five

Robust test by using alternative samples.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Robust_test_by_using_alternative_samples_/29140072
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This study uses data from the China Health and Nutrition Survey (CHNS) in 2004, 2006, and 2015 and employs a fixed-effects model based on Driscoll-Kraay standard errors to investigate the impact of occupation type, employment type, and work unit type on workers’ health and the underlying mechanisms. The main findings suggest that higher levels of occupation type and employment type are associated with better self-rated health among workers, but simultaneously increase the probability of chronic diseases, demonstrating a “dual effect” of occupational characteristics on health. Additionally, workers in the public sector have a higher probability of chronic diseases and lower self-rated health compared to those in the non-public sector. Furthermore, the impact of occupation type, employment type, and work unit type on health is greater for male workers than for female workers. The negative impact of an increase in occupation type on chronic diseases is significantly higher in the absence of overtime work and for workers engaged in moderate and heavy physical labor. The mechanism analysis reveals that work intensity, labor income, and work hours play a crucial role in explaining the impact of occupation on health, jointly accounting for a significant portion of the impact of employment type on chronic diseases, occupation type on self-rated health, and work unit type on self-rated health.
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2025-05-23
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