Various studies have revealed an association between cigarette smoking and increased risk for multiple sclerosis (MS). However, its role in neuromyelitis optica spectrum disorder (NMOSD) remains elusive. Therefore, in the present case-control study, we aimed to assess the association of active and passive cigarette smoking with the risk of MS and NMOSD. Thirty-six patients with NMOSD, 46 patients with MS, and 122 healthy individuals were included in this study. Standardized questionnaires and telephone interviews were used to collect information regarding the active and passive cigarette smoking behaviors of the patients and normal controls. The risk of MS was significantly higher among smokers than among nonsmokers (odds ratio = 2.166, 95% confidence interval: 1.109–4.170; P = .027). Further analysis of the risk between active and passive smokers, male smokers and nonsmokers showed no statistical difference. However, neither smokers nor active smokers had a greater or lower risk of NMOSD than their nonsmoking counterparts. Our preliminary study showed no significant association between cigarette smoking and the risk of NMOSD, strongly suggesting that, unlike MS, cigarette smoking might not confer NMOSD susceptibility, at least in the Northern Han Chinese population.
BackgroundThere are limited sensitive evaluation methods to distinguish people’s symptoms of peripheral fatigue and central fatigue simultaneously. The purpose of this study is to identify and evaluate them after acute exercise with a simple and practical scale.MethodsThe initial scale was built through a literature review, experts and athlete population survey, and a small sample pre-survey. Randomly selected 1,506 students were evaluated with the initial scale after exercise. Subjective fatigue self-assessments (SFSA) were completed at the same time.ResultsThe Acute Exercise-Induced Fatigue Scale (AEIFS) was determined after performing a factor analysis. In the exploratory factor analysis, the cumulative variance contribution rate was 65.464%. The factor loadings of the total 8 questions were 0.661–0.816. In the confirmatory factor analysis, χ2/df = 2.529, GFI = 0.985, AGFI = 0.967, NFI = 0.982, IFI = 0.989, CFI = 0.989, and RMSEA = 0.048. The Cronbach’s alpha coefficient for the scale was 0.872, and it was 0.833 for peripheral fatigue and 0.818 for central fatigue. The intra-class correlation coefficient for the scale was 0.536, and the intra-class correlation coefficients for peripheral fatigue and central fatigue were 0.421 and 0.548, respectively. The correlation coefficient between the total score of the AEIFS and the SFSA score was 0.592 (p < 0.01).ConclusionOur results demonstrate that the AEIFS can distinguish peripheral fatigue and central fatigue and can also reflect their correlation. This scale can be a useful evaluation tool not only for measuring fatigue after acute exercise but also for guiding reasonable exercise, choosing objective testing indicators, and preventing sports injuries resulting from acute exercise-induced fatigue.
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