Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Patients with Blepharitis Are at Elevated Risk of Anxiety and Depression

  • Chun-Chi Chiang,

    Affiliations Department of Ophthalmology, China Medical University Hospital, Taichung, Taiwan, School of Medicine, China Medical University, Taichung, Taiwan

  • Cheng-Li Lin,

    Affiliation Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan

  • Yi-Yu Tsai,

    Affiliations Department of Ophthalmology, China Medical University Hospital, Taichung, Taiwan, School of Medicine, China Medical University, Taichung, Taiwan

  • Chiao-Ling Peng,

    Affiliation Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan

  • Ya-Tang Liao,

    Affiliation Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan

  • Fung-Chang Sung

    fcsung@mail.cmu.edu.tw

    Affiliations Management Office for Health Data, China Medical University Hospital, Taichung, Taiwan, Department of Public Health, China Medical University College of Public Health, Taichung, Taiwan

Patients with Blepharitis Are at Elevated Risk of Anxiety and Depression

  • Chun-Chi Chiang, 
  • Cheng-Li Lin, 
  • Yi-Yu Tsai, 
  • Chiao-Ling Peng, 
  • Ya-Tang Liao, 
  • Fung-Chang Sung
PLOS
x

Abstract

Purpose

Population-based cohort study on the risk of anxiety and depression in patients with blepharitis is limited. This study evaluated whether blepharitis patients are at a higher risk of anxiety and depression.

Design

A retrospective cohort study.

Methods

We used the universal insurance claims data from 1997 to 2010 in Taiwan to identify annually patients with newly diagnosed blepharitis (N = 9764) and without the disease (N = 39056). Incidences, rate ratios (IRR) and hazard ratios (HR) of anxiety and depression were measured for both cohorts by baseline demographic characteristics and comorbidities until the end of 2010.

Results

Compared with the non-blepharitis cohort, the blepharitis cohort had higher incidence of anxiety (15.9 vs. 9.5 per 1000 person-years), with an adjusted HR of 1.58 (95% confidence interval (CI) = 1.46–1.70). The incidence of depression was also higher in the blepharitis cohort (7.66 vs. 5.05 per 1000 person-years), with an adjusted HR of 1.42 (95% CI = 1.28–1.58). The blepharitis cohort to the non-blepharitis cohort IRR decreased from 1.73 in the first quartile to 1.32 in the 4th quartile for anxiety, and from 1.67 to 1.29 for depression.

Conclusions

Patients with blepharitis are at elevated risks of anxiety and depression. The risk is higher in earlier period after the diagnosis of blepharitis, and declines by time, but remains significantly higher for those with blepharitis than those without blepharitis.

Introduction

Characterized by inflamed eyelids, blepharitis is a high prevalent ophthalmic complains difficult to cure in eye care practices[1]. Crust or flakes on eyelashes, stuck eyelids, reddish eyelids, and blurred vision are the common signs and symptoms[2]. The onset of blepharitis can be acute, other than the more generally form of long standing chronic inflammation. Staphylococcal infection, seborrheic, and meibomian gland dysfunction (MGD) are major etiological cause of these conditions[3]. Patients suffer discomfort evaporative dry eye disease are mainly associated with MSG because of ocular surface inflammation[2].The ocular surface condition may further exacerbate due to immune-mediated inflammatory processes[4]. The persistent discomfort eyes, and unattractive appearance, and uneasy feeling may precipitate psychological stress and negative social implications for patients, including depressed and anxious mood[1].

The WHO World Health Survey shows that patients with chronic diseases are more likely to have comorbidity of depression, particularly in patients with angina, arthritis, asthma, and diabetes[5]. For patients with blepharitis, in addition to the burden of the disease and vision disturbance, there are other factors that may contribute to the risk of psychologic condition. The drugs used to treat inflammatory diseases, such as corticosteroids, have been associated with the risk of mania, depression, and other behavioral changes[6]. There are also evidences that cytokines are able to cross the blood-brain barrier linking with behavioral changes in patients with chronic inflammation[7], [8]. A combination of these factors may place patients with ocular inflammatory diseases at an elevated risk for mood dysfunction.

Because of uncomfortable and distressing conditions, we hypothesized that patients with blepharitis would be at an increased risk of mental illness including major depression and anxiety. No large study has ever evaluated the association using prospective design. This study conducted a retrospective follow-up observation to estimate the risk of depression and anxiety in patients with blepharitis using a nationwide insurance dataset in Taiwan.

Methods and Materials

Study Design and Data Source

We obtained a representative claims data of one million insured people in the National Health Insurance Research Database (NHIRD). This universal health insurance program has covered nearly 99% of the 23.74 million residents and contracted with 97% of the hospitals and clinics for comprehensive health care in Taiwan[9]. In this study, patients with blepharitis were identified from the NHIRD inpatient and outpatient expenditure claims data files from 1997 until the end of 2010. These files contained the information on demographic status (birth date and sex) of insured population and services provided, and reimbursements for the services. The diagnoses of diseases used the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM). For the confidentiality, patient identifications were scrambled according to the Department of Health regulations to strengthen data security and protect patient's privacy. This study was exempted from full ethical review (IRB permit number: CMU-REC-101-012).

Study Subjects And Comorbidities

Patients who had made at least three outpatient visits with diagnoses of blepharitis (ICD-9-CM code 373.0) were eligible for the study and identified annually from 1997 to 2010 for the blepharitis cohort. The first diagnosis date was defined as index date for estimating the follow-up time. For each blepharitis patients, 4 persons free from the disease were identified from the rest of claims data for the non-blepharitis cohort, with age, sex and index year frequency matched. Patients with the history of depression (ICD-9-CM: 300.00, 296.2, 296.3, 300.4 and 311) or anxiety (ICD-9-CM: 300.00) before the index date or with missing information on age or sex were excluded. The diseases considered to be comorbidities included hypertension (ICD-9- CM codes 401 to 405, A260, A269), diabetes (ICD-9-CM codes 250, A181), hyperlipidemia (ICD-9-CM codes 272, A182), coronary artery disease (ICD-9-CM codes 410 to 414, A270, A279) and stroke (ICD-9-CM codes 430 to 438, A290 to A299).

Statistical Analysis

Chi-square test was used to examine the distributions of baseline demographic characteristics and comorbidities between blepharitis and non-blepharitis cohorts. Follow-up person-years were estimated for all subjects in both cohorts until depression or anxiety identified, or censored because of loss to follow-up or withdrawn from the insurance, or the end of 2010. Incidence rates of depression and anxiety were estimated by demographic status and comorbidities. The blepharitis cohort to the non-blepharitis cohort incidence rate ratio (IRR) and 95% confidence interval (CI) were calculated using Poisson regression analysis. Cox proportional hazards regression analysis was also used to measure the hazard ratios (HR) and 95% confidence intervals (CI) of depression and anxiety associated with blepharitis, adjusting for covariates. We also depicted the blepharitis cohort to the non-blepharitis cohort IRR of depression and anxiety by follow-up years in quartiles. A p value of less than 0.05 was considered to be statistically significant. All analyses were performed using the SAS statistical package for Windows, version 9.2 (SAS institute, Inc., Cary, NC, USA).

Results

This study identified 9764 persons for the blepharitis cohort and 39056 persons for the non-blepharitis cohort. Both cohorts were similar in age and sex distributions with a mean age of 54.9±18 years and near 60% of subjects were women (Table 1). Compared with the non-blepharitis cohort, patients in the blepharitis cohort were more prevalent with hypertension, diabetes mellitus, hyperlipidemia, stroke and coronary artery disease.

thumbnail
Table 1. Demographic characteristics and comorbidities in blepharitis cohort and non-blepharitis cohort.

https://doi.org/10.1371/journal.pone.0083335.t001

The incidence rate of anxiety was 1.67-fold higher in the blepharitis cohort than in the non-blepharitis cohort (15.9 vs. 9.5 per 1000 person-years), with an adjusted HRs of 1.58 (95% CI = 1.46–1.70) (Table 2). So was the incidence of depression 1.52-fold higher in the blepharitis cohort (7.66 vs. 5.05 per 1000 person-years), with an adjusted HRs of 1.42 (95% CI = 1.28–1.58). The incidence rates of both anxiety and depression were higher in women than in men, and increased with age in both cohorts. The gender and age differences in the incidence rates of anxiety were greater than that of depression. However, the age-specific blepharitis cohort to non-blepharitis cohort IRR of anxiety were higher in those in less 40 years of age, with an adjusted HR of 1.97 (95% CI = 1.59–2.43). The adjusted HR reduced to 1.56 (95% CI 1.39, 1.75) for the elderly.

thumbnail
Table 2. Incidence rates by sex, age and cohort, and blepharitis cohort to non-blepharitis cohort rate ratios and Cox model measured hazard ratios.

https://doi.org/10.1371/journal.pone.0083335.t002

The comorbidity specific analysis in the multivariable Cox proportional hazards regression model showed consistently higher incidence rates of anxiety and depression in the blepharitis cohort than in the non-blepharitis cohort (Table 3). The incidence increased further in blepharitis patients with comorbidity, particularly in those had a stroke. Figure 1 shows that the blepharitis cohort to the non-blepharitis cohort IRR for both anxiety and depression declined by follow-up time, from 1.73 in the first quartile to 1.40 in the 4th quartile for anxiety, and from 1.67 to 1.18 for depression.

thumbnail
Figure 1. Blepharitis cohort to non-blepharitis cohort incidence rate ratio of anxiety and depression by quartile of follow-up years.

https://doi.org/10.1371/journal.pone.0083335.g001

thumbnail
Table 3. Incidence of depression and anxiety, blepharitis cohort to non-blepharitis cohort rate ratio and Cox model measured hazards ratio by comorbidity.

https://doi.org/10.1371/journal.pone.0083335.t003

Discussion

Blepharitis is a common ocular disease that has been associated with many systemic medical conditions. In an age and gender matched retrospective case-control study (n = 16706 each group), Nemet et al found that patients with blepharitis are prevalent with not only psychologic conditions, but also systemic conditions and other eye conditons[10]. A survey conducted in the US showed that approximately 37% of patients seen by ophthalmologists and 47% of patients seen by optometrists have complains of blepharitis[2]. Both the ophthalmologic disorder and the associated mood dysfunction are important factors affecting the quality of life of patients. In this study, we found that patients with blepharitis had a 67% higher risk of anxiety and 52% higher risk of depression in the 9-year follow-up period. The risk of anxiety shown in our cohort analysis is consistent with the odds ratio of 1.6 (95% CI 1.4–1.9) found by Nemet et al.[10].

The occurrence of blepharitis and subsequent psychologic conditions have been associated with psychoneuroimmunology and inflammation[7], [8], [11][17]. Patients with blepharitis are at higher risk to have other medical conditions, which may also associate the psychologic consequence[10]. Recent studies have shown that chronic inflammatory and cytokines dysregulation are significant factors relate to the pathophysiology of depression and anxiety[18], [19]. Levels of circulating cytokines interleukin (IL)-1beta, IL-6, interferon gamma, and TNF-alpha are higher in depressed patients than in controls[20]. Patients with cardinal inflammation accompany with depression have elevated inflammatory cytokines and their soluble receptors presenting in peripheral blood and cerebrospinal fluid[21], [22]. Concentrations of acute phase proteins, chemokines, adhesion molecules, and inflammatory prostaglandins are also increased in peripheral blood. Eyelids are rich with blood supply. A murine model has also demonstrated that the concentration of inflammatory cytokines in tear is elevated in response to evaporative dry eye stress, which usually results from blepharitis[23]. Therefore, both psychologic disorder and blepharitis may be affected by the inflammatory reactions.

Previous studies have found that women are up to 3 times more likely to experience depressive disorders than men, including depression, anxiety, and co-existing depression and anxiety[24][30]. Our results also revealed that the incidence rates of both anxiety and depression were higher in women than in men, which is consistent with previous reports. However, the sex-specific blepharitis cohort to non-blepharitis cohort IRR shows that relative risks of both anxiety and depression are higher for men than for women. We hypothesize the sex hormone may play a role in the gender difference. Increasing evidences have shown that gene expression of the meibomiam glands, dry eye syndrome, MGD, and evaporative dry eyes are associated with sex steroids[31][39]. The incidence of anxiety increased markedly with age in our study. The hormonal therapy in postmenopausal women may have an important role leading to blepharitis and mood dysfunction[32], [34], [35], [38].

Previous clinical and community-based studies have suggested that the prevalence of depression, anxiety, and comorbid disorder decline with age[40][42]. Different study designs may attribute to the discrepancy between our finding and results from other studies. There are sufficient medical resources and facilities with convenient access to care for insured people in Taiwan. The elderly patients are easily to get the medical attention. This may explain why the incidence rates of depression and anxiety are higher in older people in this study. Compare with non-blepharitis patients, patients with blepharitis suffer from chronic ocular discomfortable and blurred vision, which affect the quality of life, especially for older people. Hence, these patients have higher tendency to develop depression and anxiety. Nevertheless, the age-specific relative risk of anxiety was some what higher for those aged 20–39 years than the elderly in the blepharitis cohort (IRRs: 1.99 vs. 1.65). The young group is the main working force; the blepharitis symptoms such as ocular discomfortable and physical appearance may affect their work performances and social activities, which induce higher anxiety than their peers without blepharitis.

In addition, compared with non-blepharitis cohort, patients in the blepharitis cohort were also more prevalent with hypertension, diabetes mellitus, hyperlipidemia, stroke and coronary artery disease. Studies have demonstrated a clear relationship between inflammation and the development of cardiovascular disease, diabetes, and cancer[43], [44]. Nemet et al also found some major cardiovascular conditions (carotid artery disease, hyperlipidemia, and hypertension) to be associated with blepharitis[10]. Our results are also consistent with their report.

There are few limitations in our study. First, we used International Classification of Diseases codes to identified diagnoses of blepharitis, depression, anxiety and other medical conditions. People with mild symptoms may not go to the doctor resulting undiagnosed cases. Patients with blepharitis might have more clinic visits than those without blepharitis. We conducted a further data analysis and found that the average number of clinic visit was higher in blepharitis patients than in the comparisons [32.3 (SD 24.4) vs. 20.0 (SD 18.1)]. Therefore, blepharitis patients are more likely to be diagnosed and to get treatment for depression and anxiety. Second, although there may be a small number of patients with undetected blepharitis would be categorized as non-blepharitis and would have a small chance of being selected as part of the comparison cohort. The sample size of each cohort was large enough to compromise the bias. However, the results need to be interpreted with caution.

Blepharitis is characterized by discomfort eyes and unattractive appearance, which may cause uneasy feeling and negative social implications for the patients. The present study shows patients with blepharitis are at higher risk of anxiety or depression. Our findings are of clinical importance given the high prevalence of blepharitis in the general population, and the fact that depression and anxiety are disorders readily treatable and often under diagnosed because its symptoms are frequently overlooked.

Author Contributions

Conceived and designed the experiments: CCC YYT. Performed the experiments: CLL CLP YTL. Analyzed the data: CLL CLP YTL. Contributed reagents/materials/analysis tools: CLL YTL FCS. Wrote the paper: CCC CLL.

References

  1. 1. McDonald MB (2009) The patient's experience of blepharitis. Ocul Surf. 7(suppl): S17–18.
  2. 2. Lemp MA, Nichols KK (2009) Blepharitis in the United States: a survey-based perspective on prevalence and treatment. Ocul Surf 7(suppl): S1–S14.
  3. 3. AAO 2008 American Academy of Ophthalmology Retina Panel (2008) Preferred Practice Pattern® Guidelines. Blepharitis. San Francisco, CA: American Academy of Ophthalmology. http://www.aao.org/ppp (accessed 3 April 2012).
  4. 4. Pflugfelder SC, Solomon A, Stern ME (2000) The diagnosis and management of dry eye: a twenty-five-year review. Cornea 19: 644–649.
  5. 5. Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, et al. (2007) Depression, chronic diseases, and decrements in health: Results from the World Health Surveys. Lancet 370: 851–858.
  6. 6. Warrington TP, Bostwick JM (2006) Psychiatric adverse effects of corticosteroids. Mayo Clin Proc 81: 1361–1367.
  7. 7. Dantzer R, O'Connor JC, Freund GG, Johnson RW, Kelley KW (2008) From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 9: 46–56.
  8. 8. Miller AH (2009) Norman Cousins Lecture. Mechanisms of cytokine-induced behavioral changes: psychoneuroimmunology at the translational interface. Brain Behav Immune 23: 149–158.
  9. 9. Cheng TM (2009) Taiwan's national health insurance system: High value for the dollar. In: Okma KGH, Crivelli L, eds. Six Countries, Six Reform Models: The Healthcare Reform, Experience of Israel, the Netherlands, New Zealand, Singapore, Switzerland and Taiwan. Hackensack, New Jersey: World Scientific 171–204.
  10. 10. Nemet AY, Vinker S, Kaiserman I (2011) Associated morbidity of blepharitis. Ophthalmology 118: 1062–1068.
  11. 11. Foulks GN (2007) The correlation between the tear film lipid layer and dry eye disease. Surv Ophthalmol 52: 369–374.
  12. 12. McCulley JP, Dougherty JM, Deneau DG (1982) Classification of chronic blepharitis. Ophthalmology 89: 1173–1180.
  13. 13. Foulks GN, Bron AJ (2003) A clinical description of meibomian gland dysfunction. Ocul Surf 1: 107–126.
  14. 14. Solomon A, Dursun D, Liu Z (2001) Pro- and anti-inflammatory forms of interleukin-1 in the tear fluid and conjunctiva of patients with dry-eye disease. Invest Ophthalmol Vis Sci 42: 2282–2292.
  15. 15. Korb DR, Scaffidi RC, Greiner JV, Kenyon KR, Herman JP, et al. (2005) The effect of two novel lubricant eye drops on tear film lipid layer thickness in subjects with dry eye symptoms. Optom Vis Sci 82: 594–601.
  16. 16. Pisella PJ, Brignole F, Debbasch C (2000) Flow cytometric analysis of conjunctival epithelium in ocular rosacea and keratoconjunctivitis sicca. Ophthalmology 107: 1841–1849.
  17. 17. Rubin M, Rao SN (2006) Efficacy of topical cyclosporin 0.05% in the treatment of posterior blepharitis. J Occul Phamacol Ther 22: 47–53.
  18. 18. Vogelzangs N, Duivis HE, Beekman AT, Kluft C, Neuteboom J, et al. (2012) Association of depressive disorders, depression characteristics and antidepressant medication with inflammation. Transl Psychiatry 2: e79.
  19. 19. Salim S, Chugh G, Asghar M (2012) Inflammation in anxiety. Adv Protein Chem Struct Biol 88: 1–25.
  20. 20. Anisman H, Merali Z, Hayley S (2008) Neurotransmitter, peptide and cytokine processes in relation to depressive disorder: Comorbidity between depression and neurodegenerative disorders. Prog Neurobiol 85: 1–74.
  21. 21. Raison CL, Capuron L, Miller AH (2006) Cytokines sing the blues: Inflammation and the pathogenesis of major depression. Trend Immunol 27: 24–31.
  22. 22. Zorilla EP, Luborsky L, McKay JR, Roesnthal R, Houldin A, et al. (2001) The relationship of depression and stressors to immunological assays: A meta-analytic review. Brain Behav Immun 15: 199–226.
  23. 23. Lam H, Bleiden L, De Paiva CS, Farley W, Stern ME, et al. (2009) Tear cytokine profiles in dysfunctional tear syndrome. Am J Ophthalmol 147: 198–205.e1.
  24. 24. Kessler R (2006) The epidemiology of depression among women. In: Keys C, Goodman S, editors. Women and Depression: A Handbook of the Social, Behavioral, and Biomedical Sciences. New York: Cambridge University Press; 22–37.
  25. 25. Weissman M, Bland R, Canino G, Faravelli C, Greenwald S, et al. (1996) Cross-national epidemiology of major depression and bipolar disorder. JAMA 276: 293–299.
  26. 26. Palanza P (2001) Animal models of anxiety and depression: how are females different? Neurosci Biobehav Rev 25: :219–233. Review.
  27. 27. Kuehner C (2003) Gender differences in unipolar depression: an update of epidemiological findings and possible explanations. Acta Psychiatr Scand 108: 163–174.
  28. 28. Pigott TA (1999) Gender differences in the epidemiology and treatment of anxiety disorders. J Clin Psychiatry 60 (Suppl 18)4–15.
  29. 29. Cohen CI, Magai C, Yaffee R, Walcott-Brown L (2006) The prevalence of anxiety and associated factors in a multiracial sample of older adults. Psychiatr Serv 57: 1719–1725.
  30. 30. Mehta KM, Simonsick EM, Penninx BW, Schulz R, Rubin SM, et al. (2003) Prevalence and correlates of anxiety symptoms in well- functioning older adults: findings from the health aging and body composition study. J Am Geriatr Soc 51: 499–504.
  31. 31. Sullivan BD, Evans JE, Cermak JM, Krenzer KL, Dana MR, et al. (2002) Complete androgen insensitivity syndrome: effect on human meibomian gland secretions. Arch Ophthalmol 120: 1689–99.
  32. 32. Sullivan BD, Evans JE, Dana MR, Sullivan DA (2002) Impact of androgen deficiency on the lipid profiles in human meibomian gland secretions. Adv Exp Med Biol 506: 449–458.
  33. 33. Sullivan BD, Evans JE, Krenzer KL, Reza Dana M, Sullivan DA (2000) Impact of antiandrogen treatment on the fatty acid profile of neutral lipids in human meibomian gland secretions. J Clin Endocrinol Metab 85: 4866–4873.
  34. 34. Sullivan DA, Jensen RV, Suzuki T, Richards SM (2009) Do sex steroids exert sex-specific and/or opposite effects on gene expression in lacrimal and meibomian glands? Mol Vis 15: 1553–1572.
  35. 35. Sullivan DA, Krenzer KL, Sullivan BD, Tolls DB, Toda I, et al. (1999) Does androgen insufficiency cause lacrimal gland inflammation and aqueous tear deficiency? Invest Ophthalmol Vis Sci 40: 1261–1265.
  36. 36. Sullivan DA, Rocha EM, Ullman MD, Krenzer KL, Gao J, et al. (1998) Androgen regulation of the meibomian gland. Adv Exp Med Biol 438: 327–331.
  37. 37. Sullivan DA, Sullivan BD, Evans JE, Schirra F, Yamagami H, et al. (2002) Androgen deficiency, meibomian gland dysfunction, and evaporative dry eye. Ann N Y Acad Sci 966: 211–222.
  38. 38. Sullivan DA, Sullivan BD, Ullman MD, Rocha EM, Krenzer KL, et al. (2000) Androgen influence on the meibomian gland. Invest Ophthalmol Vis Sci 41: 3732–3742.
  39. 39. Sullivan DA, Yamagami H, Liu M, Steagall RJ, Schirra F, et al. (2002) Sex steroids, the meibomian gland and evaporative dry eye. Adv Exp Med Biol 506: 389–399.
  40. 40. Jeste DV, Blazer DG, First M (2005) Aging-related diagnostic variations: need for diagnostic criteria appropriate for elderly psychiatric patients. Biol Psychiatry 58: 265–271.
  41. 41. Hybels CF, Blazer DG (2003) Epidemiology of late-life mental disorders. Clin Geriatr Med 19: 663–696.
  42. 42. Henderson AS, Jorm AF, Korten AE, Jacomb P, Christensen H, et al. (1998) Symptoms of depression and anxiety during adult life: evidence for a decline in prevalence with age. Psychol Med 28: 1321–1328.
  43. 43. Aggarwal BB, Shishodia S, Sandur SK, Pandey MK, Sethi G (2006) Inflammation and cancer: How hot is the link? Biochem Pharmacol 72: 1605–1621.
  44. 44. Ridker PM (2007) Inflammatory biomarkers and risks of myocardial infarction, stroke, diabetes, and total mortality: Implications for longevity. Nutr Rev 65: S253–259.