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Mult Scler Relat Disord ; 9: 104-9, 2016 Sep.
Article in English | MEDLINE | ID: mdl-27645354

ABSTRACT

BACKGROUND: Epidemiological studies suggest an important role for environmental factors in developing multiple sclerosis (MS). Furthermore several studies have indicated that the effect of environmental factors may be especially pronounced in adolescents. Recently only one study investigated and found that shift work at young age is associated with an increased risk of developing MS. In this study we focused on the effect of shift work in the vulnerable period between 15-19 years. OBJECTIVE: The aim of this study was to investigate the association between shift work at young age and the risk of developing MS. METHODS: We performed a large case-control study including 1723 patients diagnosed with MS and 4067 controls. MS patients were recruited from the Danish Multiple Sclerosis Biobank and controls from The Danish Blood Donor Study. Information on working patterns and lifestyle factors was obtained using a comprehensive lifestyle-environmental factor questionnaire with participants enrolled between 2009 and 2014. Logistic regression models were used to investigate the association between shift work at age 15-19 years and the subsequent risk of MS and were controlled for effects due to established MS risk factors. RESULTS: We found a statistically significant association when total numbers of night shifts were compared with non-shift workers. For every additional 100 night shifts the odds ratio (OR) for MS was 1.20 (95% confidence interval (CI), 1.08-1.34, p=0.001). Increasing intensity of shift work also increased MS risk. For every additional night per month the OR was 1.04 (95% CI, 1.01-1.06, p=0.002). Duration of shift work in years was not associated with risk of MS. CONCLUSION: This study supports a statistically significant association between shift work at age 15-19 years and MS risk.


Subject(s)
Employment , Multiple Sclerosis/epidemiology , Adult , Age Factors , Case-Control Studies , Denmark/epidemiology , Female , Humans , Logistic Models , Male , Odds Ratio , Risk Factors
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