Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013

Background: Women’s social roles (partnership, parenthood, and worker status) are associated with health, with more roles being associated with lower mortality rates. Few studies have examined social roles using a lifecourse perspective to understand how changing role dynamics affect health over tim...

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Main Authors: Sarah McKetta, Seth J. Prins, Jonathan Platt, Lisa M. Bates, Katherine Keyes
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:SSM: Population Health
Online Access:http://www.sciencedirect.com/science/article/pii/S235282731830123X
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spelling doaj-5e1c887c989b44eaa1178345731debeb2020-11-24T23:23:52ZengElsevierSSM: Population Health2352-82732018-12-016301308Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013Sarah McKetta0Seth J. Prins1Jonathan Platt2Lisa M. Bates3Katherine Keyes4Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA; Correspondence to: Mailman School of Public Health, 722 West 168th Street, New York, NY 10032, USA.Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, USADepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USADepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USADepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA; Center for Research on Society and Health, Universidad Mayor, Santiago, ChileBackground: Women’s social roles (partnership, parenthood, and worker status) are associated with health, with more roles being associated with lower mortality rates. Few studies have examined social roles using a lifecourse perspective to understand how changing role dynamics affect health over time. Sequence analysis is one analytic technique for examining social trajectories. Methods: Work-family trajectories were determined using social sequence analysis. We estimated mortality using age-standardized mortality rates and Poisson regression and examined the impact of personal income as a mediator. Results: We identified 5 trajectory types according to probability distributions of work/marriage/child-rearing status and descriptions in previous research: Non-working, married, later-mothers; working divorced mothers; working and non-working, never-married mothers; working, never-married non-mothers; and non-working, married earlier-mothers. Our reference group, non-working, married, later-mothers had the lowest mortality rates (1.47 per 1000 person-years). Adjusting for confounders, timing of childbearing did not impact mortality rates for married, non-working women. Working, never-married non-mothers and working and non-working, never-married mothers had the highest adjusted rates of mortality (RR = 1.81 and 1.57, respectively) these effects were attenuated slightly by the addition of household income in the model. Mortality rates for other trajectory groups were not significantly elevated in adjusted models. Conclusions: Mortality rates vary by work-family trajectories, but timing of childbearing does not meaningfully impact risk among women in this population, likely because few of the women who were married and had children also worked full-time. Household income has some mediating effect among those at highest risk of early mortality.http://www.sciencedirect.com/science/article/pii/S235282731830123X
collection DOAJ
language English
format Article
sources DOAJ
author Sarah McKetta
Seth J. Prins
Jonathan Platt
Lisa M. Bates
Katherine Keyes
spellingShingle Sarah McKetta
Seth J. Prins
Jonathan Platt
Lisa M. Bates
Katherine Keyes
Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
SSM: Population Health
author_facet Sarah McKetta
Seth J. Prins
Jonathan Platt
Lisa M. Bates
Katherine Keyes
author_sort Sarah McKetta
title Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
title_short Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
title_full Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
title_fullStr Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
title_full_unstemmed Social sequencing to determine patterns in health and work-family trajectories for U.S. women, 1968–2013
title_sort social sequencing to determine patterns in health and work-family trajectories for u.s. women, 1968–2013
publisher Elsevier
series SSM: Population Health
issn 2352-8273
publishDate 2018-12-01
description Background: Women’s social roles (partnership, parenthood, and worker status) are associated with health, with more roles being associated with lower mortality rates. Few studies have examined social roles using a lifecourse perspective to understand how changing role dynamics affect health over time. Sequence analysis is one analytic technique for examining social trajectories. Methods: Work-family trajectories were determined using social sequence analysis. We estimated mortality using age-standardized mortality rates and Poisson regression and examined the impact of personal income as a mediator. Results: We identified 5 trajectory types according to probability distributions of work/marriage/child-rearing status and descriptions in previous research: Non-working, married, later-mothers; working divorced mothers; working and non-working, never-married mothers; working, never-married non-mothers; and non-working, married earlier-mothers. Our reference group, non-working, married, later-mothers had the lowest mortality rates (1.47 per 1000 person-years). Adjusting for confounders, timing of childbearing did not impact mortality rates for married, non-working women. Working, never-married non-mothers and working and non-working, never-married mothers had the highest adjusted rates of mortality (RR = 1.81 and 1.57, respectively) these effects were attenuated slightly by the addition of household income in the model. Mortality rates for other trajectory groups were not significantly elevated in adjusted models. Conclusions: Mortality rates vary by work-family trajectories, but timing of childbearing does not meaningfully impact risk among women in this population, likely because few of the women who were married and had children also worked full-time. Household income has some mediating effect among those at highest risk of early mortality.
url http://www.sciencedirect.com/science/article/pii/S235282731830123X
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