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Infrared camera-proven water-damaged homes are associated with the severity of atopic dermatitis in children

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dc.contributor.authorSeo, SungChul-
dc.contributor.authorHan, Youngshin-
dc.contributor.authorKim, Jihyun-
dc.contributor.authorChoung, Ji Tae-
dc.contributor.authorKim, Beom Joon-
dc.contributor.authorAhn, Kangmo-
dc.date.accessioned2021-09-05T03:18:24Z-
dc.date.available2021-09-05T03:18:24Z-
dc.date.created2021-06-15-
dc.date.issued2014-11-
dc.identifier.issn1081-1206-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/96847-
dc.description.abstractBackground: Moisture problems in dwellings have been linked to respiratory symptoms, but little is known about their association with symptoms of atopic dermatitis (AD). Moreover, the questionnaire-based survey or visual inspection for water damage does not use a standardized approach for assessing dampness. Objective: To determine water damage in the houses of children with AD by assessing variations in surface temperature with an infrared camera, an interview-led questionnaire, and evaluation of the relation between the presence of water damage and the severity of AD. Methods: Fifty-two homes of patients with AD were visited, and air samples were obtained from the living room and a child's bedroom. Water damage was determined by thermal assessments using an infrared camera and by the presence of visible mold or water stains. The effect of water damage on the severity of AD was analyzed by comparing the presence or absence of water damage and other aggravating factors between water-damaged and undamaged homes. Results: Water damage was observed in 31 of 52 homes (59.6%), and the concentrations of airborne mold were significantly higher in water-damaged homes than in undamaged homes (P = .0013). However, there was no difference in airborne mold levels between homes with and those without visible mold or water stains. Logistic regression analyses showed that water-damaged homes were significantly related to moderate to severe AD (adjusted odds ratio 14.52, 95% confidence interval 1.75-121.13, P = .0025). Conclusion: Water-damaged homes affect the severity of AD in children. Infrared camera-driven assessment is a promising tool for determining moisture problems in buildings. (C) 2014 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE INC-
dc.subjectVOLATILE ORGANIC-COMPOUNDS-
dc.subjectRESPIRATORY SYMPTOMS-
dc.subjectHOUSE-DUST-
dc.subjectMICROBIAL EXPOSURE-
dc.subjectALLERGIC DISEASES-
dc.subjectMOISTURE-DAMAGE-
dc.subjectPARENTAL ATOPY-
dc.subjectAIR-QUALITY-
dc.subjectDAMPNESS-
dc.subjectMOLD-
dc.titleInfrared camera-proven water-damaged homes are associated with the severity of atopic dermatitis in children-
dc.typeArticle-
dc.contributor.affiliatedAuthorSeo, SungChul-
dc.contributor.affiliatedAuthorChoung, Ji Tae-
dc.identifier.doi10.1016/j.anai.2014.08.013-
dc.identifier.scopusid2-s2.0-84914121735-
dc.identifier.wosid000344949200011-
dc.identifier.bibliographicCitationANNALS OF ALLERGY ASTHMA & IMMUNOLOGY, v.113, no.5, pp.549 - 555-
dc.relation.isPartOfANNALS OF ALLERGY ASTHMA & IMMUNOLOGY-
dc.citation.titleANNALS OF ALLERGY ASTHMA & IMMUNOLOGY-
dc.citation.volume113-
dc.citation.number5-
dc.citation.startPage549-
dc.citation.endPage555-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAllergy-
dc.relation.journalResearchAreaImmunology-
dc.relation.journalWebOfScienceCategoryAllergy-
dc.relation.journalWebOfScienceCategoryImmunology-
dc.subject.keywordPlusVOLATILE ORGANIC-COMPOUNDS-
dc.subject.keywordPlusRESPIRATORY SYMPTOMS-
dc.subject.keywordPlusHOUSE-DUST-
dc.subject.keywordPlusMICROBIAL EXPOSURE-
dc.subject.keywordPlusALLERGIC DISEASES-
dc.subject.keywordPlusMOISTURE-DAMAGE-
dc.subject.keywordPlusPARENTAL ATOPY-
dc.subject.keywordPlusAIR-QUALITY-
dc.subject.keywordPlusDAMPNESS-
dc.subject.keywordPlusMOLD-
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