Do current OELs for silica protect from obstructive lung...
30
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=itxc20 Download by: [The UC San Diego Library] Date: 18 May 2017, At: 00:51 Critical Reviews in Toxicology ISSN: 1040-8444 (Print) 1547-6898 (Online) Journal homepage: http://www.tandfonline.com/loi/itxc20 Do current OELs for silica protect from obstructive lung impairment? A critical review of epidemiological data Perrine Hoet, Laure Desvallées & Dominique Lison To cite this article: Perrine Hoet, Laure Desvallées & Dominique Lison (2017): Do current OELs for silica protect from obstructive lung impairment? A critical review of epidemiological data, Critical Reviews in Toxicology, DOI: 10.1080/10408444.2017.1315363 To link to this article: http://dx.doi.org/10.1080/10408444.2017.1315363 Published online: 17 May 2017. Submit your article to this journal View related articles View Crossmark data
Transcript of Do current OELs for silica protect from obstructive lung...
Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=itxc20
Download by: [The UC San Diego Library] Date: 18 May 2017, At: 00:51
Critical Reviews in Toxicology
ISSN: 1040-8444 (Print) 1547-6898 (Online) Journal homepage: http://www.tandfonline.com/loi/itxc20
Do current OELs for silica protect fromobstructive lung impairment? A critical review ofepidemiological data
Perrine Hoet, Laure Desvallées & Dominique Lison
To cite this article: Perrine Hoet, Laure Desvallées & Dominique Lison (2017): Do current OELsfor silica protect from obstructive lung impairment? A critical review of epidemiological data, CriticalReviews in Toxicology, DOI: 10.1080/10408444.2017.1315363
To link to this article: http://dx.doi.org/10.1080/10408444.2017.1315363
Published online: 17 May 2017.
Submit your article to this journal
View related articles
View Crossmark data
REVIEW ARTICLE
Do current OELs for silica protect from obstructive lung impairment? A criticalreview of epidemiological data
Perrine Hoet, Laure Desvall�ees and Dominique Lison
Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institute of Experimental and Clinical Research (IREC), Universit�e Catholiquede Louvain, Bruxelles, Belgium
ABSTRACTInhalation of respirable crystalline silica (RCS) can lead to serious health effects such as silicosis andlung cancer. There also seems to be a general consensus to consider that RCS exposure is associatedwith obstructive lung impairment or chronic obstructive pulmonary disease (COPD), a leading cause ofmortality, morbidity, and disability worldwide. It is, however, not clear whether occupational exposurelevels (OELs), generally set to prevent silicosis, also protect workers from developing an obstructiveimpairment. This review aims at clarifying the potential relationship between RCS exposure andobstructive lung impairment as defined by spirometry. Eleven studies that reported both silica exposurelevels and spirometry results were identified. We systematically extracted data pertaining to (a) thepopulation studied, (b) level of exposure to RCS and other pollutants, (c) spirometry procedure andinterpretation, and (d) methodology used to investigate the relationship between RCS exposure andspirometry. These studies add supporting evidence in favor of a qualitative association between occu-pational activities exposing to RCS and obstructive lung dysfunction. However, no well-founded quanti-tative estimate can be drawn from these investigations; the available relevant literature does not allowdefining a RCS exposure threshold associated with an increased risk of obstructive lung dysfunction, asdefined by spirometry, in workers without silicosis. Further research is needed, but, as highlighted inthis review, conducting epidemiological studies with both valid exposure and outcome measurementsis a real challenge.
Abbreviations: ACOEM: American College of Occupational and Environmental Medicine; ATS: AmericanThoracic Society; COPD: chronic obstructive pulmonary disease; EC: elemental carbon; ECSC: EuropeanCommunity for Steel and Coal; ERR: exposure–response relationship; ERS: European Respiratory Society;HSE: Health and Safety Executive, UK; FEV1: Forced Expiratory Volume in 1 second; FVC: forced vital cap-acity; FU: follow up; GOLD: Global Initiative for Chronic Obstructive Lung Disease; IARC: InternationalAgency for Research on Cancer; LF: lung function; LFT: lung function test; NIOSH: National Institute forOccupational Safety and Health; OC: organic carbon; OEL: occupational exposure limit; OSHA: occupa-tional safety and health administration; RCS: respirable crystalline silica; RD: respirable dust; SCOEL:Scientific Committee on Occupational Exposure Limits; WHO: World Health Organization
ARTICLE HISTORYReceived 24 November 2016Revised 28 March 2017Accepted 31 March 2017
KEYWORDSCOPD; obstructive lungdysfunction; FEV1; lungfunction test; spirometry;occupational exposure;crystalline silica
Table of contents
Introduction ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...2Methodology ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...2Exposure characterization ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...9
Assessment of exposure to RCS ... ... ... ... ... ... ... ... ... ... ... ... 9Sampling and analysis strategies ... ... ... ... ... ... ... ... ... 9Sensitivity of the methods ... ... ... ... ... ... ... ... ... ... ... ... 10
Characterization of exposure to other pollutants ... ... ... 10Outcome characterization ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 10
LFT equipment and procedure ... ... ... ... ... ... ... ... ... ... ... 10LFT interpretation ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 12
Expression of results ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 12
Study design ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 14Critical analysis of available studies ... ... ... ... ... ... ... ... ... ... 19
Cross-sectional studies ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 19Studies using exposure proxies in the ERR analyses 19Studies using RCS in the ERR analyses ... ... ... ... ... ... 20
Longitudinal studies ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 21Studies using exposure proxies in the ERR analyses 21Studies using RCS in the ERR analyses ... ... ... ... ... ... 21
Conclusion and recommendations for further research... 23Acknowledgements ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 24Declaration of interest ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 24Supplemental material ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 24References ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 24
CONTACT Perrine Hoet [email protected] Universit�e Catholique de Louvain, Louvain Center for Toxicology and Applied Pharmacology (LTAP),Institute of Experimental and Clinical Research (IREC), Secteur Soins de Sant�e, Avenue Mounier, 53 bte B1.52.12, Bruxelles 1200, Belgium� 2017 Informa UK Limited, trading as Taylor & Francis Group
CRITICAL REVIEWS IN TOXICOLOGY, 2017http://dx.doi.org/10.1080/10408444.2017.1315363
Introduction
Chronic obstructive pulmonary disease (COPD) is a leadingcause of mortality, morbidity, and disability worldwide. It wasthe third leading cause of death worldwide in 2015 and thesixth leading cause of non-communicable disease burden(Kassebaum et al. 2016; Wang et al. 2016). COPD is a com-mon, preventable, and treatable disease that is characterizedby persistent respiratory symptoms and airflow limitation thatis due to airway and/or alveolar abnormalities usually causedby significant exposure to noxious particles or gases (GOLD2017). Tobacco smoking is a well-recognized and major riskfactor for COPD. Indoor and outdoor air pollution exposing toa complex mixture essentially comprising particulate matter,volatile organic compounds VOCs, nitrogen oxides NOx, CO,and O3 are associated with COPD development. Occupationalexposures to these agents as well as to others (e.g. coal, cot-ton, wood, silica, vanadium, and osmium dust; cadmium, andwelding fumes; endotoxins; polycyclic aromatic hydrocarbonsPAHs or isocyanates) are additional suspected or confirmedetiological factors (ERS/ELF 2013; Bang 2015; De Matteis et al.2016). The population attributable fraction of COPD linked tooccupation is estimated to about 15%, the occupational con-tribution to COPD in non-smokers being substantially greater(Balmes et al. 2003; Celli et al. 2005; Blanc & Tor�en 2007; Salvi& Barnes 2009; Blanc 2012; Omland et al. 2014; Bang 2015;Wurtz et al. 2015).
Crystalline silica (CS) is a basic component of rock, sand,and soils; the most abundant type being, by far, quartz.Cristobalite and tridymite, other varieties of naturally occur-ring CS (volcanic rock), are more generally produced fromsuperheating quartz or diatomaceous earth, which in itsnative form mainly contains amorphous silica. Significantoccupational exposures to CS may be encountered in numer-ous industrial sectors such as mining, quarrying, tunnelingand construction, as well as in activities using industrial sand(i.e. high purity silica sand >95% SiO2) such as in glass mak-ing, foundries, abrasive, ceramic, and refractory materialsmanufacturing, chemical industries, filtration or hydraulic frac-turing and construction. Cutting, chipping, drilling, grindingor blasting silica-containing materials such as brick, cement,concrete, drywall, grout, mortar, stone, sand, and tile producerespirable size particles (NIOSH 2002; Bradshaw et al. 2010;OSHA 2016; SLIC 2016).
Respirable crystalline silica (RCS) is a serious inhalationhazard that can cause silicosis, one of the world’s oldestknown occupational disease, and is classified, in the form ofquartz or cristobalite, as a human lung carcinogen (IARC1987, 1997, 2012). There also seems to be a general consen-sus to consider that RCS inhalation is associated to COPD orobstructive lung impairment (ATS 1997; WHO 2000;Easterbrook & Brough 2009; Bradshaw et al. 2010; ERS/ELF2013; HSE 2016; NIOSH 2002; OSHA 2016; SLIC 2016).Reviewing the literature on the topic, Hnizdo and Vallyathan(2003) concluded that chronic exposure to RCS can inducethe development of emphysema, chronic bronchitis, and/orsmall airways disease that can lead to airflow obstruction,even in the absence of radiological signs of silicosis. A recentmeta-analysis concluded that occupational exposure to RCS is
associated with a statistically significant decrease in FEV1(forced expiratory volume in 1 s) and FEV1/FVC (forced expira-tory volume in 1 s/forced vital capacity ratio), revealing airwayobstruction consistent with COPD (Br€uske et al. 2014).However, it is not clear whether current occupational expos-ure limits (OELs), which are generally set to prevent thedevelopment of silicosis, considered to be the critical healtheffect of RCS, also protect workers from developing anobstructive impairment. Currently recommended OELs (respir-able fraction) range from 0.15 to 0.05mg/m3 (GESTIS 2016).The European Scientific Committee of OccupationalExposure Level recommended that the OEL should lie below0.05mg/m3 of RCS to prevent silicosis (SCOEL 2003). In 2006,the American Conference for Governmental IndustrialHygienist decreased the Threshold Limit Value from 0.05 to0.025mg/m3 and in 2016, the OSHA amended its existingstandards for occupational exposure to RCS at 0.05mg/m3
(quartz, cristobalite and tridymite) and established an actionlevel at 0.025mg/m3.
The main objective of this study was to assess whetherexposure to silica at levels considered protective against sili-cosis is associated with obstructive lung impairment asdefined by spirometry, hereafter designated as lung functiontest (LFT). For this purpose, we critically reviewed epidemio-logic studies on silica-exposed workers that investigatedobstructive lung impairment by means of FEV1, FEV1/FVC inworkers without silicosis to clarify the potential exposure-response relationship. We highlight some critical issues facedwhen conducting this review.
Methodology
Published literature was searched until October 2016.Literature screening and selection as well as data extractionwere performed independently by two reviewers, with dis-agreements resolved by discussion and consensus.
A search on MEDLINE (National Library of Medicine,Bethesda, MD) was initially undertaken using the followingterms ((“Silicon Dioxide”[Mesh] OR silica OR quartz) AND FEV1)to identify potentially relevant publications. References lists ofidentified publications were checked for additional studies.The search was limited to studies published in English, French,German or Dutch in the open literature in peer-reviewed jour-nals. Among the 140 publications retrieved, 29 were consid-ered suitable for further consideration after screening theabstracts and excluding reviews, meta-analysis, case-reports,abstracts, regulatory documents, editorials, comments, andletters (besides those concerning the articles considered as eli-gible for inclusion). A close reading of these publicationsallowed selecting studies that (1) referred to workers occupa-tionally exposed to crystalline silica with quantified levels ofexposure; (2) included spirometry as outcome; (3) ascertainedthe absence of radiographic evidence of silicosis or took intoaccount in the statistical analyses identified cases of silicosis;and (4) presented original data.
Finally, 11 original studies were eligible for inclusion.These surveys concern North American, Swedish, andSpanish granite workers (Malmberg et al. 1993; Graham et al.1994; Rego et al. 2008), Norwegian tunnel workers
2 P. HOET ET AL.
Table1.
Maincharacteristicsof
thepo
pulatio
n,RC
Sexpo
sure
assessmentandLFTprocedure.
Coh
ort
sele
ctio
n E
xpos
ure
asse
ssm
ent
Out
com
e as
sess
men
tP
erio
d of
inve
stig
atio
nsP
erio
d of
mea
sure
men
tsP
erio
d of
LFT
(ye
ar)
Num
ber
of s
etti
ngs
Sam
plin
g &
ana
lysi
s st
rate
gyW
hen
(mom
ent o
f th
e da
y, b
efor
e/af
ter
shif
t)
gnilpmas fo reb
mun = n
desopx e ,slortnoc fo rebm u
NW
here
(oc
cup
heal
th s
ervi
ce, h
ospi
tal,
etc.
)
Age
, sm
okin
g st
atus
mas ,epyt( tnempiuq
Etn e
my olpme /erusopxe fo noitaru
De
equi
pmen
t acr
oss
subj
etcs
, FU
)
Mat
chin
gytilau q(
PS ,C
Q)
DS(
MG )egnar ;
DS( M
A noitartnec noC
con
trol
, sta
ndar
dize
d pr
oced
ure)
AM
(S
D; r
ange
)iniar
Tstnatullop reh to ot erusop xe no noit agitsevnI
ng (
adeq
uate
tech
nici
an tr
aini
ng)
Cal
ibra
tion
(ch
eck)
Val
idit
y (c
urve
s ac
cept
able
/rep
rodu
cibl
e, c
rite
ria)
Hei
gth
(mea
sure
d)
Res
ults
exp
ress
in &
abn
orm
al v
alue
def
init
ion
Cro
ss-s
ecti
onal
stu
dies
Jorn
a et
al.
1994
(P
otat
o so
rtin
g pl
ants
, The
Net
herl
ands
)Pe
riod
: n.i.
Air
sam
plin
g &
ana
lysi
s st
rate
gyS
piro
met
ryFE
V1,
FV
C, F
EV
1/FV
C, P
EF,
MM
EF
5 pl
ants
sam
e ag
ricu
ltur
al c
oope
rati
ve,
Peri
od: 1
988
Per
iod
n.i.
Oct
ober
aft
er p
otat
oes
harv
est,
peak
act
ivit
y)
Cau
casi
an w
oker
sP
erso
nal s
ampl
ing
(n=
21)
Whe
nn.
i.
55C
ontr
ols
(cyc
lone
), 8
-hr
coll
ecti
on
Whe
ren.
i.
0.O
ffic
e st
aff.
38
(9)
yrs
old
Sili
ca a
naly
sis:
IR
S (L
OD
: n.i.
)E
quip
men
tA
dry
spi
rom
eter
pma s tsu d
R 2 n i de nimr ete
D)
%0 2 SC ,
%33 SE ,
% 02 SN (
les
All
sub
ject
s te
sted
on
the
sam
e sp
irom
eter
116
Exp
osed
Cum
ulat
ive
expo
sure
:Q
C, S
Pn.
i.
I.29
sal
esm
en. 4
5 (1
1) y
rs o
ld"c
umul
ativ
e do
se o
f tot
al d
ust a
nd o
f sil
ica
expo
sure
Tra
inin
gn.
i.
(NS
10%
, ES
42%
, CS
48%
)es
tim
ated
from
eac
h w
orke
r's
job
hist
ory"
Cal
ibra
tion
"at r
egul
ar in
terv
als"
II.
71 b
lue
coll
ars.
46
(11)
yrs
old
Exp
dur
atio
n:ytidi la
Vsry )7. 9( 4 .21
.0"F
EV
cur
ves
reco
rded
acc
ordi
ng to
EC
SC-1
983
(NS
15%
, ES
35%
, CS
50%
)I.
16.2
(11
.8)
3 c
urve
s w
ithi
n 5
% o
r 10
0-m
L"
4. 8( 8.11.II
dl o sr y )6( 4 6 . srekrow de riter 61
.III.i .n
SP
TB
)
(NS
13%
, ES
56%
, CS
31%
).i.n
th gieH
)8. 7( 4.22. III
Mat
chin
g: c
ompa
red
wit
h co
ntro
lsE
xp le
vel:
mg/
m³
Res
ults
exp
ress
ed a
s: %
pre
d. A
M (
SD)
mronbA
)7.6–5.0( 12.2
tsud R
) an
d50.0
<p( r eivae h nemselaS
al v
alue
def
ined
as:
FEV
1 <
80%
pre
d
long
er d
urat
ion
of e
mpl
oym
ent (
p<0.
05)
RC
S0.
27 (
0.09
–0.8
4)
Cur
rent
exp
osed
old
er (
p<0.
05)
0.23
(1.
8)
Ret
ired
wor
kers
old
er (
p<0.
01),
Exp
to o
ther
pol
luta
nts:
n.i.
heav
ier
smok
ers
(p<
0.05
) an
d
smal
ler
(p<
0.05
)E
xclu
sion
: n.i.
(continued)
CRITICAL REVIEWS IN TOXICOLOGY 3
Table1.
Continued
Peri
od: n
.i.A
ir s
ampl
ing
& a
naly
sis
stra
tegy
Spir
omet
ryFE
V1,
FV
C, F
EV
1/FV
C,
FEF2
5-75
15 tu
nnel
con
stru
ctio
n si
tes
Per
iod:
199
6–19
99P
erio
dn.
i.
205
Con
trol
sP
erso
nnal
sam
plin
g L
FT in
tegr
ated
in th
e he
alth
che
ck-u
p
Hea
vy o
utdo
or c
onst
ruct
ion
wor
kers
. (c
yclo
ne, c
ellu
lose
ace
tate
fil
ters
, FR
2.2
L/m
in)
Whe
nn.
i.
41 (
10)
yrs
old
5–8-
hr c
olle
ctio
nW
here
Hea
lth
serv
ice
offi
ce, a
t wor
k si
tes
(NS
31%
, ExS
17%
, CS
52%
)Si
lica
ana
lysi
s: X
RD
(ac
cord
ing
to N
IOSH
750
0 (1
998)
)E
quip
men
tB
ello
ws
spir
omet
er
pack
-yrs
: 14
(10)
LO
D: n
.i.Q
C, S
Pn.
i.
212
Exp
osed
Con
trol
s:
n=40
R d
ust &
RC
S (1
9 w
orke
rs)
Tra
inin
gsa
me
"tra
ined
" te
chni
cian
sud R 683
=n:desopx
Edlo sry ) 01( 04 .s re kro
w lenn uT
yliadnoitarbila
C)srekro
w 151( t
(NS
28%
, ExS
18%
, CS
54%
)ytidila
V)srekro
w 721 ( SC
R 992=n
"mea
sure
men
ts in
acc
orda
nce
wit
h A
TS
(198
7)"
Pac
k -yr
s: 1
6 (1
3)E
xp d
urat
ion:
13 (
9) y
rs"
≥ 3
curv
es w
ith
FV
C w
ithi
n v
aria
tion
Mat
chin
g: a
ge, h
eigh
t, sm
okin
g ha
bits
Exp
leve
l:m
g/m
3 o
f 50
ml o
r m
ax 2
%"
Exc
lusi
on :
n.i.
R d
ust
Ctr
l0.
3, 0
.21
(0.
1–1.
1)B
TP
Sye
s
Exp
1.17
, 1.2
(0.
03–9
.3)
Hei
ght
n.i.
RC
SC
trl
0.00
3, 0
.003
(0.
001–
0.02
)R
esul
ts e
xpre
ssed
as:
% p
red.
AM
(SE
)
Exp
0.13
, 0.0
34 (
0.00
1–2.
0)C
OP
D d
efin
ed a
s:
FEV
1/FV
C <
0.7
Exp
to o
ther
pol
luta
nts:
NO
2, o
il m
ist
Mei
jer
et a
l. 20
01 (
Con
cret
e m
ater
ials
fac
tory
wor
kers
, The
Net
herl
ands
)Pe
riod
: 199
2–1
993
Air
sam
plin
g &
ana
lysi
s st
rate
gySp
irom
etry
FE
V1,
FV
C, F
EV
1/FV
C, M
ME
F
2 fa
ctor
ies,
Cau
casi
an w
orke
rs
Peri
od: 1
992–
1993
(du
ring
aut
umn
& s
umm
er)
Per
iod
n.i.
(Aut
umn)
110
Con
trol
sP
erso
nnal
sam
plin
g (n
=96
)W
hen
9 am
till
1 p
m
Off
ice
wor
kers
sam
e ge
ogra
ph a
rea
rand
omly
sel
ecte
d.i.n
er ehW
, keew eh t f o s yad
Man
ager
s, la
b pe
rson
nel,
truc
k dr
iver
sdu
ring
a 3
-we
s gnillor yrdtne
mpiuqE
.noitcelloc rh-8 ,doirep keea
l 10
L s
piro
met
er
35 (
10)
yrs
old
(cyc
lone
, cel
lulo
se a
ceta
te f
ilte
r, F
R 1
.9 L
/min
)Q
C, S
Pn.
i.
(NS
29%
, ES
26%
, CS
45%
)Si
lica
ana
lysi
s: I
RS
(LO
D: n
.i.)
Tra
inin
g"a
trai
ned
assi
stan
t"
144
Exp
osed
noitarb ilaC
)3.11–4.4(
%3.9 :D
R ni SC
R fo tnetnoc"c
alib
rati
on,
mea
urem
ents
, dat
a se
lect
ion
Pro
duct
ion
wor
kers
. 36
(10)
yrs
old
Cum
ulat
ive
expo
sure
Val
idit
yac
cord
ing
to E
CSC
(Q
uanj
er 1
983)
"
(NS
33%
, ES
21%
, CS
56%
)"H
isto
rica
l exp
for
each
wor
ker
calc
ulat
ed a
s th
e s u
m o
f B
TP
Sn.
i.M
atch
ing
: age
, hei
ght,
wei
ght,
ethn
icit
ypr
oduc
ts o
f mea
n du
st o
r R
CS
conc
entr
atio
ns a
nd y
rs
Hei
ght
n.i.
Exp
osed
: les
s al
lerg
y,w
orke
d in
spe
cifi
c jo
bs o
r dp
ts"
Res
ults
exp
ress
ed a
s: %
pre
d. A
M (
SD)
high
er s
mok
ing
stat
us, p
ack-
yrs
Exp
dur
atio
n:11
.3 (
8.4)
yrs
CO
PD
def
ined
as:
FEV
1/FV
C r
atio
<P5
(<
–1.
64 *
RSD
)E
xclu
sion
: "ex
posu
re to
occ
upat
iona
l haz
ards
(s
imil
ar in
con
trol
s &
exp
osed
)R
SD: R
esid
ual S
tand
ardi
zed
Dev
iati
on
duri
ng th
e pr
esen
t job
"E
xp le
vel:
mg/
m³
mg/
m3 -y
r
R d
ust
0.77
(0.
08–2
.67)
7.0
(6.2
)
RC
S0.
059
(0.0
003–
0.2)
0.56
6 (0
.548
)E
xp to
oth
er p
ollu
tant
s: n
.i.
Ulv
esta
d et
al.
2000
(T
unne
l wor
kers
, Nor
way
)
(continued)
4 P. HOET ET AL.
Table1.
Continued
Peri
od: 1
978–
1992
Air
sam
plin
g &
ana
lysi
s st
rate
gySp
irom
etry
FEV
1, F
VC
, FE
V1/
FVC
1 fo
undr
y. C
urre
nt &
ret
ired
wor
kers
Cum
ulat
ive
expo
sure
Per
iod
1978
–199
2,
LFT
num
ber:
≥1
LFT
for
whi
ch ≥
med
ical
rec
ords
523
FVC
eter
696
FEV
1 fr
om 1
985:
wat
er-s
eal s
piro
met
er
247
FEV
1/FV
C
2 ef
fort
sD
ata
coll
ecte
d fr
om p
lant
wal
k-th
roug
h su
r ynap
moc morf det cartxe stluse r
TFL
& yna pmoc ,syev
Rat
ed a
s ac
cept
able
and
rep
rodu
cibl
eun
ion
indu
stri
al h
ygie
ne f
iles
, em
ploy
ee in
terv
iew
sW
hen
n.i.
Est
imat
ed le
vels
of
expo
sure
by
date
, dpt
& jo
b fc
t,W
here
n.i.
(NS
17%
, CS
75%
, USS
6.5
%)
mer
ged
wit
h pe
rson
nel r
ecmorips
woleb a :4891–8791
tnemp iuq
Eetaluclac ot sdro
CE
leve
l for
eac
h em
ploy
ee
(NS
17%
, CS
75.5
%, U
SS 7
.5%
)E
arly
dat
a: d
ust c
ount
s co
nver
ted
to m
ass
conc
entr
atio
n Q
C, S
Pno
of s
ilic
a ex
posu
re, u
sed
to c
alcu
late
TW
A e
xpos
ure
Tra
inin
gN
IOSH
cer
tifi
ed c
ours
e,
(NS
15%
, CS
78%
, USS
7%
)E
xp d
urat
ion:
18.3
(7.
3) y
rsno
ong
oing
con
tinu
ing
educ
atio
n
59 (
12)
yrs
old
Exp
leve
l:m
g/m
3 -yr
Cal
ibra
tion
n.i.
Mat
chin
g be
twee
n ex
p qu
arti
les
: n.i.
R "
sili
ca"
Q1
<0.
84V
alid
ity
resu
lts
revi
ewed
, E
xlus
ion
: asb
esto
sis
(Che
st-X
R)
Q2
0.84
–2.5
rate
d fo
r ac
cept
/rep
eat c
rite
ria
Q3
>2.
5–7
.5B
TP
Sn.
i.
Q4
>7.
5H
eigh
tn.
i.E
xp to
oth
er p
ollu
tant
s: n
.i.A
bnor
mal
val
ues
defi
ned
as:
FEV
1, F
VC
: <
low
er 9
5% c
onfi
dent
lim
it
FEV
1/FV
C: <
70%
(<
60 y
rs o
ld),
<65
% (
≥ 60
yrs
old
)
Reg
o et
al.
2008
(G
rani
te w
orke
rs, S
pain
)Pe
riod
: 200
4–20
05A
ir s
ampl
ing
& a
naly
sis
stra
tegy
Spir
omet
ryFE
V1,
FV
C, F
EV
1/FV
C
"Wor
kers
fro
m c
ompa
nies
in th
e ar
ea"
Peri
od: n
.i.P
erio
dn.
i.
440
Exp
osed
(ac
tive
)P
erso
nnal
sam
plin
g. (
n=
n.i.)
LFT
inte
grat
ed in
the
year
ly c
heck
-up
dril
lers
, gri
nder
s, la
bore
rs, m
anso
rycy
clon
e, m
easu
.i.nneh
W)SI
N yb stnemer
37.1
(18
–62
) yr
s ol
dSi
lica
anal
ysis
: IR
S (L
OD
: n.i.
)W
here
n.i.
(NS
38%
; ExS
19%
; CS
41%
; USS
1%
)co
nten
t of
RC
S in
RD
: 20.
8%E
quip
men
tM
aste
rlab
Bod
y-T
rans
fer
by J
aege
rM
atch
ing
betw
een
exp
quin
tile
s : n
.i.C
umul
ativ
e ex
posu
reQ
C, S
Pn.
iE
xclu
sion
: ast
hmat
ics
"cal
cula
ted
from
his
tori
cal d
ata
abou
t sil
ica
expo
s ure
leve
lsT
rain
ing
"fol
low
ing
AT
S (1
994)
as
far
as
avai
labl
e at
NIS
sin
ce 1
991,
cur
rent
val
ues,
que
stio
nnai
re.
Cal
ibra
tion
trai
ned
pers
onne
l, ca
libr
atio
n &
Val
ues
foun
d in
199
1 ex
trap
olat
ed r
etro
spec
tive
lyV
alid
ity
acce
pt/r
epro
duct
cri
teri
a ar
e co
ncer
ned"
wit
h va
lues
foun
d in
199
1"B
TP
Sn.
i.
Exp
dur
atio
n: 1
3.2
(1–
44)
yrs
Hei
ght
n.i.
Exp
leve
l:m
g/m
³*m
g/m
3 -yr
Abn
orm
al v
alue
def
ined
as:
RC
S0.
27–0
.41
Q1
0.40
(0.
06–0
.92)
FEV
1 %
pre
d <
P50
(=
109%
)
Q2
2.03
(0.
94–3
.23)
FEV
1/FV
C <
70%
Q3
4.89
(3.
36–6
.59)
Q4
8.76
(6.
75–1
1.7)
* cu
rren
t mea
n ac
cord
ing
to jo
b
Her
tzbe
rg e
t al
. 200
2 (A
utom
otiv
e fo
undr
y w
orke
rs, U
SA)
Exp
to o
ther
pol
luta
nts:
n.i.
(continued)
CRITICAL REVIEWS IN TOXICOLOGY 5
Table1.
Continued
Ehr
lich
et a
l. 20
11 (
gold
min
ers,
Sou
th A
fric
a)Pe
riod
: 200
0–2
001
Air
sam
plin
g &
ana
lysi
s st
rate
gySp
irom
etry
FEV
1, F
VC
1 m
ine
Peri
od: 2
000–
2001
Per
iod
2000
-200
1,
Bla
ck S
outh
Afr
ican
Per
sonn
al s
ampl
ing
(bre
athi
ng z
one)
(n=
506,
112
wor
pu-kcehc ylraey eht ni detargetni TF
L)srek
520
Exp
osed
(cyc
lone
, cel
lulo
se a
ceta
te f
ilte
r, F
R 1
.9 L
/min
)W
hen
n.i.
,noit celloc tfihsll ufd lo sry )9.95– 1.73 ;4.4( 7 .6 4
retneC htlae
H lanoitapuccO s'eni
Mereh
Wdoirep d- 5
smok
ing:
n.i.
Sili
ca a
naly
sis:
XR
D (
LO
D: n
.i.)
Equ
ipm
ent
pneu
mot
acho
grap
h E
xclu
sion
: n.i.
"tec
hniq
ue c
onfo
rmin
g in
pri
ncip
le w
ith
NIO
SH75
00"
QC
, SP
"AT
S cr
iter
ia (
1995
) us
ed fo
r Q
C"
gniniarT
)1.93–0 ;3. 5(
% 4 1 :D
R ni SC
R fo t netn oc"t
rain
ed s
taff
"
Cum
ulat
ive
expo
sure
Cal
ibra
tion
prio
r to
eac
h ne
w s
essi
on
yn.
i.tidila
V ,erianno itseuq ,stne
m erusaem lannosrep :
ME J inte
rvie
w, c
ompa
ny p
erso
nnel
& e
mpl
oym
ent b
urea
u da
ta,
BT
PS
n.i. sey
thgi eH
)metsys t ne
mnrevo g( at ad ecn all ievrus tsud
Exp
dur
atio
n:av
war:s a des ser pxe stluse
Rsry )5.43
–3. 6 ; 3. 5( 8. 12
lues
. AM
(SD
; ran
ge),
P50
Exp
leve
l::sa denifed ssol ssecx
Ery-³
m/gm
³m/g
m
M
A .eulav devresbo su nim detcider
P 2.8
573 .0t sud
R(S
D; r
ange
), P
50
vresbo :ng is e vitisoP
)8.2 2–0 ;09 .2(
) 607.0–
0 ;890.0(ed
< p
redi
cted
for
age
, hei
ght
ci derp > de vresb o : ngis e vita ge
N59. 7 :0 5
P763 .0 :0 5
Pte
d fo
r ag
e, h
eigh
t
RC
S0.
053
1.15
(0.0
16; 0
–0.0
96)
(0.4
4; 0
–3.3
08)
P50
: 0.0
51P
50: 1
.13
Exp
to o
ther
pol
luta
nts
: n.i.
Lon
gitu
dina
l stu
dies
Mal
mbe
rg e
t al
. 199
3 (G
rani
te w
orke
rs, S
wed
en)
Peri
od: 1
976–
1988
Air
sam
plin
g &
ana
lysi
s st
rate
gySp
irom
etry
FEV
1, V
C, F
EV
1/V
C, F
EF5
0 (+
oth
er m
easu
rem
ents
)
FU: 1
2 yr
s
Peri
od: n
.i.P
erio
d19
76 a
nd 1
988
45C
ontr
ols
"yea
rly
grav
imet
ric
dust
mea
sure
men
ts w
ith
LFT
num
ber
2
Mal
es f
rom
a h
ealt
h su
rvey
pers
onal
or
stat
iona
ry fi
lter
cas
sett
esW
hen
"Sam
e pe
riod
in 1
976
& 1
988"
45E
xpos
edpl
aced
at d
iffe
rent
wor
k st
atio
ns."
Whe
reU
nive
rsit
y ho
spit
al, c
lini
cal p
hysi
olog
y dp
t
. i.n : si syla na aciliSsrehs ur c etinar
GE
quip
men
tsp
irom
eter
dif
fere
nt in
197
6 &
198
8
%91 :
DR ni S
CR f o tnetnoc
)s re krow evit ca llit s 32(
.i. nP S ,
CQ
% 52 –
52 (
32–7
3) y
rs o
ldE
xp d
urat
ion:
gran
ite
crus
hers
: 21.
7 (4
–40
) yr
sT
rain
ing
n.i.
(sam
e tec
hnic
ian
in 1
976
& 1
988)
Mat
chin
g: a
ge, h
eigh
t, .i.n
noi tarbilaC
s ry )54–
81( 3.6 2 :e vi tca
smok
ing
habi
ts in
197
6E
xp le
vel:
mg/
m3
mg/
m3*
Val
idit
yn.
i.E
xclu
sion
: sub
ject
s w
ith
pleu
ral p
laqu
es
R d
ust
< 1
976
0.87
0.92
BT
PS
n.i.
1976
–198
80.
830.
68H
eigh
tn.
i.
RC
S<
197
60.
210.
21R
esul
ts e
xpre
ssed
as:
raw
val
ues.
AM
(S
D)
1976
–198
80.
180.
16%
pre
d
*sti
ll a
ctiv
e
Cum
ulat
ed a
mou
nt: R
dus
t: 3
2 m
g; R
CS:
7.2
mg
Exp
to o
ther
pol
luta
nts
: n.i.
(continued)
6 P. HOET ET AL.
Table1.
Continued
Gra
ham
et
al. 1
994
(Gra
nite
wor
kers
, USA
, Ver
mon
t)Pe
riod
: 197
9–19
87A
ir s
ampl
ing
& a
naly
sis
stra
tegy
Spir
omet
ryFE
V1,
FV
C, F
EV
1/FV
C
48 91–3 891 :doire
Pseirrau q 6
& s dehs eno ts 07P
erio
d19
79–1
987,
132
Con
trol
sL
FT
res
ults
ext
ract
ed f
rom
med
ical
rec
ords
noz gnihtaerb( gnilpmas l annosre
P srekro
w eciffo 9 5
reb
mun TF
L )314
=n( )e≥3
(41%
NS,
32%
ES,
27%
CS)
Whe
ren.
i.ilac ,retl if
CV
P ,enolcyc (srekr o
w yrrauq roodtu o 37
brat
ion,
FR
2 L
/min
)W
hen
n.i.
noitc el loc tfihslluf)S
C %65 ,S
E %52 ,S
N %91(
Equ
ipm
ent
1979
–198
3: s
ame
wat
er-s
eale
d sp
irom
eter
.i.n :s is yla na aci liS)e vi tca ( de sop x
E97 5
1985
–198
7: r
epla
cem
ent b
y a
"sim
ilar
mac
hine
"
iverp n o d esab( .cte ,re tsalbd nas ,ret tuc ,rehs il op
t su jda s eulav 1V
EF ,C
VF)67 91 ,079 1 ni set a
mi tse su oed
to th
e di
ffer
ence
(19.
5% N
S, 3
5.5%
ES,
45%
CS)
Exp
dur
atio
n:19
.3 (
11.4
) yr
sQ
C, S
Pn.
i.
43 (
12)
yrs
old
in 1
983
Exp
leve
l:m
g/m
³T
rain
ing
n.i.
Mat
chin
g: n
.i.R
dus
t0.
601
(0.3
68)
Cal
ibra
tion
dail
y ca
libr
atio
n
Exc
lusi
on: n
.i.R
CS
0.06
Val
idit
yac
cept
abil
ity
acco
rdin
g to
Fer
ris
1978
Exp
to o
ther
pol
luta
nts:
n.i.
BT
PS
yes
Hei
ght
n.i.
Res
ults
exp
ress
ed a
s:
raw
val
ues.
AM
(S
D)
Her
tzbe
rg e
t al
. 200
2 (G
ray
iron
aut
omot
ive
foun
dry
wor
kers
, USA
)Pe
riod
: 197
8–1
992
See
abov
eSe
e ab
ove
1 fo
undr
yL
FT n
umbe
r ≥5
for
whi
ch ≥
2 ef
fort
s
242
Exp
osed
rate
d as
acc
epta
ble
and
repr
oduc
ible
(age
, hei
ght,
smok
ing
habi
ts: n
.i.)
Exl
usio
n: a
sbes
tosi
s (C
hest
-XR
)
Möh
ner
et a
l. 20
13 (
Ura
nium
wor
kers
, Ger
man
y, W
istm
ut C
ohor
t)Pe
riod
: 197
1–19
90A
ir s
ampl
ing
& a
naly
sis
stra
tegy
Spir
omet
ryFE
V1,
FV
C, F
EV
1/FV
C
Seve
ral m
ines
9–19
87791
doireP
tn em ssess a pxe ev itcepsor ter ev isne tx
Enno srep
& sllo ryaP
sry )0 .71 –6. 0 ;5. 4( 8 .7 :e
mi t UF
t lus er TF
L& ytilicaf gn ini
m no atad :)V
UG
D( e lif las
extr
acte
d fr
om m
edic
al r
ecor
ds
hs ,e pyt bo j ,tfah s en im
)sre nim re
mrof ( desop xE
12 41)51–
2 ;6.2( 5 reb
mun TF
Lecnesb a ,reb
mu n stfi
9 1 li tn u s0591 :stn emeru sae
M8–
36)
yrs
old
1( 4 .02sry 31 .2 :
TFL nee
wteB
& srete
minok :s08
rel pmas ts u d
R drad natsd lo sry .1 3 : yrte
mo rips ts als
Whe
nn.
i.
(NS
13%
; con
tinu
ous
S 45
.5%
; USS
41.
5%)
Whe
reC
ompa
ny H
ealt
h se
rvic
esSi
lica
ana
lysi
s: I
RS
(LO
D: n
.i.)
– %0 1(
% 3. 31. i.n : sel it ni uq pxe nee
wte b g ni hctaM
tnempi uq
E ts ud
R ni ztrauq )%22
Stol
lber
g sp
irom
eter
(m
ade
by W
ism
ut)
Exc
lusi
on: a
ge <
18 y
rs-o
ldC
umul
ativ
e ex
posu
rege
nera
lly
used
base
d on
job
hist
ory
and
JEM
QC
, SP
n.i.
Nes
ted
case
–con
trol
stu
dyE
xp d
urat
ion:
.i.ngniniar
Tsry )9.9 1–
7 8.0 ; 8.4( 8. 21
233
CO
PD
cas
esE
xp le
vel:
mg/
m³
Cal
ibra
tion
n.i.
1115
Con
trol
s.i.n
ytidi laV
)7 0.2 –0 ;33 .0( 55 .0
t sud R
Exc
lusi
on: F
EV
1/F
VC
<70
% a
t fir
st L
FT
s eyS
PT
B)07 3.0
–0 ;8 40. 0( 470.0
SC
R
Exp
to o
ther
pol
luta
nts:
As
Hei
ght
n.i.
Res
ults
exp
ress
ed a
s:
raw
val
ues.
AM
(S
D; r
ange
)
firs
t obs
erva
tion
of
FU.
CO
PD
def
ined
as:
FE
V1/
FVC
<0.
7
(continued)
CRITICAL REVIEWS IN TOXICOLOGY 7
Table1.
Continued
Ulv
esta
d et
al.
2001
(T
unne
l wor
kker
s, N
orw
ay)
Peri
od: 1
991–
1999
A
ir s
ampl
ing
& a
naly
sis
stra
tegy
Spir
omet
ryFE
V1,
FV
C, F
EF2
5-75
16 c
onst
ruct
ion
site
sId
em U
lves
tad
et a
l. 20
00
idem
Ulv
esta
d et
al.,
200
0
249
Con
trol
sC
umul
ativ
e ex
posu
re
Per
iod
1991
& 1
999
0.a
178
outd
oor
cons
truc
tion
wor
kers
base
d on
sam
e m
ea2
rebmun
TFL
,stnemerus
(NS
29%
, ExS
19%
, CS
52%
)ad
just
ed f
or s
ick
leav
e &
dah doirep kro
w retfa :TF
L tsrifneh
Wecnesba regnol
star
ted
39 (
10)
yrs
old
Exp
dur
atio
n:19
(8)
yrs
seco
nd L
FT: a
fter
� 1
wee
k of
f.
0.b
71w
hite
col
lars
Exp
leve
l:m
g/m
3m
g/m
3 -yr
Equ
ipm
ent
sam
e in
199
1 an
d 19
99
(NS
41%
, ExS
28%
, CS
31%
)R
dus
t0.
a0.
3 (0
.19)
2.1
(0.1
)T
rain
ing
"sam
e 2
trai
ned,
exp
erie
nced
tech
nici
ans
41 (
8) y
rs o
ld0.
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8 P. HOET ET AL.
(Ulvestad et al. 2000, 2001; Bakke et al. 2004), US automotivefoundry workers (Hertzberg et al. 2002), German uraniumworkers (M€ohner et al. 2013), South African gold miners(Ehrlich et al. 2011), and Dutch workers exposed to non-cal-cined diatomaceous earth (Jorna et al. 1994) and to concretedust (Meijer et al. 2001).
To identify key study(ies), we systematically extracted datapertaining to (a) the population studied, (b) level of exposureto RCS and other pollutants, and (c) spirometry procedureand interpretation of results. The main data are summarizedin Table 1.
Exposure characterization
Assessment of exposure to RCS
As seen in Table 1, the reported levels of exposure to RCScover a wide range of exposure: from 0.0003 to 0.84mg/m3
with cumulative exposure from 0.06 to 38mg/m3-year. Inmost publications, exposure levels lack precision; arithmeticmeans are often the only figures provided. Exposure is speci-fied to be to a-quartz in the investigations on tunnel workers(Ulvestad et al. 2000, 2001; Bakke et al. 2004), whereas inautomotive foundry workers, exposure is to “silica” withoutfurther precision (Hertzberg et al. 2002). In potatoes sortingworkers, exposure is to non-calcined diatomaceous earth,which contains, in its native form, up to 1% crystalline silicaas cristobalite (Jorna et al. 1994).
Sampling and analysis strategiesReliable quantitative determination of RCS implies three crit-ical steps; sample collection, measurement of respirable dustfraction and determination of the CS content in the dustsamples. Since methodological issues and uncertainties in thequantification of exposure to RCS can bias the risk estimates,these key procedures should comply with international stand-ards (Dahmann et al. 2008). These were not necessarily avail-able at the time measurements were performed in somestudies. Attention was paid in this review to air sampling(equipment, calibration, monitoring) and analysis strategies(gravimetric and RCS analysis).
In most instances, this information is poorly described, andassessing the level of confidence of the reported data israther challenging. No publication reported to have followeda validated method available at the time, except studies onNorwegian tunnel workers in which silica analysis was per-formed by X-ray diffraction (XRD) according to NIOSH 7500(1998) (Ulvestad et al. 2000, 2001; Bakke et al. 2004). For thegoldminers' cohort (Ehrlich et al. 2011), silica analyses weremeasured by XRD, using a technique “which conforms inprinciple with National Institute for Occupational Safety andHealth (NIOSH) 7500, a method approved by the SouthAfrican Department of Minerals and Energy”.
Current methods for sampling airborne silica use a cyclonewith a cassette to collect the respirable fraction of the aero-sol, crystalline silica being measured by XRD or infrared spec-trophotometry (IR). Early dust measurements relied onparticle counting, by light microscopy, of respirable-sized
particles collected either by thermal precipitators, impingersor konimeters with no specific measurements of silica. Theselevels, expressed as numbers of particles per unit volume,were subsequently converted to estimates of gravimetric con-centrations. Uncertainties are likely associated with the con-versions of these values into quartz exposure levels(Dahmann et al. 2008). In automotive foundry workers(Hertzberg et al. 2002), it is simply stated that “The early datareported as dust counts were converted to an estimate of themass concentration of silica exposure, and used to calculatetime-weighted average exposures for the various jobs at thefoundry. These data were merged with the results of 8-hmass-respirable sampling”. Considering another paper by thesame team (Rosenman et al. 1996), it is specified that “earlysilica exposure data obtained using midget impingers pro-vided estimates of dustiness at a specific task or in a certainarea. Weighted total dust exposure from impinger data wasconverted to an estimate of silica exposure by multiplying itby the average % of quartz in bulk samples; an estimate ofexposure in mass units (mg/m3) was obtained by multiplyingby 0.09” without further details. Exposure characterization isconsidered a major weakness in this study (high uncertaintyabout RCS measurements, no explanation about cumulativeexposure assessment) and too questionable for drawingmeaningful conclusions useful for the objective of the pre-sent review. The survey on uranium workers is also based onkonimetric data, but in contrast to the previous study, theycarried out extensive side-by-side measurements for the ori-ginal mine equipment from the 1950s until the 1980s withthe originally used konimeters and modern standard respir-able dust samplers. The results were used to develop a pro-cedure for recalculating konimetric data obtained underhistorical conditions into respirable dust mass. To simulatethe original conditions, it was attempted to find sites withinthe still open mines (early 1990s) with conditions as similaras possible to the years between 1946 and 1953. This allowedthe construction of a very comprehensive job exposurematrix (JEM) with reliable quantitative exposure estimates(M€ohner et al. 2013).
In the series of investigations on Norwegian tunnel work-ers, it is stated that technology did not change substantiallysince 1980. Thus, results of personal sampling measurementscarried out, in 15/16 construction sites in 1996–1999 and rep-resenting 33% of all construction projects carried out by thecompany during this period, were used to characterize expos-ure in the 1991-cross-sectional (Ulvestad et al. 2000) as wellas in the two subsequent longitudinal studies covering theperiod between 1991 and 1999 (Ulvestad et al. 2001) andbetween 1989 and 2002 (Bakke et al. 2004). In these laststudies (Ulvestad et al. 2001; Bakke et al. 2004), cumulativeRCS exposure was calculated for each worker based on thesame measurements (1996–1999) (Ulvestad et al. 2001). Forall these studies, personal air sampling duration was 5–8 hbecause of limited battery capacity of the sampling equip-ment and high dust load on the filter, but was consideredrepresentative for the whole 10-h workshift. All subjectsworked for 11 consecutive days and were off site for 10 d.
To assess exposures of the South-African goldminers incurrent jobs under research conditions, a random sample of
CRITICAL REVIEWS IN TOXICOLOGY 9
100 workers were requested to participate in personal fullshift monitoring over a 5-d period, providing 506 measure-ments. As these measurements covered only 26 of the 85jobs represented in the sample of 520 miners chosen formedical examination, data were supplemented by routinedust measurements from the company’s mandatory dust sur-veillance program, adding a total of 715 records. These data,as well as company data, the expertise of an occupationalhygienist familiar with the mine, a questionnaire and if neces-sary an interview with the miners were used to elaborate aJEM and estimate the cumulative exposure (Churchyard et al.2004; Ehrlich et al. 2011).
Sensitivity of the methodsConfidence in some very low reported RCS levels, some ofwhich concerning measurements in the 70's, is questionablein view of the low sensitivity of the methods used. Notably,the limit of detection (LOD) is a real issue, ranging from0.020 to 0.065mg/m3 according to the analytical methods(GESTIS 2016). In 1974, NIOSH recommended an exposurelimit value of 0.05mg/m3 for free CS. This value was estab-lished taking into account the technical capacity of theequipment for the collection of air samples, and the LOD ofthe analytical methods for quantitative determinations of sil-ica at this time. In the 2002 update, analytical methods werenot considered to allow for measurements below 0.05mg/m3
and NIOSH did not recommend lowering their value (NIOSH2002). In line with this, Stacey (2007) highlighted the difficul-ties in making reliable measurements of RCS at low levels.Theoretical LODs of the analytical techniques (5–10 lg persample, equivalent to 0.005–0.01mg/m3 for an 8-h samplecollected at 2.2 l/min) are difficult to achieve in real samplesbecause of issues such as sampling times <8 h, measurementprecision, interferences in the sample, and reliable calibrationstandards. Measurements of 0.025mg/m3 and short-termmeasurement of samples (about 4 h) at 0.05mg/m3 arebeyond the limit of what can be reliably measured using theexisting methods and techniques. In 2016, testing four differ-ent personal cyclones in laboratory, OSHA concluded thatthe lowest detectable RCS concentrations resulting in thecollection of at least 10 lg (LOQ for quartz for OSHA MethodID-42 ranged) range between 10 (GK2.69 cyclone, flow rate4.2 l/min) and 25 lg/m3 (DO cyclone, 1.7 l/min) for a 4-h col-lection and between 5 and 12 lg/m3 for a 8-h collection.Importantly, these results were obtained by sticking to vali-dated methods in 2016 (OSHA 2016). RCS levels reported inthe retrieved studies rely on measurements made before2002 and none of these discusses nor even mentions theLOD of their analyses. One exception is Ulvestad et al. (2015)who report in their very recent investigation, a LOD of 10 lg(13lg/m3 based on an 8-h sampling period at a flow rate of1.6 l/min), using the NIOSH Method 7500 (NIOSH 2003).
The question also arises about the most relevant exposuremetrics. Traditional cumulative exposure metric may not bethe optimum predictor of obstructive dysfunction. Whether a40-year exposure to 0.1mg/m3 would be equivalent to 2years exposure to 2.0mg/m3 (i.e. both leading to an exposureof 4mg/m3-years) remains to be answered. The pattern of
exposure and the rate of dose-delivery may be of importance;it could be hypothesized that high intermittent doses mightbe needed to cause an inflammatory response triggeringlong-term effects.
Characterization of exposure to other pollutants
The mean percentage of silica in respirable dust was 9%(range: 4–11%) in concrete dust workers (Meijer et al. 2001),about 12% in potatoes sorting workers (Jorna et al. 1994), 13(7–33%) in uranium miners (M€ohner et al. 2013), 14%(0–16.5%) in gold miners (Ehrlich et al. 2011), and rangedfrom 10 to 25% in granite workers (Malmberg et al. 1993;Rego et al. 2008). So, CS is only a fraction of the respirabledust, the rest of which remained uncharacterized in all avail-able studies and, in most studies no attempt was made tolook at exposure to other pollutants. A comprehensive JEMfor all underground jobs of the German uranium miningindustry was developed for respirable dust and arsenic (Asaverage concentrations calculated to be about 18 lg/m3
between 1971 and 1976,<5 lg/m3 from 1976). But, it did notinclude other pollutants to which underground mining opera-tions may expose (Dahmann et al. 2008; M€ohner et al. 2013).Neither did the comprehensive JEM elaborated for the under-ground goldminers (Churchyard et al. 2004; Ehrlich et al.2011). In contrast, co-exposure is fully described in the longi-tudinal studies on tunnel workers, in which exposure meas-urements were carried out to estimate personal current and/or cumulative exposure to total dust, respirable dust, oil mistand vapor, nitrogen dioxide (NO2), volatile organic chemical(VOC), formaldehyde, ammonia (NH3), elemental carbon (EC),and carbon monoxide (CO) (Ulvestad et al. 2001; Bakke et al.2004).
Outcome characterization
Many sources of variability may impact the quality of thelung function testing, and reliability depends on accurateinstrumentation and proper operating maneuvers as well ason adequate interpretation of the results. In occupational sur-veys, distinguishing the signal of interest (i.e. decrease in LFassociated with occupational exposure) from the backgroundnoise is a major issue. It implies (a) appreciating whether themeasured change reflects a true loss in pulmonary functionor is only a result of test variability and (b) if associated withoccupational exposure, distinguishing the effect of a particu-lar agent where multiple exposures exist. Therefore, identifiedstudies were reviewed bearing in mind some critical issuesrelated to lung function testing (equipment and procedure),study design (cross-sectional versus longitudinal), and inter-pretative strategies.
LFT equipment and procedure
Since the first standardization work issued in Europe in 1958under the auspices of the European Community for Coal andSteel (ECCS) (Jouasset 1960), a number of recommendationsdesigned to minimize the many technical and biological
10 P. HOET ET AL.
sources of variability in LFT and to achieve maximal accuracyand precision, improving the chance to correctly identifying asignal of interest, have been issued by several institutions/agencies during the last decades. The most used are those ofthe American Thoracic Society (ATS), the EuropeanRespiratory Society (ERS), and the American College ofOccupational and Environmental Medicine (ACOEM) whopublished a series of recommendations that evolved overtime (e.g. ATS 1979; NIOSH 1981, 1982; Quanjer 1983; ATS1987a; Quanjer 1993; ATS 1995; ACOEM 2000; NIOSH 2003;Miller et al. 2005a, 2005b; ACOEM 2011; OSHA 2013; ATS2014; Redlich et al. 2014). Summarizing these recommenda-tions is beyond the scope of this review, but, some essentialcomponents of a valid spirometry and the main features thatmight be relevant when critically reviewing studies are givenin online Supplemental data.
Reaching high-quality spirometry can be achieved, includ-ing within a working environment, provided compliance withstandardization recommendations and comprehensive qualitycontrol are carried out (Enright et al. 2004; Enright 2010).Assuming that this is the case in most situations is quiteunrealistic. Studies aiming at evaluating LFT quality havebeen published with highly variable results and it was statedthat in most common settings where spirometry is performed(including in occupational screening settings, and as part ofresearch studies), it is commonly encountered that only halfof the spirometry tests successfully meet widely-acceptedstandards (Enright & Schermer 2013).
Most studies retrieved in the present review rely on theinterpretation of LFT data acquired during routine occupa-tional surveillance programs (Malmberg et al. 1993; Grahamet al. 1994; Ulvestad et al. 2000; Hertzberg et al. 2002; Bakkeet al. 2004; Rego et al. 2008; Ehrlich et al. 2011; M€ohner et al.2013).
Given the scarce relevant information generally supplied,rating LFT quality to assess the reliability of the results is achallenge:
� None of the reviewed studies specifies whether theequipment was correctly calibrated and operating proce-dures standardized. It is, therefore, not possible to guar-antee that compliance with minimum standards forequipment performance (accuracy, precision, range ofmeasurements), validation, routine quality controls withcalibration and calibration checks, operating/procedurecharacteristics and technician training was secured. Instudies examining LFT results of workers from differentoccupational sites, it is likely that these LFT were per-formed in different facilities, but standardization of theprocedure is not guaranteed. None of the longitudinalstudies excludes the possibility that the LFT conditionsmight have changed over time; several studies evenreport a change of spirometer over time (Malmberg et al.1993; Graham et al. 1994; Hertzberg et al. 2002; M€ohneret al. 2013). The impact of change of device has beenobserved by several teams (e.g. Chinn et al. 2006; Liistroet al. 2006; Bridevaux et al. 2015). Using medical screen-ing data collected in 1884 chemical plant workersbetween 1973 and 2003, Wang et al. (2009) examined
the influence of multiple factors on repeated measure-ments of FEV1. Controlling for age, height, race, gender,cigarette smoking and changes in body weight, FEV1results obtained from different volume spirometers dif-fered on average by as much as 95ml, i.e. three to fourtimes the normal mean annual longitudinal decline. In alongitudinal study on refractory ceramic fibers (RCF)workers in five manufacturing locations, McKay et al.(2011) measured an average FEV1 difference rangingfrom �38 to þ44ml between the five spirometershandled by well-trained technicians.
� The only studies specifying that the same position waskept for all LFT measurements are those on the tunnelworkers cohort (Ulvestad et al. 2000, 2001; Bakke et al.2004), the uranium and gold miners cohorts (Ehrlich et al.2011; M€ohner et al. 2013). BTPS (Standardized to baro-metric pressure at sea level, body temperature, saturatedwith water vapor) adjustment is specified for the tunnelcohort (Ulvestad et al. 2000, 2001; Bakke et al. 2004), theVermont granite workers (Graham et al. 1994), and theuranium cohort (M€ohner et al. 2013).
� With respect to LFT scheduling, the time of the day isspecified in the study on concrete materials workers(Meijer et al. 2001). Besides the fact that pulmonary func-tion shows circadian variations, measuring lung functionbefore or after the shift, in day-shift or night-shift work-ers, is likely to have an impact on the results. One canassume that pulmonary function before the shift willreflect a possible chronic effect of exposure, whereas atthe end of the shift it will be more influenced by theexposure of that day (an acute component).
� Although LFT results are known to be sensitive to thetechnician effect and the importance of the techniciantraining is emphasized in all guidelines, none of the stud-ies included in this review provides assurance of qualityregarding the training of the technicians performing theLFT. One study reports about following NIOSH certifiedcourse but without ongoing continuing education(Hertzberg et al. 2002). In the tunnel workers cohort, LFTwere performed by “technicians with special training”(Ulvestad et al. 2001; Bakke et al. 2004), and in the goldminers by a “trained staff” (Ehrlich et al. 2011). When test-ing is to be done at multiple sites, it should be preferablycarried out by a single qualified technician able to con-sistently monitor the test performance at the differentsites in order to assure comparability
� Regarding the validity of the test, some investigatorsreported that they followed acceptability and reproduci-bility criteria available at the time (Jorna et al. 1994;Ulvestad et al. 2000; Meijer et al. 2001; Ulvestad et al.2001; Bakke et al. 2004; Rego et al. 2008). Some studiesexcluded curves not fitting quality criteria (Hertzberget al. 2002; M€ohner et al. 2013) One need to be aware,though, that analyses restricted to FEV1 values thatstrictly meet ATS criteria may result in a population biasby excluding data from subjects who have abnormallung function and obscuring underlying dose–responserelationships in the same manner as the healthy workereffect (Eisen et al. 1985; Kellie et al. 1987; Sumner et al.
CRITICAL REVIEWS IN TOXICOLOGY 11
2015). Eisen et al. (1983) showed that workers from theVermont granite cohort with persistent LFT-failure (i.e.measurements that did not meet the ATS reproducibilitycriteria of <200ml) across a 6-year survey had faster ratesof FEV1 decline (82ml/year) than did subjects with noneor only intermittent failures (46ml/year). These authorssuggested introducing a new dichotomous covariate toindicate whether or not the data were from excessivelyvariable efforts. In this manner, test failure could be con-trolled for and estimates of dose–response associationwould be unbiased (Eisen et al. 1987). In a further ana-lysis, these authors observed subjects who left the work-force or ceased to participate in the Graham et al. (1994)study after the initial survey and concluded that this sur-vey suffered from a selection bias due to subjects lost tofollow-up (Eisen et al. 1995). Therefore, the ATS suggestsreproducibility criteria to be used as a guide to determinewhether more than three acceptable maneuvers areneeded. These criteria are not to be used for excludingresults from reports or for excluding subjects from astudy, but for assigning a test quality statement for eachsubject tested. The only criterion for unacceptable subjectperformance is fewer than two acceptable curves (ATS1987b, 1995; Miller et al. 2005b).
� Finally, it should not be overlooked that certain condi-tions can affect test results. LFT should be avoided withinabout one to four hour of vigorous exercise, smoking,using a bronchodilator, a heavy meal, consuming alcoholor caffeine; within 3 d to 3 weeks after recovering froman illness that lasted three weeks or less, etc. Postponingthe testing is often impractical in reality. In such a situ-ation, an appropriate notation can be made in the work-er's record so that this information can be noted in anyanalysis or retrospective data review. These points shouldbe checked, and any deviations recorded and taken intoaccount in the interpretation (ATS 1991; Miller et al.2005b; OSHA 2013; Redlich et al. 2014). None of the stud-ies reviewed here reports having taken these aspects intoaccount. Carrying out LFT requires a quiet environmentand sufficient time and subjects should be as relaxed aspossible before and during the tests. Such conditions arelikely to be rarely fulfilled when LFT are performed inoccupational settings where subject testing time is oftenlimited. In a recent study investigating whether currentlyexposed tunnel workers are at risk of short-term LFimpairment, Ulvestad et al. (2015) observed an impact ofhaving a cold at the examination on the FEV1 decrease.
LFT interpretation
Expression of resultsPercent predicted, LLN: Expressing results as % predicted (%pred) or as value below LLN, whether in internal controls orin exposed workers, compares by definition to the valuesobserved in a reference population. It is crucial that the refer-ence cohort be representative. These reference values shouldbe established (a) in healthy non-smoking subjects havingthe same anthropometric and ethnic characteristics, (b) using
the same kind of LFT instrument and testing procedure.Considerable variations between published reference valuesor prediction formulas are observed and the choice of refer-ence equations may strongly affect the results. Most of theEuropean studies included in this review (Jorna et al. 1994;Ulvestad et al. 2000; Meijer et al. 2001; Ulvestad et al. 2001;Bakke et al. 2004; Rego et al. 2008) used the prediction equa-tions of the ECSC/ERS (Quanjer et al. 1983, 1993) which arethe most frequently used. One should note that these refer-ence equations are somewhat outdated; they were derivedfrom lung function measurements of subjects, includingsmokers, studied in the years 1954–1980, from different studypopulations and from several data sets, and appear to under-estimate FEV1 and FVC. A task force of the ERS-Global LungInitiative (GLI) published new reference values based on74 187 records from healthy non-smoking males and femalesfrom 26 countries across five continents in 2012 (Quanjeret al. 2012). Malmberg et al. (1993) and M€ohner et al. (2013)used national data banks (Fridriksson et al. 1981; Hedenstromet al. 1986; Br€andli et al. 1996, 2000). In the USA, NationalHealth and Nutrition Examination Survey (NHANES) III refer-ence equations published in 1999 (Hankinson et al. 1999)and, if not available on older spirometers, the Crapo et al.(1981) and the Knudson (Knudson 1983) equations are rec-ommended (ATS 1991; ACOEM 2000; Pellegrino et al. 2005;ACOEM 2011; OSHA 2013) as used by Hertzberg et al. (2002).For the cohort on black South-African male miners conductedin 2000–2001, Ehrlich et al. (2011) used prediction equationsbased on a 1988 study of black South African men engagedin non-dusty occupations in Johannesburg (Louw et al.,1996).
Spirometric indices used to define obstruction. In all guide-lines (ATS 1987b, 1991; Siafakas et al. 1995; Celli et al. 2004;Bakke et al. 2011; OSHA 2013) the very first step of spirom-etry interpretation is the determination of FEV1/FVC ratio,with obstructive lung impairment being defined as adecrease in FEV1 out of proportion of any decrease in (F)VC,the severity being based on the decline of FEV1. So, FEV1/FVC ratio is critical for determining if a subject has airflowobstruction.
Graham et al. (1994), Malmberg et al. (1993), Meijer et al.(2001), M€ohner et al. (2013), Ulvestad et al. (2000) and, intheir cross-sectional study, Hertzberg et al. (2002) used theFEV1/FVC ratio to report obstructive defect. In the studyamong potatoes workers, FEV1/FVC was reported but a FEV1decrease was taken as a criterion of airflow limitation, with-out consideration of the FEV1/FVC ratio (Jorna et al. 1994).Neither did Ehrlich et al. (2011), Ulvestad et al. (2001), orBakke et al. (2004) report on the FEV1/FVC ratio and in theirlongitudinal study, Hertzberg et al. (2002) calculated FEV1and FVC decline per mg “silica”/m3 but not FEV1/FVC ratio.
The acceleration of the age-related decline in lung func-tion, as assessed by FEV1, has become the hallmark of theprogression to COPD since the well-known study entitled“The natural history of COPD” published some 40 years ago.Fletcher and Peto (1977) determined FEV1 every 6 monthsduring an 8-year follow-up in a cohort of 792 workers andconcluded that COPD results from an accelerated decline in
12 P. HOET ET AL.
FEV1 over time. Although a reduced FEV1 often indicates“obstructed” or narrowed airways, it does not prove the pres-ence of an obstructive defect. A reduction in FEV1 with a nor-mal or high FEV1/FVC ratio is seen in restrictive defects.Moreover, as emphasized in the ATS/ERS recommendations,special attention must be paid when FEV1 is decreased andFEV1/FVC ratio is normal or almost normal. This pattern mostfrequently reflects failure of the patient to inhale or exhalecompletely. It may also occur when the flow is so slow thatthe subject cannot exhale long enough to empty the lungsto residual volume (Pellegrino et al. 2005).
As seen in Table 1, some studies used forced expiratoryflow at 25–75% of FVC (FEF25–75%, also called maximummid-expiratory flow (MMEF)) and the forced expiratory flowat 75% of FVC (FEF75%). These indicators have beendescribed as being more sensitive to the presence of “smallairways obstruction” or distal airway obstruction. However,this has been challenged and recent investigations haveshown that these parameters do not provide additional infor-mation beyond that provided by FEV1, FVC, and FEV1/FVC indetecting LF impairment (Quanjer et al. 2014). Current prac-tice guidelines discourage their use for diagnosing small air-way disease and recommend continuing to use FEV1, FVC,and FEV1/FVC as indicators of obstructive disease.
Abnormal values definition. Several approaches were usedto define “abnormal values”, an obstructive impairment, orfor diagnosing COPD and interpretation of LFT results differsamong the studies included in the present review. Threepapers (Ulvestad et al. 2000; M€ohner et al. 2013; Rego et al.2008) used a fixed cutoff of FEV1/FVC ratio (<0.7) to diag-nose “COPD cases”. For Hertzberg et al. (2002), FEV1/FVCratios <70% and <65% were considered abnormal for partici-pants <60 and �60 years of age at testing, respectively; forFVC and FEV1, the 5th percentile (P5) of predicted was usedas cutoff for abnormal results. A FEV1 value <80% predictedwas used to define obstruction among potatoes workers(Jorna et al. 1994) and for Spanish granite workers a FEV1value <50% predicted was considered as abnormal (Regoet al. 2008). For the gold miners, an “excess loss” was definedas the difference between the predicted and observed valuesof FEV1 and FVC, a positive sign for this variable denoting anobserved value less than predicted, a negative sign anobserved value exceeding the predicted (Ehrlich et al. 2011).To compare actual to reference LF levels, Meijer et al. (2001)used both % predicted and standardized residuals(SR¼ (observed-predicted)/residual standard deviation [RSD]);COPD was defined as a FEV1/FVC ratio at P5 or lower(��1.64�RSD). This heterogeneity calls for some comments.
The practice of using fixed cutoff such as the absoluteFEV1/FVC ratio <0.70 (based on a normal ratio between 0.70and 0.80 in healthy adults) as recommended in the GOLDguidelines is largely disputed. A subject's LFT result is an indi-vidual figure that depends, among other factors, on his/herrace, ethnicity, and varies inversely with advancing age andincreasing height. Using % predicted to define what is“normal” may be valid as long as the between-subject stand-ard deviation (SD) remains stable across all ages and for alllung function parameters. As pointed out by Miller and
Pincock (1988) more than 25 years ago, the between-subjectsSD vary over the age range, the gender and the height andis not the same for all indices. Using fixed cutoff strategies todetermine an obstructive defect tends to substantially under-diagnose airway obstruction in younger workers(<45–50 years old), and to overestimate airway obstruction inolder workers (false-positive results) (Hnizdo et al. 2006;Roberts et al. 2006; Quanjer et al. 2013). An overwhelmingnumber of population-based studies illustrates the risk of mis-classification when using fixed ratio or % predicted value(Viegi et al. 2000; Hnizdo et al. 2006; Hansen et al. 2007;Medbo & Melbye 2007; Shirtcliffe et al. 2007; Roche et al.2008; Swanney et al. 2008; Vollmer et al. 2009; Miller et al.2011; Tilert et al. 2013).
The threshold below which a value is considered“abnormal” is often set so that 95% of a reference populationwill have values above the LLN. Assuming a normal distribu-tion, –1.64�RSD marks the lower P5. An 80% cutoff is not thedeviation from the mean by 1.64 SD.
Thus, an obstructive defect being defined by a reducedabsolute FEV1/FVC ratio below LLN, set at P5 of adequate ref-erence values, has been recommended (Quanjer et al. 1983;ATS 1991; Quanjer et al. 1993; ATS 1995; ACOEM 2000; Celliet al. 2004; Pellegrino et al. 2005; ACOEM 2011; Redlich et al.2014; Rennard & Drummond 2015). LLN better incorporatesthe expected changes in flow that occur with normal agingin healthy individuals that a fixed ratio or %. As pulmonaryfunction declines with age, the P5-LLN also declines, labelingonly 5% of normal individuals in each age group as“abnormal”. The LLN denoted by the standardized residual(SR) (or z-score) indicating how many standard deviations thesubject's result is from predicted value would be an even bet-ter approach. Main advantages of this approach is that asame cutoff for this dimensionless index applies across allages, sex, ethnic groups, and LFT indices and it allows for thecalculation of the probability of a value to be within a normaldistribution (Harber & Tockman 1982; Miller & Pincock 1988;Swanney et al. 2008; Stanojevic et al. 2010). FollowingQuanjer et al. (2012), the LLN used should be appropriate forthe purpose. Hence, if there is prior evidence of lung disease,a borderline value of FEV1/FVC, FEV1 or FVC is more likely tobe associated with disease and a LLN at the P5 (LLN 5%, z-score�1.64) is clinically acceptable. In contrast, in epidemio-logical studies and case finding among asymptomatic sub-jects, where the cost and consequences of false-positive andfalse-negative test results are over-riding, a LLN correspond-ing to the P2.5 (LLN 2.5%, z-score�1.96) is recommended asthe decision limit.
It is important to recognize that COPD is characterized byprogressive airflow limitation that is not fully reversible. Thekey defining spirometric feature of COPD is post-bronchodila-tor decrease in FEV1/FVC (GOLD). The use of post-broncho-dilator results is supported by the fact that subjects withasthma, which may be reversible, may be misdiagnosed ashaving COPD. Asthmatic subjects show more reversibilitythan COPD subjects even when they have post-BD airflowobstruction. If pre- (rather than post-)bronchodilator spirom-etry is used, COPD prevalence may be overestimated by 5%to as much as 35% (e.g. Sterk 2004; Johannessen et al. 2005;
CRITICAL REVIEWS IN TOXICOLOGY 13
P�erez-Padilla et al. 2007; Tilert et al. 2013). Not a single studyin the present review took this aspect into consideration, nordid they consider drug intake that might influence LFTresults. Two studies excluded asthmatics (Ulvestad et al. 2001;Rego et al. 2008). One study reports on 4.6% of the subjectshaving asthmatic attacks, without further precision (Jornaet al. 1994). It must, however, be recognized that post-bron-chodilator LFT are rarely used in surveillance programs per-formed in occupational setting and we did not focus furtheron the irreversible feature of COPD.
Study designThe design of the study may significantly impact LFT results.The present review comprises five investigations with a cross-sectional design (Jorna et al. 1994; Ulvestad et al. 2000;Meijer et al. 2001; Rego et al. 2008; Ehrlich et al. 2011), fivewith a longitudinal design (Malmberg et al. 1993; Grahamet al. 1994; Ulvestad et al. 2001; Bakke et al. 2004; M€ohneret al. 2013), and one with both cross sectional and longitu-dinal design (Hertzberg et al. 2002).
In cross-sectional studies, results are compared to refer-ence values and are particularly sensitive to inter-individualvariability. The inter-individual variability has been attributedto gender for 30%, height 20%, ethnicity 10%, age 8%, bodyweight 2%, and technical factors 3%. Smoking is probably themost important single factor, accounting for perhaps a thirdto a half of the residual variation (Becklake 1986). In longitu-dinal investigations, comparison is with self-tests, eliminatingthe inter-individual variability issue and allowing evaluationof individual change over time. This may be especially usefulin early detection of an excessive, i.e. faster than expected,decline in FEV1 over time. Healthy workers who have resultsabove 100% predicted may develop, in response to inhalationhazardous exposures, a significant decline even when FEV1itself remains within the reference values. These workerswould still have a “normal” lung function as measured cross-sectionally (Hankinson & Wagner 1993; Pellegrino et al. 2005;Hnizdo et al. 2007, 2010; Kreiss et al. 2012). Intra-individualvariability may, however, become a concern in longitudinalstudies.
It should also be noted that most reference equationsused to calculate % predicted values, e.g. ECSC or NHANESequations, are derived from cross sectional investigations.Yet, annual decline in LF determined longitudinally is oftencompared with predicted decline determined cross-sectionally.
These inter-, intra-individual variabilities entail major chal-lenges when conducting epidemiological studies, amongwhich: the selection of an adequate reference populationand/or control group, the sample size, in case of a follow-up,its length and the number of tests.
Matching groups. Comparison with adequate values,whether it is to an internal control group or to an externalpopulation is of critical importance. In occupational settings,an internal control group of “unexposed” workers is oftenused, limiting some sources of inter-individual variability.Matching for the main factors influencing LF, i.e. gender,
height, ethnicity, age, or smoking status is of paramountimportance. Considering physical activity and socio-economicstatus would be even better. All studies considered in thisreview comprised men only, eliminating the issue of gendervariability. As summarized in Table 1, matching with respectto height, age, ethnicity, and smoking habits was, however,not systematically reported. Height, which appears to be aneven more important explanatory variable than age in inter-individual variability, is not always considered. Importantlyheight should be measured, not self-reported. According tothe ECSC equation, in adult men, each cm would increase theFEV1 by 43ml, while the age-related decrease would be30ml/year. The GLI-equation more recently confirmed theimportance of the accuracy of the values entered for heightand age matters (Quanjer et al. 2012). Three included studiesconsidered categories of exposure without indication ofmatching for height, age, ethnicity, smoking status, betweenthese subgroups of exposure (Hertzberg et al. 2002; Regoet al. 2008; M€ohner et al. 2013).
Regarding the smoking status, one can notice a muchhigher percentage of current smokers in exposed as com-pared to controls, particularly when the control group con-sisted of office workers (Graham et al. 1994; Jorna et al. 1994;Meijer et al. 2001; Ulvestad et al. 2001; Bakke et al. 2004). Inthe retrospective study of Norwegian tunnel workers (Bakkeet al. 2004) and the automotive foundry workers cohort(Hertzberg et al. 2002), smokers and non-smokers were con-sidered separately. Noteworthy, a general tendency for smok-ers to be more prevalent in the most noxious environmenthas been described in other occupational settings, forinstance in welders or in RCF workers (Beach et al. 1996;McKay et al. 2011). The potential association between RCSexposure level and smoking status was not tested in any ofthe studies reviewed. In addition, in several studies, controlgroups comprised white collar workers (Graham et al. 1994;Jorna et al. 1994; Meijer et al. 2001; Ulvestad et al. 2001;Bakke et al. 2004) or subjects from a health survey(Malmberg et al. 1993), likely introducing a bias. When calcu-lating predicted change associated with exposure to RCS,some of these confounders in LF measurements were con-trolled by means of multiple linear regressions but not sys-tematically (cf. Table 2).
Sample size. Matching for these main factors may not alwaysbe possible when subgroups are small (Harber & Lockey1991). Using inter-individual variability standard deviation(SD) from ECSC (Quanje 1983), Davison et al. (1986) calcu-lated that at least 750 men (375 controls, 375 exposed)would be required to have an 80% chance to detect a meanFEV1 difference of 100ml at the 5% significant level. For adifference of 200ml and 300ml, each group should include100 and 45 subjects, respectively. Subgroups of 45 subjectsor less were used in several investigations included in thepresent review (Malmberg et al. 1993; Jorna et al. 1994;Graham et al. 1994; Ulvestad et al. 2001; Hertzberg et al.2002). In these studies, differences may not be detectedbecause an inadequate number of subjects are studied andthe absence of an exposure–response association may beattributed to the small sample size.
14 P. HOET ET AL.
Table 2. Main data analyses and results relevant to the relationship between RCS exposure and LFT changes.
Main data analysesResults of analyses between RCS exposure and LFT change
Predicted additional LFT decline associated with RCS exposure
Cross-sectional studiesJorna et al. (1994)LFT difference between the 4 groups. ANOVA n.i.
FEV1 (% pred), FEV1/FVC: current and retired workers< controls (p< 0.05)FVC (% pred): nss
Predicted change in LFT (retired excluded). MLRConfounders tested: age, height, weight, pack-yrsExplanatory variables included in final model: age, height, pack-yrs, dust-CEFEV1 ss related to dust-CE (p¼ 0.032); FVC, FEV1/FVC: nss
Airflow limitation incidence (whole group)23/172 (13.4%)
Ulvestad et al. (2000)LFT difference (mean, 95%CI) between tunnel workers and outdoor workers. n.i.
Adj. for: yrs in same job, atopy, smoking status.FEV1, FVC, FEV1/FVC: tunnel workers< controls
Predicted annual change in FEV1. MLRCovariables included: yrs employed in same job, pack-yrs, atopy
Risk of COPD: tunnel vs outdoor workersControlling for: yrs employed, smoking status, atopy
OR (95% CI) for COPDCovariables: occup group, smoking status, yrs employed, atopy
NB: age not included in analyses due to high correlation with yrs employed
Meijer et al. (2001)Mean LFT levels expressed as % of external ref population. Student’s t-test n.i.
FEV1/FVC (% pred): concrete workers< controls (p¼ 0.02)FEV1 (% pred), FVC (% pred): nss
Age, standing height-Standardized Residual-LFT predicted change. MLRExplanatory variables included: smoking status, history of allergy, “exposure to dust”
COPD prevalence in concrete workers and controls. Fischer’s exact testCOPD defined as FEV1/FVC< P5 (�-1.64�RSD)7% vs 3%: nss (p¼ 0.1)
Difference between levels in concrete workers with and without COPD. Student’s t-testCOPD no COPD
RCS 0.05 (0.03) 0.05 (0.03) nssRCS-CE 0.4 (0.3) 0.6 (0.6) nss
Hertzberg et al. (2002)Relationship between abnormal LFT and RCS-CE. Contingency tables.
p trend by quartile of RCS-CESmokers Never smokers
FEV1 p¼ 0.06 nssFVC p¼ 0.042 nssFEV1/FVC p¼ 0.011 nss
OR for incidence of abnormal values. LRCalculated for RCS-CE, adj for pack-yrs, ethnicity
1mg/m3-yr 2mg/m3-yr
FEV1 1.14 1.3FVC 1.09 1.19
LFT predicted change in FEV1, FVC, FEV1/FVC. MLR 1mg RCS/m3-yrCovariables included: age, height, ethnicity, pack-yrs, FEV1 26mL p¼ 0.0001RCS-CE besides foundry, RCS-CE FVC 34mL p¼ 0.0001
FEV1/FVC 0.37% p¼ 0.0001
Rego et al. (2008)Predicted FEV1, FEV1/FVC change. MLR 1mg RCS/m3-yr
Explanatory variables tested: age, silicosis, pack-yrs, silica�pack-yr, RCS-CE FEV1 0.221% pred p¼ 0.001FEV1/FVC 0.185 p¼ 0.005
Risk of having an abnormal FEV1 value. LROR adjusted for age, pack-yrs, silicosis
OR (95%CI) p
Q1 1Q2 0.831 (0.432–1.613) nssQ3 0.868 (0.432–1.743) nssQ4 1.755 (0.873–3.527) nssQ5 2.37 (1.04–5.40) 0.02
(continued)
CRITICAL REVIEWS IN TOXICOLOGY 15
Table 2. Continued
Main data analysesResults of analyses between RCS exposure and LFT change
Predicted additional LFT decline associated with RCS exposure
Ehrlich et al. (2011)Bivariate association with FEV1, FVC. 1mg RCS/m3-yr 0.01mg RCS/m3
Variables tested: length of service, silicosis, tuberculosis, smoking FEV1 156mL (45; 268) 36mL (5; 67)RD-CE, RD, RCS-CE, RCS FVC 150mL (29; 271) 47mL (14; 80)
Predicted FEV1, FVC change. MLR 1mg RCS/m3-yr 0.01mg RCS/m3
Explanatory variables included: length of service, silicosis, tuberculosis FEV1 95.6mL (�13; 204) 24mL (�5; 54)RD-CE, RD, RCS-CE, RCS FVC 118.6mL (�3; 240) 40mL (7; 73)
Longitudinal studies
Malmberg et al. (1993)% difference in LFT between granite workers and control workers. 1988 n.i.
FEV1 (L), VC (L): nssFEV1/VC: �4.5 (p< 0.01)
12-yr LFT average change in granite workers compared to referents"expressed in % of average absolute values for referents measured in both 1976 and 1988"
FEV1 4.6% (p< 0.02)VC nssFEV1/VC 5.4% (p< 0.02)
Correlation between change in LFT and RCS inhaled dose:nss
Graham et al. (1994)Mean (SD) annual FEV1, FVC, FEV1/FVC change. n.i.
By exposure status (absolute values unadjusted for initial value, height, age)S, ExS, NS considered separately
ANCOVA. Variables tested:Age, height, smoking status, initial valueGranite duration of exposure, job (shed vs office workers)
Hertzberg et al. (2002)Linear mixed-effects model for longitudinal data Annual LFT change per mg/m3 of mean silica exposure.
Adj for pack-yrs, ethnicity FEV1 1.1mL p¼ 0.001FVC 1.6mL p¼ 0.011
M€ohner et al. (2013)Predicted change in FEV1, FEV1/FVC: linear mixed-effects regression models 1mg RCS/m3 -yr
Explanatory variables tested: BMI, age, height, weight, smoking status, RCS-CE FEV1 2.07% (0.95; 3.2)FEV1/FVC 2.75% (1.95; 3.55)
Influence of RCS median exposure on FEV1/FVC change:RCS-AE estimates per mg/m3 -yr<0.072mg/m3 �3.2% (95%CI: �5.1 to �1.3), p¼ 0.001�0.072mg/m3 �2.7% (95%CI �4 to �1.4), p< 0.001
COPD stage I incidence associated with RCS-CEmg/m3 -yr mean OR (95%CI) adj for smoking<0.1412 0.0648 1.000.1412–0.2950 0.2156 1.83 (1.05–3.19)0.2950–0.5560 0.4191 2.65 (1.54–4.58)0.5560–0.9386 0.7351 2.47 (1.39–4.38)0.9386–1.2847 1.0765 1.78 (0.86–3.69)>1.2847 1.6184 3.83 (1.93–7.57)per mg/m3 -yr 0.5787 1.81 (1.27–2.56)
Ulvestad et al. (2001)LFT change after 8 yrs.
FEV1 (L) Drillers vs ctrls (outdoorþwhite collar workers) p< 0.001Shortcreters vs ctrls p< 0.001
FVC (L) Drillers vs ctrls: nssShortcreters vs ctrls: nss
Predicted annual change in FEV1. MLR. 1mg RCS/m3-yrCovariables tested: age, smoking, atopy, job group FEV1 34 (SE 15) mL p¼ 0.02Variables included in final model: age, current smoking, RD-CE, RCS-CE
Correlation between independent exposure variables.Spearman correlation coefficient (r)RCS-CE vs R dust-CE 0.47RCS-CE vs NO2 0.95
Bakke et al. (2004)LFT decrease. Difference between first and last observation. Paired t test
In all groups # FEV1 (p< 0.01)# FVC (p< 0.01) 1mg RCS/m3-yr
Predicted annual change in FEV1. MLR Non smokers Ever smokersExplanatory variables tested (ES, NS considered separately):
age, weight, observation time,T dust-CE, RD-CE, RCS-CE, oil mist-CE, oil vapour-CE, formaldehyde-CEVOC-CE, NO2-CE, CO-CE, FEV1 nss nss
(continued)
16 P. HOET ET AL.
Length of follow up (FU) and number of LFT. As above-mentioned, intra-individual variability may become of concernin longitudinal investigations and determining when LFTdecline is considered excessive is rather challenging. Theyear-to-year intra-variability reaching 15%, this variability mayexceed the true annual decline, and reliable rates of changefor a subject cannot be calculated without prolonged FUcomprising sufficient LFT (Pellegrino et al. 2005). Hnizdo et al.(2005) have shown that it takes 5–8 years to establish therate of LF decline with sufficient precision in an individual.When testing is done on an annual or less frequent basis, theslopes provided by the linear regression models during thefirst 5 years may not provide a reliable estimate of the “true”rate of decline. Moreover, calculations of longitudinal changesin FEV1 (DFEV1) based only on 2 or 3 data points can varymarkedly. With only two or three surveys, survey bias may besignificant. Examining DFEV1 in seven surveys performedover a period of 11 years in adults, Burrows et al. (1986)showed that when only two tests are available to evaluatechange, the large variability necessitates relatively largechanges to be confident. Had studies been carried out onlyin Surveys II and V, there would have appeared to be a slightmean increase in FEV1 over time, whereas using only SurveysV and VI would have produced an apparent mean decline inFEV1 of 35.4ml/year.
Because of this intra-individual issue, yearly change�15%FVC and FEV1 are estimated to be meaningful changes inhealthy subjects (ACOEM 2000, 2005; Pellegrino et al. 2005;ACOEM 2011; OSHA 2013; ATS 2014). This 15% decline frombaseline FEV1 (plus expected average age-loss) can be calcu-lated either by the % predicted method or the volumemethod. The ATS (2014) specifies that “With increasing yearsof follow-up these methods detect smaller annual % declinesin FEV1 as abnormal, for example 15% decline in Year 1 offollow up to 4% annual decline with 5 years of follow up”.The other approach is based on the slope, calculated by lin-ear regression using all available acceptable spirometryresults over time. To be considered as significant or excessive,it should be steeper than 90–100ml/year over at least4–6 years (ACOEM 2005), 60–90ml/year over a minimum of5–8 years of follow up for reliable estimates of FEV1 slope(ATS 2014). More recently, a computerized approach (asSpirometry Longitudinal Data Analysis software (SPIROLA,Morgantown, WV), developed by NIOSH) has been developedto facilitate ongoing monitoring of data quality and longitu-dinal data precision during the early years of spirometrymonitoring (over the first 5–8 years of FU, although smallshort-term longitudinal changes (<5 years) may be difficult to
interpret because the relatively large inherent FEV1 technicalvariability in spirometry testing). Most interestingly, thismethod can be used for individuals and groups of workers.The software calculates a threshold FEV1 Limit ofLongitudinal Decline (LLD) based on the actual data precisionand hence, determines whether the decline exceeds whatwould be predicted based on an expected rate of declineand expected FEV1 within-person variability. It allows pro-grams with quality spirometry (e.g. 3–5% variability) to estab-lish lower thresholds for excessive decline without losingspecificity in predicting subsequent excessive FEV1 decline.LLD-based thresholds for programs with more variability(about 6%) are quantitatively similar to the 15% approachabove (Hnizdo et al. 2010b; ATS 2014).
None of the longitudinal studies included in the presentreview used any of these approaches nor discussed the intra-individual variability issue in FU. The importance of thelength of FU and number of LFT calls for caution when inter-preting results of certain papers. Also, one has to be awarethat to limit the intra-variability issue, longitudinal investiga-tions also have to consider changes in smoking habits orweight, which was not the case in the reviewed papers.
Discordance between cross-sectional and longitudinalstudies. In general, cross-sectional and longitudinal surveysprovide discordant estimate of expected LF decline. A steeperannual decline is generally obtained when regression analy-ses are derived from a cross-sectional approach, which aremore sensitive to population heterogeneity, compared withlongitudinal studies (Sherrill et al. 1992; Lebowitz 1996;Hendrick et al. 2005; Johnsen 2009; McKay et al. 2011). Thishas been largely demonstrated with age-related FEV1 decline,which tends to be greater when predicted from cross-sec-tional data than from longitudinal pulmonary function data(e.g. Burrows et al. 1986; Louis et al. 1986; Glindmeyer et al.1987; Vollmer et al. 1988; Van Pelt et al. 1989). The ageregression coefficient for FEV1 and FVC, determined cross-sec-tionally at each visit, was more than twice the longitudinalannual change computed from the same data as the mean ofthe slopes of each subject's regression lines (Glindmeyeret al. 1982). Reviewing 22 studies, which estimated the effectof aging on FEV1, Hendrick et al. (2005) found that the cross-sectional estimates varied from �20 to �70ml/year(mean �34), and the longitudinal estimates from þ0.1 to�19.5ml/year (mean �9). Using medical screening data col-lected in 1884 chemical plant workers between 1973 and2003, Wang et al. (2009) concluded to an age-related loss in
Table 2. Continued
Main data analysesResults of analyses between RCS exposure and LFT change
Predicted additional LFT decline associated with RCS exposure
Correlation between independent exposure variables.Pearson correlation coefficient (r)RCS-CE vs R dust-CE 0.48RCS-CE vs NO2 0.48
LFT: only FEV1/FVC, FEV1, FVC results are included; MLR: multiple linear regression; LR: logistic regression; RD: respirable dust; RCS respirable cristalline silica; CE:cumulative exposure; AE: average exposure; nss: not statistically significant; (;): 95%CI.
CRITICAL REVIEWS IN TOXICOLOGY 17
FEV1 for white males of 31.5ml/year in the cross-sectionalstudy and 23.8ml/year in the longitudinal study.
Similarly, regarding the impact of occupational exposureon LFT, the annual decline found in longitudinal analyses wasgenerally lower than expected from cross-sectional data. Thiswas, for instance, shown in British miners (Love & Miller1982), US coal miners (Seixas et al. 1993), Swedish insulationwool construction workers (Albin et al. 1998; McKay et al.2011), or RCF exposed workers (McKay et al. 2011). No con-sistent longitudinal decline in FVC or FEV1 with increasingRCF exposure category was observed, although cross-sec-tional changes were observed for subjects in the highestexposure category (McKay et al. 2011). In the present review,one study reported both cross-sectional and longitudinal data(Hertzberg et al. 2002). The cross-sectional investigation, cal-culated that a cumulative exposure to silica at 1mg/m3-yearwould be associated with a loss of 26.1ml of FEV1, 17.2ml ofFVC, and 0.39% of FEV1/FVC and the merely described longi-tudinal data analysis to an additional 1.1ml/year decline inFEV1, and a 1.6ml/year decline in FVC for each mg/m3 of sil-ica exposure.
Actually, the age or exposure regression coefficient forFEV1, FVC drawn from cross-sectional investigations, does notrepresent longitudinal observations of the effect, but ratherreflects the differences between individuals (Hendrick et al.2005; McKay et al. 2011). Cross-sectional studies model meanrates of change from all subjects by age. Whereas in longitu-dinal studies, slopes may be obtained by first estimating indi-vidual rates of change, then averaging across all subjects(McKay et al. 2011).
Moreover, cohort effects (year of birth), period effects(year of survey), healthy worker effect, changes in risk factors,and learning effect have been proposed to account for theobserved differences between cross-sectional and longitu-dinal estimates of annual decline in lung function (Xu et al.1995; Kerstjens et al. 1997). Younger subjects from a cross-sectional study do not necessarily have the same mean FEV1as did those at the older end of the age range when theywere of similar young age. Difference could be attributed inpart to gradual increase in adult standing height, changes inambient air pollution, respiratory infections, vaccinations,types of cigarettes, diet, and lifestyles over time, but alsochanges in techniques and apparatus during the time a studyis performed, and learning effects (subjects with LFT experi-ence achieving higher spirometric values). For example, Xuet al. (1995) demonstrated, in a 24-year longitudinal study,significant period and birth cohort effects in FEV1 decline.Looking at period effects in four different survey periods,they found an increase of 250ml for the average level ofFEV1 for men and of 219ml for women in the last surveyperiod (1985–1990) compared with the first survey period(1973–1978).
In addition, being a “snapshot” at a single point in time,cross-sectional analyses cannot inform on when dysfunctionfirst developed in any one worker and are limited in theirability to provide reliable information on exposure–responserelationship. They are likely more sensitive to past exposureinfluences, whereas longitudinal analyses are more sensitiveto influences affecting annual decline within the study period
(Glindmeyer et al. 1982, 1987). Given the duration of expos-ure and the moment LFT were performed, it is likely that, inmost papers considered here, exposure had started beforethe initial lung function measurement, except for the studyon uranium workers (M€ohner et al. 2013).
Interaction between time-dependent variables.Longitudinal studies should allow for consideration of time-dependent variables between different examinations.However, a major challenge in these surveys is addressingthe interaction between cumulative exposure to the agent ofinterest and all the time-dependent variables on LF decline.Partial collinearity is expected between cumulative exposureand other variables exerting a cumulative effect with the pas-sage of time such as aging, smoking (status, pack-year),exposure to other occupational or environmental pollutants,weight gain, duration of employment, or time since retire-ment. Aging is known to be a major determinant of LFdecline but an additional difficulty is that changes in FVC andFEV1 are non-linear and decline faster with advancing age.The typical average rate of decline is considered to be30ml/year. However, as the subject ages, FEV1 decreaseaccelerates; lung function would decrease by approximately20ml/year during middle age, and then more rapidly byabout 38ml/year at 60 years old (Kerstjens et al. 1997; Langeet al. 1998). McKay et al. (2011) nicely demonstrated theseissues conducting both cross-sectional and longitudinal inves-tigations on RCF workers. They showed that cross-sectionalanalyses do not adequately address time-dependent changesthat correlate with age such as pack-years and weight gain.As these are positively correlated, it is difficult to estimatethe effect of each independently. They also demonstrated, intheir 17-year FU investigation, that traditional longitudinalmodels (linear regression, GEE) may not account for the non-linear, age-related decline in LF and do not adequately parti-tion age-related changes from other time-dependent varia-bles. When workers were each assigned a level of cumulativeRCF exposure and modeled longitudinally by age groups, noconsistent exposure-related decline in FVC or FEV1 wasfound. This model partitioning the non-linear effects of age-ing, smoothed age effects across all intervals and increasedthe precision of the estimates improving study power todetect change as demonstrated with the significant findingsrelated to current smoking status, pack-years of smoking, ini-tial weight, and weight gain.
None of the studies included in the present reviewaddressed the issue of time-dependent changes associatedwith aging, change in smoking habits or weight, nor theassociation between time-dependent variables such as age,cumulative exposure, duration of exposure, pack-years. Onestudy simply excluded age from the analysis because of ahigh correlation between age and duration of exposure(Ulvestad et al. 2000).
Initial LFT values. Cross-analyses represent a “snapshot” intime and do not account for the initial FEV1 value. ExaminingLF change (difference between the final and initial measure-ment) in longitudinal studies assumes that (a) the mean initialmeasurement does not differ between exposure groups
18 P. HOET ET AL.
(otherwise, the difference should be regarded as a con-founder if LFT were obtained before exposure) and (b) theinitial lung function is not a determinant of change (Irwig1985). On the one hand, as would be expected from theeffect due to the regression towards the mean, the higherthe initial lung function the higher would the absolute yearlydecline during the follow up. On the other hand, the so-called horse racing effect, which is the tendency for individu-als with faster rates of decline over time in the lung functionto have lower initial values because of past decline, shouldbe considered (Irwig 1985; Burrows et al. 1987; Irwig et al.1988; Carta et al. 1996). Also, low maximally attained lungfunction in early adulthood can result in COPD later in life,even when the rate of decline in FEV1 is within the normalrange (Lange et al. 2015; Rennard & Drummond 2015).
The absence of difference between exposure groups at ini-tial LFT measurements is not systematically reported in the lit-erature considered here. No significant differences wereobserved in LF data across job groups at the start of the firstlongitudinal survey on Norwegian tunnel workers (Ulvestadet al. 2001). In the second one, Bakke et al. (2004) noted thatthere were no statistical differences among the six subgroupsat the first observation, although the three reference sub-groups generally had slightly better predicted FEV1 valuethan the tunnel workers. Several papers included in the pre-sent review provided initial LFT results but none regressedsimultaneously LFT change on RCS exposure and initial lungfunction. Graham et al. (1994) carried out an analysis of covari-ance to separate out the effects on LF of several variablesincluding initial LFT value and concluded to a significantnegative correlation of initial FEV1 (p< 0.002), FVC (p< 0.001),and FEV1/FVC ratio (p< 0.001). Regression coefficients are pro-vided but the absence of unit for both the independent anddependent variables makes these data difficult to interpret.
Critical analysis of available studies
When assessing exposure-response relationships in epidemio-logical studies, the reliability of exposure data, the health out-come assessment, and the potential bias and confoundingfactors have to be addressed. In light of the critical aspects,as discussed above, with respect to the reliability of RCSexposure assessment as well as LFT measurements, anappraisal checklist (see Supplementary data) was elaboratedto systematically analyze the eleven studies included in thepresent review. The suitability of the data analyses to addressthe question of the ERR between RCS and obstructive impair-ment was also checked. Table 1 summarizes the main charac-teristics of the population, RCS exposure assessment and LFTprocedure. Table 2 summarizes the main data analyses andthe results relevant to the relationship between RCS exposureand LFT changes.
Cross-sectional studies
Studies using exposure proxies in the ERR analysesThe main purpose of Jorna et al. (1994) was to determinewhether respiratory hazards, pneumoconiosis and airflow
limitation, are associated with the exposure mix, high in dia-tomaceous dust, in potato sorting. There was no evidence ofsilicosis at chest-XR, and serum levels of type III procollagen(P-III-P), used as a marker to detect a fibrogenic activity pos-sibly indicative for pneumoconiosis, were within referencerange. Information regarding RCS exposure is scarce. It isstated that job continuity of most workers allowed properestimation of the individual (cumulative) dose of total dustand of silica exposure from each worker's job history, butonly the “cumulative dose” for total dust, with a questionableunit (gh/m3) is provided. RCS exposure levels (mg/m3) areprovided for five job categories (sorting, transport, loading,etc.). By contrast, average LF results are given for controls,short term exposed, currently exposed and retired, with nodata on their respective exposure level to RCS. These sub-groups are inhomogeneous in terms of the number of sub-jects and confounders. Assuming that the five job categoriesconcern the currently exposed, one could tentatively con-clude that exposure to an average RCS level of 0.27mg/m3 isassociated with a significant (p< 0.05) decrease in FEV1/FVCand % pred FEV1 when compared with controls. However,currently exposed workers are older and tend to be heaviersmokers than controls, who moreover are white collars. In themultiple linear regression carried out on all workers exceptretired workers (because of the large difference in age),height, weight, smoking, and dust (cumulative) exposure, butnot RCS, were included as independent variables. Airflow limi-tation incidence is reported for the whole group; no attemptwas made to distinguish between exposure groups. The anal-yses did not stratify by RCS exposure level. Overall, severalaspects preclude using of this study to establish a relevantERR: (1) in the statistical analyses, no attempt was made toclarify the relationship between RCS and LF, (2) data regard-ing both exposure characterization to RCS and LFT measure-ments lack precision, and (3) no data regarding exposure toother possible contaminants is provided.
The cross-sectional study on Norwegian tunnel workersaimed at assessing the occurrence of respiratory symptomsand airflow limitation in these workers and to relate the find-ings to years of exposure (Ulvestad et al. 2000). All tunneland other heavy construction workers (n¼ 417) employed at15 work sites were invited to participate in a cross sectionalstudy (response rate 100%). None of the tunnel workers hadradiological signs of silicosis. A main advantage of this studyis the internal reference group comprising heavy constructionworkers with the same working schedule as the tunnel work-ers but who worked in the open. RCS as well as NO2, oil mistand inorganic gases exposure was rigorously assessed butdata analyses were conducted using job as tunnel worker asa proxi for exposure to RCS. Thus, this study is not inform-ative on the ERR between RCS exposure and LF change.
The objective of Meijer et al. (2001) was to examine theventilatory effects of exposure to low levels of concrete dustcontaining CS and to identify workers at risk for COPD.Production workers from two concrete materials-producingfactories without radiographic evidence of silicosis were com-pared with internal controls comprising managers, officeworkers, and laboratory personnel. The reliability of RCSmeasurement can be problematic in view of the very low
CRITICAL REVIEWS IN TOXICOLOGY 19
minimal level reported (0.0003mg/m3). An interesting point isthe use of standardized residual (SR) lung function and SR-FEV1/FVC at the P5 or lower to define COPD, as recom-mended (see Spirometric indices used to define obstruction).The mean current and cumulative RCS exposure levels weresimilar in concrete workers with (n¼ 10) and without(n¼ 134) COPD. Compared with internal controls, the FEV1/FVC mean level expressed as % of an external referencepopulation was reduced in concrete workers (p¼ 0.02). In themodel assessing predicted changes in LF, “exposure to dust”(unit not provided but supposedly mg/m3) is included as avariable, not RCS. It is only mentioned that “introducingcumulative exposure (dust-years or silica-years) as measure ofexposure into the linear regression models did not improvethe results”, implying that a mean RCS-CE up to 0.566mg/m3-year would not be associated with a LF decline. In addition,(a) the very low reported minimal level of exposure castsdoubts on the accuracy and reliability of the exposure esti-mates; (b) cumulative exposure determination is poorlydescribed; (c) other potential exposures are not considered.
Studies using RCS in the ERR analysesIn their cross-sectional study on automotive foundry workers,Hertzberg et al. (2002) examined the relationship between sil-ica-exposure and obstructive impairment using quartiles ofcumulative exposure expressed as mg/day/m3. Individualswith radiographic findings of parenchymal changes consistentwith asbestosis or silicosis were excluded from the analyses.Although an effort to collect exposure data was made, confi-dence in the accuracy and the precision of the exposure char-acterization is considered a major issue of the study (highuncertainty about RCS measurements, limited explanationabout CE assessment which is the only metric used in theanalyses, exposure to other pollutants not considered) (seeSampling and analysis strategies). LFT quality is also question-able; results were extracted from medical records obtainedbetween 1978 (when the company began such testing) and1992 with different spirometers. To address major qualitycontrol issues, all LFT were reviewed and quality rated forFEV1 and FVC separately. Only workers having at least twoacceptable and reproducible efforts according to ATS recom-mendations (1987) were included in the study. The numberof workers with acceptable LFT results by number of yearthese tests were available is highly variable. Using contin-gency table methods, relationships between quartiles of RCS-CE and LFT (abnormal value and % pred) were assessedaccounting for the smoking status. From a cohort of 1072workers, only 247 were considered to have at least one LFTfor which two or more efforts were rated as acceptable andreproducible for FEV1/FVC. Subgroups of the cells in the con-tingency tables included a highly variable number of subjects(from 21 to 160 for smokers and from 4 to 36 for non-smok-ers). Smokers represented a large majority, leaving only 37non-smokers to be included in the analysis (from 4 to 12workers per quartile of exposure); such small sample sizescan hinder the detection of any effect. Information onimportant confounders is not available and, there is no indi-cation of matching for factors such as ethnicity, age, or
height between quartiles of exposure. Odds ratios for theincidence of abnormal FEV1 and FVC values for 20 and 40years of exposure at a variety of TWA levels and a tableshowing the results of a linear regression of LFT change con-trolling for silica, pack-years, ethnicity, age, height, and expos-ure to silica at other job are given, but without anyexplanation. The particularly succinct description of statisticalanalyses further limits the usefulness of this publication.Hence, although interesting, this study raises too many con-cerns for drawing meaningful conclusions useful for theobjective of the present review.
The objective of the study on Spanish granite workers wasto evaluate and analyze exposure and respiratory illnessamong granite workers (Rego et al. 2008). This study doesnot clearly mention how subjects identified with silicosis(17.5%) were handled. Data provided are too limited toadequately characterize the reliability of RCS exposure, whichappears uncertain, as well as LF measurement quality. Thepaper reports on quintiles of RCS-CE levels but there is noindication on how they were determined, neither on the dis-tribution of height, age, ethnicity, smoking in these exposure-related subgroups. 4.3% of the workers are reported to havea FEV1/FVC<70%, without specifying their quintile of expos-ure. Also, statistics are unclear (number of subjects includedin the different analyses, strategy to handle confounders,regression coefficient in the linear regression difficult to inter-pret). When investigating the relationship between quintilesof silica exposure and obstructive defect, a logistic regressionin which FEV1 values below 50% predicted were consideredas abnormal is performed. No consideration is given forpotential co-exposure to other agents. All these aspects ser-iously reduce the relevance of this publication or defining avalid ERR.
Ehrlich et al. (2011) investigated the ERR between respir-able dust, RCS, and LF loss in black South African gold min-ers among which 18.1% suffered from silicosis, 27.8% fromtuberculosis, and 5.4% from both diseases. RCS exposurecharacterization relies on a comprehensive JEM (see Samplingand analysis strategies), which is a strength of this investiga-tion; the lack of information on exposure to other potentialpollutants a limitation. Precision of RCS exposure levels ishigher (AM, SD, range, P50) than in most other studies. Yet,the lowest reported levels bring into question their accuracy.Also, description of the LFT procedure is succinct, although itis the only study indicating that height and weight weremeasured. FEV1/FVC ratio is not reported. Excess loss wasdefined as the difference between the predicted andobserved values of FEV1 and FVC, and thus intrinsicallyadjusted for age and height. Bivariate associations betweenFEV1 and FVC excess loss and several variables were tested;RCS-CE or average RCS were significant. Smoking played norole in lung function loss, which is consistent with previousstudies of black miners. The likely reason for this is a lowdaily consumption of cigarettes. The survey comprised work-ers with silicosis and/or tuberculosis. Introducing both dis-eases as mediators in the multivariate analysis to estimatethe direct effect of exposure not mediated by them, Ehrlichet al. (2011) showed that the estimated effect of cumulativeand average RCS exposures on FEV1 excess loss was not
20 P. HOET ET AL.
anymore significant. Average RCS still showed direct signifi-cant effects on FVC excess loss, which does not reflect thecharacteristic pattern of an obstructive syndrome. These find-ings are against the evidence of an association between anexposure to a mean RCS level of 1.15mg/m3-years or0.050mg/m3 and an obstructive lung dysfunction. However,miners were found to have on average better LF than a ref-erence population drawn from non-dust exposed workers inJohannesburg, which may reflect a healthy worker “survivor”effect limiting the suitability of these data to establish arobust ERR.
Longitudinal studies
Studies using exposure proxies in the ERR analysesMalmberg et al. (1993) investigated changes in LF in graniteworkers over a 12-year period. One granite crusher had chestradiographic changes suggestive of silicosis. This study can-not be used to address our objective due to key limitations.RCS exposure assessment is minimally described and preci-sion of the reported RCS exposure levels is weak. LFT proce-dures lack sufficient information to assess the reliability ofthe results. Only two LFT, with a change of spirometer, wereconducted leading to untrustworthy results. In addition, LFchanges in current and retired workers were compared withthose in controls recruited in a health survey introducing abias. Compared with controls, the granite crushers showed a4.5% significantly lower FEV1/VC at the second LFT but com-parison at the first LFT is not available. Some of the LF varia-bles measured at the second LFT on the referent populationdeviated significantly from predicted values and the differ-ence in change between granite crushers and referents isexpressed in % of the average values for referents measuredin both LFT. Moreover, the small sample size can hinder thedetection of an ERR. Noteworthy, the decrease in LF over the12-year period seemed to be more pronounced in the groupwho had not been exposed to silica-containing dust for theentire period (due to retirement or change in job). Theauthors hypothesize that the changes in LF in retired workersmay be due to retained silica, and that any changes may con-tinue for a long time after stopping of work. The averagechanges in FEV1 and FEV1/FVC over the 12 years of observa-tion were significantly greater in granite workers than inreferents suggesting airway obstruction. As noted by theauthors, these changes are small compared with the normalvariability within a healthy population (about 20%). Finally,the only data concerning an ERR between RCS exposure andLF is the following statement “the change in lung functiondid not correlate significantly with the inhaled dose of respir-able quartz in the granite crushers or with age or differentsmoking measures”.
The purpose of the study on the Vermont granite workerswas to characterize the rate of LF change and to determinewhether exposure to the relatively low levels of granite dustprevailing in this industry significantly affected LF loss(Graham et al. 1994). All workers, including stone shed,quarry, and office, were offered LFT biennially from 1979 to1987. The longitudinal loss of LF calculation is based on a
sample of 711 workers tested at least three times. Timebetween first and last LFT is not available. LFT are too brieflydescribed to assess reliability and the equipment changedover time. Average annual change in FEV1/FVC, FEV1, andFVC unadjusted for covariates is given for the categories ofworkers. The mean annual FEV1/FVC loss in non-smokerstends to be lower in the quarry workers compared with bothoffice workers and shed worker but standard deviations arehigh and no statistical test compares the results between thegroups. Estimates of longitudinal FEV1, FVC, and FEV1/FVCloss are compared among inhomogeneous subgroups includ-ing between 14 and 259 subjects, according to their exposurestatus and smoking status. There is no data regarding expos-ure of the quarry workers, whereas in the stone sheds, ambi-ent dust levels were well characterized during 1983–1984. Aserious flaw is that the estimate of quartz concentration wasmade using measurements of total dust concentration and“previous estimates of percentage quartz present in granitedust (10%)”, not on measurements of RCS. Finally, an ERRanalysis in terms of years worked in granite or job was made,not RCS exposure making this study non-informative withrespect to our objective.
Studies using RCS in the ERR analysesAt the same time, as their cross-sectional investigation onautomotive foundry workers, Hertzberg et al. (2002) also con-ducted a longitudinal study on 242 workers with at least fiveLFT over a period of maximum 13 years. Average and min-imum FU duration and time interval between testing are notprovided. The method of selection of the subjects is not clear.FEV1 considered as acceptable were available for at least5 years for 328 workers and FVC for 52 workers. As summar-ized for the cross-sectional study, exposure data as well asoutcome data are not considered to be adequate to addressthe objective of the present review. In addition, the meanannual FEV1 and FVC changes per mg/m3 of mean silicaexposure are given without any explanation about the han-dling of the data except that values are adjusted for pack-years and ethnicity.
M€ohner et al. (2013) made a particularly thorough andimpressive job to characterize exposure to RCS in the largeWismut cohort of former uranium miners, and constructed acomprehensive JEM with robust quantitative exposure esti-mates (see Sampling and analysis strategies). The cohortincludes only workers born between 1954 and 1956 toensure that none had worked underground in mines before1971 when RCS exposure levels could have been muchhigher. AM, SD and range of mg/m3 are given, but are notprovided for RCS-CE that is the metric used in most analyzes.The young mean age of this large cohort at entry in Wismut(20.4; 18–36 years old) largely excludes exposure to otheroccupational risk factors before. No miner showed signs ofsilicosis during the period under study. Statistically significantdeterminants of longitudinal changes in FEV1/FVC ratio andFEV1 identified by linear mixed-effects regression were age,height, continuous smoking, uncertain smoking, and cumula-tive exposure to respirable quartz, i.e. all tested variablesexcept BMI. Exposure to 1mg/m3-year respirable quartz was
CRITICAL REVIEWS IN TOXICOLOGY 21
calculated to cause a significant average additional reductionin FEV1/FVC of 2.75%. The annual age-related decline inFEV1/FVC for a non-smoker was 0.76%. For a continuoussmoker, on an average, an additional annual decline of0.18% was calculated, but the SD for this parameter was rela-tively large. Dividing the dataset into two groups accordingto the median exposure concentration (above or below0.072mg/m3) did not seem to influence the relationship.Controlling for age, height, BMI, a male smoker, 176 cm-talland 20 years old, worker, would fall below P5 of 70% predFEV1/FVC after 35 years of exposure at 0.1mg/m3, at the ageof 55 years; a non-smoker at more than 70 years (estimationmade on a figure). A nested case–control study showed anERR between quintiles of RCS-CE and FEV1/FVC ratio <0.7.These interesting observations are clouded by uncertaintiesin the reliability of LFT. Spirometric data were gatheredthrough routinely performed medical checkups in differentmedical facilities over a period of 20 years, with equipmentchange, which constitutes main shortcomings. The authorsstate that identical rules and similar equipment were usedfor all medical facilities and measured values were standar-dized in 1970, so that they assume that the spirometric dataform a homogeneous data and that “the quality of the studydata is as good as it can be under the conditions of routinelycaptured data”. Yet, no information on LFT procedure is pro-vided and confidence in LFT results is not optimal. It is indi-cated that “As some spirometries from the early years didnot fit the quality criteria, they were excluded from furtheranalysis” without further precision. Data rely on an averageof 5 LFT (from 2 to 15), with a time elapsed between firstand last LFT ranging from 0.6 to 17 years, resulting in aninhomogeneous data set. It is not clear why, for the nestedcase–control study, subjects for whom only at least one spir-ometry with an FEV1/FVC value of<0.7 was recorded weredenoted as case. Additionally, the mean FEV1/FVC was 83%(range 54–99) at entry, casting further doubt about the reli-ability of the measures given the young age covered by theFU. For 21.5% of the miners, at least one spirometry with anFEV1/FVC value <0.7 was recorded, and 5% had already ful-filled the criterion at their first spirometry. This finding is notfurther discussed by the authors, but this is at odds with thenotion that COPD is a slowly developing condition that isnot usually manifest until midlife. One could tentativelyhypothesize that the observed reduced LF reflects an acuteeffect. Regarding potential exposure to other pollutants,arsenic ambient concentration was characterized. However,no account was taken of the many other pollutants to whichworkers may be exposed in uranium mines, among whichdiesel exhaust and NO2 (NRC 2012) that can induce chroniclung inflammation and are associated to COPD (Wegmannet al. 2005; Weinmann et al. 2008; Andersen et al. 2011; Hartet al. 2012).
Ulvestad et al. (2001) examined whether undergroundconstruction workers exposed to tunneling pollutants had anincreased risk of decline in LF and respiratory symptomscompared with reference subjects working outside the tun-nel atmosphere. None of the tunnel workers had radio-graphic signs of pneumoconiosis at the start of the survey.There were no cases with new radiographic findings during
the FU period. The internal control group comprised heavyoutdoor construction workers but also white collar construc-tion employees likely to be characterized by different life-style factors. Only two LFT were performed at the start andthe end of an 8-year period. LFT were carried out at differ-ent work sites but by the same trained technicians in bothperiods, and in accordance with the ATS recommendations.A shortcoming is that the first LFT were conducted after theworkers had started their work period, whereas the secondLFT, after at least 1week off. Only FEV1 and FVC results areprovided, not FEV1/FVC. Estimates of cumulative historicalexposure before the survey were based on the assumptionthat the excavation technology and type of machinery usedhad not changed substantially since 1980. Considering themean age and duration of exposure at entry in the FU,some workers started exposure before 1980 at a time RCSexposure was supposedly higher. However, no associationsbetween the historical-CE to tunneling pollutants anddecreases in lung function were observed. By contrast,adjusting for age and pack-years, RCS-CE during the 8-yearperiod was associated with increased reductions in FEV1compared with controls, but there was a negative ERRwith larger decreases in FEV1 at lower RCS exposures(0.019mg/m3, including only 17 workers) compared to thehigher exposure group (0.044mg/m3). No association wasobserved for FVC. Controlling for age and RD-CE, but notheight, nor ethnicity, the additional predicted FEV1 declineassociated with exposure to 1mg quartz/m3 year was calcu-lated to be 34ml in non-smokers and 44ml in current smok-ers. Exposure characterization to RCS and other pollutants towhich tunnel workers are exposed is a major strength of thestudy (see Sampling and analysis strategies). Correlationsbetween the exposure variables were high and distinguish-ing between the various pollutants and the effects on theairways was difficult; the authors chose to select RD andRCS for the final statistical analyses.
The study considered to be the most useful is an exten-sion of the above-mentioned work on tunnel workers, aim-ing to confirm the findings of a relation between CE torespirable dust and RCS and LF changes in other tunnelworkers not previously studied (Bakke et al. 2004). Theauthors also investigated whether exposures other than RDand RCS were associated with LF changes. They checked,by means of sound statistical analyses, whether the workerswithin the job groups were uniformly exposed to dust andgases. Workers with at least two LFT were included. The FUtime was highly heterogeneous, with a minimal of 0.4 yearraising question. Spirometric measurements were performedusing two bellow spirometers by technicians trained to cali-brate the equipment and carry out the examinations. FEV1/FVC ratio is not provided. Reduced FVC was significantlyassociated with RCS-CE in both non-smokers and eversmokers. FEV1 reduction was not associated with RCSexposure in non-smokers but a significant association wasobserved in smokers and several other exposure variables.The final and best regression model showed the mostimportant exposure variable was NO2, in both smokers andnon-smokers. Inclusion of RCS did not improve the modelsignificantly.
22 P. HOET ET AL.
Conclusion and recommendations for furtherresearch
This review aimed at clarifying the exposure–response rela-tionship between RCS and obstructive pulmonary dysfunc-tion, to determine whether current OELs established toprevent silicosis also protect from the development of airwayobstruction. Although the literature on impaired lung func-tion associated with silica is abundant, only eleven relevantpapers that reported both RCS exposure levels and LFT wereretrieved. These studies add some supporting evidence infavor of a qualitative association between–occupational activ-ities exposing to RCS and obstructive lung dysfunction. Thereis, however, no convincing evidence of an ERR between RCSexposure and obstructive LF. Limitations/weaknesses regard-ing either the exposure or the lung function assessment, orboth, introduce considerable uncertainties, and no well-founded quantitative estimates can be drawn from theseinvestigations.
Thus, none of these studies was denoted suitable toaddress the question raised, because (a) surrogates such asjob or duration of exposure, or silica-containing dust wereused to assess RCS exposure–obstructive defect relationships,(b) the ERR between RCS and LFT was not adequatelyaddressed, and/or (c) they were considered of low confidencewith respect to exposure characterization and/or LFT proced-ure. None of the included studies had the same specificobjective of the present review and none had an appropriate,relevant analysis to address this objective.
The most robust series of investigations (Bakke et al. 2004)found no clear relationship between RCS exposure and LFTamong subgroups of workers with long-term exposure toaverage levels ranging from 0.019 to 0.044mg/m3 (from 0.10to 0.35mg/m3-year). Thus, the relevant available literaturedoes not allow the defining of a RCS exposure thresholdassociated with an increased risk of obstructive lung dysfunc-tion, as defined by spirometry, in workers without silicosis.Further research is needed to explore this issue, but as high-lighted in this review, conducting epidemiological studieswith both valid exposure and outcome measurementpresents a real challenge.
A first challenge is the design of the study. Cross-sectionalstudies may provide important data about a cohort at a spe-cific point in time, and the association between the outcomeand current or previous exposure can be studied.Longitudinal studies are generally regarded as necessary tobring forward further knowledge on a potential causal rela-tionship between exposures and outcomes. Importantly,cross-sectional and longitudinal studies are intrinsically differ-ent and may yield different inferences; comparing resultsfrom both studies is hazardous. Both have their advantagesand disadvantages. Cross-sectional studies reflect changesassociated with past noxious influences, whereas longitudinalstudies are sensitive to influences that exist during the studyperiod, constituting a main difference. Cross-sectional investi-gations are particularly vulnerable to population heterogen-eity, cohort effect, and healthy worker effect. Longitudinalstudies are generally thought to be more sensitive and reli-able since each subject is his/her own control and, provided
they cover a sufficient period, are more likely to produce avalid measure of an occupational exposure effect. Such test-ing may be especially useful in early detection of an exces-sive, i.e. faster than expected, decline in FEV1 over time.Comparison with baselines should be performed wheneverpossible to allow evaluation of change over time in an indi-vidual or in a group compared with a measured, rather thana predicted value. However, longitudinal studies are suscep-tible to errors caused by selective participation in multiplesurveys, loss to FU, learning effects. Provided that the groupsare homogeneous with respect to the many sources of LFvariability, comparing groups of workers defined by well-char-acterized levels of exposure is of great interest to clarify theexposure–response relationship and avoids comparing to anexternal reference population.
A second challenge is to characterize the exposure to RCS.Exposure characterization is of utmost importance wheneverinvestigating the ERR involving any pollutant but the lowsensitivity of RCS analysis is a real issue. RCS collection andanalyses should stick to the most recent guidelines (e.g.NIOSH 2003; HSE 2005). Moreover, it is to be emphasizedthat the most relevant exposure metric related to obstructiveLF changes remains to be determined. Lung dysfunctioncaused by RCS (repeated) short-term high level exposure maynot equate with that produced by the same dose over a lon-ger period of time. Finally, exposure is rarely only to RCS andother pollutants should be examined and taken into account.
Many factors and sources of variability may impact the val-idity and reliability of the results and it is often challengingto determine what constitutes a true decline in LF, ratherthan a change due to the many sources of variability. If oneis trying to measure the effect of occupational exposure to achemical agent on LF, all other sources of variability in spir-ometry measurements introduce noise and should be mini-mized as effectively as possible. Technical factors related tothe equipment (spirometer and software), operating proced-ure and measurements conditions (temperature, altitude,etc.), quality control standards applied, and technician com-petence, as well as biological factors related to the workerand including intra- (body position, motivation, LF circadianrhythm, health condition, LF performed within a short time ofvigorous physical activity/heavy workload or a heavy meal)and inter-individual parameters (gender, age, height, weight,race, smoking, socio-economic status, degree of physicalactivity, muscularity, residence (urban or rural), air pollution(urban, home)) are all contributing to the variability of theresults. LFT measures should be performed according to con-sensual recommendations to limit technical variability (e.g.Miller et al. 2005a, 2005b; ACOEM 2011; OSHA 2013; ATS2014). A critical issue in cross-sectional studies, which modelmean rates of change from all subjects, is the inter-subjectsvariability, which can add up/combine to the intra-individualvariability and the measurement biases and errors. In longitu-dinal studies, intra-subjects variability may become of con-cern and to estimate the rate of LF decline with sufficientprecision and reliability, FU time must be at least 5–8 yearsincluding at least three LFT. LFT measurements should bemade by the same well-qualified technician, using the sameinstrument throughout the observation period. Approaches
CRITICAL REVIEWS IN TOXICOLOGY 23
to detect an excessive individual decline in FEV1 over timeare recommended (ACOEM 2005; Redlich et al. 2014). Also, asoftware intended to assist in ongoing monitoring data andinterpreting computerized longitudinal spirometry data forindividuals as well as for a group is available (SPIROLA, devel-oped and maintained by the Center for Diseases Control). Aslong as LFT have been conducted sticking to recommenda-tions, results can be extracted from routine occupationalhealth checkups provided accurate and complete records areproperly maintained. Adequate recordkeeping, as completeas possible, including not only spirometry test reports butalso equipment specification and maintenance records, andpersonnel training and evaluation records, is considered acritical component of a good quality spirometry program. Itbecomes of overriding interest when conducting studiesbased on data extracted from medical records.
Importantly, measurements should be made at the sametime of the day (for all workers and across the years) avoidingdiurnal variations in lung function, and after some days off,to exclude the effect of short-term exposure.
Influence of some sources of variability can never betotally ruled out in observational studies. However, whenconducting a study relying on LFT results, adequate strategiesto deal with these sources of measurements error biases oreffect of confounding factors should be developed at themethodological (design of the study, strict matching criteria)and/or statistical levels and clearly explained in the publica-tion. Accurate data modeling is of main importance. Whenanalyzing data and predicting LF change, whether in longitu-dinal or cross sectional studies, analyses should at leastinclude the main factors known to influence LF: gender,measured height, ethnicity, age and smoking habits/status.Equipment change and technician change (because of LFT indifferent sites or serial LFT for FU study) are to be taken intoaccount. Longitudinal studies should also take into accountvariables such as initial weight, weight change during the FUperiod, smoking habits and changes in smoking status, cumu-lative pack-years and current smoking status, initial LFTresults. Age-related LF decline is a two-fold problem, whichshould be adequately addressed: the interaction betweentime-dependent variable and the non-linear aging-associateddecline. Partitioning of the non-linear age-related changesfrom other time-dependent exposure variables requires spe-cific statistical approaches (e.g. McKay et al. 2011).
In epidemiological studies investigating LF impairment,FEV1 is regularly the only parameter provided, being consid-ered as the most suitable of the spirometry measures for theevaluation of LF changes over time as it is least variablewithin a person, least prone to measurement error, and isdecreased in both obstructive and restrictive impairment.Accelerated decline in FEV1 over time may reflect anobstructive dysfunction; however, the key spirometric featureof an obstructive impairment is a reduced FEV1/FVC and apersistent airflow limitation is confirmed by the presence of apost-bronchodilator reduced ratio. Using a fixed cutoff ofFEV1/FVC to denote an obstructive impairment is discour-aged. A value below LLN set at P5 of adequate reference val-ues, or even better converted to standardized residual,is currently recommended (e.g. Pellegrino et al. 2005;
Stanojevic et al. 2010; ACOEM 2011; OSHA 2013; ATS 2014).Emphasize is placed on the international spirometry referenceequations established by the Global Lung Function Initiative(GLI) (Quanjer et al. 2012). It should also be stressed that spir-ometry only partly captures the clinical features of COPD,which is, in addition, characterized by persistent respiratorysymptoms.
Finally, statistical results should be discussed in light withtheir clinical relevance, which may sometimes appear lowrelative to the high variability in LFT results.
Acknowledgements
The authors gratefully acknowledge the insightful comments and sugges-tions of the external reviewers selected by the Editor and anonymous tothe authors. These comments were particularly helpful in improving themanuscript.
Declaration of interest
The authors’ affiliation during the course of this work is as shown on thecover page. Dr. Desvall�ees is currently employed by an occupationalhealth care service in France. The work reported in the paper was con-ducted during the normal course of employment at the University (UCL)without any external sponsorship. The authors have not appeared in anylegal or regulatory proceedings related to the contents of this reviewduring the last 5 years. Further, the authors have not been engaged totestify in the future as experts in litigation related to the compounds dis-cussed in this paper. DL was an expert at the SCOEL (ScientificCommittee on Occupational Exposure Limits) from 2006 until 2015 (didnot participate in the discussion on Silica document published in 2003).D. L. and P. H. are members of the Scientific Committee of the BelgianFunds for Occupational Diseases, but the subject of interest was not dis-cussed during these last 10 years. P. H. is, since 2014, an expert at theANSES (Agence Nationale de s�ecurit�e sanitaire de l’alimentation, del’environment et du travail) Scientific Committee setting theOccupational Exposure Limits. Silica has not been discussed during thatperiod. The ANSES launched in February 216 a call for experts to partici-pate in a task group on Silica aiming at updating the knowledge on silicaexposure, its hazards and risks. None of the authors participates in thistask group. The review is exclusively the professional work product ofthe authors.
Supplemental material
Supplemental data for this article can be accessed here.
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