Cancer's impact on employment and earnings--a population-based study from Norway.
BACKGROUND
Increased attention is being paid to the long-term health and well-being of people living with a history of cancer. Of particular concern is cancer's effect on productivity and work ability, which in turn is important for persons' financial situation, life satisfaction, and social relationships. We explored the extent to which Norwegian cancer survivors stay affiliated to working life compared to the cancer-free population, and quantified cancer-associated earning declines.


RESULTS
Logistic regression models were estimated to explore the impact of cancer on employment using register data covering the entire Norwegian population in 2001, 567,000 men and 549,300 women 40-59 years old, of whom 34,000 were diagnosed with cancer. These analyses revealed that a cancer diagnosis was strongly associated with not being employed. Log-linear regression models were used to estimate the effect of cancer on labor earnings in 2001 for those employed. Cancer was associated with a 12% decline in earnings overall. Leukemia, lymphomas, lung, brain, bone, colorectal, and head-and-neck cancer resulted in the largest reductions in employment and earnings. Earning declines were strongly associated with educational level. In addition, linear regression models were used to estimate differentials in earnings before and after cancer. These results accorded well with those from cross-sectional models.


CONCLUSIONS
Cancer survivors are less likely to be employed than the cancer-free population, and undertake modifications in their employment, e.g. reduce work-hours or hold lower-wage jobs, which result in reduced earnings. A social class gradient is present and must be addressed to accommodate appropriate intervention from welfare societies.
Syse
Astri
A
Cancer Registry of Norway, Montebello, Oslo, Norway. astri.syse@medisin.uio.no
Tretli
Steinar
S
Kravdal
Øystein
Ø
D000328:Adult; D004522:Educational Status; D004651:Employment / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000191:economics* / Q000453:epidemiology* / Q000473:pathology; D009664:Norway / Q000453:epidemiology; D017741:Survivors / Q000706:statistics & numerical data*; D014937:Work / Q000706:statistics & numerical data*
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