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Factors affecting workforce participation and healthy worker biases in U.S. women and men.


ABSTRACT: PURPOSE:To investigate potential attenuation of healthy worker biases in populations in which healthy women of reproductive age opt out of the workforce to provide childcare. METHODS:We used 2013-2015 data from 120,928 U.S. women and men aged 22-44 years participating in the Gallup-Healthways Well-Being Index. We used logistic regression to estimate adjusted prevalence odds ratios (PORs) and 95% confidence intervals (CIs) for associations between health and workforce nonparticipation. RESULTS:Women and men reporting poor health were more likely to be out of the workforce than individuals reporting excellent health (POR: 3.7, 95% CI: 3.2-4.2; POR: 6.7, 95% CI: 5.7-7.8, respectively), suggesting potential for healthy worker bias. For women (P < .001) but not men (P = .30), the strength of this association was modified by number of children in the home: POR: 7.3 (95% CI: 5.8-9.1) for women with no children, decreasing to POR: 0.9 (95% CI: 0.6-1.5) for women with four or more children. CONCLUSIONS:These results are consistent with attenuation of healthy worker biases when healthy women opt out of the workforce to provide childcare. Accordingly, we might expect the magnitude of these biases to vary with the proportion of women with differing numbers of children in the population.

SUBMITTER: Johnson CY 

PROVIDER: S-EPMC5836747 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Factors affecting workforce participation and healthy worker biases in U.S. women and men.

Johnson Candice Y CY   Rocheleau Carissa M CM   Lawson Christina C CC   Grajewski Barbara B   Howards Penelope P PP  

Annals of epidemiology 20170825 9


<h4>Purpose</h4>To investigate potential attenuation of healthy worker biases in populations in which healthy women of reproductive age opt out of the workforce to provide childcare.<h4>Methods</h4>We used 2013-2015 data from 120,928 U.S. women and men aged 22-44 years participating in the Gallup-Healthways Well-Being Index. We used logistic regression to estimate adjusted prevalence odds ratios (PORs) and 95% confidence intervals (CIs) for associations between health and workforce nonparticipat  ...[more]

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