Assessment of sunlight exposure across industries and occupations using blood vitamin D as a biomarker

• Published in: Journal of occupational health 2022-01, Vol.64 (1), p.e12318-n/a
• Main Authors: Koh, Dong‐Hee, Park, Ju‐Hyun, Lee, Sang‐Gil, Kim, Hwan‐Cheol, Jung, Hyejung, Kim, Inah, Choi, Sangjun, Park, Donguk
• Format: Article
• Language: English
• Subjects: Age; Armed forces; Biomarkers; Blood; Body mass index; Body size; Calciferol; cancer; carcinogen; Construction industry; Exposure; Fisheries; Health risks; Housing; Humans; Laboratories; Melanoma; Military; Multiple regression models; Normal distribution; Nutrition Surveys; Occupational exposure; Occupational health; Occupations; Original; Overweight; Population studies; Questionnaires; Seasons; Skin cancer; Sun; Sunlight; Ultraviolet radiation; Ultraviolet Rays; Vitamin D; Vitamin deficiency
• ISSN: 1348-9585; 1341-9145; 1348-9585
• DOI: 10.1002/1348-9585.12318

Objective Exposure to ultraviolet (UV) radiation from sunlight induces the production of essential vitamin D, whereas overexposure to sunlight leads to skin cancer. Sunlight exposure has been measured using questionnaires, dosimeters, and vitamin D levels. Several studies have measured vitamin D in the working population; however, these studies were limited to certain occupations such as farmers and construction workers. In the present study, we evaluated sunlight exposure using blood vitamin D as an exposure surrogate across industries and occupations. Methods The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationwide study representing the Korean population. We analyzed data from KNHANES between 2008 and 2009. We examined the association between vitamin D levels and pertinent personal, seasonal, residential, and occupational factors. Furthermore, we developed a multiple regression model with factors other than occupational factors (industry and occupation) and obtained residual values. We computed the third quartile (Q3) of the residuals and then calculated the fractions exceeding the Q3 level for each combination of industry and occupation. Results Age, sex, body mass index, year, season, latitude, living area, living in an apartment, industry, and occupation were significantly associated with vitamin D levels. Based on the exceeding fraction, the armed forces showed the highest exceeding fraction level of 0.71. Conclusions Our results present the high exposure groups to sunlight across industries and occupations. Our results may provide a source for prioritizing occupational groups with a high risk of adverse health effects from sunlight exposure.