Again, the years of detention and age were important aspects in
the overall QoL assessment. In addition, the time spent on exercise,
and the intensity of the bodily movement increased with age and
years spent in prison. It is likely that inmates with long-term
sentences and older individuals feel the need to organize interests/
activities in order to improve how to spend their time and to also
achieve better life satisfaction: a systematic physical activity plan may
help build a better social network.
21
There are two main strengths of this study. First, the sample size
was sufficiently large, and typically, in this type of research, the
organization to collect data of the sample is complex and in
addiction though the individuals involved very willing, they often
found it difficult to talk and to express their opinion. Second
strength of this study is that the missing data weren’t statistically
significant by gender, age and nationality when considering the
overall characteristics of the sample studied.
Limitations
Substantial limits, however, were also present in this study.
There was a high rate of missing or unreasonable data. This
problem was underlined in the pilot investigation.
11
In the present
study, ‘not speaking the Italian or English languages’ or ‘being
unable to read’ were contained with a large support of the re-
searchers during the administration, this thanks to the past
operating experience acquired. Nevertheless the investigation
presented many missing values: the majority of missing data was
found among Italian inmates. This is probably due to different
causes such as the foreign prisoners asking more support during
their compilation of the questionnaire and/or the researchers
having paid more attention to those who doesn’t speak Italian.
The goodness of fit in the models was low. It is probable that
other covariates could better explain the QoL of inmates, although
MET was still a significant predictor of the mental health
component. In addition the questionnaire did not assess the
presence of mental illness or comorbidities in the prisoner, and
this could have an impact on the analysis due to a potential for
unmeasured confounding.
Another limit is that although a sufficient percentage of total
prisoners were covered, the sample had low representativeness to
the overall prison population in Italy. The sample was built on a
voluntary participation basis, and according to logistical and ethical
reasons. It did, however, possibly raise awareness among the jail staff
and prisoners, and this may be a way of increasing participation in
future studies of this type. Much hard work was carried out in
communicating the importance of the research and in the
collection of questionnaires.
Furthermore the study design did not allow us to analyse whether
a good level of physical activity led to a high quality of life or, on the
contrary, whether a high quality of life stems from a good level of
physical activity: the study cannot exclude the presence of reverse
causality, especially due to the cross-sectional study design.
Another point of weakness is that the measurement of HRQoL
was done using the SF12; the version Short Form 36 Health Survey
with 36-item (SF36), could perhaps point out other components not
examined in this study.
Some data could be affected by recall bias, such as initial weight or
BMI measurement. Other shortcomings could also e present, such as
educational biases linked to the different organization of school
systems in other countries.
Finally, the presence of PEAs too is to be interpreted with caution.
In fact, though the presence of spaces dedicated to physical activity is
clearly important, no description of the characteristics of such spaces
is collected (i.e. presence of training equipment, or how big a PEAs
Table 3 Logistic regression model for MET-high
Covariates MET-high
a
OR
CI95%
inf sup
Gender Male
b
1
Female 0.53
0.33
0.87
Educational level Illiterate/primary school
b
1
Middle school 1.11 0.74 1.70
High school/university 1.26 0.68 2.32
Number of cigarettes per daily Non smoker
b
1
1–10 1.28 0.79 2.09
11–20 0.92 0.55 1.55
>21 1.17 0.65 2.10
Children No
b
1
Yes 0.92 0.58 1.46
Nationality Italian
b
1
Non Italian 1.78
1.14
2.78
Continent Europe
b
1
Non-European 0.82 0.42 1.61
Prison San Vittore (Milan)
b
1
Pagliarelli (Palermo) 0.69 0.43 1.37
Regina Coeli (Rome) 1.32 0.69 2.49
Rebibbia (Rome) 1.07 0.56 2.04
Eboli (Salerno) 1.25 0.43 3.58
Age (years) 0.98
0.96
1.00
Years of detention 1.04
1.00
1.08
PCS 1.02
1.00
1.05
MCS 1.03
1.01
1.04
Hosmer and Lemeshow‘s test 0.095
a: ‘MET-high’ categorizes the METwk score in a dichotomous variable: 6000 vs. <6000.
b: Reference group.
:P< 0.05
Health related quality of life and physical activity in prison 5of7
was in terms of m
2
). However, it is known that the PEA within the
jails studied here was very different from prison to prison: in some
cases, this was represented by a simple room or an open space
without any fitness equipment, in other jails by a real gym, or
playing fields, and one even had a vegetable plot. Ideally, the hope
is that the space dedicated to physical activity acquires a clearer
definition. A proper regulation based on accepted and appropriate
measurement of these spaces should be imposed so that all prisons
could follow such guidelines.
In view of these considerations, it suggests that physical exercise
could be used as an important component of a multifaceted
approach to reducing psychological ill health in prison populations.
Increased exercise volume is correlated with decreased hopeless-
ness.
22
Though correlation was statistically significant but weak,
due to the complex nature of prisoners health, the potential to
decrease rates of self-harm and improve mental health provides
further impetus to include exercise regimens as an integral factor
within inmate health management plans. There is a definite relation-
ship between supervised exercise and improved mental health
among sentenced prisoners. It is likely that a complex interaction
and sense of efficacy and mastery, or perhaps simple distraction, may
lead to a change in self-conception.
10
Physical activity teaches
discipline, record keeping, goal-setting, and employs inmates’
leisure time thus reducing boredom and ‘burns off’ tension.
23
According to the Italian Constitution ‘punishments must aim at
rehabilitating the condemned’
24
in order to return healthy and
renewed persons to the community, the physical activity could be
confirmed as a major positive aspect for inmates’ detention.
Jails could be the ideal place for physical activity promotion,
through the creation of training programs that are simple,
effective and cost effective ways.
11
Conclusions
The findings underline that physical and mental components of QoL
are linked to physical activity and, in particular, to a more intense
physical activity level. The cross-sectional study did not establish clear
casual relationships, but it is likely that investing in fitness areas, im-
plementing programs promoting physical activity, with due precau-
tions and consideration of the variability of cases, could allow for
better health conditions in Italian prisons, as well as decreasing the
rates of potential self-harm and support rehabilitation of inmates.
25
However, it is observed that the prevalence of recommended level
of physical activity and mean of PCS were not significantly different
from those of the Italian general adult population; on the other
hand, the mental health score was significantly worse. It would be
worthwhile to conduct other experimental studies to investigate this
causal relationship, because knowing how to achieve and maintain a
good quality in one‘s own life is a prerequisite to a better social
reintegration at the end of detection.
Key points
The physical and mental components of inmates’ Quality of
Life were associated to a high level of physical activity.
The quality of life is directly proportional to time spent in
physical activity.
High heterogeneity was found in the Jails concerning the
physical exercises areas and fitness equipment.
The models studied indicated that the Quality of Life is
associated to several aspects of the prisoner‘s life and the
physical activity would seem an aspect currently not essential.
Supplementary data
Supplementary data are available at EURPUB online.
Acknowledgements
The authors would like to thank Jail Administration Departments,
pedagogical legal officers, educators, social assistants of the Prisons
and collaborators in the Universities. In particular:
– Jail Administration Department, Provveditorato Regionale per la
Lombardia, Dr. Maria Siciliano.
– Casa Circondariale ‘S. Vittore’ (Milan), Dr. Giovanna Longo and
Dr. Emanuela Merluzzi.
– Jail ‘Regina Coeli’ (Rome): Prison Director added Dr. Simona
Mellozzi and pedagogical legal officers: Margherita Marras,
Francesca Calafiore, Francesca D’Andrea, Carmela Vetrone,
Isabella Rinaldi Tufi, Samanta De Panfilis, Elena D’Angelo.
– Jail ‘Rebibbia’ Female Section (Rome): Prison Director Dr. Ida
Del Grosso and pedagogical legal officer Dr. Sabrina Maschietto.
– Jail ‘Rebibbia’ Male Section (Rome): Prison Director Dr. Stefano
Ricca and Head of the pedagogical section Dr. Antonio Turco.
– Istituto a Custodia Attenuata per il Trattamento delle
Tossicodipendenze e/o Alcol dipendenze (Eboli).
– Casa Circondariale ‘Pagliarelli’ (Palermo): Prison Director Dr.
Francesca Vazzana; Heads of the pedagogical section Dr.
Rosaria Puleo.
– Dr. Marco Siclari, Department of Public Health and Infectious
Diseases, Sapienza University of Rome.
– Dr. Sandro Provenzano, Department of Sciences for Health
Promotion and Mother and Child Care ‘Giuseppe
D’Alessandro’, University of Palermo.
Conflicts of interest: None declared.
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