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Co-effect of Demand-control-support Model and Effort-reward Imbalance Model on Depression Risk Estimation in Humans: Findings from Henan Province of China*

Supporting Files
File Language:
English


Details

  • Alternative Title:
    Biomed Environ Sci
  • Personal Author:
  • Description:
    Objective

    To investigate the co-effect of Demand-control-support (DCS) model and Effort-reward Imbalance (ERI) model on the risk estimation of depression in humans in comparison with the effects when they are used respectively.

    Methods

    A total of 3 632 males and 1 706 females from 13 factories and companies in Henan province were recruited in this cross-sectional study. Perceived job stress was evaluated with the Job Content Questionnaire and Effort-Reward Imbalance Questionnaire (Chinese version). Depressive symptoms were assessed by using the Center for Epidemiological Studies Depression Scale (CES-D).

    Results

    DC (demands/job control ratio) and ERI were shown to be independently associated with depressive symptoms. The outcome of low social support and overcommitment were similar. High DC and low social support (SS), high ERI and high overcommitment, and high DC and high ERI posed greater risks of depressive symptoms than each of them did alone. ERI model and SS model seem to be effective in estimating the risk of depressive symptoms if they are used respectively.

    Conclusion

    The DC had better performance when it was used in combination with low SS. The effect on physical demands was better than on psychological demands. The combination of DCS and ERI models could improve the risk estimate of depressive symptoms in humans.

  • Subjects:
  • Source:
    Biomed Environ Sci. 26(12):962-971.
  • Pubmed ID:
    24393505
  • Pubmed Central ID:
    PMC4701206
  • Document Type:
    Journal Article
  • Funding:
    CC999999/Intramural CDC HHS/United States
  • Place as Subject:
    China
  • Volume:
    26
  • Issue:
    12
  • Collection(s):
  • Main Document Checksum:
    urn:sha256:78a43b3be38acb71fa84ea248bc882c857a257015bffe872901c6915879dc570
  • Download URL:
  • File Type:
    Filetype[PDF - 336.11 KB ]

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