Publication: Lung Function, Interstitial Lung Abnormalities, and Mortality in Shanghai Textile Workers
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2024-05-06
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Wang, Hantao. 2024. Lung Function, Interstitial Lung Abnormalities, and Mortality in Shanghai Textile Workers. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.
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Abstract
Endotoxins, components of the outer membrane of Gram-negative bacteria, are prevalent in cotton dust, a common occupational hazard in the textile industry. Three core studies of this dissertation were integrated to provide a comprehensive understanding of various long-term health effects of endotoxin exposure among textile workers in Shanghai.
The first study examined the effect of endotoxin exposure on lung function decline, utilizing inverse probability weightings in marginal structural models to adjust for potential selection biases like the healthy worker survivor effect (HWSE). The second study focused on the association between ILAs and lung function, revealing that increased cumulative exposure to cotton dust correlates with a higher prevalence of interstitial lung abnormalities (ILAs), which, in turn, are marginally associated with declines in forced vital capacity (FVC). The third study extended the mortality analysis of the Shanghai Textile Worker cohort, revealing a suggestive association between long-term endotoxin exposure and increased risks of non-lung cancer mortality, cardiovascular, cerebrovascular, and all-cause mortality.
Overall, these findings emphasize the critical impact of endotoxin exposure on various health outcomes, advocating for enhanced preventive strategies and exposure control in the textile industry and other settings where airborne endotoxin occurs. The application of advanced statistical methodologies to tackle challenges in occupational health research, such as HWSE,
further enriches the significance of this work, offering a methodological framework for future studies in similar settings.
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Keywords
cotton dust, endotoxin, healthy worker survivor effect, interstitial lung abnormality, marginal structure model, occupational epidemiology, Environmental health
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