title: Use of life course work-family profiles to predict mortality risk among US women.
abstract: OBJECTIVE
  We examined relationships between US women's exposure to midlife work-family demands and subsequent mortality risk.
  
  
  METHODS
  We used data from women born 1935 to 1956 in the Health and Retirement Study to calculate employment, marital, and parenthood statuses for each age between 16 and 50 years. We used sequence analysis to identify 7 prototypical work-family trajectories. We calculated age-standardized mortality rates and hazard ratios (HRs) for mortality associated with work-family sequences, with adjustment for covariates and potentially explanatory later-life factors.
  
  
  RESULTS
  Married women staying home with children briefly before reentering the workforce had the lowest mortality rates. In comparison, after adjustment for age, race/ethnicity, and education, HRs for mortality were 2.14 (95% confidence interval [CI] = 1.58, 2.90) among single nonworking mothers, 1.48 (95% CI = 1.06, 1.98) among single working mothers, and 1.36 (95% CI = 1.02, 1.80) among married nonworking mothers. Adjustment for later-life behavioral and economic factors partially attenuated risks.
  
  
  CONCLUSIONS
  Sequence analysis is a promising exposure assessment tool for life course research. This method permitted identification of certain lifetime work-family profiles associated with mortality risk before age 75 years.
authors.affiliation: Erika L. Sabbath is with the School of Social Work, Boston College, Chestnut Hill, MA, and the Center for Population and Development Studies, Harvard University, Cambridge, MA. Ivan Mejía Guevara is with the Center for Population and Development Studies, Harvard University. M. Maria Glymour is with the Department of Epidemiology and Biostatistics, University of California-San Francisco, and the Department of Health and Social Behavior, Harvard T. H. Chan School of Public Health, Boston, MA. Lisa F. Berkman is with the Center for Population and Development Studies, Harvard University, and the Departments of Health and Social Behavior, Epidemiology, and Global Health and Population, Harvard T. H. Chan School of Public Health.
authors.forename: Erika L
authors.initials: EL
authors.lastname: Sabbath
authors.forename: Ivan Mejía
authors.initials: IM
authors.lastname: Guevara
authors.forename: M Maria
authors.initials: MM
authors.lastname: Glymour
authors.forename: Lisa F
authors.initials: LF
authors.lastname: Berkman
mesh_terms: D017677:Age Distribution; D000368:Aged; D005260:Female; D006801:Humans; D008875:Middle Aged; D009026:Mortality / Q000639:trends*; D012306:Risk; D012907:Smoking / Q000401:mortality; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D016387:Women's Health / Q000706:statistics & numerical data*; D014937:Work / Q000706:statistics & numerical data*