Airborne Particle Exposure and Extrinsic Skin Aging

Abstract

For decades, extrinsic skin aging has been known to result from chronic exposure to solar radiation and, more recently, to tobacco smoke. In this study, we have assessed the influence of air pollution on skin aging in 400 Caucasian women aged 70-80 years. Skin aging was clinically assessed by means of SCINEXA (score of intrinsic and extrinsic skin aging), a validated skin aging score. Traffic-related exposure at the place of residence was determined by traffic particle emissions and by estimation of soot in fine dust. Exposure to background particle concentration was determined by measurements of ambient particles at fixed monitoring sites. The impact of air pollution on skin aging was analyzed by linear and logistic regression and adjusted for potential confounding variables. Air pollution exposure was significantly correlated to extrinsic skin aging signs, in particular to pigment spots and less pronounced to wrinkles. An increase in soot (per 0.5 × 10(-5) per m) and particles from traffic (per 475  kg per year and square km) was associated with 20% more pigment spots on forehead and cheeks. Background particle pollution, which was measured in low residential areas of the cities without busy traffic and therefore is not directly attributable to traffic but rather to other sources of particles, was also positively correlated to pigment spots on face. These results indicate that particle pollution might influence skin aging as well.

Full text

Airborne Particle Exposure and Extrinsic Skin Aging
Andrea Vierko
¨tter
1
, Tamara Schikowski
1,2
, Ulrich Ranft
1
, Dorothea Sugiri
1
, Mary Matsui
3
, Ursula Kra
¨mer
1,4
and Jean Krutmann
1,4
For decades, extrinsic skin aging has been known to result from chronic exposure to solar radiation and, more
recently, to tobacco smoke. In this study, we have assessed the influence of air pollution on skin aging in 400
Caucasian women aged 70–80 years. Skin aging was clinically assessed by means of SCINEXA (score of intrinsic and
extrinsic skin aging), a validated skin aging score. Traffic-related exposure at the place of residence was
determined by traffic particle emissions and by estimation of soot in fine dust. Exposure to background particle
concentration was determined by measurements of ambient particles at fixed monitoring sites. The impact of air
pollution on skin aging was analyzed by linear and logistic regression and adjusted for potential confounding
variables. Air pollution exposure was significantly correlated to extrinsic skin aging signs, in particular to pigment
spots and less pronounced to wrinkles. An increase in soot (per 0.510
5
per m) and particles from traffic (per
475 kg per year and square km) was associated with 20% more pigment spots on forehead and cheeks.
Background particle pollution, which was measured in low residential areas of the cities without busy traffic and
therefore is not directly attributable to traffic but rather to other sources of particles, was also positively correlated
to pigment spots on face. These results indicate that particle pollution might influence skin aging as well.
JID JOURNAL CLUB ARTICLE: For questions, answers, and open discussion about this article, please go to http://www.nature.com/jid/journalclub
Journal of Investigative Dermatology (2010) 130, 2719–2726; doi:10.1038/jid.2010.204; published online 22 July 2010
INTRODUCTION
According to the United Nations Department of Economic and
Social Affairs Population Division, the proportion of the world’s
human inhabitants who can be classified as aged is increasing
dramatically (Department of Economic and Social Affairs (ESA),
2002). Aging is accompanied by progressive deterioration of
structure and function of all tissues, including visible signs of
both intrinsic and extrinsic skin aging. In this regard, skin aging
is of particular importance, because it has medical, psycho-
logical and social consequences. Among all organs skin is
the most visible, and skin aging directly impacts individual
self-esteem (Gupta and Gilchrest, 2005). This is illustrated best
by the fact that the current market for cosmetic and medical
products devoted to the prevention and treatment of skin aging
has 15 billion US$ worth of sales worldwide (Yarosh, 2008).
Aging results from the combined action of intrinsic and
extrinsic factors. From a preventive point of view, the latter are
of particular interest because they can be modified more easily.
In the case of skin, extrinsic skin aging can be clearly
distinguished from intrinsic skin aging at a clinical, histological,
and molecular level. Clinical symptoms of extrinsic skin aging
include coarse wrinkles, irregular pigment spots, and elastosis
(Yaar et al., 2003). For decades, it has been thought that extrinsic
skin aging results predominantly from exposure of skin to solar
radiation, and the terms extrinsic and photoaging have been
used synonymously. There is, however, growing evidence that
other environmental factors may contribute to skin aging as
well. In particular, exposure of skin to tobacco smoke was found
to be an independent pathogenic factor (Schro
¨der et al., 2006).
Ambient particulate matter (PM) represents another envir-
onmental threat to which millions of humans worldwide are
exposed. Adverse effects of PM on human health are currently
a serious concern and have been shown to include a higher
risk for cancer, pulmonary, and cardiovascular diseases
(Beelen et al., 2008; Castano-Vinyals et al., 2008). The health
effects of ambient PM exposure on human skin in general, and
on skin aging in particular, have not yet been studied.
A major mechanism by which ambient PM exerts its
detrimental effects is through the generation of oxidative
stress (Donaldson et al., 2005), an important contributor to
extrinsic skin aging (Schro
¨der et al., 2006). Particles in the
nanosize range, especially those from traffic sources, are
considered among the most harmful components of ambient
PM. These nanoparticles cause oxidative stress in part
because their physical properties, i.e. small size but large
surface per unit mass, make them highly reactive toward
biological surfaces and structures (Donaldson et al., 2005).
It has been postulated that these particles can serve as
carriers for organic chemicals and metals that are capable of
&2010 The Society for Investigative Dermatology www.jidonline.org 2719
ORIGINAL ARTICLE
Received 24 February 2010; revised 11 May 2010; accepted 7 June 2010;
published online 22 July 2010
1
Institut fu
¨r umweltmedizinische Forschung an der Heinrich-Heine-
Universita
¨tDu
¨sseldorf gGmbH, Du
¨sseldorf, Germany;
2
Institute for Social
and Preventative Medicine at Swiss Tropical Institute Basel, Associated
Institute of the University of Basel, Basel, Switzerland and
3
The Este
´e Lauder
Companies, Melville, New York, USA
Correspondence: Jean Krutmann, Institut fu
¨r umweltmedizinische Forschung
an der Heinrich-Heine-Universita
¨tDu
¨sseldorf gGmbH, Auf’m Hennekamp
50, Du
¨sseldorf 40225, Germany. E-mail: krutmann@rz.uni-duesseldorf.de
4
These authors contributed equally to this work.
Abbreviations: PAH, polycyclic aromatic hydrocarbon; PM, particulate
matter; SCINEXA, score of intrinsic and extrinsic skin aging

localizing in mitochondria and generating reactive oxygen
species (Li et al., 2003). In particular, polycyclic aromatic
hydrocarbons (PAHs) are adsorbed on the surface of
suspended PM in air of urban areas (Menichini, 1992). PAHs
can activate xenobiotic metabolism, which converts PAHs
to quinones. Quinones are redox-cycling chemicals, which
produce reactive oxygen species, and are therefore thought to
be key compounds in PM toxicity (Penning et al., 1999).
In view of the recent evidence that human skin (1) is exposed
to increased levels of ambient PM, which can penetrate skin
either through hair follicles or transepidermally (Lademann
et al., 2004), and (ii) possesses the necessary armamentarium to
respond to PM-bound PAHs (Fritsche et al., 2007; Jux et al.,
2009), we hypothesized that long-term exposure to air pollution
might lead to extrinsic skin aging through oxidative stress
generated by the particles themselves or by associated PAHs.
We tested the first part of this hypothesis in an epidemiological
study using a cohort of Caucasian women aged 70–80 years
(SALIA study, study on the influence of air pollution on lung
function, inflammation, and aging).
RESULTS
Study subjects and study areas
We investigated skin aging signs in 400 women in the SALIA
study cohort in 2008/2009. In Table 1 a description of all relevant
data of these study subjects is given separately for the participants
investigated in the Ruhr area and in the rural area (Borken). And in
Table 2 general information of the studyareacitiesaswellasof
other European cities is given. Table 1 shows that the participants
were almost equally distributed between rural and urban areas.
The women from the Ruhr area were slightly older (arithmetic
mean (AM) ¼74.3 years) than the women from Borken (AM
¼74.0 years). We also asked about known influencing factors of
skin aging. In this regard, about 17% had o10 years of school
education, indicating a worse social status. The mean body mass
index (BMI) was 27.6 in both study regions. Hormone replacement
therapy (HRT) was taken by 44.1% of the women from the Ruhr
area and by 29.1% of the women from Borken. There were more
women who ever smoked in the Ruhr area (23.2%) than in the
rural area (13.2%). More than 50% of the women had skin type I
or II according to Fitzpatrick. Concerning sun exposure behavior,
womenfromtheRuhrareamoreoftenreportedtohavehad
sunburns before the age of 21 years (52.1%) than women from
Borken (32.3%). Also women from the Ruhr area more often used
sunbeds (16.1%) than women from Borken (10.6%). Exposure to
PM was determined by four objective measurements as described
in detail in the Materials and Methods section. Briefly, we
determined the distance of participants’ residence to the next busy
road. Here, nearly 20% of the women lived 100 m or less away
from a busy road. The mean level of traffic-related particle
Table 1. Description of SALIA study subject characteristics
Ruhr area Rural area (Borken)
Sample size N211 189
Data from questionnaire
Age range AM (Min, Max) 74.3 (70.9–79.2) 74.0 (68.6–78.8)
o10 Years of school education %Yes (n) 16.1 (34) 18.0 (34)
BMI AM (95% CI) 27.6 (27.0–28.3) 27.6 (26.9–28.2)
Ever used HRT %Yes (n) 44.1 (93) 29.1 (55)
Ever smoked %Yes (n) 23.2 (49) 13.2 (25)
Light skin type (Fitzpatrick skin type I or II) %Yes (n) 55.5 (117) 54.0 (102)
At least one sunburn before the age of 21 %Yes (n) 52.1 (110) 32.3 (61)
At least one sunbed use %Yes (n) 16.1 (34) 10.6 (20)
Data from GIS-based models (2000/2003)
Distance p100 m from a busy road
(410,000 cars per day) %Yes (n) 21.8 (46) 15.3 (29)
Emission inventory 2000
Particles from traffic (kg a
1
km
2
) AM (IQR) 899.9 (736.8) 225.7 (215.7)
Soot (10
5
m
1
) AM (IQR) 2.2 (0.3) 1.7 (0.1)
Measurement at single stations from 2003–2007
PM
10
background concentration in ambient air (mgm
3
) AM (IQR) 27.9 (3.4) 25.2 (0)
Abbreviations: AM (95% CI), arithmetic mean (95% confidence interval); BMI, body mass index; HRT, hormone replacement therapy; IQR, interquartile
range; Max, maximum; Min, minimum; %Yes (n), percentage and number of study subjects with respective characteristic.
2720 Journal of Investigative Dermatology (2010), Volume 130
A Vierko
¨tter et al.
Airborne Particles and Skin Aging

emission was 899.9 kg a
1
km
2
intheRuhrareaand
225.7 kg a
1
km
2
in Borken. The mean absorbance as a measure
of soot concentration in fine particles was around 2.0 10
5
per
m and the 5-year mean of the background PM with an
aerodynamic diameter of 10 mm(PM
10
) concentration was
approximately 26.5 mgm
3
.IncomparisontootherEuropean
cities, the cities of the Ruhr area are very highly polluted (Table 2).
Clinical signs of skin aging
Skin aging was assessed by means of the SCINEXA (score of
intrinsic and extrinsic skin aging). This score includes skin aging
signs that are characteristic for extrinsic and intrinsic skin aging,
and we previously showed that this score is suitable to deter-
mine and differentiate between extrinsic and intrinsic skin aging
(Figure 2; Vierko
¨tter et al., 2009). The occurrence of clinical
signs of skin aging in the SALIA study cohort is shown in
Table 3. The distribution of the score values of pigment
spots and seborrheic keratosis was log-normally distributed
and therefore the geometric mean was given. The geometric
mean of the score values of pigment spots was about 3.0 on
forehead up to more than 20.0 on forearm. The mean score
value of seborrheic keratosis on the upper part of the body
was 3.2. The distribution of the wrinkle grades, the grades of
telangiectasia as well as the laxity grades were normally
distributed, and in these cases the AM was given. The AM for
all wrinkles on different locations on the face was around 3.0.
The mean grade of telangiectasia was nearly 2.0 and the
mean laxity grade of the face was nearly 4.0. Solar elastosis
on the cheek was present in approximately 37% of women.
Association between exposure to airborne particles and
occurrence of skin aging signs
A significant association was found between traffic-related
airborne particles and signs of extrinsic skin aging, i.e.,
pigment spots on face and nasolabial fold. All adjusted mean
ratios and odds ratios (OR) are presented in Table 4.
There were 22% more spots on forehead and 20% more
spots on cheeks per increase of one interquartile range (IQR)
of the PM
2.5
absorbance ( ¼soot). For particles from traffic,
Table 2. Data about population density, latitude, temperature, and particle pollution by traffic of all cities
of the SALIA study area and further cities for comparison
City Country
Population density
per km
2
at the end
of year 2008 Latitude
Mean of daily
lowest temperature
in the year 2009
Mean of daily highest
temperature in the
year 2009
Soot (10
5
m
1
)
in the year 2000
Cities of SALIA study area
Borken Germany 260.9 51.9 7.1 15.9 1.66
Duisburg Germany 2122.2 51.4 9.3 17.2 2.12
Essen Germany 2756.6 51.5 7.2 14.2 2.43
Gelsenkirchen Germany 2499.2 51.6 — — 2.20
Dortmund Germany 2084.2 51.5 7.5 14.3 2.00
Other European cities for comparison
1
Munich Germany 4275.0 48.0 5.7 14.9 1.84
— Netherlands 397.2 50–54 5.6 13.5 1.64
Stockholm Sweden 4252.0 59.4 2.5 9.9 1.28
1
Adapted from Brauer et al. (2003).
Table 3. Description of skin aging signs evaluated
with SCINEXA
Extrinsic skin aging signs
Pigment spots
On forehead GM (95% CI) 3.3 (2.7–4.1)
On cheeks GM (95% CI) 8.1 (7.2–9.0)
On upper side of the forearm GM (95% CI) 22.7 (20.1–25.6)
On back of the hand GM (95% CI) 9.4 (8.3–10.8)
Coarse wrinkles
On forehead AM (95% CI) 3.2 (3.1–3.3)
In the crow’s feet area AM (95% CI) 2.8 (2.8–2.9)
Under the eyes AM (95% CI) 3.6 (3.5–3.6)
On upper lip AM (95% CI) 3.4 (3.3–3.5)
Nasolabial fold AM (95% CI) 3.7 (3.7–3.8)
Solar elastosis %Yes (n) 36.8 (147)
Telangiectasia AM (95% CI) 1.9 (1.8–2.1)
Intrinsic skin aging signs
Laxity AM (95% CI) 3.6 (3.5–3.7)
Seborrheic keratosis
1
GM (95% CI) 3.2 (2.8–3.7)
Abbreviations: AM (95% CI), arithmetic mean (95% confidence interval); GM
(95% CI), geometric mean (95% confidence interval); %Yes (n), percentage
and number of study subjects with respective skin aging symptom.
1
Seborrheic keratosis was evaluated in 368 study subjects.
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we found 16% more spots on forehead and 17% more spots
on cheeks per increase of one IQR. There was also a slight
increase of spots on cheeks per one IQR of background PM
10
concentrations of 8%. Furthermore, soot, particles from traffic,
and to a lesser extent the PM
10
background concentrations
were associated with a slightly more pronounced nasolabial
fold. Distance of 100 m or less from a busy road was also
associated with 35% more pigment spots on forehead and
15% more pigment spots on cheeks. However, it was not
significant, because the number of study subjects living close
to a busy road was too small.
The statistical models used accounted for other factors
known to influence skin aging. In the following the main
results for the influence of these factors are presented as
arithmetic or geometric mean ratio (AMR/GMR) and its 95%
confidence interval (95% CI). It was found that HRT was
associated with fewer wrinkles under the eyes (AMR: 0.93;
95% CI: 0.88–0.98) and less pronounced nasolabial folds
(AMR: 0.97; 95% CI: 0.93–1.00). Women with a skin type I or
II had significantly less spots on forehead (GMR: 0.72; 95%
CI: 0.56–0.92) and on cheeks (GMR: 0.69; 95% CI:
0.55–0.86); fewer wrinkles under the eyes (AMR: 0.95;
95%CI: 0.89–1.00) and on upper lips (AMR: 0.95; 95% CI:
0.89–1.00); and less solar elastosis (OR: 0.62; 95% CI:
0.41–0.95), but more pronounced telangiectasia (AMR: 1.12;
95% CI: 0.98–1.27) in comparison to skin type III or IV.
Sunburns in childhood and sunbed use were associated with
more spots, e.g., 40–50% more spots on forehead. Smoking
(current or prior) was associated with more wrinkles on upper
lips (AMR: 1.13; 95% CI: 1.07–1.20), increased solar elastosis
(OR: 2.11; 95% CI: 1.24–3.58), more pronounced telangiect-
asia (AMR: 1.26; 95% CI: 1.07–1.45), and laxity of the face
(AMR: 1.06; 95% CI: 1.00–1.11). Social status had no further
influence on skin aging when all influencing factors were
taken into account in one model.
DISCUSSION
This study provides epidemiological evidence that traffic-
related PM represents an important environmental factor that
contributes to extrinsic skin aging in humans. This conclusion
is based on the present observation that not only (i) an
increase in soot, but also (ii) an increase in particles from
traffic, and (iii) higher PM
10
background concentrations were
associated with more pigment spots on the face and more
pronounced nasolabial folds. The distance of residence to the
closest busy road was also associated with more pigment
spots, but this effect did not reach significance.
For determination of traffic-related PM, we applied the
most up to date state-of-the-art method according to Brauer
et al. (2003). Here, the exact geographic coordinates of each
study participants’ address were determined by geographic
information system, and the respective PM concentrations
Table 4. Association between different skin aging signs and exposure to airborne particles
Distance p100 m from
a busy road
Soot (per increase
of 0.5 10
5
m
1
)
Traffic-associated particles
(per 475 kg a
1
km
2
)PM
10
(per 5 lgm
3
)
Skin aging sign MR/OR 95% CI PMR/OR 95% CI PMR/OR 95% CI PMR/OR 95% CI P
Pigment spots
On forehead
1
1.35 0.98–1.86 0.068 1.22 1.03–1.45 0.022 1.16 1.06–1.27 0.002 1.07 0.99–1.15 0.078
On cheeks
1
1.15 0.86–1.54 0.362 1.20 1.03–1.40 0.019 1.17 1.08–1.27 0.000 1.08 1.01–1.15 0.027
On forearm
1
0.95 0.70–1.30 0.756 1.08 0.92–1.27 0.334 1.05 0.97–1.15 0.243 1.02 0.95–1.09 0.634
On back of hands
1
1.13 0.80–1.58 0.484 1.12 0.94–1.34 0.200 1.09 0.99–1.20 0.072 1.02 0.95–1.10 0.529
Wrinkles
On forehead
2
0.97 0.88–1.06 0.504 0.96 0.91–1.01 0.078 0.99 0.96–1.02 0.390 0.99 0.97–1.01 0.153
Crow’s feet
2
0.99 0.92–1.06 0.731 0.98 0.94–1.01 0.208 0.98 0.96–1.00 0.114 0.99 0.97–1.00 0.077
Under the eyes
2
1.00 0.94–1.07 0.830 0.99 0.96–1.03 0.662 0.99 0.97–1.01 0.287 0.97 0.97–1.00 0.054
On upper lip
2
1.01 0.94–1.08 0.736 1.03 0.99–1.06 0.168 1.01 0.99–1.03 0.333 1.01 0.99–1.02 0.320
Nasolabial fold
2
1.04 1.00–1.08 0.056 1.04 1.01–1.06 0.001 1.03 1.01–1.04 0.000 1.01 1.01–1.02 0.020
Further skin aging symptoms
Solar elastosis
1
0.81 0.47–1.40 0.451 1.15 0.87–1.53 0.327 1.02 0.87–1.18 0.849 1.32 0.73–2.40 0.363
Telangiectasia
1
0.83 0.64–1.01 0.067 0.91 0.81–1.01 0.069 0.95 0.90–1.01 0.082 0.94 0.73–1.15 0.572
Laxity
1
1.03 0.98–1.09 0.270 1.00 0.97–1.03 0.913 1.00 0.99–1.02 0.744 1.00 0.94–1.06 0.955
Seborrheic keratosis
1
1.17 0.68–1.65 0.504 1.13 0.87–1.39 0.325 1.01 0.87–1.15 0.898 1.18 0.63–1.73 0.523
Abbreviations: BMI, body mass index; 95% CI, 95% confidence interval; HRT, hormone replacement therapy; MR, mean ratio; OR, odds ratio.
1
Adjusted for age, skin type, sunburns, sunbed use, and smoking,
2
Adjusted for age, BMI, HRT, skin type, sunburns, sunbed use, and smoking.
Significant associations with a P-value o0.05 are marked in bold.
2722 Journal of Investigative Dermatology (2010), Volume 130
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Airborne Particles and Skin Aging

were assigned for this address using measurements and land
use regression. Furthermore, as the SALIA study participants
were (i) mainly housewives, (ii) almost all remained at the
same address for the last 30 years, and (iii) the pattern of
pollution of the different investigated cities remained the
same over the last decades, exposure of residence reflects
long-term exposure. Even in the hypothetical case that we
have studied only a random subgroup of all women willing to
participate, it is very unlikely that we have introduced bias
because (i) participation did not depend on air pollution
(Ranft et al., 2009) and (ii) participation could not depend on
skin aging signs as this aim of the study was not known to
participants beforehand.
The association between PM and skin aging symptoms
was strongest for pigment spot formation. The pathogenesis of
pigment spots is not very well understood. It has been
suggested that solar radiation is an important pathogenetic
factor and skin aging-associated pigment spots are therefore
also called lentigines solaris. In support of this hypothesis is
the finding that pigment spots are mainly present in
chronically sun-exposed areas of the skin (Garbe et al.,
1994), and that after chronic exposure to UVB radiation a
delayed induction of pigmented spots has been observed in
the skin of mice (Kadono et al., 2001). Here, we confirm
that UV exposure is significantly associated with a more
pronounced occurrence of pigment spots. UV exposure,
however, does not explain why pigment spots are the leading
skin aging symptom in Asians (Tschachler and Morizot,
2006), who, in contrast to Caucasians, avoid sun exposure
and thus should have less rather than more pigment spots. In
this regard, it is of interest that a number of recent
mechanistic studies indicate that skin pigmentation may
occur in the absence of UV radiation. For example, treatment
of melanocytes with selected oligonucleotides was able to
induce tyrosinase activity and subsequent melanin synthesis
in the absence of UV exposure (Eller and Gilchrest, 2000). Of
particular interest to this study, aryl hydrocarbon receptor
ligands, such as dioxin or PAHs, have recently been shown
to induce melanocyte proliferation and thereby skin tanning
in mice (Krutmann et al., 2008). PAHs are frequently bound
to the surface of combustion-derived PM and this mechanism
may therefore provide a scientific rationale for the association
between pigment spots and exposure to traffic-related PM
that we have observed. Accordingly, the strongest effect was
seen for soot, which carries a high concentration of surface-
bound PAHs.
The ability of particles to penetrate into skin is a matter of
debate. Different skin penetration studies have used a variety
of nanoparticle types as well as different experimental models
(Tinkle et al., 2003; Toll et al., 2004; Baroli et al., 2007;
Nohynek et al., 2007; Rouse et al., 2007). It is therefore
not surprising that conflicting results have been obtained. To
the best of our knowledge, however, no skin penetration
studies have been carried out with ambient PM, and more
specifically with the fraction of combustion-derived nano-
particles in the PM mixture. In general, there is no doubt that
particles can penetrate into the hair follicles depending on
their size (Lademann et al., 2004). Through this pathway
ambient particles may be able to reach viable cells in deeper
skin layers such as melanocytes and thus serve as Trojan
horses by releasing surface-bound PAHs and/or directly
affecting the function of skin cells. Further mechanistic
studies are required to determine the relative contribution
of such particles themselves versus particle-bound substances
to extrinsic skin aging.
In this study, in addition to traffic-related PM, we studied a
number of other factors thought to influence skin aging. All
these influencing factors were analyzed together with the
influence of air pollution in a multivariate statistical model.
Here, the use of HRT was associated with fewer wrinkles, as
previously described (Dunn et al., 1997). We also observed
that a light skin type was associated with less pigment spots,
less coarse wrinkles and elastosis, but more pronounced
telangiectasia. This is again consistent with previous reports
that these particular skin types show different characteristics
of extrinsic skin aging than darker skin types (Lober and
Fenske, 1990). In this study, reported sunburns in childhood
and sunbed use were associated with more pigment spots, but
not with more wrinkles, although both symptoms are known
to result from chronic UV exposure. It is therefore possible
that a more detailed UV exposure history is required to detect
the effect of UV exposure on wrinkles. However, it is unlikely
that the effects of air pollution on skin aging are confounded
by sun exposure, as all investigated cities lay next to
each other and the general climate and UV radiation flux is
essentially identical in these cities. Moreover, the effect
estimates for air pollution were not changed after including
assessments characterizing sun exposure in the models.
A smoking history was associated with more wrinkles, more
elastosis, and more pronounced telangiectasia, and these
observations are in agreement with the existing literature
(Kennedy et al., 2003; Schro
¨der et al., 2006). Taken
together these results indicate that the design and protocol
chosen for this study are suitable to test influencing factors
on skin aging with perhaps minor limitations for the UV
exposure effects.
To our knowledge, this is the first study to describe an
association between airborne particles and extrinsic skin
aging. Further studies should be conducted to confirm these
results not only in Caucasians, but also for other ethnic
groups such as Asian populations, where extrinsic skin
aging is predominantly characterized by the development
of pigment spots.
MATERIALS AND METHODS
Study design and study participants
The SALIA study was initiated as a cross-sectional study between
1985 and 1994 as part of the Environmental Health Survey, which
was an element of the Clean Air Plan introduced by the Government
of North-Rhine Westphalia in Germany. A detailed description of the
SALIA study has been previously provided by Schikowski et al.
(2005). The study areas were chosen from the Ruhr district in
Germany and two rural counties north of the Ruhr district. They
represent a range of exposures to airborne PM from traffic and steel
and coal industries. In Table 2 the investigated cities are presented
with data about population, geographical position, climate, and air
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A Vierko
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Airborne Particles and Skin Aging

pollution conditions. For comparison reasons we provide these data
for other European city regions that were not investigated in the
SALIA study. In comparison with these European cities, the cities of
the Ruhr area are the areas most highly polluted with soot. In the
baseline investigation, all women aged 54–55 living in predefined
areas were asked to participate. The study was restricted to women
because the aim was to investigate the effects of exposure to airborne
PM, which would have been difficult in men of this region, who had
predominantly worked as miners with high PM exposure at their
work places. In Figure 1, a flow chart presents the SALIA study
cohort from baseline to follow-up in 2008/2009. In 2008 and 2009,
we conducted a follow-up of the SALIA study, in which we
investigated 402 women randomly selected out of all surviving
women, which gives their agreement for further investigations. The
women were now 70–80 years old. Of these, 400 women
participated in the skin examination. The Medical Ethics Committee
of the Ruhr University Bochum, Germany approved the follow-up
study. The Declaration of Helsinki Principles was followed and all
study participants were informed in detail by written form and have
given written consent.
Assessment of skin aging symptoms and its influencing factors
Skin aging symptoms, which are characteristic for intrinsic and
extrinsic skin aging, were evaluated on the basis of a validated skin
aging score, called SCINEXA (Vierko
¨tter et al., 2009), with slight
modifications to the original version. In Figure 2 the modified
SCINEXA for the SALIA study is shown. Extrinsic skin aging was
represented by pigment spots (lentigines), coarse wrinkles, elastosis,
and telangiectasia, whereas laxity and seborrheic keratosis indicated
intrinsic skin aging.
Pigment spots and seborrheic keratosis were given a value of 0 if
there were no spots or seborrheic keratosis, 5 indicated 1–10 spots or
seborrheic keratosis, 30 represented 11–50 spots or seborrheic
keratosis, and 75 indicated more than 50 spots or seborrheic
keratosis. Coarse wrinkles, telangiectasia, and laxity were scored
from 0 (not present) to 5 (very severely present) according to
photoreference scales (Tschachler and Morizot, 2006). Solar
elastosis was evaluated as Yes (present) or No (not present). The
study subjects were asked not to use any skin care products or
cosmetics on the day of examination.
Other variables, which might influence skin aging, were
determined by standardized interviews. These contained questions
about UV exposure (e.g., sunburns in childhood and sunbed use),
skin type according to Fitzpatrick (1988), social status (years of
school education), BMI, smoking history, and intake of HRT.
Assessment of exposure to airborne PM
Different approaches for the assessment of airborne PM were used.
First, based on the subject’s residential address and on available
traffic counts for the year 2000, distance of the residential address to
the next busy road with more than 10,000 cars per day was
determined using geographic information system. If a subject lived
100 m or less to a busy road, they were considered to have high
exposure to traffic-related particles. Second, we assessed the
exposure to motor vehicle exhaust by using emission inventories
from the year 2000 provided by the State Environment Agency of
North Rhine Westphalia (LANUV). These inventories are given in a
1 km grid and estimate particle emission per square kilometer. Third,
blackness of fine particle filters was used to estimate soot
concentration from traffic-related sources and was then assigned to
each individual’s address by land-use regression models (Hochadel
et al., 2006). This exposure assessment was identical to those
in the ‘‘Traffic-Related Air Pollution and Childhood Asthma’’ study
(Brauer et al., 2003; Cyrys et al., 2003). Here, PM
2.5
absorbance
was determined as a marker for soot according to ISO 9835.
Fourth, measurements of total suspended particles or PM with an
aerodynamic diameter of 10 mm (PM
10
) were provided by monitoring
stations distributed over the Ruhr district in an 8 km grid, which have
been maintained by the State Environment Agency for more than
25 years. Total suspended particle measurements were converted
into PM
10
estimates using a factor of 0.71 (Gehring et al., 2006).
These measurements mainly reflect broadscale background variations
1985– 1994: Baseline investigation
4,874 Participants
2006: Questionnaire follow-up
2,116 Responded after three distributions
1,639 Agreed to participate in further examinations
399 Died by 2003 (mortality follow-up)
196 Died by 2006
252 Addresses not available
2008/2009: Follow-up examination
402 Randomly selected women, 400 of these
women participated in skin aging evaluation
153 Died by 2008 (mortality follow-up II)
75 Addresses not available
Figure 1.Flowchart showing the SALIA cohort from baseline until follow-up
in 2008/2009.
Skin aging signs: Localization: Scoring:
Extrinsic signs
Pigment spots1
On forehead 0 (0), 1–10 (5), 11–50 (30), >50 (75)
On cheeks 0 (0), 1–10 (5), 11–50 (30), >50 (75)
On upper side of the forearm 0 (0), 1–10 (5), 11–50 (30), >50 (75)
On back of the hand 0 (0), 1–10 (5), 11–50 (30), >50 (75)
Coarse wrinkles2
On forehead Grade 0 to 5
Wrinkles in crow’s feet area Grade 0 to 5
Under the eyes Grade 0 to 5
On upper lip Grade 0 to 5
Nasolabial fold Grade 0 to 5
Solar elastosis On cheeks Yes/no
Telangiectasia On cheeks Grade 0 to 5
Intrinsic signs
Laxity2Ovality of the face Grade 0 to 5
Seborrheic keratosis1On upper part of the body 0 (0), 1–10 (5), 11–50 (30), >50 (75)
1Scoring of spots and seborrheic keratosis with counts in paratheses, 2Grading with
photoreference scales: 0 = si
g
n not present, up to 5 = si
g
n very severely present.
Figure 2.Applied skin aging score on the basis of SCINEXA (score of
intrinsic and extrinsic skin aging; Vierko
¨tter et al., 2009).
2724 Journal of Investigative Dermatology (2010), Volume 130
A Vierko
¨tter et al.
Airborne Particles and Skin Aging

in air quality. The individual exposure to this background air
pollution was estimated by the PM
10
concentrations of the
monitoring station next to the participant’s residential address
averaged over the years 2003–2007.
Therefore, the total ambient PM was classified as (i) motor
vehicle exhaust, which was assessed indirectly by the subject’s
distance from a busy road and appropriate emission inventories;
(ii) soot, as estimated by blackness of PM
2.5
filters and; (iii) total
suspended particles (PM
10
), a value provided by long-term monitor-
ing stations.
Statistical analysis
A descriptive analysis summarizing evaluated skin aging indicators,
known influencing factors of skin aging, and air pollution data was
performed.
To analyze the effect of airborne particles on skin aging
symptoms adjusted for further factors influencing skin aging, we
used linear and logistic regression models. The adjusted regression
coefficients were transformed to GMR for log-normally distributed
symptoms with 95% CI, for normally distributed symptoms to
adjusted AMR with 95% CI (Schikowski et al., 2005; Vierko
¨tter et al.,
2009), and for categorical variables to adjusted OR with 95% CI. The
formulas for GMR (equation 1), AMR (equation 2), and OR (equation 3)
are the following:
GMRi¼expðbiÞð1Þ
AMRi¼bi
Mtotal
þ1ð2Þ
ORi¼expðbiÞð3Þ
where b
i
represents regression coefficient and M
total
the total mean.
The GMR and AMR are relative values for continuous variables
and are comparable in their meaning to the OR. They are more
easily interpreted than a simple regression coefficient. They describe
the relative change in skin aging signs when exposure is increased
by one unit. As exposure units, we used the IQR observed in the
population. An IQR means the difference of the 75th quartile and
the 25th quartile of the distribution of the particle pollution variables
(soot: 0.5 10
5
m
1
; traffic emissions: 475 kg a
1
km
2
and PM
10
:
5mgm
3
). Like the OR, a GMR or AMR of 1 means that there is no
association, a GMR or AMR o1 means a negative association, and a
GMR or AMR 41 means a positive association.
In all models, data were adjusted for age (by year), Fitzpatrick
skin type (light vs. dark skin type), number of sunburns before the age
of 21, sunbed use (yes or no), and smoking history. BMI (kg m
2
) and
HRT were additionally included in the model for coarse wrinkles.
The mutually adjusted association was defined as significant if the
P-value was o0.05. The statistical computing was carried out using
SAS 9.2 (SAS/STAT Software; SAS Institute, Cary, NC, 2002–2003).
CONFLICT OF INTEREST
The authors state no conflict of interest.
ACKNOWLEDGMENTS
The SALIA follow-up study was funded by the German Statutory Accident
Insurance (DGUV). The investigation of the skin was funded by SFB 728,
BMU (TP C1), and a grant from the Este
´e Lauder. Road maps with emissions
from traffic and PM values from measurement stations were maintained from
the State Environment Agency of North Rhine Westphalia (LANUV). We also
thank all study participants.
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