Table 3

Linear regression slope parameter, that is, the difference-in-differences estimate of sex differences in sickness absence 5 years after a hospital admission (imputing zero days of absence for all years after a death for those deceased) for 18 disease categories

(1)(2)(3)
All, n=1 867 0135.156***4.392***5.126***
Accident, n=201 273†5.175***6.693***7.771***
Blood, n=997316.757***12.188***12.320***
Congenital, n=55305.9403.6604.458
Digestive, n=219 6197.569***7.349***8.137***
Ear, n=25 6604.068*4.190*5.567***
Endocrine, n=40 5380.2400.1221.212
Eye, n=22 6855.576***6.132***6.717***
Factors, n=55 1360.6412.662**4.150***
Genitourinary, n=168 6595.230***1.570*1.759*
Circulatory (ICD-10=I00–I99), n=255 6877.385***6.900***7.779***
Infection, n=40 9464.349***4.153***4.411***
Mental (ICD-10=F00–F99), n=63 0655.474***4.947***6.713***
Musculoskeletal (ICD-10=M00–M99), n=149 8462.981***4.009***5.592***
Neoplasms (ICD-10=C00–D48), n=223 8756.097***1.1081.626*
Nerve, n=44 0759.607***10.469***11.461***
Respiratory, n=81 9817.317***7.294***8.061***
Skin, n=14 0400.1141.3422.710
Symptoms, n=244 4259.487***9.419***10.173***
Covariates‡
Factors§
  • Column (1) makes no covariate adjustments. Column (2) adjusts for covariates observed before the admission (see notes in the table). Column (3) adjusts for factors (see notes in the table).

  • *p<0.05, **p<0.01, ***p<0.001.

  • †n is the sample size. This is the number of individuals multiplied by the number of time periods included in the analysis.

  • ‡Age in years, level of education (three levels: less than secondary, secondary and postsecondary), own and spousal earnings, and dummies for whether the individual or the spouse has earnings above the sickness insurance cap.

  • §Indicators for calendar year, occupational sector and disease category (where feasible).

  • ICD-10, International Statistical Classification of Diseases and Related Health Problems.