Demographic-Specific Rates for Life Events in the Cardiovascular Health Study and Comparisons With Other Studies. Issue 1 (26th March 2018)

• Record Type: Journal Article
• Authors: Vitaliano, Peter P; Fitzpatrick, Annette L; Williams, Lee E; Montano, Michalina A; Russo, Joan E
• Is Part Of: Innovation in aging. Volume 2:Issue 1(2018)
• Publication Date: 2018-03-26
• Subjects: Education -- Gender -- Life events -- Married -- Race -- Stress; Aging -- Periodicals; Gerontology -- Periodicals; 612.67
• DOI: 10.1093/geroni/igy005
• Languages: English
• ISSNs: 2399-5300

Abstract

Abstract: Purpose of the Study: (1a) We use the Cardiovascular Health Study (CHS), a multi-site heterogeneous sample of Medicare enrollees ( N = 5, 849) to provide rates for specific life events experienced within 6 months; (1b) We present rates for 29 other studies of community-residing older adults ( N = 41, 308); (2) For the CHS, we provide demographic-specific rates and predicted probabilities for age [young-old (65–75) vs old-old (≥75)], gender, race, marital status, and education. Design/Methods: The CHS sample is 57.6% women, 84.2% white (15.8% black), and 66.3% married. Mean age is 72.8 years (standard deviation [ SD ] = 5.6, range = 65–100) and education is 13.7 years ( SD = 4.8). Life events were interviewer-assessed. Regressions estimated associations of life event rates with demographic groups (e.g., age), controlling for other demographic variables (e.g., gender, etc.). Results: (1a) CHS rates ranged from 44.7% (death of someone close) to 1.1% (retirement/work changes). (1b) Most life event studies used total scores and only 5 that met our inclusion criteria used time intervals <1 year; longer intervals were associated with higher rates. (2) In the CHS, the life event for illnesses was related to 5 demographic variables (net the other 4 demographic variables), difficulties caregiving to 4, and worse relationships to 3 demographic variables. Race was related to 8 life events, marital status to 7, education to 6, and age to 4 events. Implications: By identifying demographic groups at highest risk for life events, this research focuses on older adults at greatest risk for health problems. These data are necessary for translating research into interventions, practice, and policy.