Skip to main content

Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Table 6 Impact of Fatigue on Employment and Earnings

From: The economic impact of chronic fatigue syndrome in Georgia: direct and indirect costs

All effects estimated relative to not-fatigued (NF) population, (Standard Errors in Parentheses)
  Employment: Adjusted odds ratio (OR) of working in the prior 4 weeks relative to NF sample
  Model with reported education Model with imputed education
Incremental Expenditures attributed to CFS 0.15***
(0.10)
0.12***
(0.08)
Incremental Expenditures Attributed to ISF 0.14***
(0.08)
0.14***
(0.08)
  Earnings over the past 4 weeks ($), adjusted impact measured relative to NF sample
  Linear OLS GLM gamma for (y+1) TPM
  Model with reported education Model with imputed education Model with reported education Model with imputed education Model with reported education Model with imputed education
Incremental Expenditures attributed to CFS -878.24**
(337.60)
-1079.47***
(347.64)
-503.11
(392.52)
-658.30**
(298.83)
-266.30
(261.26)
-394.96
(255.41)
Incremental Expenditures Attributed to ISF -408.37*
(284.75)
-405.39
(283.90)
-1019.04
(654.78)
-1029.23
(665.62)
-22.37
(235.84)
-25.94
(235.60)
AIC 8397.40 8398.11 17.32 17.31 538.28 538.28
BIC 8451.49 8452.20 -1509.96 -1511.78 -1399.67 -1399.46
  1. * p < 0.1, ** p < 0.05, ***p < 0.01.
  2. Full model results for logistic regression on employment and GLM on earnings in Additional file 2, Table S3.