Importance The ocular surface is continuously exposed to the environment. Although studies have focused on associations between outdoor environmental conditions and dry eye, information on associations between the indoor environment… Click to show full abstract
Importance The ocular surface is continuously exposed to the environment. Although studies have focused on associations between outdoor environmental conditions and dry eye, information on associations between the indoor environment and dry eye is lacking. Objective To determine associations between the indoor environment and dry eye. Design, Setting, and Participants This prospective cross-sectional study sample of 97 veterans with a wide range of dry eye metrics was recruited from the Miami Veterans Affairs Healthcare eye clinic from October 19, 2017, to August 30, 2018. Dry eye metrics were first evaluated in the clinic, followed by indoor home environmental metrics within 1 week using a handheld particle counter. Data were analyzed from October 19, 2017, to August 30, 2018. Main Outcomes and Measures Symptoms of dry eye were assessed with standardized questionnaires. Dry eye signs were assessed via standard examination. Indoor environmental metrics included temperature, humidity, and particulate matter mass and count. Results Of the 97 participants included in the analysis, 81 (84%) were men, with a mean (SD) age of 58.2 (11.9) years. Dry eye symptoms were in the moderate range with a mean (SD) Ocular Surface Disease Index (OSDI) score of 31.2 (23.6). Humidity was associated with worse symptoms and signs, including OSDI score (r = 0.30 [95% CI, 0.07-0.49]; P = .01), inflammation (r = 0.32 [95% CI, 0.10-0.51]; P = .01), Schirmer score (r = -0.25 [95% CI, -0.45 to 0.02]; P = .03), eyelid vascularity (r = 0.27 [95% CI, 0.05-0.47]; P = .02), and meibomian gland dropout (r = 0.27 [95% CI, 0.05-0.47]; P = .02). In multivariate analyses, particulate matter of 2.5 μm or less (PM2.5) was associated with dry eye metrics when adjusted for demographic characteristics, comorbidities, medications, and interaction variables. For example, a 1-unit increase in instrumented PM2.5 level was associated with a 1.59 increase in the OSDI score (95% CI, 0.58-2.59; P = .002), a 0.39 reduction in Schirmer score (95% CI, -0.75 to -0.03; P = .04), a 0.07 increase in meibomian gland dropout (95% CI, 0.01-0.13; P = .02), and a 0.06 increase in inflammation (95% CI, 0.02-0.11; P = .009). Conclusions and Relevance When adjusting for humidity, this study found that increased particulate matter exposure was associated with worse dry eye metrics. Humidity was positively associated with dry eye metrics, potentially because higher humidity increases microbial growth and particulate matter size and mass.
               
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