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Long Beach Longitudinal Study: Aging, Cognition, and Health in Older Adults

The Long Beach Longitudinal Study aims to document cognitive change in healthy older adults and identify the mechanisms of change through individual differences models. This study includes a relatively large sample of the oldest-old, with data collected on social context, age, cognition, health, and lifestyle factors. Collaborators include researchers from USC Davis School of Gerontology.

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Long Beach Longitudinal Study: Aging, Cognition, and Health in Older Adults

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  1. Long Beach Longitudinal StudyElizabeth Zelinski, PhDRita and Edward Polusky Chair in Aging and EducationUSC Davis School of Gerontology Funded by US National Institute on Aging Grants R01-AG10569 and T32-AG00037

  2. Acknowledgements • Funded in part by Grant R13AG030995-01A1 from the National Institute on Aging • The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government. Friday Harbor Psychometrics Workshop 2010

  3. Collaborators • Kristin Antonio • Josette Bowers • Megan Braziel • Lisa Breen • Kerry Burnight, PhD • Sarah Canetti • Grace Sit Chan • Kami Chin • Althea De Pietro • Robin Engberg • Elena Estrada • Michael Gilewski, PhD • Amber Hall, PhD • ShoshanaHindin • George Holman • Patricia Housen, PhD • Robert Kennison, PhD • Deanah Kim • Shirley Kirksey • Christianne Lane • Kayan Lewis, PhD • Jack McArdle, PhD • Kevin Petway • Joyce Riley • Mariette Salama • K. Warner Schaie, PhD • Aisha Shaheen • Marc Simpao, MD • Susan Stewart, PhD • Erin Westphal

  4. Purposes of the Long Beach Longitudinal Study • to document cognitive change in healthy older adults • to identify mechanisms of change with individual differences models • extend models of change to a relatively large sample of the oldest-old: 50% of sample is currently over age 80

  5. Social Context Age Cognition Health Context Model Effects of aging on the social and health-related environment. These affect cognition in older adults, though cognitive status may affect some aspects of health and social functioning.

  6. Data • Each panel retested every 3-5 years • Goal--development of growth models of cognitive change and its correlates throughout adulthood • Measures are of • STAMAT: • INDUCTIVE REASONING: letter series & word series • SPACE: figure rotation & object rotation • Word fluency (EXECUTIVE) • VOCABULARY (STAMAT & 2 ETS advanced vocabulary) LIST RECALL: 2 lists TEXT RECALL: 3 short passages WORKING MEMORY: 3 measures SPEED: pattern, number, letter comparison RARE WORD DEFINITION Disourse production • Lifestyle: Life Complexity Inventory: Social networks, neighborhood, educational & cultural activities, exercise • Personality: NEO-PI-R (5 factors) • Memory Functioning Questionnaire: Frequency of Forgetting • Health: Seattle Health Behaviors (+ specific medical conditions) • IN PROCESS (oldest participants): • Blood samples for DNA/RNA analysis; blood lipids, markers for vascular & inflammatory risk • Imaging: Brain: brain volume & specific structures, WMH, cortical thickness; • Carotid intima media thickness, • Retinal photography • All participants: • HRS physical function measures (BP, BMI, tandem walk, gait speed), lung capacity, grip strength • HRS cognitive measures

  7. 1978 1981 1994-95 1997-98 2000-02 2003-05 Panel 1/ Cohort 1 N = 583 Panel 1/ Cohort 1 N = 264 Panel 1/ Cohort 1 N = 106 Panel 1/ Cohort 1 N = 42 Panel 1/ Cohort 1 N = 15 16 year birth cohort difference from Panel 1 Panel 2/ Cohort 2 N = 630 Panel 2/ Cohort 2 N = 352 Panel 2/ Cohort 2 N = 173 Panel 2/ Cohort 2 N = 133 22-year birth cohort difference from Panel 1 6-year birth cohort difference from Panel 2 Panel 3/ Cohort 3 N = 911 Panel 3/ Cohort 3 N = 513 2007-10 Panel 1/ Cohort 1 N = 0 Panel 1/ Cohort 1 N = 20 Panel 2/ Cohort 2 N = 102 Panel 3/ Cohort 3 N = 296

  8. IQ Subtests, Cohort, and Change (Zelinski & Kennison, 2007) • Compared age changes in people 55-82 • Compared 2 16-year birth cohorts • Average birth years • Cohort 1: 1906 (1897-1923) • Cohort 2: 1922 (1912-1939) • Recalibration of test scores into the same interval metric via Rasch scaling to compare relative age and cohort differences • Hypothesis: cohort differences in more fluid abilities; no differences in more crystallized

  9. Zelinski & Kennison, 2007

  10. Longitudinal Age Effects by Cohort Growth model over age; Intercept age 72 More recently born cohort better performance at intercept for more fluid like abilities Larger cohort differences for reasoning & recall; but age declines on average Zelinski & Kennison, 2007

  11. Do accelerations of age slopes vary by cohort? • Data in Zelinski & Kennison modeled at the average age of the sample • Measures differed at the intercept; do age declines accelerate at the same point across measures? • Do the cohorts have similar age breakpoints? • Are cohort differences observed at the average intercept observed at the best-fitting age breakpoints for each of the measures ? Kennison & Zelinski, in preparation

  12. Multiple Adaptive Regression Splines of Change Points over Age by Cohort The advantage enjoyed by Cohort 2 at the first turning point is reduced or eliminated by very old age The initially greater cognitive reserve enjoyed by the later-born cohort may be more limited late in life due to age related declines or less selection at older ages compared to Cohort 1. The oldest Cohort 1 members may have had greater cognitive reserve due to selective survival (their Time 1 scores were higher than those of Cohort 2) Kennison & Zelinski, in preparation

  13. Cohort differences in Activities as a predictor of change

  14. Means, Thresholds, and Factor Loadings of Mental And Physical Fitness Activities aMeans also represent the proportion of people reporting any participation in the activity because of categorical (0,1) coding.

  15. Strict (strong) invariance of a categorical cognitive activity factor across 16-year cohorts and over 3 years (2 cohorts x 2 measurement occasions each)

  16. Mental Physical Longitudinal Self-Reported Activities by Cohort Zelinski, Lewis, Kennison & Watts, 2008

  17. “new” 1994+ measures

  18. Multiple Group Factor Analysis Results (3 age x 2 occasions) Zelinski & Lewis, 2003

  19. Models of List and Text recall as Related but Separate Outcomes Replication of model across two panels at Time 1 Replication of model within panels at Time 1 comparing retested subjects and Time 2 dropouts Replication of model within 1994-95 panel over time 1 & time 2 comparing time 3 dropouts Attrition did not markedly change results in the models, even over samples and over more than one retest. This implies that relatively similar underlying patterns of cross-sectional interindividual differences in these measures across adulthood hold. Lewis & Zelinski, 2010

  20. Findings • No evidence of increased factor SDs or correlations • Over test occasions • Over retestee/dropout status • Between Panels 1 & 2 compared to Panel 3 • Conclusion: Structural relationships in LBLS remain invariant under a wide variety of cross sectional data samples • Measurement of resource constructs stable • No evidence for dedifferentiation

  21. Older Adults desperate for WiFi, Death Valley Visitor Center, March 19, 2009 One reason Why I have hope for the future of LONGITUDINAL RESEARCH IN aging

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