Original Article

Relationship between Ocular Surface Alterations and
Concentrations of Aerial Particulate Matter

María A Gutiérrez1,2, PhD, FIACLE; Daniela Giuliani2, BS; Atilio A Porta2, PhD; Darío Andrinolo1, PhD

1University Extension Environmental Programme (PAEU), Faculty of Exact Sciences, National University of La Plata, Buenos
Aires, Argentina

2Center for Environmental Research (CIM), UNLP - CONICET, Buenos Aires, Argentina

ORCID:
María A. Gutiérrez: https://orcid.org/0000-0002-3491-6151

Abstract

Purpose: To evaluate ocular surface alterations in two populations at different exposure levels to particulate
matter (PM) in their living and work environments.
Methods: A cross-sectional study was conducted, including 78 volunteers from Argentina who lived and
worked under different pollution levels in an urban (U; n = 44) or industrial zone (I; n = 34). Mean exposure
level to PM was evaluated. Responses to the Ocular Symptom Disease Index and McMonnies questionnaire
were obtained from all subjects. Subsequently, an assessment through the Schirmer I test (ST), slit lamp
microscopy, vital staining, and tear breakup time was conducted. Statistical analyses with Chi-square and
Bartlett’s tests, as well as Student’s t-tests and principal component analysis (PCA), were performed.
Results: Particles of size < 2.5 μm (PM2.5) level was significantly higher in the I group than the U group (P =
0.04). Ocular surface parameters including bulbar redness, eyelid redness, and the degree of vital staining
with fluorescein (SF) and lissamine green (SLG) exhibited difference between the groups. With regards to
the tear film, statistically significant differences in the ST value and meibomian gland dysfunction between
the groups were detected (P = 0.003 and P = 0.02, respectively). Conjunctival SF and SLG, and ST values
were identified as factors which could distinguish groups exposed to different PM levels.
Conclusion: Subjects exposed to higher levels of PM in the outdoor air presented greater ocular surface
alterations. Thus, ST, SF, and SLG values could be used as convenient indicators of adverse health effects
due to exposure to air pollution.

Keywords: Environmental; Ocular Surface; Particulate Matter; Schirmer I Test; Vital Staining

J Ophthalmic Vis Res 2019; 14 (4): 419–427

Correspondence to:

María A. Gutiérrez, PhD, FIACLE. University Extension
Environmental Programme (PAEU), Faculty of Exact
Sciences, National University of La Plata, 47 and 115 St.,
Buenos Aires 1900, Argentina.
E-mail: mgutierrez@biol.unlp.edu.ar

Received: 08-11-2018 Accepted: 11-06-2019

Access this article online

Website:
https://knepublishing.com/index.php/JOVR

DOI:
10.18502/jovr.v14i4.5441

INTRODUCTION

The ocular surface comprises various structures in
contact with the environment, namely the palpebral
and bulbar conjunctival epithelium, corneoscleral
limbus, corneal epithelium, and tear film, which pro-
vide anatomical, physiological, and immunological

This is an open access journal, and articles are distributed under the terms of
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allows others to remix, tweak, and build upon the work non-commercially, as
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How to cite this article: Gutiérrez MA, Giuliani D, Porta AA, Andrinolo
D. Ocular Surface Changes due to Air Particles. J Ophthalmic Vis Res
2019;14:419–427.

© 2019 JOURNAL OF OPHTHALMIC AND VISION RESEARCH | PUBLISHED BY KNOWLEDGE E 419

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

protection. The adnexal structures, including the
anterior lamellae of the eyelids, eyelashes, meibo-
mian glands, and lacrimal system, are essential for
appropriate protection and function of the ocular
surface.[1] The ocular surface functions in generat-
ing good visual quality, nourishing and lubricating
tissues, and protecting the eye against cellular
debris and foreign particles.[2] It can be affected
by trauma, infections, or environmental factors,
which may compromise the structural integrity of
its components. This can lead to various forms
of corneal and conjunctival dysfunction such as
increasing order of severity, pain and itching,[3]
mild corneal abrasion to severe loss of stem cells,
decreased vision,[4] and blindness.[5]

Ocular surface disorders occur in patients with
various conditions including limbal stem-cell defi-
ciency and ocular surface disease (OSD) due to
systemic diseases.[1] Dry eye is an ocular surface
disorder which has a prevalence rate of 5 to 50%
worldwide. Dry eye is considered a multifactorial
OSD characterized by a loss of homeostasis of
the tear film, ocular symptoms of instability and
hyperosmolarity of the tear film, and inflammation.
Ocular surface damage and sensorineural anoma-
lies may have etiological roles in this disease.[6]
Clinically, dry eye is characterized by a loss of
tear volume, rapid breakup of the tear film, and
increased evaporation of tears from the ocular
surface.[7]

Recent studies have demonstrated subclinical
alterations of the ocular surface that can be
attributed to air pollution. These include changes
in the tear break-up time (TBUT) and Schirmer I test
(ST) value, [8–12] the incidence of palpebral affec-
tations such as blepharitis,[13] and effects on the
ocular mucosa that indicate a significant positive
association between exposure to the air pollutant
nitrogen dioxide and goblet cell hyperplasia in the
human conjunctiva.[14] Additionally, reports have
indicated that the presence of high concentrations
of air pollutants such as nitric oxide, nitrogen diox-
ide, or sulfur dioxide makes the tear film increas-
ingly acidic. Collectively, these findings suggest
that symptoms of ocular discomfort and alterations
in the TBUT could be used as bioindicators of
the adverse health effects of air pollution due to
vehicular traffic.[10]

The mechanisms by which air pollutants interact
with the tear film, cornea, and conjunctiva remain
unclear, although increases in MUC5AC mRNA

level upon chronic exposure to particulate matter
(PM) and nitrogen dioxide have been implicated.[12]
Further studies focused on the compensatory
mechanisms of the ocular surface to changes
induced by chronic exposure to air pollution and
patient susceptibility are required to enable early
treatment that prevents chronic disorders and pro-
motes eye health.

This study aimed to evaluate ocular surface
alterations in two populations at different exposure
levels to PM in their living and work environments.

METHODS

Study Population

A total of 78 volunteers between 18 and 62 years
old, who lived and worked in La Plata (n = 44)
and Ensenada (n = 34), two regions in Argentina
with different pollution levels, were included in this
study. La Plata is the capital of the province of
Buenos Aires, which has a high vehicle-to-person
ratio and was considered the urban zone (U) in
this study. Ensenada is a city with high levels of
air pollution, mainly due to industrial activity, and
was considered the industrial zone (I) [Figure 1].
Both study areas have similar meteorology due
to geographical proximity (6 km), with North and
North-East winds at an average speed of 15.9
km/h, a humidity of 68.9%, and a temperature of
18.2ºC. The sex distribution of both populations
was 45% female and 55% male, and the ages of
the subjects from Ensenada and La Plata (mean ±
SD) were 34 ± 13 and 29 ± 6 years, respectively.
An affidavit of residency and working place was
obtained from all volunteers to ensure a minimum
of 14 h daily exposure to the study area. Tests
were performed simultaneously in both groups in
the laboratory of the University Extension Environ-
mental Programme (PAEU, Programa Ambiental de
Extensión Universitaria) at the Faculty of Exact Sci-
ences (Facultad de Ciencias Exactas), the National
University of La Plata (UNLP, Universidad Nacional
de La Plata).

The study was conducted according to the
Declaration of Helsinki of 1975, as revised in
2000. The research protocol was approved by the
Central Advisory Committee on Bioethics (Comité
Consultivo Central de Bioética) of the UNLP, and
informed consent was obtained from all subjects
before they were registered in the study.

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Figure 1. Map of the cities of La Plata, Berisso, and Ensenada, depicting both study areas –industrial zone (dark gray box) and
urban zone (light gray box) – and monitoring points (black circles), obtained from Google My Maps.

The exclusion criteria were as follows: preg-
nancy, usage of oral/topical antibiotics or pre-
scribed eye medications, or usage of contact
lenses. In all participants, medical treatment with
drugs of any kind was withheld during the study
period.

Previous reports have indicated an expected
value of maximal percentage variation expressed
as coefficient of variation (CV%) of approximately
60%.[9, 10] Based on the results obtained through
statistical calculations corresponding to this disper-
sion value,[8] a total of 30 volunteers per treatment
group (zone) were considered adequate to allow
statistical conclusions with 80% power (beta, type
II error) and a significance level of 0.01 (alpha, type
I error).

Assessment of Exposure

PM was utilized as an indicator of air pollution
exposure, and samples were collected using a low-
volume sampler (PM-2.5 MiniVol𝑇𝑀 TAS; AirMetrics
Co., Springfield, Oregon, USA). This draws air at
a rate of 5 L/min through an impactor, separating
it according to particle size, and a filter, thereby
capturing PM.[15] A polytetrafluoroethylene (PTFE)
membrane with a 46.2-mm diameter and 2-μm
pore-size was used as the filter. Particles of size
< 2.5 μm (PM2.5) and aerodynamic diameter ≤ 10
μm (PM10) were both detected. Gravimetric analysis

was used to determine the particle content of
each sample. Data of PM level in both working
areas were obtained through discrete monitor-
ing.

Analysis of the Ocular Surface

All analyses were performed in the morning by
the same examiner, at the same setting, under the
same conditions of temperature and humidity.

Questionnaires

The ocular surface disease index (OSDI) and
McMonnies (MM) questionnaires in validated
Spanish-translated form[16–18] were given to all
subjects before examination and clinical tests.

Ocular Surface Structure

The evaluation of the ocular surface was performed
using slit-lamp biomicroscopy with an adapted
imaging system (Canon EOS Rebel T3i digital
single-lens reflex camera) 30 min after the ST.
Aspects of the eyelids, cornea, conjunctiva, and
tear film were evaluated and entered into the
patient’s medical record, according to the Cornea
and Contact Lens Research Unit (CCLRU) guide-
lines and Efron grading scales.[19, 20]

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Evaluation of the Tear Film

Schirmer I test: Study participants were subjected
to the ST (Hub Pharmaceuticals, CA, USA) without
the use of topical anesthesia. An obtained value ≤
10 mm was considered abnormal.[21]

Tear-meniscus Height: A slit lamp was used to
establish the central height of the tear meniscus
in relation to the free edge of the lower eyelid. A
tear meniscus height < 0.35 mm was considered to
indicate low tear volume and suspected dry eye.[22]

Tear Break-Up Time: TBUT was measured with
fluorescein (SF) strips (Hub Pharmaceuticals, CA,
USA) moistened with saline solution, which were
gently applied to the inferior fornix. A value ≤ 10
sec was considered abnormal.[23]

Meibomian Gland Dysfunction: Meibomian gland
dysfunction (MGD) was observed using digital slit-
lamp biomicroscopy[24] and graded using the Efron
scale.[20]

Lipid Patterns: Interferometric images can be
acquired using specular reflection techniques. In
our study, such images were acquired using a high-
intensity slit lamp at a magnification of 25×.[25] The
observed patterns were classified according to the
system of Guillon.[26]

Corneal and Conjunctival Vital Staining

In this study, vital staining with SF and lissamine
green (SLG) was conducted using dye-impregnated
strips (Hub Pharmaceuticals, CA, USA) moistened
with saline solution that were gently applied to the
inferior fornix. The respective pattern of corneal
and conjunctival staining was graded,[19, 27] and
the presence of the lid parallel conjunctival folds
(LIPCOF) was taken into account.[28]

Statistical Analysis

The data acquired were tested for normality and
heterogeneity of variance using Chi-Square anal-
ysis and Bartlett’s test, respectively. Student’s t-
tests were performed for normally distributed data
to determine statistically significant differences
between two means. A P-value < 0.05 was con-
sidered to indicate statistical significance. Principal
component analysis (PCA) was used for dimension
reduction of the data; consequently, the number
of variables was decreased to a few principal

components (PCs) that accounted for most of the
variation. All calculations were performed using
Infostat software (Universidad Nacional de Cór-
doba, Córdoba, Argentina).

RESULTS

Exposure to Air Pollution

To confirm the previously reported differences in
air quality of the two selected areas,[29, 30] PM levels
at both locations were monitored throughout the
study period with the help of local volunteers. Mean
values obtained through these discrete measure-
ments throughout the study period are shown in
Table 1.

The level of PM2.5was significantly higher in zone
I than in zone U (P < 0.024, Student’s t-test),
which confirmed the presence of differences in air
pollution between the two studied areas.

Moreover, an increase was also detected in
the PM10 level in zone I in comparison with zone
U. However, the difference was not statistically
significant.

Analysis of the Ocular Outer Surface

Results obtained for the different variables and
accompanying parametric comparisons (Student’s
t-test) are shown in Table 2.

With regards to the results shown in Table 2,
higher levels of bulbar redness (BR) and lid redness
(LR), increased SF and SLG staining values, and
an increased MGD grade were noted in the I
group compared to the U group. This suggested
that the former population were more susceptible
to developing higher levels of epithelial damage
and MGD than the latter population. In addition,
statistically lower mean ST values were obtained
in the I group, which indicated abnormalities in the
tear film.

No significant differences were present between
the groups with respect to the OSDI and MM
questionnaires.

Consequently, six variables that showed signif-
icant differences between the two groups were
included in the PCA utilized as a multivariate
dimensionality-reduction tool. Data (volunteers in

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Table 1. PM levels in both studied areas are expressed as the annual average. The results are expressed as mean ± SD. The
asterisk denotes significant differences (P < 0.04) in PM 2.5 levels between populations I and U.

n I n U P

PM2.5[µg/m
3] 13 17.1 ± 8.4* 7 10.5 ± 3.6* 0.024

PM10[µg/m
3] 5 41.4 ± 16.4 5 28.2 ± 9.5 0.127

PM, particulate matter; I, industrial; U, urban; SD, standard deviation; n, number

Table 2. Outer segment characteristics. The values of the number of the sample (n) are detailed; the mean (μ); the median (m);
and the standard deviation (SD) for each study area are provided. The P-value is also reported according to the Student’s T-test.
The variables that presented significant differences between populations (*) are indicated in bold font.

Variables Industrial Zone Urban Zone

µ m SD µ m SD P

Questionn-
aires

OSDI score 8.88 4.16 11.8 7.19 4.16 8.68 0.3046

McMonnies score 7.56 6.50 5.71 7.20 6.00 4.81 0.6749

Ocular
surface

Without
vital
staining

Bulbar redness (grade)* 2.79 3.00 0.56 2.39 2.00 0.60 0.0001

Lid redness (grade)* 2.47 2.50 0,48 2.15 2.00 0.62 0.0009

Limbal redness (grade) 2.29 2.00 0.78 2.42 2.5 0.71 0.289

Blepharitis (grade) 0.58 0.00 0.97 0.36 0.00 0.84 0.145

With vital
staining

Fluorescein Type of cornea (grade) 0.26 0.00 0.65 0.35 0.00 0.62 0.426

Depth of cornea (grade) 0.18 0.00 0.33 0.27 0.00 0.44 0.220

Extent of cornea (grade) 0.18 0.00 0.33 0.25 0.00 0.37 0.316

Conjunctival (grade)* 3.23 3.00 0.73 2.48 3.00 0.64 –

LIPCOF (grade) 2.24 2.50 0.93 2.42 3.00 0.89 0.231

Lissamine
green

Lissamine green (grade)* 2.17 2.00 1.14 1.25 1.00 0.87 –

Tear Film Volume Schirmer I Test (mm)* 24.73 29.50 11.20 31.33 35.00 5.39 –

Tear meniscus height (mm) 0.25 0.25 0.09 0.29 0.30 0.1 0.041

Stability TBUT (s) 5.65 5.20 3.12 6.40 5.35 3.46 0.245

Lipid layer MGD (grade)* 0.45 0.00 0.63 0.17 0.00 0.36 0.001

OSDI, ocular surface disease index; LIOCOF, lid parallel conjunctival folds

six-dimensional space) were presented as a two-
dimensional graph defined by the first two direc-
tions of maximal variability of the data points [axis
or PC], as shown in Figure 2.

Based on PCA, 54% of the total data variability
was attributed to the main plane (PC 1 and 2).
The variables of conjunctival staining with SF and
SLG were increased to the left on the horizontal

axis, indicating a strong positive correlation with
PC 1. Conversely, that of ST was increased to
the right on the same axis, indicating nega-
tive correlation; the two variables had a strong
inverse relationship. In contrast, the variables of
BR, LR, and MGD were considered to have pos-
itive correlations with PC 2. As shown in Figure
2, the areas of provenance of the sample are

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Figure 2. Principal component analysis graph. Each point represents a volunteer: the open circle and black triangle correspond
to zones U and I, respectively. The vectors represent the projection of variables: BR, Bulbar redness; LR, Lid redness; SF, Vital
staining with fluorescein; SLG, Vital staining with lissamine green; ST, Schirmer I test; and MGD, Meibomian gland dysfunction.
Analysis was carried out using the Infostat software.

clearly separated in the horizontal direction of the
plot.

DISCUSSION

Existing reports in the literature on the effects
of air pollution on ocular health are limited to
physiological symptoms or signs and/or alterations
at a morphological level.[4] As such, reports on the
impact of atmospheric pollution on ocular health
at a clinical level, which could ultimately progress
professional practice, are lacking.

In order to characterize ocular health in individ-
uals exposed to different levels of air pollutants,
as well as to identify the associations between
effectors and symptoms, reports have indicated the
use of various tests and/or questionnaires.[8, 9, 11, 12]
The OSDI evaluates ocular alterations based on the
symptomatology declared by patients independent
of their environmental conditions. In our study, the
OSDI was not effective in distinguishing popula-
tions exposed to different concentrations of PM
[Table 2]. Here, normal values were noted in both
populations, in agreement with those reported
by Schiffman et al and Miller et al.[16, 31] Both
the United States National Eye Institute (NEI) and
the Tear Film and Ocular Surface Society (TFOS)
recommend the use of the OSDI for all optomet-
ric/ophthalmological consultations. Nevertheless,

objective tests to evaluate the ocular surface
should also be performed, since the association
between clinical tests and questionnaires used for
diagnosis is not adequate.[32, 33] Objective clinical
tests are essential to identify patients with early
alterations who may not present any symptoms.

In our study, significant differences in ocular
surface alterations which correlated with increased
PM2.5 in the I group were identified [Table 2]. This is
consistent with the results of other studies includ-
ing populations exposed to high air pollution,[9]
pollutants related to traffic,[10] and individuals who
travel to highly contaminated areas.[8]

PCA involving the statistically different variables
was performed. As a result, ST value and conjunc-
tival SF and SLG staining grades were identified
as three variables that could discriminate between
individuals from the two zones with different levels
of air pollution, indicating their potential use as
bioindicators of the health status of the ocular
surface. From a clinical point of view, these vari-
ables enable classification of the population into
eight groups, represented in Figure 3 by eight
3D cubes. From a clinical point of view, these
variables enable classification of the population
into eight groups, represented in Figure 3 by eight
3D cubes. In this analysis, cut-off values for each
variable (SF, 3; SLG, 3; ST, 10 mm) were employed
to analyze the effects on the population according

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Figure 3. Projection of variables that separate populations with different levels of particulate matter (PM). SF, Vital staining with
fluorescein; SLG, Vital staining with lissamine green; and ST, Schirmer test I. The black cube represents the population that
exhibits alteration of all three variables, while the white cube represents the population that does not present any alteration of
these variables. The cut-off values of each variable were SF: 3; SLG: 3; and ST: 10 mm.

to the combination of significant variables against
environmental factors.

Regarding the ST axis, the cubes below the cut-
off value of 10 mm represent individuals with tear
(aqueous) hyposecretion, corresponding to groups
with aqueous-deficient dry eye (ADDE);[4, 25] the
cubes above the cut-off (ST values of > 10 mm) cor-
respond to individuals with clinically normal eyes
in terms of basal and reflex tear secretion. Despite
noting ST values < 10 mm in some individuals, the
mean ST value of both populations was above the
cut-off level (I, 24.73 ± 11.2; U, 31.33 ± 0.0033 mm),
which indicated that both populations comprised
individuals with clinically normal ST values.

The results of our investigation agree with those
of Gupta et al who demonstrated a decrease in the
mean ST value (22.75 ± 8.91 vs 30.30 ± 7.92 mm)
in individuals exposed to high levels of pollutants,
and of Saxena who demonstrated lower mean ST
values in individuals traveling in heavily polluted
areas of New Delhi compared to controls (13.42 ±
6.67 vs 15.95 ± 6.14 mm). The unique finding of our
study was that ocular surface cellular alterations,
such as an increase in the level of vital staining
with both SF and SLG, were correlated with air
pollution.

The follow-up of individuals with normal ST
values and a trend toward high SF and SLG
values is important since tear hyperosmolarity

may damage the superficial epithelium by acti-
vating inflammatory pathways at the ocular sur-
face, as proposed by Baudouin. Moreover, this
cellular damage may cause a loss of goblet cells
and dysregulation of the expression of mucins,
which leads to instability of the tear film and
exacerbation of hyperosmolarity at the ocular
surface, thereby reinitiating the dry eye cycle.[34]
Consequently, evidence of such ocular surface
damage could indicate a high risk of developing
recurrent or chronic inflammation in these indi-
viduals. Therefore, early detection would enable
prompt therapeutic intervention aimed at prevent-
ing the development of dry eye disease. More-
over, recent studies have demonstrated PM2.5-
induced human corneal epithelial cell damage in
vitro.[35]

Considering the collective findings of previous
studies and those of our study, a study to develop
a clinical index of ocular alterations including
the aforementioned three variables is therefore
required. Based on our results, the relationship
among these variables (formula) is expressed as
the sum of the loads of each variable multiplied by
the standardized variable as follows:

Formula = 0.7748 × (𝑆𝐹 − 𝜇SF/SDSF)
+0.7453 × (SLG − 𝜇SLG/SDSLG)
−0.5944 × (ST − 𝜇ST/SDST)

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Ocular Surface Sensitivity to Particulate Matter; Gutiérrez et al

Where ST, SF, and SGL are considered as coef-
ficients. ST, Schirmer I test; SF, vital staining
with fluorescein; SGL, vital staining with lissamine
green; μ, mean; SD, standard deviation.

Further studies to validate the relationship
between air pollution and effects at the ocular
level are required to develop tools to facilitate
the diagnosis of patients and enable the differ-
entiation of individuals with ocular surface alter-
ations sensitive to different levels of air pollution.
Moreover, given the increased prevalence of dry
eye worldwide,[30, 36–39, 41] the early detection of
incipient and asymptomatic alterations is impor-
tant, since it is a key aspect for improving patients’
quality of life.[42]

In conclusion, subjects exposed to higher levels
of PM in outdoor air presented greater ocular
surface alterations. Our study highlights that ST, SF,
and SLG values have potential uses as convenient
indicators of adverse health effects due to expo-
sure to air pollution.

Financial Support and Sponsorship

The authors would also like to thank the Univer-
sidad Nacional de La Plata (UNLP), the Consejo
Nacional de Investigaciones Científicas y Técnicas
(CONICET) and the Centro de Investigaciones
Científicas (CIC) for their financial support to the
present study.

Conflicts of Interest

There is no conflict of interest.

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