Erin E Kent1,2, Amy Davidoff3, Janet S de Moor1, Timothy S McNeel4, Katherine S Virgo5, Diarmuid Coughlan6, Xuesong Han7, Donatus U Ekwueme8, Gery P Guy8, Matthew P Banegas9, Catherine M Alfano7, Emily C Dowling10, K Robin Yabroff7. 1. a Division of Cancer Control and Population Sciences, Healthcare Delivery Research Program, National Cancer Institute , Rockville , Maryland , USA. 2. b ICF International , Fairfax , VA. 3. c Department of Health Policy & Management , School of Public Health, Yale University , New Haven , Connecticut , USA. 4. d Information Management Services, Inc. , Rockville , Maryland , USA. 5. e Department of Health Policy and Management , Rollins School of Public Health, Emory University , Atlanta , Georgia , USA. 6. f Division of Cancer Control and Population Sciences, Surveillance Research Program, National Cancer Institute , Rockville , Maryland , USA. 7. g American Cancer Society , Atlanta , Georgia , USA. 8. h Centers for Disease Control and Prevention, Division of Cancer Prevention and Control , Atlanta , Georgia , USA. 9. i Kaiser Permanente Center for Health Research , Portland , Oregon , USA. 10. j Massachusetts General Hospital , Boston , Massachusetts , USA.
Abstract
BACKGROUND: We examined the longitudinal association between sociodemographic factors and an expanded definition of underemployment among those with and without cancer history in the United States. METHODS: Medical Expenditure Panel Survey data (2007-2013) were used in multivariable regression analyses to compare employment status between baseline and two-year follow-up among adults aged 25-62 years at baseline (n = 1,614 with and n = 39,324 without cancer). Underemployment was defined as becoming/staying unemployed, changing from full to part-time, or reducing part-time work significantly. Interaction effects between cancer history/time since diagnosis and predictors known to be associated with employment patterns, including age, gender/marital status, education, and health insurance status at baseline were modeled. RESULTS: Approximately 25% of cancer survivors and 21% of individuals without cancer reported underemployment at follow-up (p = 0.002). Multivariable analyses indicated that those with a cancer history report underemployment more frequently (24.7%) than those without cancer (21.4%, p = 0.002) with underemployment rates increasing with time since cancer diagnosis. A significant interaction between gender/marital status and cancer history and underemployment was found (p = 0.0004). There were no other significant interactions. Married female survivors diagnosed >10 years ago reported underemployment most commonly (38.7%), and married men without cancer reported underemployment most infrequently (14.0%). A wider absolute difference in underemployment reports for married versus unmarried women as compared to married versus unmarried men was evident, with the widest difference apparent for unmarried versus married women diagnosed >10 years ago (18.1% vs. 38.7%). CONCLUSION: Cancer survivors are more likely to experience underemployment than those without cancer. Longer time since cancer diagnosis and gender/marital status are critical factors in predicting those at greatest risk of underemployment. The impact of cancer on work should be systematically studied across sociodemographic groups and recognized as a component of comprehensive survivorship care.
BACKGROUND: We examined the longitudinal association between sociodemographic factors and an expanded definition of underemployment among those with and without cancer history in the United States. METHODS: Medical Expenditure Panel Survey data (2007-2013) were used in multivariable regression analyses to compare employment status between baseline and two-year follow-up among adults aged 25-62 years at baseline (n = 1,614 with and n = 39,324 without cancer). Underemployment was defined as becoming/staying unemployed, changing from full to part-time, or reducing part-time work significantly. Interaction effects between cancer history/time since diagnosis and predictors known to be associated with employment patterns, including age, gender/marital status, education, and health insurance status at baseline were modeled. RESULTS: Approximately 25% of cancer survivors and 21% of individuals without cancer reported underemployment at follow-up (p = 0.002). Multivariable analyses indicated that those with a cancer history report underemployment more frequently (24.7%) than those without cancer (21.4%, p = 0.002) with underemployment rates increasing with time since cancer diagnosis. A significant interaction between gender/marital status and cancer history and underemployment was found (p = 0.0004). There were no other significant interactions. Married female survivors diagnosed >10 years ago reported underemployment most commonly (38.7%), and married men without cancer reported underemployment most infrequently (14.0%). A wider absolute difference in underemployment reports for married versus unmarried women as compared to married versus unmarried men was evident, with the widest difference apparent for unmarried versus married women diagnosed >10 years ago (18.1% vs. 38.7%). CONCLUSION:Cancer survivors are more likely to experience underemployment than those without cancer. Longer time since cancer diagnosis and gender/marital status are critical factors in predicting those at greatest risk of underemployment. The impact of cancer on work should be systematically studied across sociodemographic groups and recognized as a component of comprehensive survivorship care.
Authors: Mary Stergiou-Kita; Alisa Grigorovich; Victrine Tseung; Elizabeth Milosevic; Debbie Hebert; Stephanie Phan; Jennifer Jones Journal: J Cancer Surviv Date: 2014-07-04 Impact factor: 4.442
Authors: Miao Yu; Leah M Ferrucci; Ruth McCorkle; Elizabeth Ercolano; Tenbroeck Smith; Kevin D Stein; Brenda Cartmel Journal: J Cancer Surviv Date: 2012-01-05 Impact factor: 4.442
Authors: Matthew P Banegas; Jennifer L Schneider; Alison J Firemark; John F Dickerson; Erin E Kent; Janet S de Moor; Katherine S Virgo; Gery P Guy; Donatus U Ekwueme; Zhiyuan Zheng; Alexandra M Varga; Lisa A Waiwaiole; Stephanie M Nutt; Aditi Narayan; K Robin Yabroff Journal: J Cancer Surviv Date: 2019-05-23 Impact factor: 4.442