title: Gender differences in functional health: latent curve analysis assessing differential exposure.
abstract: OBJECTIVE
  To examine gender difference in trajectories of functional limitations among middle-aged and older adults using a comprehensive set of predictors and method not previously used to examine this topic.
  
  
  METHODS
  Two-part latent curve models were used to analyze data from the Health and Retirement Study. These models differentiate the occurrence of limitations from the number of limitations at both baseline and over time.
  
  
  RESULTS
  Females had 3.70 times greater odds of having any limitations and had 28% more limitations at baseline compared with males, but there was no gender difference in the onset of limitations over time or in the number of limitations over time. Differences in employment status, income, wealth, depressive symptoms, arthritis, cancer, and eyesight partially explained the gender gap.
  
  
  CONCLUSIONS
  Females are disadvantaged in terms of occurrence and number of limitations at baseline but the gender gap remains stable over time, suggesting differences occur before late-middle and old age. Females' lack of full-time employment, and lower levels of income and wealth translate into worse functional health. It is important to improve the socioeconomic status of females while also addressing the health conditions that contribute to functional limitations for males and females.
authors.affiliation: Department of Sociology, St. Lawrence University, Canton, New York. lrohlfsen@stlawu.edu.
authors.forename: Leah S
authors.initials: LS
authors.lastname: Rohlfsen
authors.affiliation: Sociology Program, Sanford School of Social and Family Dynamics, Arizona State University, Tempe.
authors.forename: Jennie Jacobs
authors.initials: JJ
authors.lastname: Kronenfeld
mesh_terms: D000203:Activities of Daily Living; D000368:Aged; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011446:Prospective Studies; D012737:Sex Factors; D012959:Socioeconomic Factors
keywords: Functional limitations; Gender; Health and Retirement Study; Two-part latent curve analysis.