Association between low income, depression, self-efficacy and mass-incident-related strains: an understanding of mass incidents in China.
BACKGROUND
This study investigated the associations between income, depression, self-efficacy and health and the strains associated with mass incidents in a Chinese city. It further investigated whether depression, self-efficacy and health status mediate relationships between income and mass-incident-related strains.


METHODS
A representative sample of mass-incident participants from Chong Qing, aged 18 years and over, participated using a questionnaire. Of the 480 surveys returned, 465 (88%) were usable. Structural equation modelling was used to analyse the relationship model to use strains as the main outcome variable, income as a predictor and self-rated general health status, depression and self-efficacy as mediators.


RESULTS
High levels of strains were significantly associated with low levels of income, and this association was mediated by a fair to poor level of health status, depression and low levels of self-efficacy.


CONCLUSIONS
Income as an indicator of social inequality revealed its significant predictive role in the occurrence of mass incidents through its impact on high levels of strains and its association with depression, fair to poor health and low levels of self-efficacy. Further study will benefit from a follow-up study to determine the causal relationship between income and strains, and a representative population that includes children and the elderly be included in the next phase of the study.
Griffith Health Institute and School of Public Health, Griffith University, Logan Campus Meadowbrook, Queensland Q4131, Australia. j.sun@griffith.edu.au
Jing
J
Sun
Nicholas
N
Buys
Xinchao
X
Wang
D000223:Adaptation, Psychological; D000293:Adolescent; D000328:Adult; D002681:China / Q000453:epidemiology; D003415:Crime / Q000523:psychology* / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D003863:Depression / Q000453:epidemiology / Q000523:psychology*; D005260:Female; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D011203:Poverty / Q000191:economics / Q000523:psychology* / Q000706:statistics & numerical data; D011594:Psychometrics; D018570:Risk Assessment; D012307:Risk Factors; D020377:Self Efficacy; D012923:Social Class; D013315:Stress, Psychological / Q000150:complications* / Q000453:epidemiology / Q000523:psychology; D011795:Surveys and Questionnaires; D055815:Young Adult