Long Beach Longitudinal Study Elizabeth Zelinski, PhD Rita and Edward Polusky Chair in Aging and Education USC Davis School of Gerontology Funded by US National Institute on Aging Grants R01-AG10569 and T32-AG00037

Friday Harbor Psychometrics Workshop 2010 Acknowledgements Funded in part by Grant R13AG A1 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.

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 Shoshana Hindin 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

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

Age Health Context Social Context Cognition 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.

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

year birth cohort difference from Panel 1 6-year birth cohort difference from Panel 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 Panel 2/ Cohort 2 N = 630 Panel 2/ Cohort 2 N = 352 Panel 2/ Cohort 2 N = 173 Panel 2/ Cohort 2 N = 133 Panel 3/ Cohort 3 N = 911 Panel 3/ Cohort 3 N = year birth cohort difference from Panel 1 Panel 1/ Cohort 1 N = 20 Panel 2/ Cohort 2 N = 102 Panel 3/ Cohort 3 N = 296 Panel 1/ Cohort 1 N = 0

IQ Subtests, Cohort, and Change (Zelinski & Kennison, 2007) Compared age changes in people Compared 2 16-year birth cohorts Average birth years –Cohort 1: 1906 ( ) –Cohort 2: 1922 ( ) 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

Zelinski & Kennison, 2007

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

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

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

Cohort differences in Activities as a predictor of change

Mean/Proportion a (SD)ThresholdSELoadingsSE Factor Cohort/ Panel 1 Cohort/ Panel 2Invariant over Cohorts/Panels Baseline N Mental Fitness Educational.28 (.45).42 (.49) =10 Cultural.30 (.46).41 (.49) Going out to Movies.12 (.32).31 (.47) Self-Improvement.28 (.45).39 (.49) Volunteering.32 (.47).41 (.49) Writing/ Correspondence.59 (.49).68 (.47) Physical Fitness Fitness.40 (.49).60 (.49) =1 0 Participant Sports.28 (.45).24(.43) Walking.67 (.47).81 (.40) Outdoor Hobbies.38 (.49).50 (.50) Means, Thresholds, and Factor Loadings of Mental And Physical Fitness Activities a Means also represent the proportion of people reporting any participation in the activity because of categorical (0,1) coding.

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

Longitudinal Self-Reported Activities by Cohort MentalPhysical Zelinski, Lewis, Kennison & Watts, 2008

“new” measures

Zelinski & Lewis, 2003 Multiple Group Factor Analysis Results (3 age x 2 occasions) Factor SD Factor Correlations SpdWMTxtLst Full Information Data Voc Spd WM Txt Lst.79 Retested Subjects Only Voc Spd WM Txt Lst.78

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 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

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

ONE REASON WHY I HAVE HOPE FOR THE FUTURE OF LONGITUDINAL RESEARCH IN AGING Older Adults desperate for WiFi, Death Valley Visitor Center, March 19, 2009