Literature DB >> 32614410

Association of the Indoor Environment With Dry Eye Metrics.

Amy Huang1, Julia Janecki2, Anat Galor3,4, Sarah Rock5, Dhariyat Menendez2, Abigail S Hackam4, Bennie H Jeng6, Naresh Kumar5.   

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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Year:  2020        PMID: 32614410      PMCID: PMC7333174          DOI: 10.1001/jamaophthalmol.2020.2237

Source DB:  PubMed          Journal:  JAMA Ophthalmol        ISSN: 2168-6165            Impact factor:   7.389


  33 in total

1.  Indoor particles and symptoms among office workers: results from a double-blind cross-over study.

Authors:  Mark J Mendell; William J Fisk; Marty R Petersen; Cynthia J Hines; Maxia Dong; David Faulkner; James A Deddens; Avima M Ruder; Douglas Sullivan; Mark F Boeniger
Journal:  Epidemiology       Date:  2002-05       Impact factor: 4.822

2.  Environmental factors affect the risk of dry eye syndrome in a United States veteran population.

Authors:  Anat Galor; Naresh Kumar; William Feuer; David J Lee
Journal:  Ophthalmology       Date:  2014-02-21       Impact factor: 12.079

3.  Prevalence and risk factors associated with nonspecific building-related symptoms in office employees in Japan: relationships between work environment, Indoor Air Quality, and occupational stress.

Authors:  K Azuma; K Ikeda; N Kagi; U Yanagi; H Osawa
Journal:  Indoor Air       Date:  2014-10-24       Impact factor: 5.770

4.  Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution.

Authors:  C Arden Pope; Richard T Burnett; Michael J Thun; Eugenia E Calle; Daniel Krewski; Kazuhiko Ito; George D Thurston
Journal:  JAMA       Date:  2002-03-06       Impact factor: 56.272

5.  Seasonal Variation in Dry Eye.

Authors:  Naresh Kumar; William Feuer; Nicole L Lanza; Anat Galor
Journal:  Ophthalmology       Date:  2015-04-06       Impact factor: 12.079

6.  Validation of the 5-Item Dry Eye Questionnaire (DEQ-5): Discrimination across self-assessed severity and aqueous tear deficient dry eye diagnoses.

Authors:  Robin L Chalmers; Carolyn G Begley; Barbara Caffery
Journal:  Cont Lens Anterior Eye       Date:  2010-01-25       Impact factor: 3.077

7.  Acute air pollution-related symptoms among residents in Chiang Mai, Thailand.

Authors:  Phongtape Wiwatanadate
Journal:  J Environ Health       Date:  2014 Jan-Feb       Impact factor: 1.179

8.  World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.

Authors: 
Journal:  JAMA       Date:  2013-11-27       Impact factor: 56.272

9.  A multicentric case-control study on the impact of air pollution on eyes in a metropolitan city of India.

Authors:  S K Gupta; S C Gupta; Renu Agarwal; Srivastava Sushma; S S Agrawal; Rohit Saxena
Journal:  Indian J Occup Environ Med       Date:  2007-01

10.  Air pollutant particulate matter 2.5 induces dry eye syndrome in mice.

Authors:  Gang Tan; Juan Li; Qichen Yang; Anhua Wu; Dong-Yi Qu; Yahong Wang; Lei Ye; Jing Bao; Yi Shao
Journal:  Sci Rep       Date:  2018-12-13       Impact factor: 4.379

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  5 in total

1.  Error in Table.

Authors: 
Journal:  JAMA Ophthalmol       Date:  2021-06-10       Impact factor: 7.389

2.  Dry Eye Symptoms and Signs in US Veterans With Gulf War Illness.

Authors:  Victor Sanchez; Brandon S Baksh; Kimberly Cabrera; Anjalee Choudhury; Katherine Jensen; Nancy Klimas; Anat Galor
Journal:  Am J Ophthalmol       Date:  2021-11-13       Impact factor: 5.258

3.  Indoor Airborne Microbial Concentration and Dry Eye.

Authors:  Sarah Rock; Anat Galor; Naresh Kumar
Journal:  Am J Ophthalmol       Date:  2020-10-14       Impact factor: 5.488

4.  Associations between Biomarkers of Metal Exposure and Dry Eye Metrics in Shipyard Welders: A Cross-Sectional Study.

Authors:  Ying-Hsi Liou; Ying-Jen Chen; Wei-Liang Chen; Kuan-Ying Li; Ting-Yu Chou; Yung-Chi Huang; Chung-Ching Wang; Ching-Huang Lai
Journal:  Int J Environ Res Public Health       Date:  2022-02-17       Impact factor: 3.390

5.  Shift Work and Dry Eye Disease in the Korean Working Population: A Population-Based Cross-Sectional Study.

Authors:  Joonho Ahn; So-Jung Ryu; Jihun Song; Hyoung-Ryoul Kim
Journal:  Int J Environ Res Public Health       Date:  2021-05-20       Impact factor: 3.390

  5 in total

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