Xiaoyi Cui1, Xi Lu, Aya Hisada, Yuki Fujiwara, Takahiko Katoh. 1. Department of Public Health, Faculty of Life Sciences, Kumamoto University, 1-1-1 Honjou, Chuo-ku, Kumamoto, 860-8556, Japan, bjcxy860508@hotmail.com.
Abstract
OBJECTIVE: This study was designed to determine the correlation between mental health and multiple chemical sensitivity (MCS). METHOD: The present study was conducted at two companies in 2011; both in Kyushu, Japan. The "subjective symptoms" subscale of the "Self-diagnosis Checklist for Assessment of Workers' Accumulated Fatigue" was used as a mental health subscale. To determine if multiple chemical exposure has an impact on mental health, we composed an original path model using structural equation analysis. RESULT: Our final path model can be regarded as good: CMIN/DF = 1.832, CFI = 0.996, and RMSEA = 0.038, AIC = 71.158. As expected, chemical sensitivity and other chemical sensitivity scores predicted the health effects of multiple chemical exposure (β = 0.19, 0.64). Mental health was predicted by symptom severity and life impact (β = 0.56 and 0.12), which were both affected by multiple chemical exposure (β = 0.38 and 0.89, respectively). CONCLUSION: As far as we are aware, this is the first study using path analysis to explore whether MCS can indicate mental health in worker populations worldwide, and we found a significant causal relationship between them. This could indicate that more focus should be placed on the impact of MCS on mental health in future investigations.
OBJECTIVE: This study was designed to determine the correlation between mental health and multiple chemical sensitivity (MCS). METHOD: The present study was conducted at two companies in 2011; both in Kyushu, Japan. The "subjective symptoms" subscale of the "Self-diagnosis Checklist for Assessment of Workers' Accumulated Fatigue" was used as a mental health subscale. To determine if multiple chemical exposure has an impact on mental health, we composed an original path model using structural equation analysis. RESULT: Our final path model can be regarded as good: CMIN/DF = 1.832, CFI = 0.996, and RMSEA = 0.038, AIC = 71.158. As expected, chemical sensitivity and other chemical sensitivity scores predicted the health effects of multiple chemical exposure (β = 0.19, 0.64). Mental health was predicted by symptom severity and life impact (β = 0.56 and 0.12), which were both affected by multiple chemical exposure (β = 0.38 and 0.89, respectively). CONCLUSION: As far as we are aware, this is the first study using path analysis to explore whether MCS can indicate mental health in worker populations worldwide, and we found a significant causal relationship between them. This could indicate that more focus should be placed on the impact of MCS on mental health in future investigations.
Authors: Changmin Tang; Chaojie Liu; Pengqian Fang; Yuanxi Xiang; Rui Min Journal: Int J Environ Res Public Health Date: 2019-08-22 Impact factor: 3.390