Purpose
To estimate dry eye prevalence in the Beaver Dam Offspring Study (BOSS), including a young adult population, and investigate associated risk factors and impact on health-related quality of life.
Design
Cohort study.
Methods
The BOSS (2005-2008) is a study of aging in the adult offspring of the population-based Epidemiology of Hearing Loss Study cohort. Questionnaire data on health history, medication use, risk factors, and quality of life were available for 3275 participants. Dry eye was determined by self-report of frequency of symptoms and the intensity of those symptoms. Associations between dry eye and risk factors were analyzed using logistic regression.
Results
The prevalence of dry eye in the BOSS was 14.5%: 17.9% of women and 10.5% of men. In a multivariate model, statistically significant associations were found with female sex (odds ratio [OR], 1.68; 95% confidence interval [CI], 1.33-2.11), current contact lens use (OR, 2.01; 95% CI, 1.53-2.64), allergies (OR, 1.59; 95% CI, 1.22-2.08), arthritis (OR, 1.44; 95% CI, 1.12-1.85), thyroid disease (OR, 1.43; 95% CI, 1.02-1.99), antihistamine use (OR, 1.54; 95% CI, 1.18-2.02), and steroid use (OR, 1.54; 95% CI, 1.16-2.06). Dry eye was also associated with lower scores on the Medical Outcomes Study Short Form 36 (β = −3.9, P < .0001) as well as on the National Eye Institute 25-Item Visual Function Questionnaire (NEI VFQ-25) (β = −3.4, P < .0001) when controlling for age, sex, and comorbid conditions.
Conclusions
The prevalence of dry eye and its associated risk factors in the BOSS were similar to previous studies. In this study, dry eye was associated with lower quality of life on a health-related quality-of-life instrument and the vision-specific NEI VFQ-25.
Dry eye is a multifactorial disease of the tears and ocular surface, resulting in symptoms of discomfort, visual disturbance, and tear film instability with potential damage to the ocular surface. Dry eye can be characterized by a dry, gritty, or burning feeling in the eyes, which may be accompanied by excessive tearing or sensitivity to light, among other symptoms. Prevalence estimates of dry eye disease and severe symptoms have largely varied by study, ranging between 5% and 35%. Dry eye has been shown to affect visual functioning, including visual acuity, as well as to have a negative impact on some health-related quality-of-life measures. It has also been found to be correlated with anxiety and depression.
The known association between dry eye and age has led to thorough study of the disorder in older adult populations, generally focusing on those over 50 years of age. The prevalence and associated risk factors for dry eye have not been widely investigated in younger populations. One of the few investigations that included a wider age range of adults (21-90) was conducted in a very specific group of Veterans Affairs patients. Further, the impact of dry eye on quality of life in younger populations is relatively unknown. In one study including younger adults it was found that both health-related quality-of-life measures and a vision-specific measure were sensitive to severity of dry eye, though this was in a small sample recruited from eye clinics.
The aims of this investigation in a large cohort predominately composed of middle-aged adults were to determine the prevalence of dry eye symptoms, identify independent risk factors, and quantify their impact on quality of life.
Methods
The Beaver Dam Offspring Study (BOSS) is an ongoing cohort study of aging in the adult children of the population-based Epidemiology of Hearing Loss Study (EHLS). Baseline examinations of BOSS participants (n = 3285), aged 21-84 years, took place between 2005 and 2008. Information on symptoms of dry eye was provided by 3275 participants. The BOSS was approved by the Health Sciences Institutional Review Board of the University of Wisconsin, all participants provided written informed consent, and all study protocols were carried out in accordance with the tenets of the Declaration of Helsinki.
The BOSS examination consisted of an extensive questionnaire including demographic information, employment history, medical history, risk behaviors, and health-related quality of life. Questionnaires were completed by in-person interviews conducted by technicians trained to a standard protocol or, for those unable to come to the examination sites, by self-administration through a web-based or mailed form (n = 439).
Participants were asked: “How often do you have dry eyes, a dry, gritty, or burning feeling?”; “How much does the dryness in your eyes bother you?”; “Is there a season of the year when the dryness in your eyes is the worst?”; and “Are you currently using eye drops at least once a day for dry eyes?” Objective measures of dry eye, such as the tear break-up time (TBUT) test, Schirmer test, or rose bengal staining, were not administered and information regarding previous doctor diagnosis was not available. Participants who reported that symptoms were present sometimes or more often and that they were moderately bothersome or greater, or those who reported currently using eye drops at least once a day for dry eyes, were considered to be cases.
Health conditions considered in this investigation include history of allergies and doctor-diagnosed systemic diseases including arthritis, osteoporosis, thyroid disease, and diabetes. Hypertension was present if subjects had a measured systolic blood pressure greater than 140 mm Hg or a measured diastolic blood pressure greater than 90 mm Hg (Dynamap Procare 120; GE Medical Systems, Milwaukee, Wisconsin, USA) or had a history of having been told by a doctor that they had high blood pressure and were currently using antihypertensive medications. Information on history of head injury and loss of consciousness was also collected.
Other covariates were considered based on previous findings and biologic plausibility. Medications considered in these analyses included antihistamines, antianxiety medications, acetaminophen, benzodiazepine, anticholinergics, antidepressants, statins, steroids, diuretics, multivitamins, and, among women, hormones used for birth control, infertility, or hormone replacement therapy. Contact lens use (current and past), smoking (current status, pack-years smoked, number of cigarettes per day), alcohol consumption (previous year and grams of ethanol per week), and season at interview were also considered in the analyses.
The Medical Outcomes Study Short Form 36 (SF-36) and the National Eye Institute 25-Item Visual Function Questionnaire (NEI VFQ-25) were administered to assess quality of life. The Physical Component Summary (PCS), Mental Component Summary (MCS), General Health Perception Index (GHPI), and Bodily Pain Index (BPI) were calculated for the SF-36. The composite and 12 subscale scores were calculated for the NEI VFQ-25. The self-administered Center for Epidemiologic Studies Depression Scale (CES-D) was used to assess symptoms of depression.
Risk factor investigation consisted of χ 2 analysis, as well as age- and sex-controlled logistic regression models. Associations were considered statistically significant at or below P value = .05. Additionally, a stepwise procedure was performed to create a final model estimating independent odds of dry eye by risk factor. Risk factors with results suggestive of association ( P value <.10) in age- and sex-adjusted models were considered for entry into the final model. Age and sex were retained in the model, while retention of all other variables was determined by a 2-tailed P value at or below .05.
Mean score differences were calculated between those with and without dry eye symptoms on both the vision-specific and health-related quality-of-life instruments through ordinary single and multiple linear regression models. Finally, the association between dry eye and depressive symptoms (score of 16 or greater on the CES-D) was estimated using logistic regression. All statistical analyses were conducted using SAS version 9.2 (SAS Institute, Cary, North Carolina, USA).
Results
Prevalence
The mean age of the 3275 participants was 49 years (range 21-84 years), 1789 participants (54.6%) were female, and 2271 (69.3%) had higher than a high school education ( Table 1 ). The prevalence of dry eye symptoms was 14.5% overall (14.1% in those aged 21-49 years, 15.2% in those 50 and older) and was significantly higher in women than in men (17.9% vs 10.5%, P < .0001). Although a slight increase in prevalence of dry eye symptoms was observed by age, this trend for the population overall did not reach statistical significance ( P = .06). When stratified by sex, the effect of age on dry eye differed between men and women. In men, estimated prevalence was similar among all age groups and there was no observed effect of age ( P = .91), whereas in women prevalence increased with age ( P = .02), though this interaction was not significant in multivariable models ( Figure 1 ).
| Characteristic | N (%) Overall | N (%) <50 Years of Age | N (%) ≥50 Years of Age | P Value |
|---|---|---|---|---|
| N | 3275 | 1764 | 1511 | .17 |
| Female | 1789 (54.6) | 983 (55.7) | 806 (53.3) | |
| Male | 1486 (45.4) | 781 (44.3) | 705 (46.7) | |
| Age | ||||
| 21-34 | 179 (5.5) | 179 (10.1) | NA | NA |
| 35-44 | 931 (28.4) | 931 (52.8) | NA | |
| 45-54 | 1227 (37.5) | 654 (37.1) | 573 (37.9) | |
| 55-64 | 710 (21.7) | NA | 710 (47.0) | |
| 65-84 | 228 (7.0) | NA | 228 (15.1) | |
| Education (y) | ||||
| <12 | 75 (2.3) | 31 (1.8) | 42 (2.8) | <.0001 |
| 12 | 902 (27.5) | 439 (24.9) | 463 (30.6) | |
| 13-15 | 1088 (33.2) | 597 (33.8) | 491 (32.5) | |
| 16+ | 1183 (36.1) | 688 (39.0) | 495 (32.8) | |
| Smoking history | ||||
| Never | 1751 (53.5) | 1011 (57.3) | 740 (49.0) | <.0001 |
| Past | 927 (28.3) | 392 (22.2) | 535 (35.4) | |
| Current | 576 (17.6) | 351 (19.9) | 225 (14.9) | |
| Alcohol consumption (grams of ethanol per week) | ||||
| 0 | 348 (10.6) | 155 (8.8) | 193 (12.8) | <.0001 |
| 1-14 | 1323 (40.4) | 690 (39.1) | 633 (41.9) | |
| 15-74 | 766 (23.4) | 449 (25.5) | 317 (21.0) | |
| 75-140 | 392 (12.0) | 231 (13.1) | 161 (10.7) | |
| >140 | 426 (13.0) | 229 (13.0) | 197 (13.0) | |
| Body mass index | ||||
| <25 | 607 (18.5) | 418 (23.7) | 189 (12.5) | <.0001 |
| 25-29.9 | 947 (28.9) | 519 (29.4) | 428 (28.3) | |
| 30+ | 1254 (38.3) | 593 (33.6) | 661 (43.7) |
a Column percentages may not add to 100% due to missing data.
Risk Factors
In separate age- and sex-adjusted models, arthritis, osteoporosis, allergies, thyroid disease, severe headaches or migraine in the previous 3 months, and history of head injury were associated with increased odds of dry eye. Use of a number of medications, including antihistamines, acetaminophen, benzodiazepine, antidepressants, and steroids, also was associated with dry eye in the overall population ( Table 2 ). The association of use of steroids with symptoms of dry eye was only significant with inhaled steroid use (odds ratio [OR] = 2.04, 95% confidence interval [CI] = 1.24, 3.33), as oral steroid use did not exhibit a statistically significantly association (OR = 1.47, 95% CI = 0.63, 3.42). Additionally, use of multivitamins was associated with symptoms of dry eye in those under the age of 50.
| Risk Factor | <50 Years of Age a | ≥50 Years of Age a | Overall a |
|---|---|---|---|
| Age b (per increase in age group) | 1.07 (0.87, 1.33) | 1.23 (1.00, 1.50) | 1.01 (1.00, 1.02) |
| Sex | |||
| Male | 1.00 [Reference] | 1.00 [Reference] | 1.00 [Reference] |
| Female | 1.60 (1.21, 2.11) | 2.23 (1.65, 3.01) | 1.88 (1.53, 2.30) |
| Contact lens use | |||
| Never | 1.00 [Reference] | 1.00 [Reference] | 1.00 [Reference] |
| Past | 1.13 (0.79, 1.63) | 1.58 (1.13, 2.21) | 1.34 (1.05, 1.71) |
| Current | 2.39 (1.73, 3.29) | 1.58 (0.98, 2.55) | 2.14 (1.65, 2.77) |
| Chronic conditions | |||
| Arthritis | 2.07 (1.46, 2.94) | 1.31 (0.97, 1.77) | 1.59 (1.26, 2.00) |
| Osteoporosis | 2.29 (0.70, 7.54) | 1.50 (0.85, 2.65) | 1.70 (1.02, 2.82) |
| Allergies | 1.53 (1.12, 2.10) | 2.19 (1.54, 3.10) | 1.81 (1.43, 2.28) |
| Thyroid disease | 1.45 (0.90, 2.33) | 1.72 (1.17, 2.54) | 1.62 (1.20, 2.18) |
| Migraine headache | 1.57 (1.15, 2.13) | 1.91 (1.31, 2.79) | 1.69 (1.33, 2.15) |
| History of head injury | |||
| None | 1.00 [Reference] | 1.00 [Reference] | 1.00 [Reference] |
| No loss of consciousness | 0.99 (0.60, 1.64) | 1.06 (0.64, 1.75) | 1.04 (0.73, 1.49) |
| Loss of consciousness | |||
| <5 minutes | 1.16 (0.78, 1.72) | 1.63 (1.07, 2.47) | 1.34 (1.01, 1.79) |
| ≥5 minutes | 2.38 (0.64, 8.85) | 0.51 (0.07, 3.91) | 1.24 (0.42, 3.62) |
| Medication use | |||
| Antihistamines | 1.45 (1.01, 2.09) | 1.94 (1.35, 2.79) | 1.65 (1.28, 2.13) |
| Acetaminophen | 1.24 (0.90, 1.70) | 1.34 (0.95, 1.88) | 1.28 (1.02, 1.62) |
| Benzodiazepine | 0.77 (0.32, 1.83) | 2.25 (1.34, 3.78) | 1.59 (1.03, 2.45) |
| Antidepressants | 1.27 (0.87, 1.84) | 1.68 (1.15, 2.45) | 1.44 (1.11, 1.88) |
| Steroids | 1.62 (1.07, 2.45) | 2.06 (1.43, 2.98) | 1.84 (1.40, 2.42) |
| Multivitamin | 1.43 (1.09, 1.88) | 1.03 (0.77, 1.37) | 1.03 (0.77, 1.37) |
| Hormones (women) | 1.85 (1.18, 2.90) | 1.05 (0.53, 2.09) | 1.54 (1.06, 2.24) |
Among women, those who had used hormones (for birth control, infertility, or menopausal symptoms) were more likely to report dry eye. This effect also differed by age. Among women under the age of 50 years who reported having a period in the past 12 months, use of hormones for contraception, fertility, or hormone replacement therapy was associated with a 71% increase in odds of dry eye symptoms (OR = 1.71, 95% CI = 1.08, 2.73). There was no association between hormone use and dry eye among women 50 years of age and older.
There was no association between a history of smoking or alcohol consumption and dry eye overall or stratified by age. Past and current contact lens use was found to be associated with dry eye symptoms compared to those who had never used contact lenses (OR = 1.34, 95% CI = 1.05, 1.71, and OR = 2.14, 95% CI = 1.65, 2.77, respectively). Current contact lens use displayed a stronger association (OR = 2.39) in those under 50 years of age. The season at interview was not associated with self-report of dry eye symptoms.
In the multivariable model, dry eye symptoms were associated with age, sex, current contact lens use, arthritis, allergies, thyroid disease, migraine headache, antihistamine use, and steroid use in the population overall ( Table 3 ). Results were similar when current contact lens wearers were excluded from the analysis (data not shown). In analysis limited to those younger than 50 years, female sex, current contact lens use (compared to those who had never used contact lenses), arthritis, allergies, and multivitamin use were all significantly associated with dry eye symptoms ( Table 3 ). In those 50 years of age or older, age, female sex, allergies, migraine headache, and use of antihistamines and benzodiazepine were associated with dry eye symptoms.
| Risk Factor | <50 Years of Age | ≥50 Years of Age | Overall |
|---|---|---|---|
| Age a (per increase in age group) | 1.08 (0.85, 1.37) | 1.31 (1.03, 1.65) | 1.12 (1.00, 1.27) |
| Sex | |||
| Male | 1.00 [Reference] | 1.00 [Reference] | 1.00 [Reference] |
| Female | 1.41 (1.02, 1.95) | 1.76 (1.25, 2.47) | 1.45 (1.14, 1.85) |
| Contact lens use | |||
| Past | 0.92 (0.61, 1.38) | NA | 1.09 (0.83, 1.43) |
| Current | 2.38 (1.67, 3.37) | NA | 2.09 (1.56, 2.79) |
| Chronic conditions | |||
| Arthritis | 2.14 (1.46, 3.13) | NA | 1.41 (1.09, 1.82) |
| Allergies | 1.49 (1.05, 2.10) | 2.06 (1.37, 3.10) | 1.54 (1.18, 2.01) |
| Thyroid disease | NA | NA | 1.40 (1.00, 1.97) |
| Migraine headache | NA | 1.71 (1.10, 2.65) | 1.44 (1.10, 1.90) |
| Medication use | |||
| Antihistamines | NA | 1.80 (1.23, 2.63) | 1.41 (1.07, 1.86) |
| Steroids | NA | NA | 1.47 (1.10, 1.97) |
| Benzodiazepine | NA | 2.08 (1.21, 3.56) | NA |
| Multivitamin use | 1.44 (1.06, 1.94) | NA | NA |
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