Int
ern
at
i
onal
Journ
al of
P
u
bli
c Hea
lt
h S
c
ie
nce (IJPH
S)
Vo
l.
7
, No
.
4,
Decem
ber
201
8,
pp. 2
23
~
230
IS
S
N: 22
52
-
8806,
DO
I: 10
.11
591/ij
phs.
v7
i
4.522
5
223
Journ
al h
om
e
page
:
https:
//
ww
w.i
aesco
re
.c
om
/j
our
nals/
ind
ex.
php/IJP
H
S
Predi
ctin
g Smok
ing Beh
aviors
am
ong Juni
or High
School
Stu
dents in Ghan
a
Emm
a
nu
el
Th
omp
s
on
1
,
Se
i
d
u
S
of
o
2
1
Depa
rtment of
Mathe
m
at
i
cs,
So
uthe
ast
Miss
ouri
State
Univ
ersity,
Un
it
ed
Stat
es
2
Depa
rtment of
Hea
lt
h
,
Hum
an P
erf
orm
anc
e & Rec
re
at
ion
,
Sout
hea
st Missouri
S
ta
t
e
Univer
si
t
y
,
Un
it
ed
Stat
es
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
A
ug
25
, 201
8
Re
vised
Oct
2
4
, 2
01
8
Accepte
d
Nov 13
, 201
8
Despite
th
e
r
ising
rate
of
sm
oking
in
sub
-
Sahar
a
Afric
an
count
ri
e
s,
m
ea
sures
to
cont
rol
the
t
obac
co
epi
demi
c
have
b
ee
n
l
imite
d
to
d
eve
lop
e
d
count
ri
es.
The
purpose
of
the
pr
ese
nt
stud
y
was
to
r
ec
om
m
end
pre
dictive
m
odel
s
fo
r
det
ermining
pr
e
dic
tors
of
sm
oking
te
nd
enc
i
es
among
juni
or
h
igh
school
student
s
in
Gha
na.
The
2009
Gl
obal
Youth
Tob
ac
co
Surve
y
(G
YTS)
serve
d
as
the
d
ata
sourc
e.
The
GY
TS
is
a
school
-
b
ase
d
s
urve
y
design
ed
t
o
enha
n
ce
the
abi
l
ity
of
co
untri
es
to
m
onit
or
toba
cc
o
use
a
m
ong
y
outh
and
to
guide
th
e
implementa
t
ion
and
eva
lu
at
ion
o
f
toba
cc
o
cont
ro
l
and
pre
vention
progra
m
s.
Logi
t
m
odel
and
forward
select
i
on
were
used
t
o
choose
pre
d
ic
t
i
ve
var
i
ables
for
sm
oking
tendenc
i
es
and
b
eha
viors.
Re
ce
i
ver
Oper
at
ing
Chara
c
te
rist
ic
(ROC)
cur
ve,
Ar
ea
under
the
cur
ve
(AU
C)
and
C
-
Inde
x
were
v
al
i
dat
ion
tool
s
used
to
assess
the
pre
dictiv
e
power
of
rec
om
m
ende
d
m
odel
s.
Result
s
show
ed
prom
ising
pote
nti
al
for
diff
ere
n
t
pre
dic
t
ive
m
odel
s:
where
stude
nts
sm
oked,
havi
ng
frie
nds
who
sm
oked,
havi
ng
peopl
e
sm
ok
e
in
the
ir
pre
sen
ce
,
ch
ewing
toba
c
co
produc
t
s,
and
a
stud
ent’s
sex
significan
tly
pr
edi
c
te
d
their
sm
oking
te
nden
ci
es.
Ke
yw
or
d:
Bi
nar
y l
ogist
ic
r
e
gr
essi
on
C
-
I
nd
e
x
Fo
r
wa
rd
sel
ect
ion
sel
ect
ion
Gh
a
na
Copyright
©
201
8
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed
.
Corres
pond
in
g
Aut
h
or
:
Em
m
anu
el
Thom
ps
on,
Dep
a
rtm
ent o
f M
at
hem
a
ti
cs,
Southeast M
iss
ouri Stat
e
Un
i
ve
rsity
,
1 Un
i
ver
sit
y Pl
aza, Cape
G
ir
a
rd
ea
u, MO
6701, U
nited Stat
e
s.
Em
a
il
: et
ho
m
ps
on@sem
o.
ed
u
1.
INTROD
U
CTION
To
bacco
kill
s
a
la
rg
e
nu
m
ber
of
it
s
us
e
rs
wh
e
n
us
e
d
a
s
pr
esc
ribe
d
by
t
he
m
anu
fact
urers.
Global
ly
,
six
m
il
l
ion
pe
ople
die
annuall
y
fr
om
tob
acco
us
e,
an
d
est
i
m
at
ed
to
reach
e
igh
t
m
il
li
on
by
2030
[
1].
Re
s
earch
sh
ows
t
hat
wom
en
and
c
hildre
n
are
the
m
os
t
aff
ect
ed
by
the
drug
[2
]
.
Me
asur
e
s
to
co
ntr
ol
the
epi
dem
i
c
ha
ve
been lim
it
ed
to d
e
velo
ped co
untrie
s.
Wh
e
reas
t
obac
co
us
e
a
ppears
to
be
decli
ning
in
m
any
devel
op
e
d
c
ountri
es,
it
is
inc
rea
sing
in
t
he
dev
el
op
i
ng
w
orl
d
[
3],
in
pa
rt
du
e
to
the
e
c
onom
ic
gr
owth
in
s
om
e
devel
op
in
g
c
ountr
ie
s.
Conseq
ue
nt
ly
,
the
tob
acc
o
in
dus
try
is
capit
al
i
zi
ng
on
t
he
econom
ic
gr
owth
in
th
es
e
countries
in
te
r
m
s
of
to
bacco
adv
e
rtise
m
ents
[4
]
.
Africa
n
countries
hav
e
lowe
r
rates
of
t
ob
acc
o
ta
xation,
an
d
le
ss
strin
gen
t
to
bacc
o
adv
e
rtisi
ng
res
tric
ti
on
s
in
c
om
par
ison
to
hi
gh
e
r
inc
om
e
countries
[5
]
.
In
c
reasin
g
to
ba
cco
ta
xes
by
10
%
gen
e
rall
y
decre
ases
tob
acc
o
consum
ption
by
about
8%
in
low
-
i
nco
m
e
and
m
idd
le
-
inc
om
e
cou
ntries.
Ma
ny
Sub
-
Sa
ha
ran
c
ountries
have
fail
ed
to
al
loc
at
e
the
ap
pro
pr
ia
te
fi
nan
ci
a
l
resour
ces
t
o
tob
acc
o
pr
e
ve
n
ti
on
pro
gr
am
s,
des
pi
te
the co
st
-
ef
f
ect
iveness o
f
s
uch pr
ogram
s [
6].
To
bacco
u
se
is
pr
evale
nt
in
G
han
a
.
The
c
omm
on
fo
rm
s
of
us
a
ge
inclu
de
no
t
only
ci
gar
e
tt
e
s
m
ok
ing
,
bu
t
al
s
o
pip
e
sm
ok
ing
,
che
wing,
s
nif
fin
g
an
d
or
al
or
na
sal
us
e
[
7].
Un
ti
l
rece
ntly
,
there
w
e
re
no
stu
dies
sh
owin
g
to
bac
co
prevale
nce
f
or
the w
hole
c
ountry
[
8].
The
rates
of
sm
ok
ing
am
ong
the g
ene
ral
popula
ti
on
in
Gh
a
na
a
re
rela
ti
vely
low,
with
m
al
es
s
m
ok
ing
m
or
e
tha
n
f
e
m
al
es
[9
]
.
Ea
r
li
er
m
od
el
s
of
the
to
bacc
o
e
pi
dem
ic
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2252
-
8806
IJPHS
V
ol.
7
,
No.
4
,
Decem
ber
2018:
223
–
230
224
fail
ed
to
ex
plain
the
lo
ng
de
la
y
betwee
n
in
cr
ease
in
sm
ok
in
g
a
nd
the
i
ncr
e
ase
in
sm
ok
in
g
-
relat
ed
m
or
ta
li
ty
i
n
dev
el
op
i
ng
c
ount
ries
li
ke
Ghana
[
10
]
.
Stag
e
on
e
epi
dem
i
c
is
char
act
erized
by
higher
prevale
nce
of
s
m
ok
ing
a
m
on
g
m
al
es
t
han
fem
al
es.
Howe
ver,
the
World
Healt
h
Orga
nizat
ion
[
1
1]
repo
rted
hi
gh
e
r
rates
am
on
g
the
youth,
sug
gesting
a rise
in
the
fu
tu
re u
se.
An
un
der
sta
nd
i
ng
of
sm
ok
in
g
pa
tt
ern
s
am
on
g
ado
le
sce
nts
ca
n
sh
e
d
li
gh
t
on
tre
nds
in
sm
ok
ing
init
ia
ti
on
[
12
]
.
G
r
ow
t
h
in
t
he
Ghanaian
t
ob
acc
o
industry
is
a
c
on
ce
r
n.
T
he
growt
h
has
le
d
to
the
ind
ust
ry
ta
rget
ing
the
po
pula
ti
on
es
pecial
ly
the
youth
.
For
exam
ple,
researc
h
s
hows
tha
t
tob
acc
o
ad
ver
t
isem
ent,
per
m
i
ssion
to
sm
oke
on
sc
hool
co
m
po
unds
,
a
nd
par
e
ntal
s
m
ok
i
ng
wer
e
ass
oc
ia
te
d
with st
ud
e
nts’
intenti
ons to
s
m
ok
e [13]
.
The
Gove
rn
m
en
t
of
Gh
a
na
a
nd
Ci
vil
S
ociet
y
Orga
nizat
ion
s
(CSOs)
a
re
putt
ing
in
place
m
easur
es
to
reduce
the
pre
valence
of
to
ba
cco
us
e
in
the
co
un
t
ry.
First,
CSOs
ha
ve
reache
d
an
agr
eem
ent
with
the
Nati
on
al
De
velop
m
ent
Plan
nin
g
C
omm
issi
on
(
N
DP
C)
for
the
inclusi
on
of
the
T
obacco
Con
tr
ol
Me
as
ures
of
the
Publi
c
Hea
lt
h
Act
in
the
40
-
ye
ar d
e
velo
pm
ent
agenda
[
14
]
.
CS
Os
w
ho
are
c
omm
itte
d
to
re
duci
ng
tob
acc
o
add
ic
ti
on
a
nd
it
s
relat
ed
dise
ases
an
d
deat
h.
Sc
hool
sm
oking
poli
ci
es
an
d
par
e
ntal
sm
ok
i
ng
be
ha
viors
a
re
i
m
po
rtant
i
n
re
du
c
i
ng
sm
ok
in
g
inte
ntio
ns
a
m
on
g
G
ha
naia
n
yo
uth
[
13]
.
F
ur
t
her
m
or
e,
t
he
li
te
ratur
e
s
ho
ws
t
hat
sm
ok
ers
are
li
ke
ly
to
ha
ve frie
nd
s
wh
o
sm
oke
[
15
]
.
Re
search
s
ugge
sts
that
the
r
at
e
of
sm
ok
in
g
am
on
g
G
ha
naian
yo
uth
c
ou
l
d
incr
ease
in
the
f
uture.
An
unde
rstan
ding
of
t
h
e
sm
ok
in
g
te
nde
ncies
a
m
on
g
the
y
ou
t
h
in
G
ha
na
is
warra
nted.
T
he
obj
ect
ives
of
t
he
pr
ese
nt
st
ud
y
i
nclu
ded
:
(
1)
T
o
reco
m
m
end
an
a
ppr
opriat
e
pr
e
dicti
ve
m
odel
to
in
form
po
li
cy
on
to
bac
co
us
e
and
c
ontrol
in
Gh
a
na
a
nd
(
2)
T
o
determ
ine
pr
e
dictor
s
of
sm
ok
ing
te
nden
ci
es
am
ong
ju
nio
r
high
sch
oo
l
stud
e
nts
(JHS)
in
Gh
a
na
.
A
n
unde
rstan
di
ng
of
the
pre
dictors
an
d
a
ppr
op
riat
e
predict
ive
m
od
el
for
sm
ok
i
ng
te
nd
e
ncies
am
ong
st
ud
e
nts
would
al
low
public
healt
h
poli
cym
aker
s
a
nd
a
dm
inist
rator
s,
c
omm
un
it
y
le
ader
s
,
and
sc
hool
ad
m
in
ist
rator
s
to
dev
el
op
ef
fe
ct
ive
s
m
ok
in
g
pr
e
ven
ti
on
pro
gr
am
s
[13]
,
aim
ed
at
red
ucin
g
sm
ok
ing
te
nd
e
ncies am
on
g t
he
you
t
h.
2.
RESEA
R
CH MET
HO
D
The
Gl
obal
Youth
T
obacco
S
urvey
(
GY
T
S)
[16]
data
on
Gh
a
na
f
or
20
09
ser
ve
d
as
the
data
source
.
The
G
YTS
is
a
school
-
based
su
r
vey
that
helps
countries
m
on
it
or
tob
acc
o
us
e
am
on
g
yout
h.
The
2009
data
are
the
m
os
t
cu
rr
e
nt
to
bacc
o
s
urvey
data
f
or
Gh
a
na
t
o
date.
The
G
YTS
al
so
gu
i
des
i
n
t
he
im
ple
m
entat
ion
a
nd
evaluati
on
of
t
ob
acc
o
c
ontrol
and
prev
entio
n
pr
ogram
s.
The
20
09
(
8,295)
obser
vatio
ns
an
d
m
any
var
ia
bles
.
Of
t
he
8,2
95
obser
vatio
ns
,
on
ly
5971
(
72%)
we
re
a
naly
zed
.
A
ppr
oxim
a
te
l
y
28%
(
2324
)
of
the
obser
vat
ion
s
wer
e
d
isc
a
rd
e
d d
ue
to
m
issi
ng
d
at
a
.
2.1
.
Va
ri
ab
le
s
The
var
ia
bles
us
e
d
we
re
as
f
ollow
:
T
he
re
s
pons
e
var
ia
ble
was
“
Wh
et
her
a
stud
e
nt
ha
d
ever
trie
d
or
exp
e
rim
ented
with
ci
ga
rett
e
sm
ok
ing
,
eve
n
one
or
t
wo
pu
ff
s
?
”
Thi
rty
-
two
(
32)
predict
or
s
wer
e
us
e
d
(refer
t
o
app
e
ndix
).
Be
f
or
e
fitt
in
g
the
log
it
m
od
el
,
the
GY
S
T
datas
et
was
div
ide
d
into
two
set
s:
Trainin
g
a
nd
t
est
in
g.
The
trai
ning
se
t
wh
ic
h
co
ns
ti
tuted
70%
of
t
he
entire
dataset
was
us
e
d
to
s
pecify
the
pr
e
di
ct
ive
m
od
el
a
nd
t
he
rem
ai
nin
g
30
%
was
use
d
as a
te
sti
ng
set
to
p
er
form
ou
t
-
of
-
sam
ple
valida
ti
on
o
f
the
pre
dicti
ve
acc
ur
ac
y
of
the
m
od
el
.
2.2
.
Log
it
m
od
el
Let
represe
nt
rando
m
vari
ables
ta
king
values
∈
(
0
,
1
)
with
pro
bab
il
it
y
1
−
and
resp
ect
ively
.
T
his im
plies:
(
)
=
(
1
−
)
.
(1)
Suppose t
he
l
ogit
of
prob
a
bili
ty
o
f
is gi
ven
by
(
1
−
)
=
⇒
=
1
+
.
(2)
The pre
dicti
ve fo
rm
o
f
(
2) ca
n be
w
ritt
en
as:
(
|
)
=
1
1
+
−
,
(3)
wh
e
re
an
d
are
vecto
rs of p
redi
ct
or
s a
nd slo
pe
s r
es
pecti
vely
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJPHS
IS
S
N: 22
52
-
8806
Predict
ing
Smokin
g
Be
havi
ors
amo
ng J
unio
r H
ig
h Sc
hool
Students
in
G
hana.
..
(
E
mma
nuel
T
hom
pson
)
225
To
est
im
at
e (2
)
, th
e l
og
li
ke
li
hood is
g
i
ven b
y
:
(
)
=
[
∏
(
)
=
1
]
,
=
∑
[
(
)
+
(
1
−
)
(
1
−
)
]
,
=
1
=
∑
[
(
(
|
)
)
+
(
1
−
)
(
1
−
(
|
)
)
]
.
=
1
Let
∇
(
)
=
(
)
an
d
(
)
=
2
(
)
repr
esent
the
gr
a
di
ent
of
the
l
ogli
kelihood
a
nd
the
he
ssian
m
at
rix
resp
ect
ively
.
No
cl
os
ed
-
f
or
m
so
luti
on
,
s
o
resort
to
Ne
w
ton
Ra
phs
on’s
al
go
rithm
fo
r
approxim
at
e
s
olu
ti
on.
New
t
on Rap
hson’s al
gorithm
[
17]
is
giv
e
n
as
foll
ow
s:
1.
Start f
ro
m
so
m
e init
ia
l values
0
.
2.
Set
=
−
1
(
−
1
)
−
1
∇
(
−
1
)
(a
lo
op).
3.
Re
peat ste
p 2
unti
l
is cl
os
e
to
−
1
.
Infer
e
nce is c
a
rr
ie
d o
ut as
foll
ow
s:
√
(
̂
−
)
→
(
0
,
(
)
−
1
)
as
→
∞
,
wh
e
re
(
)
=
−
(
)
is fis
her inf
or
m
at
ion
a
nd
(
)
−
1
is t
he varia
nce
-
c
ovaria
nce
m
a
trix.
2.2.1.
V
ariab
l
e
sel
ection
-
f
or
w
ard
s
tepwi
se sele
ction
We
beg
i
n
with
the
interc
ept
m
od
el
then
a
dd
pr
e
dictor
s
one
at
a
ti
m
e
un
ti
l
al
l
pr
e
dictors
are
i
n
the
m
od
el
.
The
c
hoic
e
of
pr
e
dict
or
t
o
be
a
dded
to
the
m
od
el
at
each
ste
p
de
pe
nd
s
on
w
hich
a
m
on
g
the
rem
a
ini
ng
pr
e
dictor
s
giv
e
s
the
m
axi
m
um
add
it
ion
al
im
pr
ov
em
ent
to
the
fit
(
Dev
ia
nc
e).
T
he
sin
gle
best
m
od
el
is
chose
n
us
in
g
t
he
Ak
ai
ke
Inform
at
ion
Crit
erio
n
(AI
C)
an
d
Ba
ye
si
an
Inform
at
ion
Crit
erio
n
(BI
C).
AI
C
a
nd
B
IC
are
com
pu
te
d
as
fo
ll
ow
s:
=
−
2
+
2
,
=
−
2
+
log
(
)
,
wh
e
re
is t
he n
um
ber
of
pr
e
di
ct
or
s,
is t
he num
ber
o
f o
bs
er
va
ti
on
s,
and
is t
he
lo
g
-
li
kelihood.
2.3
.
Predi
ction
m
e
trics
A
co
nfusi
on
m
at
rix
con
ta
i
ns
inf
or
m
at
ion
about
act
ual
a
nd
predict
ed
cl
assifi
cat
ion
s
done
by
a
cl
assifi
cat
ion
s
yst
e
m
.
Table
1
s
hows
t
he
c
onf
us
io
n
m
at
ri
x
f
or
a
tw
o
-
cl
ass
cl
assifi
er.
The
tr
ue
posit
ive
rat
e
(
TPR
)
is
giv
e
n
by
the
rati
o
of
the
true
po
sit
ive
(
TP
)
to
the
su
m
of
the
true
po
sit
ive
an
d
false
neg
at
i
ve
(
FN
).
The
false
po
sit
ive
rate
(
FPR
)
is
ob
t
ai
ne
d
as
the
rati
o
of
the
false
posit
ive
(
FP
)
to
the
s
um
of
the
false
po
sit
ive
and tr
ue negati
ve (
TN
).
Table
1.
C
onf
usi
on Mat
rix
Predicted
Class
Total
Rate
Actu
al Class
=
1
̂
=
1
̂
=
0
TP
FN
+
=
+
=
0
FP
TN
+
=
+
At
dif
fer
e
nt
th
reshold
s
say
s
0.00,
0.0
1,…,
1.0
0,
a
gr
a
ph
of
TPR
(se
ns
it
iv
it
y)
against
F
PR
(1
-
s
pecifi
ci
ty
)
i
s
plo
tt
ed
t
o
obta
in
the
recei
ver
op
e
rati
ng
cha
racteri
sti
c
(RO
C)
cu
rv
e
.
N
um
erical
ly
,
the
area
un
der
t
he
ROC
curve
al
s
o
ref
e
rr
e
d
to
as
t
he
a
rea
under
c
urv
e
(
AU
C
).
T
he
AU
C
m
easur
es
the
pr
e
dicti
on
accuracy
of
th
e
log
it
m
od
el
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2252
-
8806
IJPHS
V
ol.
7
,
No.
4
,
Decem
ber
2018:
223
–
230
226
2.4
.
C
-
I
nde
x
Ba
sed
on
our
data,
(
,
)
are
the
act
ual
res
ponse
obser
vatio
ns
la
belle
d
1
a
nd
0
w
hile
(
|
)
an
d
(
|
)
are t
he
c
orrespondin
g p
red
ic
t
ed pr
obabili
ti
es. For
each
pai
r
(
,
)
, th
e C
-
Inde
x
i
s d
e
fine
d
as:
,
=
[
(
|
)
>
(
|
)
|
=
1
,
=
0
]
.
Eq
uiv
al
ently
,
,
=
[
′
>
′
|
=
1
,
=
0
]
.
Let
,
(
1
)
=
′
|
=
1
,
(
0
)
=
′
|
=
0
,
1
=
Numbe
r
of
1
′
s
,
an
d
0
=
Numbe
r
of
0
′
s
.
Fo
r
all
p
ai
r
s
(
,
)
,
th
e C
-
I
ndex
is es
tim
a
te
d
by t
he t
est
stat
ist
ic:
=
1
1
×
0
∑
∑
{
(
1
)
,
(
0
)
}
0
=
1
,
1
=
1
w
he
re
{
(
1
)
,
(
0
)
}
=
{
1
,
if
(
1
)
>
(
0
)
,
0
.
5
,
if
(
1
)
=
(
0
)
,
0
,
(
1
)
<
(
0
)
.
<
0
.
5
Im
plies
po
or
pr
e
dicti
on
acc
ur
acy
by
the
m
od
el
.
If
=
0
.
5
,
then
the
m
od
el
pr
edict
ion
acc
uracy
is
the
sam
e
as
a
ran
dom
gu
ess
.
Wh
e
n
>
0
.
5
an
d
=
1
are
ind
ic
at
io
ns
of
bette
r
a
nd
pe
rf
ect
m
od
el
pr
edict
ion
accuracies
r
es
pe
ct
ively
.
3.
RESU
LT
S
A
ND AN
ALYSIS
3.1
.
Model
asse
ss
ment m
etrics
This
stu
dy
us
e
d
the
G
YTS
da
ta
to
sp
eci
fy
a
m
od
el
for
pr
edict
ing
the
li
kelihoo
d
of
s
m
ok
ing
at
the
j
unio
r
hi
gh
sc
hool
le
vel
in
Gh
a
na.
Ta
ble
2
presents
re
sul
ts
on
the
m
od
el
assess
m
ent
m
et
rics
us
ing
bo
t
h
th
e
trai
ning
an
d
t
he
te
sti
ng
set
s.
A
f
ull
log
it
m
od
el
with
32
predict
ors
a
n
d
t
wo
sel
ect
ed
lo
git
m
od
el
s
bas
ed
on
forw
a
r
d
sel
ect
ion
with
the
le
ast
A
IC/B
IC
wer
e
est
im
a
ted
an
d
com
par
ed
us
in
g
C
-
in
dex
a
nd
C
-
Ind
ex
pe
r
Pr
e
dictor.
The m
od
el
w
it
h
the
least
A
IC of
2029.
06 chose
14 pre
dictors w
hile t
he
m
od
el
w
it
h
the lea
st
BIC o
f
2086
resu
lt
ed
in 6
pr
e
dictor
s s
how
n
in
Ap
pe
nd
i
x
.
The
C
-
Inde
x
and
t
he
C
-
I
ndex
per
P
red
ic
to
r
wer
e
us
e
d
to
c
heck
t
he
predi
ct
ive
accuracie
s
of
the
fu
ll
m
od
el
and
the
two
sel
ect
e
d
m
od
el
s.
The
C
-
I
nd
e
x
for
the
fu
ll
m
od
el
(
85.
15%)
was
la
rg
e
r
tha
n
tha
t
of
t
he
AIC
-
base
d,
a
nd
BIC
-
based
m
od
el
s
in
the
trai
nin
g
set
.
The
C
-
I
ndexes
fo
r
the
A
IC
-
base
d
and
BI
C
-
bas
e
d
m
od
el
s
on
the
trai
ning
set
wer
e
84.65%
an
d
82
.
00%
res
pe
ct
ively
.
Si
m
il
a
rly
,
the
C
-
Inde
x
for
the
f
ull
m
od
el
(80.6
7%)
was
la
rg
er
t
han
tha
t
of
the
A
IC
-
ba
sed
an
d
BIC
-
base
d
m
od
el
s
i
n
the
te
sti
ng
s
et
.
The
C
-
I
nde
xes
f
or
the
A
IC
-
base
d
an
d
BIC
-
base
d
m
od
el
s
on
t
he
te
sti
ng
set
wer
e
81.
7
4%
and
80.
86%
re
sp
ect
ively
sho
wn
in
Table
1.
T
he
C
-
I
nd
e
x
per
Pr
e
dictor
f
or
t
he
f
ull
m
od
el
,
AI
C
-
base
d,
an
d
BI
C
-
base
d
m
od
el
s
on
the
t
rainin
g
s
e
t
wer
e
2.6
7%
,
6.05%
and
13.67
%
resp
ect
ively
.
Si
m
il
arly
,
the
C
-
Index
e
s
per
Pr
edict
or
for
the
three
m
od
el
s
on
the test
ing set
wer
e
2.52%,
5.
84
%, a
nd
13.48%
res
pecti
vely
sh
ow
n
i
n
Ta
ble 2.
Table
2.
M
od
el
A
sses
sm
ent M
et
rics
Descripti
o
n
Fu
ll M
o
d
el
AIC
-
Mod
el
BIC
-
Mod
el
#
of
Pr
ed
icto
rs Sel
ected
32
14
6
C
-
Ind
ex
-
T
rainin
g
Set
(%
)
8
5
.51
8
4
.65
8
2
.00
C
-
Ind
ex
-
T
estin
g
Set
(%
)
8
0
.67
8
1
.74
8
0
.86
C
-
Ind
ex
Per
P
redic
to
r
–
Tr
ain
in
g
Set
(
%)
2
.67
6
.05
1
3
.67
C
-
Ind
ex
Per
P
redic
to
r
–
Testin
g
Set
(
%)
2
.52
5
.84
1
3
.48
Evaluation Warning : The document was created with Spire.PDF for Python.
IJPHS
IS
S
N: 22
52
-
8806
Predict
ing
Smokin
g
Be
havi
ors
amo
ng J
unio
r H
ig
h Sc
hool
Students
in
G
hana.
..
(
E
mma
nuel
T
hom
pson
)
227
A
com
par
iso
n
of
the
thr
ee
C
-
I
nd
e
xes
pe
r
pr
e
dictor
in
di
cat
ed
that
the
BIC
-
ba
sed
m
od
el
had
th
e
highest
power
per
predict
or
,
fo
ll
owe
d
by
th
e
A
IC
-
based
m
od
el
bo
t
h
in
the
trai
ni
ng
an
d
te
sti
ng
set
s.
Of
te
n,
m
od
el
assessm
ent
m
et
rics
based
on
trai
ni
ng
set
s
te
nd
to
le
a
d
to
over
fitt
ing.
Th
ere
fore,
te
s
ti
ng
set
s
a
re
use
d
t
o
choose
t
he
m
os
t
approp
riat
e
m
od
el
.
The
ch
os
e
n
m
od
el
w
ou
l
d
be
base
d
on
t
he
te
sti
ng
set
with
C
-
I
nd
ex
pe
r
Pr
e
dictor
a
nd
pa
rsim
on
y. The
BIC
-
ba
sed
m
od
el
f
it
thes
e cri
te
ria.
3.2
.
ROC cur
ves
of the F
ull
,
AI
C,
and t
he BI
C
-
b
as
e
d m
od
e
ls
Figure
1
s
how
s
the
ROC
curves
of
the
Fu
ll
(left),
A
IC
(m
idd
le
)
a
nd
the
BIC
(r
ig
ht)
-
ba
sed
m
od
el
s.
Figure
1
com
par
es
t
he
AUC
for
the
trai
ning
(
gr
ey
)
a
nd
t
he
te
sti
ng
(b
la
c
k)
set
s
of
t
he
th
ree
m
od
el
s.
Essentia
ll
y, the
AUC is
nu
m
erical
ly
the sa
m
e
as the
C
-
I
ndex
.
Figure
1. ROC
Curves
for F
ull (left),
AIC (m
idd
le
)
, a
nd BI
C (r
i
gh
t)
-
Ba
se
d
Mo
dels
3.3
.
Predi
cto
r
s
of
smok
in
g tend
enci
es
Table
3
pr
e
sen
ts
the
fitt
ed
BI
C
-
Mode
l
with six
(
6)
p
re
dicto
rs
that
res
ulted
in
the
hi
ghest
C
-
I
nd
e
x
pe
r
pr
e
dictor
.
The
six
pr
e
dictor
var
ia
bles
sig
nificantl
y
pr
e
di
ct
ed
stud
e
nts’
s
m
ok
in
g
te
ndencies
.
First,
wh
e
re
stud
e
nts
sm
oked
sig
nifica
ntly
pr
e
dicte
d
t
heir
s
m
ok
in
g
te
nd
e
ncies.
Partic
ipants
w
ho
“Ne
ve
r
s
m
ok
ed
ci
gar
et
te
s”
ser
ved
as
the
co
m
par
ison
or
r
efere
nce
gro
up.
Partic
ipa
nts
who
sm
ok
ed
at
ho
m
e,
scho
ol,
at
a
fr
ie
nd
’s
hous
e
,
at
public
e
ve
nts
or
oth
e
r
places,
had
sig
nificantl
y
highe
r
odds
of
sm
oking
t
han
th
os
e
w
ho
ind
ic
at
ed
t
hey
did
not
sm
ok
e.
Sec
ond,
ha
ving
their
cl
ose
st
fr
ie
nd
sm
ok
e
was
a
sig
nificant
pr
e
dic
tor
of
par
ti
ci
pa
nts’
s
m
ok
ing
te
nden
ci
es.
Stud
e
nts
who
in
dicat
ed
none
of
their
c
losest
fr
ie
nds
s
m
ok
ed
serv
e
d
as
the
com
par
ison
gr
oup.
Partic
ipa
nts
w
ho
in
dica
t
ed
so
m
e,
m
os
t
or
al
l
of
thei
r
f
rien
ds
sm
oked
had
si
gnific
antly
higher
od
ds
of
sm
ok
ing
tha
n
those
who
ha
d
ze
ro
f
rien
ds
who
sm
ok
ed.
Thir
d,
t
he
“
nu
m
ber
of
days”
pe
op
le
hav
e
sm
ok
ed
i
n
st
ud
e
nts’
ho
m
es
in
thest
udents’
prese
nce
sig
nificantl
y
pr
e
dicte
d
t
heir
te
nde
ncy
t
o
s
m
ok
e.
Stud
e
nts
who
ind
ic
at
ed
t
he
y
had
ze
ro
pe
op
le
sm
ok
e
i
n
their
hous
e
in
the
pa
st
7
days
se
r
ved
as
the
com
par
ison
gr
oup.
Th
os
e
who
in
dicat
ed
1
-
2,
3
-
4,
5
-
6
or
7
people
sm
ok
ed
in
their
hous
e
the
past
7
day
s
ha
d
sign
ific
a
ntly
hig
he
r
odds
of
s
m
ok
in
g.
F
ourt
h,
ha
vi
ng
c
hew
e
d
a
ny
form
of
tob
acc
o
products
oth
e
r
tha
n
ci
gar
et
te
s
in
t
he
past
30
days
sign
i
ficantl
y
pr
e
dicte
d
st
udents’
sm
ok
in
g
te
nd
e
ncies.
St
ud
e
nts
who
i
ndic
at
ed
they
ever
c
he
wed
a
ny
f
or
m
of
to
bacc
o
pro
du
ct
s
oth
e
r
tha
n
ci
gar
et
te
s
in
the
past
m
on
th
had
higher
odds
of
sm
ok
ing
ci
ga
r
et
te
s
than
tho
s
e
who
di
d
not.
Fifth,
a
stu
de
nt’s
se
x
was
a
sign
ific
a
nt
pr
e
dictor
of
the
te
nd
e
ncy
to
sm
ok
e.
Fem
al
es
had
a
lo
w
er
od
d
of
sm
ok
in
g
ci
ga
rett
es
than
t
heir
m
ale
counter
pa
rts.
Finall
y,
w
hether
or
no
t
disc
us
sin
g
the
ef
fects
of
sm
ok
ing
in
JHS
cl
asses
abo
ut
the
eff
ect
s
of
sm
ok
ing
as
a
predict
or
of
sm
ok
in
g
te
nd
e
ncies
res
ulted
in
m
ixed
res
ults.
Stu
den
ts
who
res
ponded
“
Yes”
to
discu
ssin
g
about
the
ef
f
ect
s
of
sm
ok
ing
in
th
ei
r
cl
asses
ser
ved
as
the
c
om
par
ison
group.
St
udents
w
ho
res
ponde
d
“No
”
ha
d
si
gnific
antly
lowe
r
od
ds
of
sm
ok
ing
ci
ga
r
et
te
s.
Ther
e
we
re
no
si
gn
i
ficant
dif
fer
e
nces
i
n
the
te
nd
e
ncie
s
to
sm
ok
e
ci
ga
rett
es
for
th
os
e
wh
o
r
esp
onde
d
“y
es
” an
d
th
os
e
wh
o
in
dicat
ed
the
y were
not s
ur
e
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2252
-
8806
IJPHS
V
ol.
7
,
No.
4
,
Decem
ber
2018:
223
–
230
228
Table
3.
Fit
te
d
Ba
ye
sia
n
I
nform
at
ion
Crit
erio
n
-
M
od
el
Variable
z
-
Sco
re
Od
d
s Ratio
Prob
ab
ility
(I
n
terce
p
t
)
-
1
1
.89
2
0
.11
6
0
.10
4
W
h
ere
do
y
o
u
us
u
ally
s
m
o
k
e?
(
Nev
er
s
m
o
k
ed
)
Ho
m
e
1
2
.27
3
9
.91
5
0
.90
8
Sch
o
o
l
3
.63
7
2
.95
5
0
.74
7
W
o
rk
5
.09
1
1
9
.63
1
0
.95
2
Friend
s’ Hou
se
8
.74
4
2
6
.65
5
0
.96
4
So
cial E
v
en
ts
4
.09
7
9
4
.34
1
0
.99
0
Pu
b
lic Places
7
.47
1
1
3
.00
9
0
.92
9
Oth
er
5
.02
2
2
7
.17
3
0
.96
5
Do
any
o
f
y
o
u
r
clo
ses
t f
riend
s s
m
o
k
e
cig
arettes?
(
No
n
e)
So
m
e
5
.61
1
2
.25
7
0
.69
3
Mos
t
2
.00
8
1
.85
7
0
.65
0
All
3
.62
7
3
.54
7
0
.78
0
Du
ring
the p
ast 7
days,
o
n
ho
w da
y
s h
av
e
m
an
y
peo
p
le hav
e s
m
o
k
ed
in y
o
u
r
h
o
m
e,
in
y
o
u
r
p
resence?
(
0
)
1
-
2
5
.88
2
2
.68
1
0
.72
8
3
-
4
2
.70
6
2
.35
4
0
.70
2
5
-
6
3
.22
1
2
.66
3
0
.72
7
5
-
7
3
.32
4
2
.22
5
0
.69
0
Du
ring
the p
ast 3
0
days (
m
o
n
th
)
hav
e y
o
u
ever
ch
ewed
an
y
f
o
r
m
of
tob
acc
o
p
rod
u
cts
o
th
er
th
an
cigarettes?
(
Yes)
No
-
4
.20
2
0
.51
2
0
.33
8
Sex
(
Mal
e)
Fe
m
ale
-
3
.47
6
0
.65
0
0
.39
4
Du
ring
this
sch
o
o
l
y
ear
,
d
id
y
o
u
dis
cu
ss
in an
y
of
y
o
u
r
cl
ass
es ab
o
u
t the ef
fects of
s
m
o
k
in
g
?
(
Yes)
No
-
3
.46
7
0
.64
2
0
.39
1
No
t Sure
1
.31
2
1
.30
9
0
.56
7
|
z
|
> 1.6
4
m
eans
st
atistically
sig
n
if
ican
t at
th
e 10
% lev
el
|
z
|
>
1
.96
m
eans
st
atistically
sig
n
if
ican
t at
th
e 5%
level
|
z
|
>
2
.58
m
eans
st
atistically
sig
n
if
ican
t at
th
e 1%
level
4.
DISCU
SSI
ON
The
prese
nt
stud
y
use
d
the
GY
T
S
20
09
da
ta
to
sp
eci
fy
a
m
od
el
f
or
predict
in
g
the
li
kelihoo
d
of
sm
ok
ing
at
th
e
j
unio
r
hi
gh
sch
oo
l
le
vel
in
Gh
a
na.
A
m
a
j
or
fi
nd
i
ng
of
the
stud
y
was
that
wh
e
re
stud
e
nts
sm
ok
ed
sign
i
ficantl
y
pr
ed
ic
te
d
their
sm
ok
ing
te
nde
ncies
-
the
ho
m
e,
sch
oo
l,
a
f
rien
d’
s
hous
e,
an
d
public
even
ts
are
en
vi
ron
m
ents
that
w
ou
l
d
i
ncr
eas
e
the
li
kelih
oo
d
th
at
JH
S
st
udents
w
ould
s
m
ok
e.
F
or
exa
m
ple,
par
e
ntal
s
m
oking
be
ha
viors
are
i
m
po
rtant
in
red
uci
ng
s
m
ok
ing
intenti
on
s
am
on
g
G
han
ai
a
n
yout
h
[1
3].
Adolesce
nts
w
it
h
par
e
nts
who
sm
ok
e
at
ho
m
e
would
m
ore
li
kely
hav
e
a
ccess
to
to
bac
co
at
hom
e
[18].
It
i
s
al
so
a
c
omm
on
pr
act
ic
e
for
par
e
nts
a
nd
oth
er
ad
ults
in
Gh
a
na
t
o
se
nd
their
c
hild
ren
or
oth
e
r
m
ino
rs
to
purc
hase
tob
ac
co
pro
duct
s
for
them
(p
aren
t
s/other
a
du
lt
s)
.
A
relat
ed
fin
di
ng
was
t
hat
the
nu
m
ber
of
pe
op
le
who
sm
ok
ed
i
n
st
ud
e
nts’
ho
m
es
in
their
presence
sig
nifi
cantl
y
pr
e
dicte
d
st
ud
e
nts’
li
ke
li
ho
od
t
o
sm
ok
e
.
To
bacco
co
ntr
ol
m
easur
es
in
G
han
a
are
spe
ci
fied
in
the
Publi
c
H
eal
th
Act
20
12
(
Act
851)
[19]
-
the
Ac
t
pro
hib
it
s
sm
oking
i
n
public
pl
aces
am
on
g
ot
her
restrict
io
ns.
U
nfo
r
tu
natel
y,
la
ck
of
en
f
orcem
ent
of
t
he
Act
unde
rm
ines G
over
nm
ent an
d
com
m
un
it
y effo
rts t
o
c
on
t
ro
l t
he negati
ve
ef
f
ect
s o
f
to
bacc
o use
[20
]
.
A
seco
nd
fin
di
ng
was
that
stud
e
nts
w
ho
sm
ok
e
d
we
re
m
or
e
li
kely
to
have
cl
os
est
fr
ie
nds
w
ho
al
so
sm
ok
ed.
This
fin
ding
is
c
on
sist
ent
with
pr
evio
us
fin
ding
s
that
sm
ok
e
rs
we
re
li
kely
t
o
have
f
rien
ds
w
ho
sm
ok
ed
[
15]
.
P
eer
in
flue
nce,
accor
ding
t
o
[21],
w
as
a
ris
k
f
act
or
for
sm
ok
i
ng.
St
ud
e
nts
w
ho
ha
d
bee
n
offer
e
d
a
ci
gar
et
te
were
m
or
e
li
kely
t
o
sm
ok
e.
In
a
ddit
ion
,
th
os
e
w
it
h
on
e
or
m
or
e
fr
ie
nds
ha
d
hi
gh
e
r
odds
to
s
m
ok
e
than
t
hose
who
had
no
f
rien
ds
[21].
Th
us
,
strat
egies
f
or
increasin
g
ad
ol
escents’
s
el
f
-
e
ste
e
m
and
dec
isi
on
-
m
aking
capa
bi
li
ti
es
are
crit
ic
al
for
sm
ok
in
g
preve
ntio
n
i
n
G
han
a
.
As
no
te
d
by
[
22
]
,
a
do
le
sce
nts
with
high
le
vels o
f sel
f
-
e
ste
e
m
w
ou
l
d
be
less su
sce
ptible t
o
pee
r pr
e
ssu
re t
ha
n
their
co
unte
r
par
ts
with lo
w
le
vels
o
f
sel
f
-
est
ee
m
.
Thir
d,
the
use
of
a
ny
f
or
m
of
to
bacc
o
pro
du
ct
s
oth
er
th
an
ci
gar
et
te
s
predict
ed
stu
de
nts’
sm
ok
in
g
te
nd
e
ncies.
Re
search
has
s
ho
wn
t
hat
in
div
i
du
al
s
w
ho
c
he
wed
oth
e
r
f
or
m
s
of
tob
acc
o
pro
du
ct
s
in
the
pa
st
m
on
th
ha
d
higher
od
ds
of
s
m
ok
ing
ci
ga
re
tt
es
than
t
ho
se
w
ho
di
d
no
t.
Sm
ok
el
e
ss
toba
cco
is
a
sig
nificant
pr
e
dictor
of
s
m
ok
ing
init
ia
ti
on
am
on
g
y
oung
ad
ult
m
al
es
.
Pa
rtic
ipants
who
us
e
d
sm
ok
el
ess
to
bacc
o
we
r
e
m
or
e
li
kely
to
beg
i
n
sm
ok
in
g
that
nonuse
rs
[23].
F
ur
t
her
m
or
e
,
sm
ok
el
ess
tob
acc
o
has
be
en
ass
ociat
ed
with
healt
h
risks
suc
h
as
cancer
c
ausin
g
substa
nc
es
[24]
and
a
dv
e
rse
car
diov
ascular
healt
h
[25],
an
d
it
is
no
t
a
feasible s
ubsti
tute f
or ciga
rett
e sm
ok
ing [
24
]
.
Finall
y,
m
al
e s
tud
e
nts h
a
d
higher pre
valence
of
sm
ok
in
g
tha
n
their f
em
al
e
counter
par
ts
. T
his f
in
ding
is
consi
ste
nt
w
it
h
t
hat
of
[
20]
,
w
ho
re
ported
higher
sm
ok
in
g
te
nde
ncies
a
m
on
g
G
ha
naian
a
du
lt
m
al
es
t
han
i
n
Evaluation Warning : The document was created with Spire.PDF for Python.
IJPHS
IS
S
N: 22
52
-
8806
Predict
ing
Smokin
g
Be
havi
ors
amo
ng J
unio
r H
ig
h Sc
hool
Students
in
G
hana.
..
(
E
mma
nuel
T
hom
pson
)
229
fem
al
es.
Thu
s,
early
sm
ok
ing
inter
ve
ntion
pro
gr
am
s
a
m
ong
sc
hool
-
ag
ed
a
do
le
sce
nts
is
warrante
d
as
ba
d
hab
it
s
a
re
diffi
cult
to
brea
k.
This
w
ou
l
d
prom
ote
healt
hy
li
festy
le
s
cho
ic
es
am
on
g
s
tud
e
nts
s
uch
a
s
the
avo
i
dan
ce
of al
cohol a
nd to
ba
cco c
onsu
m
ption [
26]
.
Find
i
ngs
from
the
pr
ese
nt
stud
y
ha
ve
im
pl
ic
at
ion
s
f
or
sc
hool
an
d
com
m
un
it
y
healt
h.
First,
sch
oo
l
sm
ok
ing
pr
e
ve
ntion
pr
ogram
s
nee
d
to
inclu
de
pa
ren
ts
a
nd
c
omm
un
it
y
le
ader
s.
Seco
nd,
st
ud
e
nts’
sel
f
-
est
ee
m
and
decisi
on
m
aking
ca
pab
i
li
ti
es
m
us
t
be
addresse
d
in
school
inter
ve
ntion
pro
gr
a
m
s
aim
ed
at
sm
ok
ing
pr
e
ve
ntion.
St
ud
e
nts
with
high
sel
f
-
est
e
e
m
would
m
or
e
li
kely
res
ist
s
m
ok
in
g
up
ta
ke
du
e
t
o
peer
pr
ess
ure
[22].
In
ad
diti
on,
st
ud
e
nts
nee
d
th
e
sk
il
ls
to
hel
p
them
m
ake
good
decisi
ons
that
w
ould
le
ad
to
healt
hy
li
festy
le
s.
Finall
y,
the
data
us
e
d
f
or
the
present
st
udy
we
re
the
m
os
t
cu
rr
e
nt
on
tob
acc
o
s
urvey
data
for
Gh
a
na,
a
nd
wer
e
pu
blished
in
20
09.
Ther
e
f
or
e,
it
is
inc
um
ben
t
on
Gh
a
na
’s
sta
keholde
rs
i
n
t
he
healt
h
sect
or
to
im
ple
m
ent
the
GY
T
S
to
gain
insig
ht
on
the
m
os
t
cur
re
nt
sm
ok
ing
beh
a
viors
a
m
on
g
school
-
goin
g
aged ad
olesce
nt
s in
the
cou
ntr
y.
The
c
urre
nt
st
ud
y
util
iz
ed
a
cl
os
ed
-
en
de
d
s
urvey
(
G
YTS)
to
e
xam
ine
j
unio
r
high
sc
ho
ol
stu
de
nts’
sm
ok
ing
te
nde
ncies.
F
uture
r
esearch
co
uld
us
e
oth
er
ap
proach
e
s
to
gain
fu
t
her
i
ns
ig
ht
on
sm
ok
ing
a
m
on
g
ado
le
sce
nts.
Fi
rst,
f
uture
rese
arch
e
rs
s
hould
include
qual
it
at
ive
appr
oaches
su
c
h
as
f
oc
us
gr
oups
to
a
ll
ow
par
ti
ci
pa
nts
to
fr
eel
y
ex
pr
es
s
their
feeli
ngs.
This
w
ould
prov
i
de
bette
r
un
der
sta
nd
i
ng
of
stud
e
nts’
te
nd
e
ncies
towa
rd
sm
ok
in
g.
Sec
ond,
the
pr
ese
nt
stu
dy
pro
vid
e
d
ag
gregated
natio
na
l
data.
Fu
t
ur
e
researc
h
us
in
g
data
disag
gr
e
gated
by
re
gion
would
rev
e
al
re
gi
on
al
disp
a
riti
es,
if
a
ny,
re
la
ti
ng
t
o
J
HS
stud
e
nts’
sm
ok
i
ng
te
nd
e
ncies.
T
hi
s
would
al
lo
w
po
li
cy
m
aker
s
and
healt
h
a
nd
sc
hool
adm
i
nistrato
rs
to
ta
rg
et
r
egi
on
s
pe
ci
fic
pr
e
dictor
s
of
t
end
ie
ncies
for
eff
ect
ive
sm
oking
prev
entio
n
interve
ntion
s
.
Finall
y,
fu
tur
e
researc
her
s
s
hould
include
m
ulti
-
age
po
pu
la
ti
ons
inclu
ding
jun
i
or
high,
se
nior
high
sc
hools
a
nd
c
olleges
an
d
un
i
ve
rsiti
es.
Re
su
lt
s
of
s
uc
h
stu
dies
woul
d
prov
i
de
a
c
om
pr
ehen
sive
inf
or
m
at
ion
on
the
pre
valenc
e
of
sm
ok
in
g
for
the
resp
ect
ive
e
ducat
ion
al
levels
in the c
ount
ry.
5.
CONCL
US
I
O
N
S
The
prese
nt
stud
y
s
howe
d
that
en
vironm
ental
issues
we
re
i
m
po
rta
nt
f
act
or
s
that
im
pacted
j
unio
r
high
sch
ool
stud
e
nts’
sm
ok
i
ng
te
nd
e
ncies.
The
hom
e,
school,
a
f
rien
d’
s
hous
e
,
an
d
pu
blic
even
t
s
were
env
i
ronm
ents
t
hat
sign
ific
a
ntly
pr
edict
ed
sm
ok
i
ng
beh
a
vior
s.
In
a
dd
it
io
n,
so
ci
al
interact
ion
s
,
especial
ly
,
with
peer
s
a
re
sig
ni
ficant
determ
inants
of
st
ud
e
nts’
sm
ok
in
g
be
hav
i
or
s
.
F
ur
t
her
m
or
e,
the
s
tud
y
re
vealed
t
hat
the
Lo
git
m
od
el
was
a
powe
rful
sta
ti
sti
cal
t
oo
l
f
or
ide
ntif
yi
ng
predict
or
s
of
G
ha
naian
j
unio
r
high
s
choo
l
stud
e
nts’ sm
ok
ing
be
hav
i
or
s
.
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