The Association Between Physical Activity and Cognition in a Racially/Ethnically Diverse Cohort of Older Adults: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

OBJECTIVE: Most prior research on physical activity (PA) and cognition is based on predominantly white cohorts and focused on associations of PA with mean (average) cognition versus the distribution of cognition. Quantile regression offers a novel way to quantify how PA affects cognition across the entire distribution. METHODS: The Kaiser Healthy Aging and Diverse Life Experiences study includes 30% white, 19% black, 25% Asian, and 26% Latinx adults age 65+ living in Northern California (n = 1600). The frequency of light or heavy PA was summarized as 2 continuous variables. Outcomes were z-scored executive function, semantic memory, and verbal episodic memory. We tested associations of PA with mean cognition using linear regression and used quantile regression to estimate the association of PA with the 10th-90th percentiles of cognitive scores. RESULTS: Higher levels of PA were associated with higher mean semantic memory (b = 0.10; 95% CI: 0.06, 0.14) and executive function (b = 0.05; 95% CI: 0.01, 0.09). Associations of PA across all 3 cognitive domains were stronger at low quantiles of cognition. CONCLUSION: PA is associated with cognition in this racially/ethnically diverse sample and may have larger benefits for individuals with low cognitive scores, who are most vulnerable to dementia.

Using an Online Panel to Crosswalk Alternative Measures of Alcohol Use As Fielded in Two National Samples.

Introduction: Accurate estimation of the health effects of drinking is hampered by inconsistent phrasing of questions about alcohol use in commonly-used health surveys (e.g., HRS, NYLS79), and measurement error in brief self-reports of drinking. We fielded an online survey to a diverse pool of respondents, assessing two versions of alcohol use questions. We used the measurement survey responses to evaluate correspondence across question versions and create a crosswalk between versions of alcohol questions from two different nationally representative studies of middle-aged adults. The measurement model can also be used to incorporate measurement error correction. Methods: Respondents to two measurement survey platforms (Centiment and Qualtrics) were asked drinking frequency and quantity questions as phrased in the Health and Retirement Study (HRS: average days per week drank in the last 3 months; quantity consumed on days drank in the last 3 months) and differently phrased questions from the National Longitudinal Survey of Youth 1979 (NLSY79: days drank in last 30 days, average quantity consumed on days drank). The order in which respondents encountered different versions of the questions was randomized. From these questions, we derived measures of average weekly alcohol consumption. In the online panel data, we regressed responses to the HRS question on responses to the NLSY question and vice versa to create imputation models. HRS (n=14,639) and NLSY79 (n=7,069) participants aged 50-59 self-rated their overall health (range 0-4, 0=excellent and 4=poor). NLSY79 or HRS participants' responses to the alcohol question from the other survey were multiply imputed (k=30) using the measurement model from the measurement survey participant data (k=30). We regressed self-rated health on each alcohol measure and estimated covariate-adjusted coefficients from observed and imputed versions of the questions. Results: The measurement survey (n=2,070) included respondents aged 50+; 64.8% female; 21.4% Hispanic, 23.95% Black, 27.1% White, and 27.6% another ("Other") self-reported racial/ethnic identity. Associations of observed alcohol question responses with self-reported health were slightly smaller than associations of imputed responses for frequency of alcohol use and consumption on days when alcohol was used. For example, using the HRS version of the frequency of alcohol use (days per week), the estimate for the observed question in HRS respondents was ꞵ =-0.045 [-0.055,-0.036]; and the estimate for the imputed version of the HRS question in NLSY79 respondents was ꞵ=-0.051 [-0.065,-0.037]. The estimated effect of average drinks per week was substantially larger for the imputed version of the measure (ꞵ for the observed question in HRS=-0.002 [-0.004,0.001], ꞵ for the imputed version of the HRS measure in NLSY79 respondents=-0.02 [-0.027,-0.012]). Patterns were similar when using the NLSY79 versions of questions as reported in NLSY79 and imputed for HRS respondents. For example, the estimated effect of average drinks per week was substantially larger for the imputed version of the NLSY79 question (ꞵ for the observed question in NLSY79=-0.006 [-0.01,-0.002], ꞵ for the imputed version of the HRS question in NLSY79 respondents=-0.019 [-0.027,-0.01]). Conclusions: Measurement inconsistencies and imperfect reliability are major challenges in estimating effects of alcohol use on health. Collecting additional data using online panels is a feasible and flexible approach to quantifying measurement differences. This approach may enable measurement error corrections, improve meta-analyses, and promote evidence triangulation.