Systemic, environmental and lifestyle risk factors for dry eye disease in a mediterranean caucasian population

Open AccessPublished:November 14, 2021DOI:https://doi.org/10.1016/j.clae.2021.101539

      Abstract

      Objectives

      To assess systemic, environmental and lifestyle risk factors for dry eye disease (DED) in a Mediterranean Caucasian population.

      Methods

      A cross-sectional study was performed on 120 Caucasian participants aged between 18 and 89 years (47.0 ± 22.8 years). Medical history, information regarding environmental conditions and lifestyle, Ocular Surface Disease Index, Dry Eye Questionnaire-5, non-Invasive (Oculus Keratograph 5 M) breakup time, tear film osmolarity and ocular surface staining parameters were assessed in a single clinical session to allow DED diagnosis based on the guidelines of the Tear Film and Ocular Surface Society Dry Eye Workshop II Diagnostic Methodology Report. A multivariate logistic regression model was constructed including those variables with a p-value less than 0.15 in the univariate analysis.

      Results

      A prevalence of 57.7 % for DED was found. No age differences were found between those with and without DED (U = 1886.5, p = 0.243). Nevertheless, the DED group had more females (X2 = 7.033, p = 0.008). The univariate logistic regression identified as potential risk factors for DED the following: female sex, sleep hours per day, menopause, anxiety, systemic rheumatologic disease, use of anxiolytics, daily medication, ocular surgery, poor diet quality, more ultra-processed food in diet, not drinking caffeine and hours of exposure to air conditioning per day. Multivariate logistic regression revealed that hours of sleep per day, menopause and use of anxiolytics were independently associated with DED (p ≤ 0.026 for all).

      Conclusions

      DED is associated with systemic, environmental and lifestyle risk factors. These findings are useful to identify potentially modifiable risk factors, in addition to conventional treatments for DED.

      Keywords

      1. Introduction

      According to the Tear Film and Ocular Surface Society Dry Eye Workshop II (TFOS DEWS II), dry eye disease (DED) is defined as a multifactorial disease characterized by the loss of tear film homeostasis, which is accompanied by symptoms of ocular dryness [
      • Craig J.P.
      • Nichols K.K.
      • Akpek E.K.
      • Caffery B.
      • Dua H.S.
      • Joo C.-K.
      • et al.
      TFOS DEWS II Definition and Classification Report.
      ]. The prevalence of DED is increasing substantially worldwide influenced by demographic, systemic and environmental factors. DED prevalence ranges from 5 to 50 % at various ages [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,

      W.-J. Yang Y.-N. Yang J. Cao Z.-H. Man J. Yuan X. Xiao et al. Risk factors for dry eye syndrome: A retrospective case-control study 92 9 2015 e199 e205 10.1097/OPX.0000000000000541.

      ], impacting quality of life, visual function, ocular healthiness and work productivity of those who suffer from it [
      • Craig J.P.
      • Nichols K.K.
      • Akpek E.K.
      • Caffery B.
      • Dua H.S.
      • Joo C.-K.
      • et al.
      TFOS DEWS II Definition and Classification Report.
      ,
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ]. Moreover, the multifactorial and heterogeneous aetiology of the disease indicated the tear film and the ocular surface integrity are highly influenced by a wide range of risk factors [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ].
      The TFOS DEWS II Epidemiology Report listed several risk factors for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ]. This meta-analysis showed that the prevalence of DED increases with age, female sex and Asian ethnicity. Nevertheless, very few of the studies included in the analysis incorporated young people. Also, the report highlighted that some of the listed risk factors are still inconclusive and there is not yet clear evidence that most of them induce DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ]. Moreover, studies have significant differences in the methodology and in the procedure followed to diagnose DED, which makes their direct comparison and the building of global conclusions particularly challenging [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. In the report, the authors argued that there is still a considerable lack of information about risk factors for DED and that the implementation of studies to assess such factors in different geographic regions is required.
      To the authors’ knowledge, there are only two studies [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] that have evaluated DED risk factors following the TFOS DEWS II guidelines for the diagnosis and identification of potential risk factors for DED, both performed on a cohort in New Zealand. Authors found that age, ethnicity, migraine, systemic rheumatologic disease, thyroid disease, use of antidepressant medication, oral contraceptive therapy, increased digital screen exposure time and reduced caffeine consumption were independently associated with DED [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. Authors [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] also acknowledged the need to analyse non-significant potential risk factors that were not very prevalent in their population. Furthermore, these studies did not consider interactions between demographic, systemic and lifestyle risk factors, since systematic risk factors were assessed separately from lifestyle factors [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ].
      This study is the first to examine DED in a Mediterranean Caucasian population using the standardised TFOS DEWS II criteria and analyzes systemic, environmental and lifestyle DED risk factors [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ]. In addition, new lifestyle and environmental risk factors have been included in the analysis.

      2. Material and methods

      One hundred and twenty Caucasian volunteers ranging in age from 18 to 89 years (47.0 ± 22.8 years) participated in this cross-sectional study. In order to evaluate different health and tear film status, no exclusion based on health or tear film parameters was made. Contact lens users were instructed not to wear their contact lenses for the 48 h prior to examination [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. Participants with ocular surgery within the previous three months were excluded. Only volunteers who lived in the region were enroled to minimize environmental differences [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. Only the right eye of each participant was assessed to avoid data bias (except for tear osmolarity which was measured from each eye as recommended). The study was carried out in accordance with the tenets of the Declaration of Helsinki and was approved by the Ethics Committee of the University of Valencia. Written consent from each participant was obtained after a verbal explanation of the protocol, nature and possible consequences of the study. Recruitment was carried out by advertisement within University dissemination channels, campus personnel and students, as well as in local public entities in nearby towns.

      2.1 Measurements

      Ocular surface was assessed using the Oculus Keratograph 5 M (K5 M; Oculus GmbH, Wetzlar, Germany) and the TearLab Osmolarity device (TearLab Corporation, San Diego, CA, USA). Measurements were taken by the same experienced examiner within a single visit. Data was acquired following the guidelines of the TFOS DEWS II Diagnostic Methodology Report, to avoid the destabilization of the tear film, in the following order [
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ]: Medical history, information regarding environmental conditions and lifestyle, Ocular Surface Disease Index (OSDI), Dry Eye Questionnaire-5 (DEQ-5), Non-Invasive Keratograph Break-Up Time (NIKBUT), tear film osmolarity and ocular surface staining. The temperature and humidity of the room were maintained at 24.1 ± 1.6 °C and 44.9 ± 5.0 %, respectively. Measurements were performed between November 2018 and January 2019, minimizing seasonal variations.
      Participants were asked about their lifestyle, medical history, use of oral or topical medications, history of ophthalmic surgery and environmental conditions. The risk factors included in the present study were those reported by the TFOS DEWS II Epidemiology Report [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. Participants with rheumatoid arthritis, gout, osteoarthritis, fibromyalgia and osteoporosis were included under the classification of systemic rheumatologic disease, while bradycardia and heart failure were included under the classification of heart disease. Participants graded the quality of their diet as good (excellent or good quality) or poor (poor or fair quality). They were instructed to consider a good diet quality if they believe as having a balanced intake of protein, carbohydrates, fruits and vegetables; whilst a poor diet quality is an unbalanced diet, associated with the intake of ultra-processed food, ready-to-eat products and sugars.
      Table 1 shows the risk factors evaluated in the present study. No participant reported a history of Sjögren syndrome, rosacea, acne vulgaris, psoriasis, lupus erythematosus, hepatitis C, steroids deficiency, chronic kidney disease or hematopoietic stem cell transplantation. Moreover, all participants used soft contact lenses daily; therefore, this variable was not included in the analysis since a binary logistic regression was not able to be performed.
      Table 1Risk factors evaluated in the present study.
      Characteristic
      Age
      Female sex
      Lifestyle
      Hours of sleep per day
      Smoking
      Number of cigarettes smoked per day
      More than 5 cigarettes smoked per day
      Contact lens wear
      Hours per week of contact lens wear
      More than 56 h per week of contact lens wear
      Computer use
      Daily hours of computer use
      More than 4 h of daily computer use
      Exercise
      Not walking (sedentary lifestyle)
      Hours walking per day
      Not practising exercise
      Hours practising exercise per week
      Medical conditions
      Menopause
      Allergic rhinitis
      Asthma
      Hypertension
      Ovarian dysfunction
      Anxiety
      Systemic rheumatologic disease
      Diabetes
      Hypercholesterolemia
      Glaucoma
      Migraine headaches
      Depression
      Heart disease
      Thyroid disease
      Schizophrenia
      Eczema
      Stress
      Medications
      Antihistamines
      Antihypertensives
      Stomach protector
      Oral contraceptive therapy
      Anticoagulants
      Anxiolytics
      Blood glucose regulators
      Topical anti-glaucoma medication
      Antidepressants
      Hypercholesterolemia medication
      Anti-inflammatories
      Medication for thyroids
      Antipsychotics
      Daily medication
      Ocular surgery
      Ocular Surgery
      Retinal surgery
      Refractive surgery
      Pterygium surgery
      Glaucoma surgery
      Cataract surgery
      Diet
      Poor diet quality
      Non-omnivorous diet
      Non-oily fish diet
      Percentage of unprocessed food in diet
      Percentage of ultra-processed food in diet
      Drinking alcohol
      Units of alcohol per week
      More than 4 units of alcohol per week
      Not drinking caffeine
      Units of caffeine per day
      Litres of water per day
      Less than 2 L of water per day
      Environment
      Working
      Hours working per day
      Working ≥ than 8 h per day
      Urban life
      Air conditioning
      Hours of exposure to air conditioning per day
      ≥ 8 h of exposure to air conditioning per day
      Central heating
      Hours of exposure to central heating per day
      ≥ 8 h of exposure to central heating per day
      The first NIKBUT of the tear film was measured three consecutive times and the median was calculated. Measurements were taken every 3 min to allow tear film stabilization between them [
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ,
      • Rico-del-Viejo L.
      • Benítez-del-Castillo J.M.
      • Gómez-Sanz F.J.
      • García-Montero M.
      • Llorens-Quintana C.
      • Madrid-Costa D.
      The influence of meibomian gland loss on ocular surface clinical parameters.
      ]. Tear film osmometry was performed in both eyes using the TearLab Osmolarity device from 50 nL tear samples collected from the lower lateral canthus tear meniscus. The interocular difference in osmolarity was calculated [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ].
      Ocular surface staining was evaluated with fluorescein strips for the assessment of the cornea, and with lissamine strips for the assessment of the conjunctiva and eyelid margins using the TFOS DEWS II recommended protocol [
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ]. The number of corneal and conjunctival spots was recorded [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ,
      • Whitcher J.P.
      • Shiboski C.H.
      • Shiboski S.C.
      • Heidenreich A.M.
      • Kitagawa K.
      • Zhang S.
      • et al.
      A Simplified Quantitative Method for Assessing Keratoconjunctivitis Sicca From the Sjögren’s Syndrome International Registry.
      ]. Positive lid wiper epitheliopathy was defined as a lid margin staining ≥ 2 mm in length and/or ≥ 25 % of sagital width (excluding Marx’s line) [
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ,
      • Korb D.R.
      • Herman J.P.
      • Greiner J.V.
      • Scaffidi R.C.
      • Finnemore V.M.
      • Exford J.M.
      • et al.
      Lid wiper epitheliopathy and dry eye symptoms.
      ].
      The sample was classified following the indications of the TFOS DEWS II Diagnostic Methodology Report for the diagnosis of DED [
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ]. Participants were classified into the DED group if they had dry eye symptoms (OSDI ≥ 13 or DEQ-5 ≥ 6) and at least one altered homeostasis marker (NIKBUT less than 10 s; osmolarity ≥ 308 mOsm/L; interocular osmolarity difference greater than 8 mOsm/L; corneal fluorescein staining greater than 5 spots; conjunctival lissamine green staining greater than 9 spots; or lid margin staining ≥ 2 mm length and ≥ 25% width).

      2.2 Statistical analysis

      Statistical analysis was carried out using SPSS v26.0 for Windows (IBM Corp, Armonk, New York, USA). Results are presented as the mean ± standard deviation (SD), as the median and interquartile range or as the number and percentage of participants, depending on the parameter.
      Normality distribution for each group was assessed via the Kolmogorov-Smirnov test or the Shapiro-Wilk test. Significant differences in age between healthy and DED groups were assessed using the Mann-Whitney U test, while sex differences between groups were evaluated using the Chi-square analysis.
      Univariate logistic regression was performed initially to identify the predictors of DED. Predictors with a p-value less than 0.15 were incorporated into the multivariate logistic regression analysis [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. Collinearity assumption was checked among variables. A p-value of less than 0.05 was considered statistically significant.
      The statistical power of the sample was calculated post-hoc using the G*Power 3.1 software [
      • Faul F.
      • Erdfelder E.
      • Lang A.-G.
      • Buchner A.
      G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences.
      ]. A statistical power of 0.8 was achieved for logistic regression analysis with the sample size of 120 participants and a significance level of 0.05.

      3. Results

      One hundred and twenty right eyes from 120 participants were measured: 60 females (50 %) and 60 males (50 %). The mean ± SD age of the participants was 47.0 ± 22.8 years, ranging from 18 to 89 years. The comparison between the cohort of the sample and the Spanish population is shown in Fig. 1.
      Figure thumbnail gr1
      Fig. 1Tornado plots representing the sample cohort (left) and the Spanish population (right).
      No participant was previously diagnosed with DED. From the total sample, 44 participants (36.7 %) were classified into the healthy group (43.2 ± 21.2 years) and 76 (63.3 %) into the DED group (49.2 ± 23.5 years) according to the criterion described in the TFOS DEWS II Diagnostic Methodology Report. Given that the cohort does not fully represent the Spanish population (Fig. 1), a corrected prevalence was calculated by multiplying the DED rate found for each age group by the age proportion in each group. Results show a corrected prevalence of DED using the TFOS DEWS II criteria for the Mediterranean Caucasian population of 57.7 % with a confidence interval of 33.3–80.9 %.
      There were no statistically significant age differences between groups (Mann-Whitney U = 1886.5, p = 0.243). Sixty participants were females (50 %) and sixty males (50 %). Twenty-five per cent of females were classified into the healthy group and 75 % into the DED group, while 48 % of males were classified into the healthy group and 52 % into the DED group. The DED group had statistically higher number of females (X2 = 7.033, p = 0.008). Table 2 shows the demographic, clinical characteristics, and environmental and lifestyle factors of participants, while Table 3 shows the ocular surface parameters of the participants.
      Table 2Demographic, clinical, environmental and lifestyle characteristics of participants.
      CharacteristicResults
      Age (mean ± SD)47.0 ± 22.8 years
      Female sex (number of participants, percentage of participants)60, 50 %
      Lifestyle
      Hours of sleep per day (mean ± SD)7.1 ± 1.2
      Smoking (number of participants, percentage of participants)31, 26 %
      Number of cigarettes smoked per day (mean ± SD)2.6 ± 6.2
      More than 5 cigarettes smoked per day (number of participants, percentage of participants)19, 16 %
      Contact lens wear (number of participants, percentage of participants)37, 31 %
      Hours per week of contact lens wear (mean ± SD)15.6 ± 29.3
      More than 56 h per week of contact lens wear (number of participants, percentage of participants)16, 13 %
      Computer use (number of participants, percentage of participants)71, 59 %
      Daily hours of computer use (mean ± SD)2.9 ± 3.1
      More than 4 h of daily computer use (number of participants, percentage of participants)37, 31 %
      Exercise
      Not walk (sedentary lifestyle) (number of participants, percentage of participants)29, 24 %
      Hours walking per day (mean ± SD)1.1 ± 1.1 h
      Not practise exercise (number of participants, percentage of participants)77, 64 %
      Hours practising exercise per week (mean ± SD)2.2 ± 4.7 h
      Medical conditions
      Menopause (number of participants, percentage of participants)21, 18 %
      Allergic rhinitis (number of participants, percentage of participants)19, 16 %
      Asthma (number of participants, percentage of participants)7, 6 %
      Hypertension (number of participants, percentage of participants)21, 18 %
      Ovarian dysfunction (number of participants, percentage of participants)5, 4 %
      Anxiety (number of participants, percentage of participants)18, 15 %
      Systemic rheumatologic disease (number of participants, percentage of participants)16, 13 %
      Diabetes (number of participants, percentage of participants)12, 10 %
      Hypercholesterolemia (number of participants, percentage of participants)11, 9 %
      Glaucoma (number of participants, percentage of participants)6, 5 %
      Migraine headaches (number of participants, percentage of participants)8, 7 %
      Depression (number of participants, percentage of participants)8, 7 %
      Heart disease (number of participants, percentage of participants)2, 2 %
      Thyroid disease (number of participants, percentage of participants)5, 4 %
      Schizophrenia (number of participants, percentage of participants)2, 2 %
      Eczema (number of participants, percentage of participants)4, 3 %
      Stress (number of participants, percentage of participants)10, 8 %
      Medications
      Antihistamines (number of participants, percentage of participants)9, 8 %
      Antihypertensives (number of participants, percentage of participants)20, 17 %
      Stomach protector (number of participants, percentage of participants)4, 3 %
      Oral contraceptive therapy (number of participants, percentage of participants)7, 6 %
      Anticoagulants (number of participants, percentage of participants)7, 6 %
      Anxiolytics (number of participants, percentage of participants)21, 18 %
      Blood glucose regulators (number of participants, percentage of participants)9, 8 %
      Topical anti-glaucoma medication (number of participants, percentage of participants)6, 5 %
      Antidepressants (number of participants, percentage of participants)4, 3 %
      Hypercholesterolemia medication (number of participants, percentage of participants)7, 6 %
      Anti-inflammatories (number of participants, percentage of participants)3, 3 %
      Medication for thyroids (number of participants, percentage of participants)3, 3 %
      Antipsychotics (number of participants, percentage of participants)2, 2 %
      Daily medication (number of participants, percentage of participants)58, 48 %
      Ocular surgery
      Ocular surgery (number of participants, percentage of participants)25, 21 %
      Retinal surgery (number of participants, percentage of participants)2, 2 %
      Refractive surgery (number of participants, percentage of participants)5, 4 %
      Pterygium surgery (number of participants, percentage of participants)1, 1 %
      Glaucoma surgery (number of participants, percentage of participants)2, 2 %
      Cataract surgery (number of participants, percentage of participants)16, 13 %
      Diet
      Poor diet quality (number of participants, percentage of participants)19, 16 %
      Non-omnivorous diet (number of participants, percentage of participants)11, 9 %
      Non-oily fish diet (number of participants, percentage of participants)79, 66 %
      Percentage of unprocessed food in diet (mean ± SD)65 ± 20 %
      Percentage of ultra-processed food in diet (mean ± SD)8 ± 11 %
      Drinking alcohol (number of participants, percentage of participants)83, 67 %
      Units of alcohol per week (mean ± SD)3.2 ± 5.0 units
      More than 4 units of alcohol per week (number of participants, percentage of participants)30, 25 %
      Not drinking caffeine (number of participants, percentage of participants)28, 23 %
      Units of caffeine per day (mean ± SD)1.5 ± 1.5 units
      Litres of water per day (mean ± SD)1.7 ± 0.8 L
      Less than 2 L of water per day (number of participants, percentage of participants)73, 61 %
      Environment
      Working (number of participants, percentage of participants)57, 48 %
      Hours working per day (mean ± SD)3.7 ± 4.1 h
      Working ≥ than 8 h per day (number of participants, percentage of participants)42, 35 %
      Urban life (number of participants, percentage of participants)49, 41 %
      Air conditioning (number of participants, percentage of participants)90, 75 %
      Hours of exposure to air conditioning per day (mean ± SD)4.2 ± 4.1 h
      ≥ 8 h of exposure to air conditioning per day (number of participants, percentage of participants)31, 26 %
      Central heating (number of participants, percentage of participants)91, 76 %
      Hours of exposure to central heating per day (mean ± SD, years)4.7 ± 4.7 h
      ≥ 8 h of exposure to central heating per day (number of participants, percentage of participants)34, 28 %
      Where: SD = Standard Deviation.
      Table 3Ocular surface parameters of participants.
      CharacteristicTotalHealthy groupDED group
      OSDI score (median, IQR)16.7, 6.3–30.34.2, 0–8.322.6, 13.9–42.7
      DEQ-5 score (median, IQR)7, 4–123, 1–510, 7–14
      NIKBUT (median, IQR)6.69, 4.40–10.66 s8.54, 4.92–15.29 s7.76, 4.21–8.36 s
      Osmolarity (median, IQR)318.0, 310.5–329.50 mOsmol/L315.5, 307.75–328.50 mOsmol/L320.0,
      312.0–331.0 mOsmol/L
      Difference in osmolarity between eyes (median, IQR)10, 4.5–19 mOsmol/L9, 4.5–11.513, 4–22
      Corneal staining greater than 5 spots (number of participants)12210
      Corneal staining greater than 9 spots (number of participants)16313
      Lid margin staining ≥ 2 mm of length and ≥ 25 % of width (number of participants)31526
      Where: IQR = Interquartile range, DED = Dry Eye Disease, DEQ = Dry Eye Questionnaire, mOsmol/L = Milliosmoles per liter, NIKBUT = Non-Invasive Keratograph Break-Up Time and OSDI = Ocular Surface Disease Index.
      Table 4 shows the univariate logistic regression and multivariate-adjusted logistic regression analysis, along with the odds ratios of DED for each factor. Given that the cohort does not fully represent the Spanish population, corrected odds ratios were calculated for each risk factor by multiplying the risk factor rate found for each age group by the age proportion in each group. The ratio between the corrected prevalence of that risk factor and the corrected odds ratio was obtained and multiplied for the odds ratio to obtain the corrected odds ratio. This procedure was repeated for each risk factor. In continuous variables, the median value was used to classify participants.
      Table 4Univariate and multivariate logistic regressions and odds ratios of dry eye disease for demographic and clinical characteristics.
      CharacteristicUnivariate logistic regressionMultivariate logistic regression
      Odds ratio/Corrected odds ratioLower CI/CorrectedUpper CI/Correctedp-valueOdds ratio/Corrected odds ratioLower CI/CorrectedUpper CI/Correctedp-value
      Age1.012/1.5220.995/1.5161.029/1.5680.164
      Age (per 10 years)1.125/1.7140.945/1.4401.338/2.0390.185
      Female sex2.806/1.6031.295/0.7406.081/3.4730.009*
      Lifestyle
      Hours of sleep per day0.654/0.7920.469/0.5680.911/1.1030.012*0.588/0.7120.388/0.4700.891/1.0790.012*
      Smoking1.298/2.2000.546/0.9263.086/5.2310.555
      Number of cigarettes smoked per day1.030/1.7460.961/1.6291.104/1.8720.406
      More than 5 cigarettes smoked per day1.307/1.8610.458/0.6523.726/5.3040.617
      Contact lens wear0.788/0.7700.355/0.3481.747/1.7120.557
      Hours per week of contact lens wear1.001/0.9810.988/0.9681.015/0.9950.825
      More than 56 h per week of contact lens wear0.897/0.8790.301/0.2952.676/2.6220.846
      Computer use0.745/0.8740.347/0.4181.598/1.9270.449
      Daily hours of computer use0.961/1.1590.852/1.0271.084/1.3070.522
      More than 4 h of daily computer use0.567/0.7660.257/0.3471.254/1.6940.161
      Exercise
      Not walk (sedentary lifestyle)0.636/0.7130.272/0.3051.489/1.6700.297
      Hours walking per day1.081/1.1460.771/0.8171.514/1.6050.652
      Not practise exercise1.412/1.7340.655/0.8043.045/3.7400.378
      Hours practising exercise per week0.827/0.9290.580/0.6511.179/1.3240.293
      Medical conditions
      Menopause7.000/3.4581.546/0.79431.705/15.6620.012*8.759/4.3271.571/0.77648.835/2.1240.013*
      Allergic rhinitis1.307/2.1860.458/0.7663.726/6.2320.617
      Asthma1.479/1.0390.275/0.1937.964/5.5930.649
      Hypertension2.080/1.5020.705/0.5096.138/4.4320.185
      Ovarian dysfunction1001139339/
      624410605.70.0000.999
      Anxiety12.390/14.3131.587/1.83396.698/111.7060.016*
      Systemic rheumatologic disease4.742/2.8171.024/0.60821.954/13.0410.047*
      Diabetes0.791/0.9080.235/0.2702.661/3.0540.705
      Hypercholesterolemia1.608/1.7650.404/0.4446.406/1.0330.501
      Glaucoma3.028/1.3290.342/0.15026.793/11.7550.319
      Migraine headaches4.362/3.3580.519/0.34036.694/28.2510.175
      Depression4.362/1.8820.519/0.22436.694/15.8330.175
      Heart disease0.573/1.6720.035/0.1029.400/27.4240.697
      Thyroid disease0.863/0.3460.139/0.0565.375/2.1530.875
      Schizophrenia0.573/0.3780.035/0.0239.400/6.2040.697
      Eczema0.566/1.3730.057/0.1385.612/13.6100.627
      Stress2.471/4.3080.501/0.87412.194/21.2610.267
      Medications
      Antihistamines1.171/2.7840.278/0.6614.937/11.7360.829
      Antihypertensives1.918/1.4040.646/0.4735.699/4.1710.241
      Stomach protector1.767/1.1500.178/0.11617.526/11.4040.627
      Oral contraceptive therapy3.686/2.0270.429/0.23631.666/17.4100.235
      Anticoagulants0.759/1.2750.162/0.2723.560/5.9790.727
      Anxiolytics15.357/7.9011.982/1.020118.972/61.2110.009*11.072/5.6971.338/0.68891.611/47.1340.026*
      Blood glucose regulators2.130/2.8060.423/0.55710.740/14.1500.359
      Topical anti-glaucoma medication3.028/1.6070.342/0.18226.793/14.2220.319
      Antidepressants1.767/1.1490.178/0.11617.526/11.3970.627
      Hypercholesterolemia medication3.686/4.7910.429/0.55831.666/41.1630.235
      Anti-inflammatories0.280/0.1690.025/0.0153.180/1.9210.305
      Medication for thyroids0.280/0.1170.025/0.0103.180/1.3280.305
      Antipsychotics0.573/0.3780.035/0.0239.400/6.2040.697
      Daily medication1.861/2.0370.873/0.9563.963/4.3380.108
      Ocular surgery
      Ocular Surgery2.111/1.9410.772/0.7105.770/5.3040.145
      Retinal surgery960552609.3/
      2,802,316,1820.0000.999
      Refractive surgery2.389/2.0700.259/0.22422.075/19.1280.443
      Pterygium surgery0.0000.0001.000
      Glaucoma surgery960552609.3/
      421442457.30.0000.999
      Cataract surgery1.875/1.5240.566/0.4606.216/5.0540.304
      Diet
      Poor diet quality3.644/3.4300.998/0.93913.312/12.5320.0503.853/3.6270.978/0.92115.168/14.2790.054
      Non-omnivorous diet1.608/1.3380.404/0.3366.406/5.3290.501
      Non-oily fish diet1.166/1.5580.535/0.7152.539/3.3930.700
      Percentage of unprocessed food in diet0.985/0.6150.966/0.6031.006/0.6280.154
      Percentage of ultra-processed food in diet1.046/1.5900.994/1.5111.102/1.6750.084
      Drinking alcohol1.055/1.3280.481/0.6052.315/2.9140.893
      Units of alcohol per week1.026/1.2100.948/1.1181.111/1.3100.529
      More than 4 units of alcohol per week1.214/1.4320.508/0.5992.900/3.4200.662
      Not drinking caffeine3.385/1.7031.182/0.5959.690/4.8760.023*
      Units of caffeine per day0.892/0.4490.695/0.3501.145/0.5760.369
      Litres of water per day0.985/1.1160.921/1.0431.053/1.1930.663
      Less than 2 L of water per day1.122/1.2710.526/0.5962.396/2.7140.766
      Environment
      Working0.739/0.6530.351/0.3101.556/1.3750.426
      Hours working per day0.968/0.8550.885/0.7821.059/0.9360.483
      Working ≥ than 8 h per day0.910/0.8000.419/0.36851.977/1.7390.812
      Urban life1.565/1.5620.725/0.7233.380/3.3730.254
      Air conditioning1.455/1.6820.626/0.7243.381/3.9080.383
      Hours of exposure to air conditioning per day1.085/1.0940.981/0.9891.201/1.2110.112
      ≥ 8 h of exposure to air conditioning per day1.584/1.5970.654/0.6593.837/3.8670.308
      Central heating1.074/1.1890.453/0.5022.547/2.8200.871
      Hours of exposure to central heating per day0.973/1.0770.900/0.9961.051/1.1640.483
      ≥ 8 h of exposure to central heating per day1.302/1.6670.562/0.7203.015/3.8610.538
      Where: CI = 95 % Confidence Interval. * = Statistically significant values. Bold = Variables included in the multivariate analysis (p < 0.15).
      Univariate logistic regression identified the following as potential risk factors for DED (p less than 0.15): Sex, sleep hours per day, menopause, anxiety, systemic rheumatologic disease, use of anxiolytics, daily medication, ocular surgery, poor diet quality, percentage of ultra-processed food in diet, caffeine intake and hours of exposure to air conditioning per day. The interaction between DED and risk factors was statistically significant for sex, sleep hours per day, menopause, anxiety, systemic rheumatologic disease, use of anxiolytics and caffeine intake (p less than 0.05 for all). The multivariate logistic regression revealed that sleep hours per day, menopause and use of anxiolytics were independently associated with DED (p ≤ 0.026 for all).

      4. Discussion

      The TFOS DEWS II Epidemiology Report noted that there is an extensive list of risk factors for DED because the tear film and ocular surface form part of a functional unit, which is influenced by lifestyle, environmental conditions, and systemic and ocular disease [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ]. The authors acknowledged the need to study the principal and emerging risk factors of DED following the diagnostic guidelines reported in the TFOS DEWS II Diagnostic Methodology Report [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Wolffsohn J.S.
      • Arita R.
      • Chalmers R.
      • Djalilian A.
      • Dogru M.
      • Dumbleton K.
      • et al.
      TFOS DEWS II Diagnostic Methodology report.
      ].
      The TFOS DEWS II Epidemiology Report determined that ageing, feminine sex, Asian ethnicity, computer use, contact lens wear, inadequate environment, and use of antihistamines, antidepressants and anxiolytics were DED risk factors with consistent evidence. Nevertheless, these outcomes cannot be directly compared with the ones reported in the present study, as the TFOS DEWS II Report was constructed on the basis of previous cross-sectional investigations in which the disease diagnosis criterion and methodology differed considerably between studies.
      Consequently, the results of the present research can only be directly compared with the recent studies carried out by Wang et al. [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] on a New Zealand population. The present study adds the analysis of the interaction between systemic, environmental and lifestyle DED risk factors. The results of this study showed that DED was independently associated with the use of anxiolytics, menopause and sleep hours per day.

      4.1 Age and sex

      The association of DED with sex and ageing has been widely reported in previous studies. Several studies found an increase in DED prevalence with age [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ,
      • Galor A.
      • Feuer W.
      • Lee D.J.
      • Florez H.
      • Faler A.L.
      • Zann K.L.
      • et al.
      Depression, post-traumatic stress disorder, and dry eye syndrome: A study utilizing the National United States veterans affairs administrative database.
      ,
      • Uchino M.
      • Yokoi N.
      • Uchino Y.
      • Dogru M.
      • Kawashima M.
      • Komuro A.
      • et al.
      Prevalence of dry eye disease and its risk factors in visual display terminal users: The Osaka study.
      ,
      • Paulsen A.J.
      • Cruickshanks K.J.
      • Fischer M.E.
      • Huang G.-H.
      • Klein B.E.K.
      • Klein R.
      • et al.
      Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ,
      • Schaumberg D.A.
      • Sullivan D.A.
      • Buring J.E.
      • Dana M.R.
      Prevalence of dry eye syndrome among US women.
      ,
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ,
      • Shehadeh-Mashor R.
      • Mimouni M.
      • Shapira Y.
      • Sela T.
      • Munzer G.
      • Kaiserman I.
      Risk Factors for Dry Eye after Refractive Surgery.
      ,

      H.C. Roh J.K. Lee M. Kim J.-H. Oh M.-W. Chang R.S. Chuck et al. Systemic comorbidities of dry eye syndrome: The Korean national health and nutrition examination survey V, 2010 to 2012 35 2 2016 187 192 10.1097/ICO.0000000000000657.

      ,
      • Lin X.
      • Wu Y.
      • Chen Y.
      • Zhao Y.
      • Xiang L.
      • Dai Q.i.
      • et al.
      Characterization of meibomian gland atrophy and the potential risk factors for middle aged to elderly patients with cataracts.
      ,
      • Farrand K.F.
      • Fridman M.
      • Stillman I.Ö.
      • Schaumberg D.A.
      Prevalence of Diagnosed Dry Eye Disease in the United States Among Adults Aged 18 Years and Older.
      ,
      • Rico-del-Viejo L.
      • Lorente-Velázquez A.
      • Hernández-Verdejo J.L.
      • García-Mata R.
      • Benítez-del-Castillo J.M.
      • Madrid-Costa D.
      The effect of ageing on the ocular surface parameters.
      ], while some did not find a significant association [
      • Tan L.L.
      • Morgan P.
      • Cai Z.Q.
      • Straughan R.A.
      Prevalence of and risk factors for symptomatic dry eye disease in Singapore.
      ,
      • Asiedu K.
      • Kyei S.
      • Boampong F.
      • Ocansey S.
      Symptomatic Dry Eye and Its Associated Factors: A Study of University Undergraduate Students in Ghana.
      ,
      • Tongg L.
      • Saw S.-M.
      • Lamoureux E.L.
      • Wang J.J.
      • Rosman M.
      • Tan D.T.H.
      • et al.
      A questionnaire-based assessment of symptoms associated with tear film dysfunction and lid margin disease in an Asian population.
      ,
      • Han S.B.
      • Hyon J.Y.
      • Woo S.J.
      • Lee J.J.
      • Kim T.H.
      • Kim K.W.
      Prevalence of dry eye disease in an elderly Korean population.
      ]. Moreover, some reports indentified that feminine sex was related to DED [
      • Galor A.
      • Feuer W.
      • Lee D.J.
      • Florez H.
      • Faler A.L.
      • Zann K.L.
      • et al.
      Depression, post-traumatic stress disorder, and dry eye syndrome: A study utilizing the National United States veterans affairs administrative database.
      ,
      • Uchino M.
      • Yokoi N.
      • Uchino Y.
      • Dogru M.
      • Kawashima M.
      • Komuro A.
      • et al.
      Prevalence of dry eye disease and its risk factors in visual display terminal users: The Osaka study.
      ,
      • Paulsen A.J.
      • Cruickshanks K.J.
      • Fischer M.E.
      • Huang G.-H.
      • Klein B.E.K.
      • Klein R.
      • et al.
      Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Schaumberg D.A.
      • Sullivan D.A.
      • Buring J.E.
      • Dana M.R.
      Prevalence of dry eye syndrome among US women.
      ,
      • Shehadeh-Mashor R.
      • Mimouni M.
      • Shapira Y.
      • Sela T.
      • Munzer G.
      • Kaiserman I.
      Risk Factors for Dry Eye after Refractive Surgery.
      ,

      H.C. Roh J.K. Lee M. Kim J.-H. Oh M.-W. Chang R.S. Chuck et al. Systemic comorbidities of dry eye syndrome: The Korean national health and nutrition examination survey V, 2010 to 2012 35 2 2016 187 192 10.1097/ICO.0000000000000657.

      ,
      • Lin X.
      • Wu Y.
      • Chen Y.
      • Zhao Y.
      • Xiang L.
      • Dai Q.i.
      • et al.
      Characterization of meibomian gland atrophy and the potential risk factors for middle aged to elderly patients with cataracts.
      ,
      • Farrand K.F.
      • Fridman M.
      • Stillman I.Ö.
      • Schaumberg D.A.
      Prevalence of Diagnosed Dry Eye Disease in the United States Among Adults Aged 18 Years and Older.
      ,
      • Rico-del-Viejo L.
      • Lorente-Velázquez A.
      • Hernández-Verdejo J.L.
      • García-Mata R.
      • Benítez-del-Castillo J.M.
      • Madrid-Costa D.
      The effect of ageing on the ocular surface parameters.
      ,
      • Tan L.L.
      • Morgan P.
      • Cai Z.Q.
      • Straughan R.A.
      Prevalence of and risk factors for symptomatic dry eye disease in Singapore.
      ,
      • Uchino M.
      • Schaumberg D.A.
      • Dogru M.
      • Uchino Y.
      • Fukagawa K.
      • Shimmura S.
      • et al.
      Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users.
      ], while others did not find a relationship [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Tan L.L.
      • Morgan P.
      • Cai Z.Q.
      • Straughan R.A.
      Prevalence of and risk factors for symptomatic dry eye disease in Singapore.
      ,
      • Tongg L.
      • Saw S.-M.
      • Lamoureux E.L.
      • Wang J.J.
      • Rosman M.
      • Tan D.T.H.
      • et al.
      A questionnaire-based assessment of symptoms associated with tear film dysfunction and lid margin disease in an Asian population.
      ,
      • Onwubiko S.N.
      • Eze B.I.
      • Udeh N.N.
      • Arinze O.C.
      • Onwasigwe E.N.
      • Umeh R.E.
      Dry eye disease: Prevalence, distribution and determinants in a hospital-based population.
      ].
      In this study, no independent association was found between DED and age or sex. Even though chi-square analysis showed that the DED group had a statistically higher number of females and that the univariate analysis identified that females were 1.6 times more likely to suffer from DED (p = 0.009), feminine sex was not found as statistically associated with DED in the multivariate analysis, which is in agreement with a previous study [
      • Asiedu K.
      • Kyei S.
      • Boampong F.
      • Ocansey S.
      Symptomatic Dry Eye and Its Associated Factors: A Study of University Undergraduate Students in Ghana.
      ]. Also in consonance with the outcomes of this study, no independent association between sex and DED was found by Wang et al. [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ]. Nevertheless, contrary to the Mediterranean Caucasian cohort results reported here, the authors did find an independent association between DED and age in their New Zealand cohort [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ].

      4.2 Medical conditions and medications

      Wang et al. [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ] also reported an independent association with migraine headaches, systemic rheumatologic disease, thyroid disease and antidepressant medication. In the present work, participants who suffered from systemic rheumatologic disease had 2.8 times more risk to suffer from DED in the univariate regression (p = 0.047), but it was not statistically significant in the multivariate analysis. Other studies [
      • Paulsen A.J.
      • Cruickshanks K.J.
      • Fischer M.E.
      • Huang G.-H.
      • Klein B.E.K.
      • Klein R.
      • et al.
      Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life.
      ,

      H.C. Roh J.K. Lee M. Kim J.-H. Oh M.-W. Chang R.S. Chuck et al. Systemic comorbidities of dry eye syndrome: The Korean national health and nutrition examination survey V, 2010 to 2012 35 2 2016 187 192 10.1097/ICO.0000000000000657.

      ,
      • Van Der Vaart R.
      • Weaver M.A.
      • Lefebvre C.
      • Davis R.M.
      The association between dry eye disease and depression and anxiety in a large population-based study.
      ,
      • Na K.-S.
      • Han K.
      • Park Y.-G.
      • Na C.
      • Joo C.-K.
      Depression, stress, quality of life, and dry eye disease in korean women: A population-based study.
      ] have also confirmed the relationship between DED and systemic rheumatologic disease since this condition causes an increased concentration of inflammatory cytokines within the tear fluid and conjunctival epithelium, which causes an inflammatory infiltration and structural damage in the lacrimal glands [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,

      H.C. Roh J.K. Lee M. Kim J.-H. Oh M.-W. Chang R.S. Chuck et al. Systemic comorbidities of dry eye syndrome: The Korean national health and nutrition examination survey V, 2010 to 2012 35 2 2016 187 192 10.1097/ICO.0000000000000657.

      ,
      • Bron A.J.
      • de Paiva C.S.
      • Chauhan S.K.
      • Bonini S.
      • Gabison E.E.
      • Jain S.
      • et al.
      TFOS DEWS II pathophysiology report.
      ,
      • Solomon A.
      • Dursun D.
      • Liu Z.
      • Xie Y.
      • Macri A.
      • Pflugfelder S.C.
      Pro- and anti-inflammatory forms of interleukin-1 in the tear fluid and conjunctiva of patients with dry-eye disease.
      ].
      Additionally, while there is inconclusive evidence as to whether menopause is a risk factor for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ], the present study found an independent association with DED. This could be because ovaries produce very low levels of estrogens and progesterone during menopause. It is thought that estrogens are responsible for the regulation of the synthesis of lipids in the meibomian glands, and both estrogens and progesterone modulate the inflammatory response. Researchers have also reported that the decrease in androgens during menopause is also associated with DED [
      • Sullivan D.A.
      • Rocha E.M.
      • Aragona P.
      • Clayton J.A.
      • Ding J.
      • Golebiowski B.
      • et al.
      TFOS DEWS II Sex, Gender, and Hormones Report.
      ,
      • Dang A.
      • Nayeni M.
      • Mather R.
      • Malvankar-Mehta M.S.
      Hormone replacement therapy for dry eye disease patients: systematic review and meta-analysis.
      ,
      • Vehof J.
      • Hysi P.G.
      • Hammond C.J.
      A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers.
      ,
      • Garcia-Alfaro P.
      • Bergamaschi L.
      • Marcos C.
      • Garcia S.
      • Rodríguez I.
      Prevalence of ocular surface disease symptoms in peri- and postmenopausal women.
      ]. Contrary to the outcomes of the present study, Wang et al. [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ] found that menopause was only statistically significant in the univariate analysis, but was not statistically significant when its interaction with other variables was analysed.
      Several studies have found an association between DED and psychological conditions such as anxiety, depression and stress [
      • Galor A.
      • Feuer W.
      • Lee D.J.
      • Florez H.
      • Faler A.L.
      • Zann K.L.
      • et al.
      Depression, post-traumatic stress disorder, and dry eye syndrome: A study utilizing the National United States veterans affairs administrative database.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ,
      • Schaumberg D.A.
      • Sullivan D.A.
      • Buring J.E.
      • Dana M.R.
      Prevalence of dry eye syndrome among US women.
      ,
      • Van Der Vaart R.
      • Weaver M.A.
      • Lefebvre C.
      • Davis R.M.
      The association between dry eye disease and depression and anxiety in a large population-based study.
      ,
      • Na K.-S.
      • Han K.
      • Park Y.-G.
      • Na C.
      • Joo C.-K.
      Depression, stress, quality of life, and dry eye disease in korean women: A population-based study.
      ,
      • Karaiskos D.
      • Mavragani C.P.
      • Makaroni S.
      • Zinzaras E.
      • Voulgarelis M.
      • Rabavilas A.
      • et al.
      Stress, coping strategies and social support in patients with primary Sjogren’s syndrome prior to disease onset: A retrospective case-control study.
      ,

      F. Malet M. Le Goff J. Colin C. Schweitzer M.-N. Delyfer J.-F. Korobelnik et al. Dry eye disease in French elderly subjects: The Alienor Study 92 6 2014 e429 e436 10.1111/aos.2014.92.issue-6 10.1111/aos.12174.

      ]. However, there is no evidence whether these diseases are a cause or a consequence of DED. The TFOS DEWS II Epidemiology Report acknowledged the need for clarifying the role of anxiolytics and antidepressants in DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Galor A.
      • Feuer W.
      • Lee D.J.
      • Florez H.
      • Faler A.L.
      • Zann K.L.
      • et al.
      Depression, post-traumatic stress disorder, and dry eye syndrome: A study utilizing the National United States veterans affairs administrative database.
      ,

      F. Malet M. Le Goff J. Colin C. Schweitzer M.-N. Delyfer J.-F. Korobelnik et al. Dry eye disease in French elderly subjects: The Alienor Study 92 6 2014 e429 e436 10.1111/aos.2014.92.issue-6 10.1111/aos.12174.

      ]. Different authors [
      • Galor A.
      • Feuer W.
      • Lee D.J.
      • Florez H.
      • Faler A.L.
      • Zann K.L.
      • et al.
      Depression, post-traumatic stress disorder, and dry eye syndrome: A study utilizing the National United States veterans affairs administrative database.
      ,
      • Paulsen A.J.
      • Cruickshanks K.J.
      • Fischer M.E.
      • Huang G.-H.
      • Klein B.E.K.
      • Klein R.
      • et al.
      Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ,
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ,

      F. Malet M. Le Goff J. Colin C. Schweitzer M.-N. Delyfer J.-F. Korobelnik et al. Dry eye disease in French elderly subjects: The Alienor Study 92 6 2014 e429 e436 10.1111/aos.2014.92.issue-6 10.1111/aos.12174.

      ,
      • Ferrero A.
      • Alassane S.
      • Binquet C.
      • Bretillon L.
      • Acar N.
      • Arnould L.
      • et al.
      Dry eye disease in the elderly in a French population-based study (the Montrachet study: Maculopathy, Optic Nerve, nuTRition, neurovAsCular and HEarT diseases): Prevalence and associated factors.
      ] found that anxiolytic medication was a risk factor for the development of dry eye. In support of this, the present study confirmed that anxiolytic medication was independently associated with DED. More precisely, participants who used anxiolytic medication were 5.7 times more likely to suffer from DED. Anxiety was identified as a potential predictor of DED (p = 0.016) in the univariate analysis, but was not independently associated with DED in the multivariate analysis. Therefore, the association between DED and anxiety could result as a consequence of the relationship between DED and anxiolytics. Besides, the use of daily medication was identified as a potential risk factor in the univariate analysis, but was not independently associated with DED in the multivariate analysis. Finally, no relationship was found with any other medical conditions.

      4.3 Lifestyle, exercise and environmental conditions

      Environmental factors such as air pollution, wind, low humidity, use of central heating or air conditioning have been suggested to impact the integrity of the ocular surface [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Asiedu K.
      • Kyei S.
      • Boampong F.
      • Ocansey S.
      Symptomatic Dry Eye and Its Associated Factors: A Study of University Undergraduate Students in Ghana.
      ,

      D.B. Azzam N. Nag J. Tran L. Chen K. Visnagra K. Marshall et al. A Novel Epidemiological Approach to Geographically Mapping Population Dry Eye Disease in the United States Through Google Trends 40 3 2021 282 291.

      ,
      • Novaes P.
      • Hilário do Nascimento Saldiva P.
      • Matsuda M.
      • Macchione M.
      • Peres Rangel M.
      • Kara-José N.
      • et al.
      The effects of chronic exposure to traffic derived air pollution on the ocular surface.
      ,
      • Gupta N.
      • Prasad I.
      • Himashree G.
      • D'Souza P.
      Prevalence of dry eye at high altitude: A case controlled comparative study.
      ]. In the present study, air conditioning was identified as a potential risk factor for DED, but it did not show a statistically significant relationship with DED in the multivariate analysis. No other variable related to the environment showed a statistically significant association with DED. In contrast to the outcomes of this study, Roh et al. [

      H.C. Roh J.K. Lee M. Kim J.-H. Oh M.-W. Chang R.S. Chuck et al. Systemic comorbidities of dry eye syndrome: The Korean national health and nutrition examination survey V, 2010 to 2012 35 2 2016 187 192 10.1097/ICO.0000000000000657.

      ] found that DED was more prevalent in those residing in urban areas and with indoor occupations. Practising regular exercise showed no association with DED either, in agreement with previous studies [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ,
      • Na K.-S.
      • Han K.
      • Park Y.-G.
      • Na C.
      • Joo C.-K.
      Depression, stress, quality of life, and dry eye disease in korean women: A population-based study.
      ,
      • Karaiskos D.
      • Mavragani C.P.
      • Makaroni S.
      • Zinzaras E.
      • Voulgarelis M.
      • Rabavilas A.
      • et al.
      Stress, coping strategies and social support in patients with primary Sjogren’s syndrome prior to disease onset: A retrospective case-control study.
      ]; although Sano et al. [
      • Sano K.
      • Kawashima M.
      • Takechi S.
      • Mimura M.
      • Tsubota K.
      Exercise program improved subjective dry eye symptoms for office workers.
      ] found that physical exercise decreased dry eye symptoms in healthy office workers, which might suggest that exercise has an optimal impact on ocular surface health.
      Regarding sleep hours per day, Murube et al. [
      • Murube J.
      REM sleep: Tear secretion and dreams.
      ] hypothesized that rapid eye movement during sleep serves to increase tear secretion and to humidify and lubricate the ocular surface. The present study confirms that participants sleeping less hours are more likely to suffer from DED. Specifically, each additional sleeping hour reduced the probability of suffering DED by 0.8 times. Conversely, Wang et al. [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] and Na et al. [
      • Na K.-S.
      • Han K.
      • Park Y.-G.
      • Na C.
      • Joo C.-K.
      Depression, stress, quality of life, and dry eye disease in korean women: A population-based study.
      ] did not find any association between DED and hours of sleep.
      It has been also reported that DED is more prevalent in contact lens wearers [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,

      W.-J. Yang Y.-N. Yang J. Cao Z.-H. Man J. Yuan X. Xiao et al. Risk factors for dry eye syndrome: A retrospective case-control study 92 9 2015 e199 e205 10.1097/OPX.0000000000000541.

      ,
      • Paulsen A.J.
      • Cruickshanks K.J.
      • Fischer M.E.
      • Huang G.-H.
      • Klein B.E.K.
      • Klein R.
      • et al.
      Dry eye in the beaver dam offspring study: Prevalence, risk factors, and health-related quality of life.
      ,
      • Tan L.L.
      • Morgan P.
      • Cai Z.Q.
      • Straughan R.A.
      Prevalence of and risk factors for symptomatic dry eye disease in Singapore.
      ,
      • Uchino M.
      • Schaumberg D.A.
      • Dogru M.
      • Uchino Y.
      • Fukagawa K.
      • Shimmura S.
      • et al.
      Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users.
      ,
      • Wang M.T.M.
      • Craig J.P.
      Natural history of dry eye disease: Perspectives from inter-ethnic comparison studies.
      ,
      • Uchino M.
      • Nishiwaki Y.
      • Michikawa T.
      • Shirakawa K.
      • Kuwahara E.
      • Yamada M.
      • et al.
      Prevalence and risk factors of dry eye disease in Japan: Koumi study.
      ]; nevertheless, the present study did not reveal an association, in agreement with other generally more recent studies [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Uchino M.
      • Yokoi N.
      • Uchino Y.
      • Dogru M.
      • Kawashima M.
      • Komuro A.
      • et al.
      Prevalence of dry eye disease and its risk factors in visual display terminal users: The Osaka study.
      ,
      • Shehadeh-Mashor R.
      • Mimouni M.
      • Shapira Y.
      • Sela T.
      • Munzer G.
      • Kaiserman I.
      Risk Factors for Dry Eye after Refractive Surgery.
      ]. Wang et al. [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ], who used the same diagnostic criterion as the present study, did not find an independent association between contact lens wear and DED either, perhaps due to advances in contact lens materials and greater use of daily disposables [
      • Morgan P.B.
      • Murphy P.J.
      • Gifford K.L.
      • Gifford P.
      • Golebiowski B.
      • Johnson L.
      • et al.
      CLEAR - Effect of contact lens materials and designs on the anatomy and physiology of the eye.
      ]. Furthermore, some studies have shown that DED is more prevalent in workers using visual displays as a consequence of a reduced blink frequency and an increase in incomplete blinking during visual display visualization, which have both shown to increase tear evaporation [

      W.-J. Yang Y.-N. Yang J. Cao Z.-H. Man J. Yuan X. Xiao et al. Risk factors for dry eye syndrome: A retrospective case-control study 92 9 2015 e199 e205 10.1097/OPX.0000000000000541.

      ,
      • Uchino M.
      • Yokoi N.
      • Uchino Y.
      • Dogru M.
      • Kawashima M.
      • Komuro A.
      • et al.
      Prevalence of dry eye disease and its risk factors in visual display terminal users: The Osaka study.
      ,
      • Uchino M.
      • Schaumberg D.A.
      • Dogru M.
      • Uchino Y.
      • Fukagawa K.
      • Shimmura S.
      • et al.
      Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users.
      ,
      • Uchino M.
      • Nishiwaki Y.
      • Michikawa T.
      • Shirakawa K.
      • Kuwahara E.
      • Yamada M.
      • et al.
      Prevalence and risk factors of dry eye disease in Japan: Koumi study.
      ]. Wang et al. [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] found that increased hours of digital screen exposure per day was independently associated with DED. Nevertheless, in agreement with other reports [
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ,
      • Asiedu K.
      • Kyei S.
      • Boampong F.
      • Ocansey S.
      Symptomatic Dry Eye and Its Associated Factors: A Study of University Undergraduate Students in Ghana.
      ,
      • Ferrero A.
      • Alassane S.
      • Binquet C.
      • Bretillon L.
      • Acar N.
      • Arnould L.
      • et al.
      Dry eye disease in the elderly in a French population-based study (the Montrachet study: Maculopathy, Optic Nerve, nuTRition, neurovAsCular and HEarT diseases): Prevalence and associated factors.
      ], the present study did not reveal an association between DED and digital display use.
      It has also been suggested that cigarette smoking is a risk factor for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Na K.-S.
      • Han K.
      • Park Y.-G.
      • Na C.
      • Joo C.-K.
      Depression, stress, quality of life, and dry eye disease in korean women: A population-based study.
      ,
      • Makrynioti D.
      • Zagoriti Z.
      • Koutsojannis C.
      • Morgan P.B.
      • Lagoumintzis G.
      Ocular conditions and dry eye due to traditional and new forms of smoking: A review.
      ,
      • Lee S.-Y.
      • Petznick A.
      • Tong L.
      Associations of systemic diseases, smoking and contact lens wear with severity of dry eye.
      ,
      • Matsumoto Y.
      • Dogru M.
      • Goto E.
      • Sasaki Y.
      • Inoue H.
      • Saito I.
      • et al.
      Alterations of the tear film and ocular surface health in chronic smokers.
      ]. Some studies state that not only is smoking a risk factor by itself, but environmental exposure to smoke can develop dry eye symptoms [
      • Makrynioti D.
      • Zagoriti Z.
      • Koutsojannis C.
      • Morgan P.B.
      • Lagoumintzis G.
      Ocular conditions and dry eye due to traditional and new forms of smoking: A review.
      ,
      • Matsumoto Y.
      • Dogru M.
      • Goto E.
      • Sasaki Y.
      • Inoue H.
      • Saito I.
      • et al.
      Alterations of the tear film and ocular surface health in chronic smokers.
      ]. Nevertheless, other authors did not find a significant association with DED and the TFOS DEWS II Epidemiology Report concluded that it is inconclusive whether smoking is a risk factor for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Uchino M.
      • Yokoi N.
      • Uchino Y.
      • Dogru M.
      • Kawashima M.
      • Komuro A.
      • et al.
      Prevalence of dry eye disease and its risk factors in visual display terminal users: The Osaka study.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ,
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ,
      • Tan L.L.
      • Morgan P.
      • Cai Z.Q.
      • Straughan R.A.
      Prevalence of and risk factors for symptomatic dry eye disease in Singapore.
      ,
      • Uchino M.
      • Schaumberg D.A.
      • Dogru M.
      • Uchino Y.
      • Fukagawa K.
      • Shimmura S.
      • et al.
      Prevalence of Dry Eye Disease among Japanese Visual Display Terminal Users.
      ,
      • Ferrero A.
      • Alassane S.
      • Binquet C.
      • Bretillon L.
      • Acar N.
      • Arnould L.
      • et al.
      Dry eye disease in the elderly in a French population-based study (the Montrachet study: Maculopathy, Optic Nerve, nuTRition, neurovAsCular and HEarT diseases): Prevalence and associated factors.
      ,
      • Uchino M.
      • Nishiwaki Y.
      • Michikawa T.
      • Shirakawa K.
      • Kuwahara E.
      • Yamada M.
      • et al.
      Prevalence and risk factors of dry eye disease in Japan: Koumi study.
      ]. In this regard, in agreement with the study of Wang et al. [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ], the results of this study did not reveal an association between DED and smoking.

      4.4 Diet

      Diet quality has been also reported as possibly associated with DED. Conditions such as vitamin A or D deficiency, eating disorders or a vegan diet might be related to DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,

      W.-J. Yang Y.-N. Yang J. Cao Z.-H. Man J. Yuan X. Xiao et al. Risk factors for dry eye syndrome: A retrospective case-control study 92 9 2015 e199 e205 10.1097/OPX.0000000000000541.

      ,
      • Machowicz A.
      • Hall I.
      • de Pablo P.
      • Rauz S.
      • Richards A.
      • Higham J.
      • et al.
      Mediterranean diet and risk of Sjögren’s syndrome.
      ,
      • Liu J.
      • Dong Y.i.
      • Wang Y.
      Vitamin D deficiency is associated with dry eye syndrome: a systematic review and meta-analysis.
      ]. In the present study, poor diet quality approached the statistical significance cut-off in the multivariate analysis (p = 0.050). The percentage of ultra-processed food was included in the multivariate analysis since it was found to be a potential predictor of DED in the univariate analysis (p = 0.084). However, it did not reveal an independent association with DED. Essential fatty acids play a relevant role in the tear film and ocular surface healthiness since they enhance the tear film lipid layer and reduce the expression of some inflammatory markers [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,

      W.-J. Yang Y.-N. Yang J. Cao Z.-H. Man J. Yuan X. Xiao et al. Risk factors for dry eye syndrome: A retrospective case-control study 92 9 2015 e199 e205 10.1097/OPX.0000000000000541.

      ,
      • Bhargava R.
      • Kumar P.
      • Phogat H.
      • Kaur A.
      • Kumar M.
      Oral omega-3 fatty acids treatment in computer vision syndrome related dry eye.
      ]. This role is still not fully understood, however [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ]. The present study did not find an association between DED and non-oily fish or non-omnivorous diet.
      Regarding alcohol consumption, the TFOS DEWS II Epidemiology Report considered the evidence as inconclusive as to whether it was a risk factor for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Moss S.E.
      • Klein R.
      • Klein B.E.K.
      Long-term incidence of dry eye in an older population.
      ]. In agreement with the study of Wang et al. [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ], the present study did not find an association between alcohol consumption and DED.
      Some studies [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ] have reported that drinking caffeine increases tear production; in the present study this factor did not reveal an independent association with DED, although the univariate analysis showed that participants who did not drink caffeine had 1.7 times more probability to suffer from DED (p = 0.023). In the study of Wang et al. [
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ] reduced caffeine intake per day was indentified as a risk factor for DED.

      4.5 Ocular surgery

      Ocular surgery, such as refractive or cataract surgery, have been identified as potential risk factors for DED [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Ahn J.M.
      • Lee S.H.
      • Rim T.H.T.
      • Park R.J.
      • Yang H.S.
      • Kim T.i.
      • et al.
      Prevalence of and risk factors associated with dry eye: The Korea National Health and Nutrition Examination Survey 2010–2011.
      ,
      • Shehadeh-Mashor R.
      • Mimouni M.
      • Shapira Y.
      • Sela T.
      • Munzer G.
      • Kaiserman I.
      Risk Factors for Dry Eye after Refractive Surgery.
      ,
      • Lin X.
      • Wu Y.
      • Chen Y.
      • Zhao Y.
      • Xiang L.
      • Dai Q.i.
      • et al.
      Characterization of meibomian gland atrophy and the potential risk factors for middle aged to elderly patients with cataracts.
      ,
      • Ferrero A.
      • Alassane S.
      • Binquet C.
      • Bretillon L.
      • Acar N.
      • Arnould L.
      • et al.
      Dry eye disease in the elderly in a French population-based study (the Montrachet study: Maculopathy, Optic Nerve, nuTRition, neurovAsCular and HEarT diseases): Prevalence and associated factors.
      ,
      • Wang M.T.M.
      • Craig J.P.
      Natural history of dry eye disease: Perspectives from inter-ethnic comparison studies.
      ,
      • Sambhi R.-D.
      • Sambhi G.D.S.
      • Mather R.
      • Malvankar-Mehta M.S.
      Dry eye after refractive surgery: a meta-analysis.
      ,
      • Garg P.
      • Gupta A.
      • Tandon N.
      • Raj P.
      Dry eye disease after cataract surgery: Study of its determinants and risk factors.
      ]. Ocular surgery was included in the multivariate analysis since it was found to be a potential predictor of DED in the univariate analysis (p = 0.145), but it did not reveal an independent association with DED.
      The present study has some limitations that must be taken into account. First, dry eye classification subtypes (aqueous deficient and evaporative) were not considered in the analysis. Thus, both types of DED were analysed altogether. Medical history, environmental and lifestyle factors were self-reported by participants, which might have induced recall bias, although this can be considered as an inherent limitation of any cross-sectional study.
      The magnitude of the prevalence of DED was higher than in previous studies of similar nature. Thus, the presented prevalence was corrected for the general population and was still notably higher than that reported in New Zealand using the same diagnostic criteria [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ,
      • Wang M.T.M.
      • Muntz A.
      • Mamidi B.
      • Wolffsohn J.S.
      • Craig J.P.
      Modifiable lifestyle risk factors for dry eye disease.
      ]. The new DED diagnostic criterion, described in the TFOS DEWS II, is less restrictive and has been reported to increase the prevalence of the disease [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ]. Heat and humidity of the region could also have increased the prevalence in a Mediterranean Caucasian population. Previous research [
      • Tesón M.
      • López-Miguel A.
      • Neves H.
      • Calonge M.
      • González-García M.J.
      • González-Méijome J.M.
      Influence of climate on clinical diagnostic dry eye tests: Pilot study.
      ] found that dry eye was more prevalent in Spain than in another country with different levels of environmental humidity. Moreover, a recent study [
      • Darbà J.
      • Ascanio M.
      Economic impact of dry eye disease in Spain: A multicentre retrospective insurance claims database analysis.
      ] informed that the number of patients with DED has increased steadily throughout the years in Spain, which might be partially caused by modern-day workplace in Spanish society. In addition, the high prevalence found in the present study might be in agreement with the high incidence of clinical tests, sale of dry eye products and the number of dry eye specialist visits reported in Spain [
      • Millán A.
      • Viso E.
      • Gude F.
      • Parafita-Fernández A.
      • Moraña N.
      • Rodríguez-Ares M.T.
      Incidence and risk factors of dry eye in a Spanish adult population: 11-year follow-up from the Salnés eye study.
      ,
      • McDonald M.
      • Patel D.A.
      • Keith M.S.
      • Snedecor S.J.
      Economic and Humanistic Burden of Dry Eye Disease in Europe, North America, and Asia: A Systematic Literature Review.
      ,
      • Viso E.
      • Gude F.
      • Rodríguez-Ares M.T.
      The association of meibomian gland dysfunction and other common ocular diseases with dry eye: A population-based study in Spain.
      ,
      • Clegg J.P.
      • Guest J.F.
      • Lehman A.
      • Smith A.F.
      The annual cost of dry eye syndrome in France, Germany, Italy, Spain, Sweden and the United Kingdom among patients managed by ophthalmologists.
      ,
      • Viso E.
      • Rodriguez-Ares M.T.
      • Gude F.
      Prevalence of and associated factors for dry eye in a Spanish adult population (The Salnes Eye Study).
      ]. Although all these points might explain the high prevalence of DED in the results, the recruitment process through an open advertisement could also have induced a higher prevalence of DED than expected in the general population.Some of these limitations are also acknowledged to exist in previous studies with similar designs [
      • Stapleton F.
      • Alves M.
      • Bunya V.Y.
      • Jalbert I.
      • Lekhanont K.
      • Malet F.
      • et al.
      TFOS DEWS II Epidemiology Report.
      ,
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ].
      Moreover, although participants were assessed in a single visit and in the same laboratory under controlled environmental conditions, seasonal variations may have induced some variability in the results. Nevertheless, such variations can be considered minimal since measurements were performed between November 2018 and January 2019. As in a previous study [
      • Wang M.T.M.
      • Vidal-Rohr M.
      • Muntz A.
      • Diprose W.K.
      • Ormonde S.E.
      • Wolffsohn J.S.
      • et al.
      Systemic risk factors of dry eye disease subtypes: A New Zealand cross-sectional study.
      ], the wide confidence intervals found, might have decreased the study power, and the high number of variables included might have induced false-positive results. Nonetheless, this issue was partially minimized by the fact that not all these variables were analysed together: although 76 variables were assessed as risk factors in the univariate analysis, only 12 of them were finally analysed together and included in the multivariate logistic regression.
      In addition, the cohort of the present study is not completely representative of the Spanish population since there is a gap in the ’50 s and ’60 s. To amend this issue, a corrected prevalence for the Spanish population and a corrected risk factor odds ratio were calculated. Likewise, the chances of finding a significant value are low in the factors that are not common in the cohort. Therefore, factors that have a low percentage of people in the sample cannot be excluded as risk factor for DED. Finally, the main limitation of this work was the number of participants recruited, which could explain the lack of association with factors such as age or sex, although the sample analysis showed that such sample size was able to provide a good level of statistical power. In any case, the results of the present study allow a hypothesis to be built for testing in future studies.
      Overall, the present study found that DED following the diagnostic guidelines of the TFOS DEWS II Diagnostic Methodology Report had a prevalence of 57.7 % in a Mediterranean Caucasian population. DED is independently associated with anxiolytic medication, less sleep hours per day and menopause. This work identifies the key risk factors of DED to be used in the screening of the condition. Clinicians should acknowledge the importance of triaging questions, systemic comorbidities and risk factors when managing a patient with dry eye symptoms. Moreover, the present study identifies potentially modifiable risk factors, in addition to conventional treatments for DED. Finally, clinicians should be aware that not only ocular surface assessment, but also systemic and environmental examination are relevant for DED participants.

      Acknowledgements

      This work was supported by the research and innovation programme under the Marie Sklodowska-Curie grant agreement [No. 642760 EDEN ITN-EJD Project Horizon 2020], an “Atracció de Talent” scholarship [UV-INV-PREDOC18F2-886420] awarded to Jose Vicente García-Marqués; and a “Formación de Profesorado Universitario” Scholarship [FPU17/03665, Ministerio de Educación, Cultura y Deporte] awarded to Cristian Talens-Estarelles. The funding sources had no role in the preparation of the manuscript. The authors would like to thank Dr. Maria Vidal-Rohr for her contribution to the development of the study protocol.

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