Association Between Life's Essential 8 and Cognitive Function Among US Older Adults

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This study explores the relationships between both the aggregate and individual CVH metrics, as defined by Life's Essential 8, and cognitive function in older adults in the United States. Methods This cross-sectional, population-based study analyzed data from the National Health and Nutrition Examination Survey conducted between 2011 and 2014, focusing on individuals aged 60 years and older. CVH was categorized as low(0–49), moderate(50–79), or high(80–100). Cognitive function was assessed through the CERAD tests, Animal Fluency test, and Digit Symbol Substitution test. Multivariable logistic models and restricted cubic spline models were employed to investigate these associations. Results This study included a total of 2,279 older adults in the United States. Only 11% of adults achieved a high total CVH score, while 12% had a low score. After adjusting for potential confounding factors, higher LE8 scores were significantly associated with higher scores on CERAD: delayed recall score(0.02[0.01, 0.03]; P < 0.001), CERAD: total score(3 recall trials)(0.04[0.02, 0.06]; P < 0.001), animal fluency: total score(0.09[0.05, 0.12]; P < 0.001), and digit symbol: score(0.29[0.18, 0.41]; P < 0.001), demonstrating a linear dose-response relationship. Similar patterns were also observed in the associations between health behavior and health factor scores with cognitive function tests. Conclusion LE8 scores exhibited positive linear associations with cognitive function. Promoting adherence to optimal CVH levels may prove beneficial in maintaining higher levels of cognitive function in older adults in the United States. Health sciences/Health care Health sciences/Neurology Life's Essential 8 Cognition NHANES Cardiovascular health Aging Figures Figure 1 Figure 2 Introduction Cognitive function changes in older adults represent a pressing concern in contemporary society, driven by the global aging trend[ 1 , 2 ]. The increase in life expectancy has resulted in a higher prevalence of cognitive impairments, spanning from mild cognitive decline to severe dementia[ 3 , 4 ]. From a medical perspective, cognitive decline poses substantial challenges, particularly with conditions like Alzheimer's disease, necessitating specialized care and management that impose a significant financial burden on healthcare systems[ 5 ]. Families often shoulder the responsibility of caring for elderly relatives with cognitive impairments, leading to caregiver burnout and affecting both caregivers' and recipients' quality of life[ 6 ]. Economically, the associated costs of cognitive impairment are staggering, encompassing medical expenses, caregiving, and institutionalization, thereby straining governments and healthcare systems[ 7 ]. Cognitive function changes in older adults present a multifaceted challenge with wide-ranging societal implications. Despite notable progress in raising awareness of cardiovascular health, the current state of heart health presents a multifaceted landscape[ 8 ]. On one hand, strides have been made in reducing smoking rates, promoting healthy diets, and increasing physical activity levels[ 9 – 11 ]. Advances in medical treatments and interventions have improved outcomes for individuals with heart conditions. Nevertheless, challenges persist. Cardiovascular disease remains the leading global cause of death, exacerbated by sedentary lifestyles, unhealthy dietary habits, and escalating obesity rates. The demands of modern life, compounded by inadequate sleep, further heighten cardiovascular risks[ 12 ]. In 2010, the American Heart Association (AHA) introduced Life's Simple 7 (LS7), a comprehensive cardiovascular health (CVH) assessment comprising elements such as a balanced diet, tobacco abstinence, a healthy BMI, regular physical activity, blood pressure control, fasting blood glucose management, and cholesterol levels, all aimed at advancing public health[ 13 ]. More recently, the AHA has enhanced the evaluation of CVH with the introduction of Life's Essential 8 (LE8)[ 14 ]. LE8 introduces updated sleep quality metrics and refined scoring algorithms compared to LS7, offering a more nuanced approach that accounts for individual variations and underscores the importance of social determinants of health and mental well-being in the preservation and enhancement of CVH[ 14 ]. "Life's Essential 8" presents a comprehensive perspective on cardiovascular health, emphasizing the critical role of lifestyle choices and risk factor management. It underscores that a well-balanced diet, regular physical activity, abstaining from tobacco, prioritizing quality sleep, weight maintenance, and effective management of blood lipids, blood glucose, and blood pressure are interconnected elements pivotal for cardiovascular well-being[ 14 ]. The adoption of these principles has the potential to significantly reduce the risk of heart disease and elevate overall quality of life. Notably, research exploring the correlation between LE8 and Cognitive function remains limited at present. The intricate relationship between cognitive function and cardiovascular health in older adults underscores their reciprocal influences on overall well-being[ 15 ]. Cardiovascular health, including key factors such as blood pressure, blood lipid profiles, and vascular function, plays a pivotal role in sustaining optimal cerebral blood flow. Conditions like hypertension and atherosclerosis, prevalent in poor cardiovascular health, can compromise cerebral perfusion, potentially leading to cognitive decline[ 16 ]. Conversely, cognitive function and mental health significantly influence one's capacity to adhere to heart-healthy lifestyle choices. The adoption of healthy habits, including regular exercise, smoking cessation, and a balanced diet, not only reduces cardiovascular risks but also correlates with enhanced cognitive function[ 17 ]. These interconnections emphasize the importance of a comprehensive health approach addressing both cognitive well-being and cardiovascular health in older adults. However, it is worth noting that the association between Life's Essential 8, the latest metric for comprehensively assessing cardiovascular health, and altered cognitive function in older adults requires further research validation. Therefore, this study aims to estimate the correlation between Life's Essential 8 and cognitive function in older adults using data from the National Health and Nutrition Examination Survey (NHANES). Methods Study population The analysis in this study strictly adhered to the NHANES analytic guidelines, which are overseen by the National Center for Health Statistics at the Centers for Disease Control and Prevention in Maryland. NHANES employs a meticulously designed stratified multi-stage sampling approach, and comprehensive documentation of the sampling and testing procedures can be found in previously published articles[ 18 ]. In summary, systematic health-related interviews and examinations occurred in 2-year cycles, ensuring the inclusion of participants from diverse geographical regions and various racial/ethnic backgrounds, thereby guaranteeing comprehensive representation in the survey. Notably, NHANES protocols have obtained ethical approval from the National Center for Health Statistics research ethics review board, and written informed consent was obtained from all enrolled participants. Cognitive testing was specifically administered to participants aged 60 years and older during the period of 2011–2014[ 19 ]. The data utilized in this study were extracted from NHANES surveys conducted between 2011 and 2014. Among the 19,931 subjects who participated in NHANES from 2011 to 2014, individuals were excluded based on the following criteria: (1) those under the age of 60 (n = 16,299), (2) those with incomplete cognitive testing data (n = 698), and (3) those with missing data on LS8 and covariates (n = 221). Consequently, a total of 2,279 subjects met the inclusion criteria for this research. The detailed flowchart illustrating this process is presented in Fig. 1 . Cognitive function Cognitive functioning was evaluated during an interview conducted at a Mobile Examination Center and assessed by skilled interviewers. This assessment comprised three distinct tests: the CERAD Word Learning sub-test (CERAD W-L), which measured immediate and delayed recall of new verbal information (a memory sub-domain); the Animal Fluency test, designed to evaluate categorical verbal fluency (a component of executive function); and the Digit Symbol Substitution Test (DSST), which gauged processing speed, sustained attention, and working memory. The CERAD test involved three consecutive learning trials and a delayed recall task. Consequently, the results are reported as three individual trial scores, each ranging from 0 to 10, a total score that combines performance across all three trials, ranging from 0 to 30, and a single score for delayed recall, ranging from 0 to 10. While there is no upper limit, in practical terms, scores for the Animal Fluency test typically range from 3 to 39, and scores for the digit symbol test range from 0 to 105. All results were recorded on the CFQ questionnaire Measurement of Life's Essential 8 The LE8 score comprises four health behaviors (diet, physical activity, nicotine exposure, and sleep duration) and four health factors (body mass index, non-HDL cholesterol, blood glucose, and blood pressure)[ 14 ]. Detailed scoring criteria for each item can be found in Table S1 . Dietary parameters were evaluated using the Healthy Eating Index (HEI) 2015, calculated based on the subject's 24-hour dietary recall[ 20 ]. The HEI score was computed as the average of two recall periods, or if only data from the first day was available, that value was used. Information regarding physical activity, nicotine exposure, sleep patterns, diabetes history, and medication history was collected through a self-report questionnaire. Physical examinations included height, weight, and blood pressure measurements, from which body mass index (BMI) was derived by dividing weight (in kilograms) by the square of height (in meters). Non-HDL(high-density lipoprotein) cholesterol and hemoglobin A1c levels were determined from collected blood samples. Each of the 8 CVH indicators received a score ranging from 0 to 100, and the total LE8 score was calculated as the unweighted average of these 8 indicators. Moreover, participants exhibiting high CVH were classified with LE8 scores between 80 and 100, those with moderate CVH fell within the 50–79 range, and individuals with low CVH were situated between 0 and 49[ 14 ]. In our study, we utilized these same cutoff points to categorize health behavior and health factor scores, enabling further exploration of the relationship between LE8 subscales and cognitive function. Study covariates The study's covariates encompassed gender (male and female), age, categorized into age groups (60–69, 70–79, and 80 + years), race/ethnicity (non-hispanic white, non-hispanic black, other hispanic, mexican american, non-hispanic asian, and others), educational attainment (less than 9th grade, college graduate or above, high school graduate/GED or equivalent, less than 9th grade, and some college or AA degree), the family income-to-poverty ratio, and alcohol consumption. Statistical analysis Given the intricate NHANES sampling design, we employed appropriate weights for the sample analysis. For initial characterization, we utilized weighted means (IQR) for continuous variables and sample sizes (weighted percentages) for categorical variables. To assess disparities in variable characteristics among the low, moderate, and high CVH groups, we applied ANOVA for differences in weighted means regarding continuous variables and the Rao—Scott χ2 test for distinctions in weighted percentages for categorical variables. Weighted linear regression was employed to investigate the correlation between LE8 scores and cognitive test results (including CERAD: Trial 1–3 Score, CERAD: Total Score (3 Recall trials), CERAD: Delayed Recall Score, Animal Fluency: Total Score, and Digit Symbol: Score), as well as the association between various CVH levels and cognitive tests. Crude models did not incorporate any potential confounding factors, whereas age-adjusted models were adjusted solely for age. Fully-adjusted models included adjustments for age, sex, race, education level, the family income-to-poverty ratio, and alcohol consumption. Furthermore, we explored the correlations between health behavior, health factor scores, and each of the LE8 scores with cognitive tests using weighted linear regression analyses, while accounting for all confounding variables. To further validate the link between LE8 scores and cognitive tests, we employed Restricted Cubic Spline (RCS). All analyses were conducted in the overall population, as well as in subgroups based on sex (women and men) and age groups (60–69 years, 70–79 years, and 80 + years), respectively. Statistical tests were two-sided, with statistical significance set at P < 0.05. All analyses were performed using R software, version 4.2.0 (R Core Team, Vienna, Austria). Result Descriptive statistics The characteristics of the study population according to CVH status were shown in Table 1 . A total of 2279 adults aged 60 years or older were included for analysis. Moderate CVH status group contained 76% of all participants. The mean age was 69.01 years, and 47% of the participants were male. Participants with high CVH status were more likely to be Non-Hispanic White, higher educational levels, to have higher PIR, and more alcohol consumption (P < 0.001). Table 1 Baseline Characteristics of the NHANES Participants Selected by Life’s Essential 8 Characteristic N 1 Overall, N = 2279 (100%) 2 Life’s Essential 8 P Value 3 Low CVH (0–49 points) , N = 359 (12%) 2 Moderate CVH (50–79 points) , N = 1717 (76%) 2 High CVH (80–100 points) , N = 203 (11%) 2 Age (years) 2,279 69.01 (63.00, 74.00) 67.78 (62.00, 72.00) 69.22 (64.00, 74.00) 68.94 (63.00, 75.00) 0.016 Age group 2,279 0.4 60–69 years 1,156 (53%) 210 (59%) 854 (52%) 92 (55%) 70–79 years 633 (27%) 95 (27%) 487 (28%) 51 (24%) 80 + years 490 (19%) 54 (15%) 376 (20%) 60 (21%) Sex 2,279 0.7 female 1,149 (53%) 194 (51%) 854 (54%) 101 (50%) male 1,130 (47%) 165 (49%) 863 (46%) 102 (50%) Race 2,279 < 0.001 Non-Hispanic White 1,165 (80%) 136 (69%) 899 (81%) 130 (88%) Non-Hispanic Black 510 (7.9%) 131 (16%) 356 (7.2%) 23 (3.2%) Other Hispanic 222 (3.5%) 42 (4.9%) 171 (3.6%) 9 (1.5%) Mexican American 195 (3.4%) 36 (5.0%) 147 (3.4%) 12 (1.8%) Non-Hispanic Asian 153 (3.3%) 5 (0.7%) 119 (3.3%) 29 (5.9%) Other/multiracial 34 (1.7%) 9 (4.2%) 25 (1.5%) 0 (0%) Education level 2,279 < 0.001 Less than 9th grade 230 (5.2%) 64 (10%) 162 (4.9%) 4 (1.1%) 9-11th grade 298 (9.9%) 65 (16%) 221 (9.6%) 12 (5.6%) High school graduate/GED or equivalent 535 (22%) 91 (23%) 416 (23%) 28 (10%) Some college or AA degree 672 (33%) 103 (38%) 510 (33%) 59 (24%) College graduate or above 544 (31%) 36 (13%) 408 (29%) 100 (59%) PIR 2,279 3.17 (1.71, 5.00) 2.42 (1.12, 3.65) 3.18 (1.74, 5.00) 3.94 (3.06, 5.00) < 0.001 Alcohol consumption 2,279 < 0.001 Non-drinker 687 (27%) 105 (25%) 523 (27%) 59 (23%) 1–5 drinks/month 1,118 (48%) 198 (60%) 829 (47%) 91 (46%) 5–10 drinks/month 104 (5.3%) 17 (3.5%) 77 (5.4%) 10 (6.7%) 10 + drinks/month 370 (20%) 39 (12%) 288 (20%) 43 (24%) 1 N not Missing (unweighted), 2 median (IQR) for continuous; n (%) for categorical, 3 Wilcoxon rank-sum test for complex survey samples; chi-squared test with Rao & Scott's second-order correction; CVH, cardiovascular health; PIR, Poverty Impact Ratio. Association between Life’s Essential 8 and cognitive function Table 2 presented the associations between Life’s Essential 8 and cognitive performance. High CVH group had a higher score in Life’s Essential 8 total score, health behaviors score, diet score, physical activity score, sleep health score, tobacco exposure score, health factors score, BMI score, BP score, Blood glucose score and blood lipids (non-HDL cholesterol) score (P < 0.001). High CVH group also showed better performance in cognitive outcomes including CERAD: trial 1–3, CERAD: delayed recall, animal fluency test, and gigit symbol test (P < 0.05). Table 2 Association between cognitive tests scores and CVH status Characteristic N 1 Overall , N = 2279 (100%)2 Low CVH (0–49 points) , N = 359 (12%)2 Moderate CVH (50–79 points) , N = 1717 (76%)2 High CVH (80–100 points) , N = 203 (11%)2 P Value 3 Life’s Essential 8 Overall 2,279 64.65 (55.63, 73.75) 42.92 (40.63, 46.88) 65.21 (58.75, 72.50) 84.48 (81.25, 86.88) < 0.001 Health behaviors 2,279 66.52 (56.25, 81.25) 42.57 (35.00, 50.00) 67.92 (56.25, 81.25) 83.08 (81.25, 87.50) < 0.001 Diet 2,279 40.22 (25.00, 50.00) 33.53 (25.00, 50.00) 40.24 (25.00, 50.00) 47.37 (50.00, 50.00) < 0.001 Physical activity 2,279 62.78 (0.00, 100.00) 14.72 (0.00, 0.00) 65.31 (0.00, 100.00) 97.87 (100.00, 100.00) < 0.001 Sleep health 2,279 85.96 (70.00, 100.00) 69.84 (40.00, 100.00) 87.25 (70.00, 100.00) 94.69 (100.00, 100.00) < 0.001 Tobacco exposure 2,279 77.12 (75.00, 100.00) 52.18 (0.00, 75.00) 78.87 (75.00, 100.00) 92.40 (75.00, 100.00) < 0.001 Health factors 2,279 62.78 (50.00, 75.00) 43.27 (32.94, 52.50) 62.50 (52.50, 72.50) 85.89 (80.00, 90.94) < 0.001 BMI 2,279 60.16 (30.00, 100.00) 34.79 (15.00, 70.00) 60.05 (30.00, 70.00) 88.47 (70.00, 100.00) < 0.001 BP 2,279 50.12 (25.00, 80.00) 32.80 (5.00, 55.00) 48.63 (25.00, 75.00) 78.95 (55.00, 100.00) < 0.001 Blood glucose 2,279 70.80 (60.00, 100.00) 48.64 (30.00, 60.00) 71.14 (60.00, 100.00) 92.56 (100.00, 100.00) < 0.001 Blood lipids (non-HDL cholesterol) 2,279 70.05 (40.00, 100.00) 56.86 (30.29, 100.00) 70.17 (40.00, 100.00) 83.57 (60.00, 100.00) < 0.001 Cognitive tests CERAD: Trial 1 Score 2,279 5.01 (4, 6) 4.75 (4, 6) 5.00 (4, 6) 5.31 (4, 6) 0.001 CERAD: Trial 2 Score 2,279 7.04 (6, 8) 6.84 (6, 8) 6.99 (6, 8) 7.55 (6, 9) < 0.001 CERAD: Trial 3 Score 2,279 7.80 (7, 9) 7.58 (7, 9) 7.77 (7, 9) 8.26 (7, 10) < 0.001 CERAD: Total Score (3 Recall trials) 2,279 19.84 (17, 23) 19.17 (17, 22) 19.76 (17, 23) 21.12 (19, 24) < 0.001 CERAD: Delayed Recall Score 2,279 6.31 (5, 8) 6.02 (5, 8) 6.28 (5, 8) 6.84 (5, 8) 0.002 Animal Fluency: Total Score 2,279 18.30 (14, 22) 16.71 (13, 20) 18.26 (14, 22) 20.25 (16, 24) < 0.001 Digit Symbol: Score 2,279 52.84 (42, 64) 46.86 (34, 58) 52.91 (42, 64) 58.90 (49, 69) < 0.001 1 N not Missing (unweighted), 2 median (IQR) for continuous; n (%) for categorical, 3 Wilcoxon rank-sum test for complex survey samples; chi-squared test with Rao & Scott's second-order correction; CVH, cardiovascular health; BMI, body mass index; BP, blood pressure; HDL, high-density lipoprotein; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease. When treating Life’s Essential 8 as a continuous measure, each 1-unit increase in Life’s Essential 8 score was associated with higher CERAD: delayed recall score (Beta: 0.02; 95%CI: 0.01, 0.03; P < 0.001), CERAD: total score (3 recall trials) (Beta: 0.04; 95%CI: 0.02, 0.06; P < 0.001), animal fluency: total score (Beta: 0.09; 95%CI: 0.05, 0.12; P < 0.001), and digit symbol: score (Beta: 0.29; 95%CI: 0.18, 0.41; P < 0.001) (Table 3 ). Similar results were obtained after adjusting for age (Table 3 ). After fully adjusting, Life’s Essential 8 score was associated with higher CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.00, 0.04; P = 0.035), animal fluency: total score (Beta: 0.04; 95%CI: 0.01, 0.07; P = 0.007), and digit symbol: score (Beta: 0.11; 95%CI: 0.02, 0.19; P = 0.015) but not CERAD: delayed recall score (Beta: 0.01; 95%CI: 0.00, 0.02; P = 0.052) (Table 3 ). When grouped according to CVH status, High CVH was significantly associated with higher CERAD: delayed recall score (Beta: 0.82; 95%CI: 0.40, 1.2; P < 0.001), CERAD: total score (3 recall trials) (Beta: 1.9; 95%CI: 1.1, 2.8; P < 0.001), animal fluency: total score (Beta: 3.5; 95%CI: 2.0, 5.1; P < 0.001), and digit symbol: score (Beta: 12; 95%CI: 7.0, 17; P < 0.001), compared to Low CVH (Table 3 ). Similar results were showed after adjusting for age or fully adjusted (Table 3 ). Beta coefficients and 95% confidence intervals of Life’s Essential 8 for CERAD: Trial1-3 were provided in Table S2. Table 3 Beta coefficients and 95% confidence intervals of Life’s Essential 8 for cognitive tests scores CERAD: Delayed Recall Score CERAD: Total Score (3 Recall trials) Animal Fluency: Total Score Digit Symbol: Score Beta 95% CI 1 p-value Beta 95% CI 1 p-value Beta 95% CI 1 p-value Beta 95% CI 1 p-value Life’s Essential 8 No-adjusted 0.02 0.01, 0.03 < 0.001 0.04 0.02, 0.06 < 0.001 0.09 0.05, 0.12 < 0.001 0.29 0.18, 0.41 < 0.001 Age-adjusted 0.02 0.01, 0.02 < 0.001 0.04 0.03, 0.06 < 0.001 0.09 0.06, 0.12 < 0.001 0.3 0.20, 0.40 < 0.001 Fully adjusted 2 0.01 0.00, 0.02 0.052 0.02 0.00, 0.04 0.035 0.04 0.01, 0.07 0.007 0.11 0.02, 0.19 0.015 CVH status (Based on Life’s Essential 8) No adjusted Low CVH (0–49 points) Reference Reference Reference Reference Moderate CVH (50–79 points) 0.26 0.00, 0.52 0.048 0.59 -0.06, 1.2 0.076 1.6 0.65, 2.5 0.002 6 2.2, 9.9 0.003 High CVH (80–100 points) 0.82 0.40, 1.2 < 0.001 1.9 1.1, 2.8 < 0.001 3.5 2.0, 5.1 < 0.001 12 7.0, 17 < 0.001 Age-adjusted Low CVH (0–49 points) Reference Reference Reference Reference Moderate CVH (50–79 points) 0.42 0.13, 0.71 0.007 0.9 0.32, 1.5 0.004 1.9 1.0, 2.8 < 0.001 7.5 4.1, 11 < 0.001 High CVH (80–100 points) 0.95 0.56, 1.3 < 0.001 2.2 1.3, 3.1 < 0.001 3.8 2.4, 5.2 < 0.001 13 9.0, 17 < 0.001 Fully adjusted 2 Low CVH (0–49 points) Reference Reference Reference Reference Moderate CVH (50–79 points) 0.19 -0.17, 0.55 0.3 0.33 -0.35, 1.0 0.3 0.94 0.14, 1.7 0.025 2.9 0.41, 5.3 0.025 High CVH (80–100 points) 0.51 0.08, 0.95 0.022 1.1 0.11, 2.1 0.031 1.7 0.41, 3.1 0.014 4.5 0.56, 8.5 0.028 1 CI = Confidence Interval; CVH, cardiovascular health; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease. 2 Fully adjusted: adjusted for age, sex, race, education level, ratio of family income to poverty and alcohol consumption. The dose-response relationship between Life’s Essential 8 and cognitive function after fully adjusting were shown in Fig. 2 . In restricted cubic spline models, Life’s Essential 8 scores were positively associated with CERAD: delayed recall score (P-overall < 0.0001, P-non-linear = 0.3340; Fig. 2 A), CERAD: total score (3 recall trials) (P-overall < 0.0001, P-non-linear = 0.7709; Fig. 2 B), animal fluency: total score (P-overall < 0.0001, P-non-linear = 0.9974; Fig. 2 C), digit symbol: score (P-overall < 0.0001, P-non-linear = 0.3446; Fig. 2 D) in a linear manner. Association between Life’s Essential 8 components and cognitive function The LE8 score comprises four health behaviors (diet, physical activity, nicotine exposure, and sleep duration) and four health factors (body mass index, non-HDL cholesterol, blood glucose, and blood pressure). Health behaviors score was associated with higher animal fluency: total score (Beta: 0.04; 95%CI: 0.02, 0.06; P < 0.001), and digit symbol: score (Beta: 0.10; 95%CI: 0.05, 015; P < 0.001) but not CERAD: delayed recall score (Beta: 0; 95%CI: 0.00, 0.01; P = 0.2), CERAD: total score (3 recall trials) (Beta: 0.01; 95%CI: 0.00, 0.02; P = 0.081), after fully adjusted (Table 4 ). Health factors score was associated with higher CERAD: delayed recall score (Beta: 0.01; 95%CI: 0.00, 0.01; P = 0.003), CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.01, 0.03; P = 0.002), animal fluency: total score (Beta: 0.03; 95%CI: 0.01, 0.05; P = 0.006), and digit symbol: score (Beta: 0.12; 95%CI: 0.04, 0.20; P = 0.003) after adjusting age (Table 4 ). When fully adjusted, no significant association was found between health factors score and cognitive function scores. The dose-response relationship between health behaviors, health factors and cognitive function after fully adjusting were shown in Figure S1 . Beta coefficients and 95% confidence intervals of health behaviors and health factors for CERAD: Trial1-3 were provided in Table S3. Higher non-HLD cholesterol scores were associated with worse animal fluency: total score (Beta: -0.01; 95%CI: -0.02, 0.00; P = 0.047), and digit symbol: score (Beta: -0.02; 95%CI: -0.04, 0.00; P = 0.047), and BMI was not significantly correlated with cognitive function scores (Table S4). Association between all Life’s Essential 8 metric (diet, physical activity, nicotine exposure, sleep duration, body mass index, non-HDL cholesterol, blood glucose, and blood pressure) and cognitive function scores was provided in Table S4. Table 4 Beta coefficients and 95% confidence intervals of health behaviors and health factors for cognitive tests scores Characteristic CERAD: Delayed Recall Score CERAD: Total Score (3 Recall trials) Animal Fluency: Total Score Digit Symbol: Score Beta 95% CI 1 p-value Beta 95% CI 1 p-value Beta 95% CI 1 p-value Beta 95% CI 1 p-value Health behaviors No adjusted 0.01 0.01, 0.02 < 0.001 0.03 0.02, 0.04 < 0.001 0.07 0.05, 0.09 < 0.001 0.22 0.15, 0.28 < 0.001 Age-adjusted 0.01 0.01, 0.02 < 0.001 0.03 0.02, 0.04 < 0.001 0.07 0.05, 0.09 < 0.001 0.22 0.16, 0.28 < 0.001 Fully adjusted 2 0 0.00, 0.01 0.2 0.01 0.00, 0.02 0.081 0.04 0.02, 0.06 < 0.001 0.1 0.05, 0.15 < 0.001 Health factors No adjusted 0.01 0.00, 0.01 0.029 0.02 0.00, 0.03 0.014 0.03 0.01, 0.06 0.02 0.12 0.03, 0.21 0.014 Age-adjusted 0.01 0.00, 0.01 0.003 0.02 0.01, 0.03 0.002 0.03 0.01, 0.05 0.006 0.12 0.04, 0.20 0.003 Fully adjusted 2 0 0.00, 0.01 0.094 0.01 0.00, 0.02 0.13 0 -0.02, 0.02 0.7 0.02 -0.04, 0.08 0.5 1 CI = Confidence Interval; 2 Fully adjusted: adjusted for age, sex, race, education level, ratio of family income to poverty and alcohol consumption. Subgroup analysis of sex and age The results of subgroup analyses are presented in Table 5 . In the male subgroup, LS8 showed a significant positive correlation with animal fluency score (Beta: 0.05; 95%CI: 0.01, 0.09; P = 0.014) after fully-adjusted. LS8 was positive correlated with CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.00, 0.04; P = 0.036) and animal fluency score (Beta: 0.04; 95%CI: 0.00, 0.07; P = 0.03) in the female subgroup. In the 60–69 years age subgroup, LS8 showed a significant positive correlation with animal fluency score (Beta: 0.04; 95%CI: 0.01, 0.08; P = 0.027) after fully-adjusted. In the 70–79 years age subgroup, no significant correlation between LS8 and cognitive tests after fully-adjusted. But in the 80 + years age subgroup, LS8 was positive correlated with animal fluency score (Beta: 0.05; 95%CI: 0.00, 0.09; P = 0.036) and digit symbol score (3 recall trials) (Beta: 0.19; 95%CI: 0.09, 0.28; P = 0.001). Subgroup analysis of sex and age for CERAD: Trial 1–3 was showed in Table S5. Table 5 Beta coefficients and 95% confidence intervals of Life’s Essential 8 for cognitive tests scores by sex and age CERAD: Delayed Recall Score CERAD: Total Score (3 Recall trials) Animal Fluency: Total Score Digit Symbol: Score Subgroup Category Beta 95% CI1 p-value Beta 95% CI1 p-value Beta 95% CI1 p-value Beta 95% CI1 p-value Sex Male No-adjusted 0.01 0.00, 0.02 0.088 0.03 0.01, 0.06 0.02 0.09 0.04, 0.13 < 0.001 0.26 0.13, 0.39 < 0.001 Age-adjusted 0.02 0.00, 0.03 0.007 0.04 0.02, 0.06 < 0.001 0.1 0.05, 0.14 < 0.001 0.3 0.19, 0.41 < 0.001 Fully-adjusted 2 0.01 -0.01, 0.02 0.2 0.02 -0.01, 0.04 0.2 0.05 0.01, 0.09 0.014 0.09 -0.01, 0.19 0.062 Female No-adjusted 0.02 0.01, 0.04 < 0.001 0.05 0.03, 0.08 < 0.001 0.09 0.05, 0.12 < 0.001 0.33 0.18, 0.49 < 0.001 Age-adjusted 0.02 0.01, 0.03 < 0.001 0.05 0.03, 0.07 < 0.001 0.08 0.04, 0.11 < 0.001 0.31 0.17, 0.45 < 0.001 Fully-adjusted 2 0.01 0.00, 0.02 0.063 0.02 0.00, 0.04 0.036 0.04 0.00, 0.07 0.03 0.11 -0.01, 0.23 0.065 Age 60–69 years No-adjusted 0.02 0.01, 0.03 0.001 0.05 0.02, 0.07 < 0.001 0.1 0.06, 0.14 < 0.001 0.29 0.15, 0.43 < 0.001 Fully-adjusted 3 0.01 0.00, 0.02 0.2 0.02 0.00, 0.04 0.12 0.04 0.01, 0.08 0.027 0.05 -0.05, 0.16 0.3 70–79 years No-adjusted 0.02 0.00, 0.04 0.085 0.04 0.00, 0.08 0.04 0.07 0.02, 0.12 0.004 0.27 0.12, 0.43 < 0.001 Fully-adjusted 3 0.01 -0.02, 0.03 0.4 0.03 -0.02, 0.07 0.2 0.03 -0.02, 0.07 0.2 0.13 -0.02, 0.27 0.077 80 + years No-adjusted 0.01 -0.01, 0.04 0.3 0.03 -0.01, 0.08 0.13 0.09 0.05, 0.12 < 0.001 0.38 0.25, 0.50 < 0.001 Fully-adjusted 3 0.01 -0.02, 0.03 0.5 0.02 -0.03, 0.06 0.5 0.05 0.00, 0.09 0.036 0.19 0.09, 0.28 0.001 1 CI = Confidence Interval; 2 Fully adjusted: adjusted for age, race, education level, ratio of family income to poverty and alcohol consumption; 3 Fully adjusted: adjusted for sex, race, education level, ratio of family income to poverty and alcohol consumption. Discussion The global landscape is witnessing a significant demographic shift, with a burgeoning aging population. By 2050, it is projected that older adults aged 60 years and above will constitute 22% of the global population. This demographic transformation brings forth unique challenges, including the rising prevalence of cognitive impairments and neurodegenerative diseases[ 21 ]. Cognitive function, encompassing memory, attention, executive function, and other mental processes, is a fundamental component of an individual's ability to lead an independent and fulfilling life. Simultaneously, cardiovascular health remains a central concern, given its pervasive impact on mortality and morbidity worldwide[ 8 ]. Cardiovascular disease (CVD) is the leading cause of death globally, underlining the need for comprehensive strategies to mitigate risk factors and promote heart health. Life's Essential 8 (LE8), an innovative metric introduced by the AHA, offers a holistic approach to assess cardiovascular health, focusing on lifestyle choices and risk factor management[ 14 ]. In this nationally representative cross-sectional study, we found that LE8 scores and its health behaviors scores and health factors scores showed a significant positive correlation with cognitive test scores of U.S. seniors aged 60 years and older. Previous study has explored the link between LS7 and cognitive functioning and found that maintaining good LS7 scores showed a significant positive correlation with better cognitive functioning[ 22 ]. Our findings are similar to previous study. The CHV definitions of LS7 were categorized into ideal, intermediate, and poor CVH for each component. This definition is less sensitive to interindividual differences and is unable to be used to assess dose-response effects[ 23 ]. Moreover, we found a significant linear relationship between LS8 and cognitive test scores by RCS analysis (Fig. 2 ), further suggesting that maintaining good LS8 scores is beneficial to cognitive function. The use of LE8 as a definition of CVH in this study adds significant evidence of a relationship between CVH and cognitive function. High CVH group (based on LS8 score) was significantly associated with higher CERAD: delayed recall score, CERAD: total score (3 recall trials), animal fluency: total score, and digit symbol: score, compared to Low CVH group (Table 3 ). Maintaining good cardiovascular status shows an important positive correlation with good cognitive function performance. One of the primary reasons for the strong connection between cardiovascular health and cognitive function is the presence of shared risk factors. Many risk factors that contribute to cardiovascular diseases, such as hypertension, diabetes, hyperlipidemia, and obesity, have also been implicated in the development of cognitive impairments and neurodegenerative diseases[ 24 – 27 ]. This overlap in risk factors underscores the importance of addressing both cardiovascular health and cognitive function in tandem. The LE8 score comprises and four health factors: BMI, non-HDL cholesterol, blood glucose, and blood pressure, to assess individual cardiovascular health. And health factors score was associated with higher CERAD: delayed recall score, CERAD: total score (3 recall trials), animal fluency: total score, and digit symbol: score after adjusting age (Table 4 ). Although our study did not find a significant association between BMI and cognitive function, excessive BMI often represents obesity, obesity can lead to cardiovascular issues, inflammation, insulin resistance, and metabolic disruptions, all of which are associated with cognitive decline. Furthermore, obesity may trigger adverse changes in brain structure and function, increasing the risk of cognitive impairments and dementia[ 28 ]. Elevated blood glucose levels, such as in diabetes, are associated with an increased risk of cognitive decline and dementia. Prolonged high blood glucose can lead to nerve damage, vascular inflammation, and structural brain changes, all of which can impact cognitive function[ 29 , 30 ]. Optimal blood pressure levels are associated with improved cognitive resilience, while hypertension has been linked to an increased risk of cognitive impairments, including Alzheimer's disease and dementia[ 24 , 31 , 32 ]. Managing blood pressure is thus essential for maintaining cognitive function and overall well-being. Health factors not only affect cardiovascular health but also exert a substantial influence on cognitive function. Maintaining favorable health factors can contribute to the preservation of cognitive function. Interestingly, our findings regarding the relationship between blood lipids and cognitive function revealed a noteworthy result: higher non-HDL cholesterol scores were inversely associated with cognitive function scores, suggesting that elevated non-HDL cholesterol levels in the serum may be indicative of better cognitive performance (Table S4). The brain is the body's highest cholesterol-containing organ, and the total serum cholesterol levels in the blood have a significant impact on brain aging and cognitive abilities[ 33 ]. To date, evidence concerning the relationship between total cholesterol levels and cognitive function in the elderly has yielded ambiguous results without a definitive consensus, which may be influenced by the aging process. Our research results align with some previous studies regarding the association between cholesterol and cognitive function. One study involving 382 individuals examined the link between cholesterol concentration and cognitive abilities, finding that lower cholesterol levels were associated with poorer cognitive function in both non-dementia and dementia patients[ 34 ]. Another study involving 1,034 participants revealed that among participants aged 70, higher total cholesterol was associated with higher cognitive ability scores[ 35 ]. However, there are also studies that have reported contrasting trends. A study of 1,159 Chinese adults aged 60 and older found that higher blood total cholesterol concentrations were associated with a faster decline in overall cognitive abilities[ 36 ]. A meta-analysis based on eight studies and involving over 21,000 individuals aged 60 and above did not establish any relationship between cholesterol and cognitive decline or dementia in the elderly[ 37 ]. Cholesterol is traditionally regarded as a risk factor for cardiovascular diseases, and lower cholesterol levels are desirable for cardiovascular events[ 38 ]. Nevertheless, recent research has suggested that cholesterol has a protective effect against certain non-cardiovascular diseases and hemorrhagic strokes, particularly among older adults[ 39 ]. Given the complex role of cholesterol, further in-depth research is needed to ascertain the optimal cholesterol levels for individuals to attain maximum benefits. The LE8 score also includes four health behaviors: diet, physical activity, nicotine exposure, and sleep duration. Health behaviors score was associated with higher animal fluency: total score, and digit symbol: score but not CERAD: delayed recall score, CERAD: total score (3 recall trials), after fully adjusted (Table 4 ). Research has shown that diet has a significant impact on brain health. Adopting a balanced diet rich in antioxidants, including fruits, vegetables, whole grains, and healthy fats, can reduce inflammation, oxidative stress, and neuronal damage, thus contributing to the protection of cognitive function[ 40 , 41 ]. Conversely, high sugar, saturated fat, and processed food consumption have been linked to an increased risk of Alzheimer's disease and dementia[ 42 ]. Furthermore, diet can also influence cardiovascular health, which in turn affects cognitive function[ 10 ]. Poor cardiovascular health can lead to inadequate blood supply to the brain, impacting memory, thinking, and attention, among other blood supply abilities[ 43 ]. Therefore, adopting healthy dietary habits is not only beneficial for the heart but also helps maintain clear thinking and memory. Physical activity promotes increased blood flow to the brain, stimulates the release of neurotrophic factors, and enhances neuronal connectivity and communication, all of which contribute to the protection and promotion of cognitive function[ 44 ]. Moreover, physical activity holds significant potential for preventing cognitive impairments and dementia[ 45 ]. Studies have consistently shown that an active lifestyle can reduce the risk of cognitive impairments in older adults, enhancing cognitive reserve capacity and making the brain more resilient[ 46 , 47 ]. Nicotine, the addictive component of tobacco, acts on the brain's neurotransmitter systems, disrupting their normal functioning and potentially leading to cognitive deficits[ 48 ]. Long-term smoking has also been linked to an increased risk of neurodegenerative conditions such as Alzheimer's disease and dementia[ 49 , 50 ]. It accelerates brain aging processes and may contribute to the accumulation of harmful proteins in the brain associated with these conditions. Quality sleep plays a crucial role in maintaining and enhancing cognitive abilities, including memory, attention, problem-solving, and decision-making[ 51 ]. During sleep, the brain undergoes essential processes that consolidate and organize information acquired during wakefulness. It helps strengthen neural connections, optimize memory storage, and clear waste products from brain cells[ 52 ]. Insufficient or poor-quality sleep disrupts these processes, leading to cognitive impairments. Chronic sleep deprivation has been linked to decreased cognitive performance, mood disturbances, and increased risk of neurodegenerative conditions such as Alzheimer's disease[ 53 ]. Based on our findings, it is evident that maintaining healthy behaviors has a more significant impact on improving cognitive function. However, this should not overshadow the crucial role that healthy elements play in sustaining cognitive function at its current level. To the best of our knowledge, this is the first large-scale, nationally representative cohort study that delves into the relationship between Cardiovascular Health (CVH) and cognitive function using Life's Essential 8. Additionally, we examined the dose-response correlation between Life's Essential 8 and cognitive function scores. Nevertheless, it's crucial to acknowledge several potential limitations. Firstly, the four health behaviors, encompassing dietary intake, physical activity, nicotine exposure, and sleep health, rely on self-reported data, which could introduce recall bias. Secondly, despite making multivariate adjustments, unmeasured or residual confounding factors might impact the observed associations. Thirdly, our findings among U.S. adults may not be directly generalizable to other populations. Lastly, the cross-sectional study design prevents us from establishing causal and temporal relationships between CVH and cognitive function. Given the promising findings and the acknowledged limitations of this study, further validation through extensive prospective cohort studies is warranted. Conclusion To summarize, a higher level of adherence to the Life's Essential 8 (LE8) criteria is associated with improved cognitive function in older adults in the United States. Considering the reasonable findings and the various limitations of this study, it is imperative that these results undergo further validation through large prospective cohort studies. Abbreviations AHA American Heart Association LS7 Life's Simple 7 CVH Cardiovascular health LE8 Life's Essential 8 NHANES National Health and Nutrition Examination Survey CERAD Consortium to Establish a Registry for Alzheimer’s Disease. DSST Digit Symbol Substitution Test HEI Healthy Eating Index BMI Body mass index HDL High-density lipoprotein RCE Restricted Cubic Spline CVD Cardiovascular disease Declarations Acknowledgements We thank the National Center for Health Statistics of the Centers for Disease Control and Prevention for sharing the NHANES data. Authors’ contributions ZL designed the study and is the principal investigator. WZ and JCT drafted the manuscript. HXZ conducted the data analysis. WZ, YYZ, JCT, and MHL critically revised the manuscript for important intellectual content and interpreted the data. ZL and HXZ accessed and verified the data. All authors approved the final version of the manuscript. MHL is the guarantor. The corresponding author (HXZ) has access to and responsibility for the raw data associated with the study. The authors read and approved the final manuscript. Funding This research was funded by the the National Natural Science Foundation of China (NSFC) (No. 82260248). Availability of data and materials Data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014 are publicly available online (https://wwwn.cdc.gov/nchs/nhanes/ Default.aspx). Declarations Ethics approval and consent to participate The NHANES was approved by the National Center for Health Statistics Research Ethics Review Board. Consent for publication No applicable. Competing interests The authors declare that they have no competing interests. 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Supplementary Files supplementaryfile.docx Cite Share Download PDF Status: Published Journal Publication published 26 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 26 Mar, 2024 Reviews received at journal 11 Mar, 2024 Reviewers agreed at journal 01 Mar, 2024 Reviewers invited by journal 01 Mar, 2024 Editor assigned by journal 01 Mar, 2024 Editor invited by journal 21 Feb, 2024 Submission checks completed at journal 21 Feb, 2024 First submitted to journal 04 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3929606","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":274124336,"identity":"ecd53e87-1137-432e-ba24-5dfb1fcf66cc","order_by":0,"name":"Huaxin Zhu","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Huaxin","middleName":"","lastName":"Zhu","suffix":""},{"id":274124337,"identity":"235b785d-8820-493f-ab40-51481aaf4e61","order_by":1,"name":"Wu Zhou","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Wu","middleName":"","lastName":"Zhou","suffix":""},{"id":274124338,"identity":"3c865f27-918e-4d88-8e22-f3d3a45b0ba5","order_by":2,"name":"Jiacong Tan","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jiacong","middleName":"","lastName":"Tan","suffix":""},{"id":274124339,"identity":"572c2fe9-877c-4a63-bbc6-add57c3a764e","order_by":3,"name":"Yanyang Zeng","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Yanyang","middleName":"","lastName":"Zeng","suffix":""},{"id":274124340,"identity":"d9abd92d-85e3-49ee-b9c9-bddea902bce1","order_by":4,"name":"Meihua Li","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Meihua","middleName":"","lastName":"Li","suffix":""},{"id":274124341,"identity":"d21ad07f-4123-4019-ad8a-f553cded288b","order_by":5,"name":"Zheng Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIie3QsQrCMBCA4YNA6pDaNYLoK1QKHe2rXCi4CYJLhw4FpRnE3ccQXFxLoFPcOzjUxV1cnEQFXU1GwfzTDffBJQAu1w/WJQDkNVBPVi1muZnQD+kynYatri0IvMmAY9w7LYkF8Vh0nWXHcclxkomCQiBXaDiMhdFGn9OSnepG7PvA9WFrJKlfqpR6OGmEphDyqZko//4kgPFMlMSKjBZ+oca0gzFYEjonrFZIn5/MUdfM+JYgULsry1UylLK63LJ8EMj1d/JJFO+BWa2/Sqw3XS6X6/96AK8EQen98WEbAAAAAElFTkSuQmCC","orcid":"","institution":"Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Zheng","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-02-05 02:50:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3929606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3929606/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-70112-3","type":"published","date":"2024-08-26T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51565665,"identity":"114c427b-5fce-4303-8e58-ac92a7f25ff8","added_by":"auto","created_at":"2024-02-23 19:05:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69871,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the study sample selection\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3929606/v1/04b2201a8aca6261d07c8f1b.png"},{"id":51565666,"identity":"7a103c3b-0be5-4bda-a699-a0afb1a9f509","added_by":"auto","created_at":"2024-02-23 19:05:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":556515,"visible":true,"origin":"","legend":"\u003cp\u003eDose-response relationship of Life’s Essential 8 (LE8) and various domains of cognitive function (A: CERAD: Delayed Recall Score, B: CERAD: Total Score (3 Recall trials), C: Animal Fluency: Total Score, D: Digit Symbol: Score). Model is adjusted for age, sex, race, education level, ratio of family income to poverty and alcohol consumption.\u003c/p\u003e","description":"","filename":"FIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-3929606/v1/c5cee39d9a858c9aecf91f4c.png"},{"id":63821050,"identity":"c960dcf5-aa5c-4322-a6f1-a94d34202fed","added_by":"auto","created_at":"2024-09-02 16:11:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2220204,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3929606/v1/8f793e71-e9e9-4c0e-a8d6-82f795f7503d.pdf"},{"id":51565667,"identity":"509816ef-556e-402c-8394-ad0ef31f0bd1","added_by":"auto","created_at":"2024-02-23 19:05:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":259889,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-3929606/v1/b4fc348b27b11226fabb833e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Life's Essential 8 and Cognitive Function Among US Older Adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCognitive function changes in older adults represent a pressing concern in contemporary society, driven by the global aging trend[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The increase in life expectancy has resulted in a higher prevalence of cognitive impairments, spanning from mild cognitive decline to severe dementia[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. From a medical perspective, cognitive decline poses substantial challenges, particularly with conditions like Alzheimer's disease, necessitating specialized care and management that impose a significant financial burden on healthcare systems[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Families often shoulder the responsibility of caring for elderly relatives with cognitive impairments, leading to caregiver burnout and affecting both caregivers' and recipients' quality of life[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Economically, the associated costs of cognitive impairment are staggering, encompassing medical expenses, caregiving, and institutionalization, thereby straining governments and healthcare systems[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Cognitive function changes in older adults present a multifaceted challenge with wide-ranging societal implications.\u003c/p\u003e \u003cp\u003eDespite notable progress in raising awareness of cardiovascular health, the current state of heart health presents a multifaceted landscape[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. On one hand, strides have been made in reducing smoking rates, promoting healthy diets, and increasing physical activity levels[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Advances in medical treatments and interventions have improved outcomes for individuals with heart conditions. Nevertheless, challenges persist. Cardiovascular disease remains the leading global cause of death, exacerbated by sedentary lifestyles, unhealthy dietary habits, and escalating obesity rates. The demands of modern life, compounded by inadequate sleep, further heighten cardiovascular risks[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In 2010, the American Heart Association (AHA) introduced Life's Simple 7 (LS7), a comprehensive cardiovascular health (CVH) assessment comprising elements such as a balanced diet, tobacco abstinence, a healthy BMI, regular physical activity, blood pressure control, fasting blood glucose management, and cholesterol levels, all aimed at advancing public health[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. More recently, the AHA has enhanced the evaluation of CVH with the introduction of Life's Essential 8 (LE8)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. LE8 introduces updated sleep quality metrics and refined scoring algorithms compared to LS7, offering a more nuanced approach that accounts for individual variations and underscores the importance of social determinants of health and mental well-being in the preservation and enhancement of CVH[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. \"Life's Essential 8\" presents a comprehensive perspective on cardiovascular health, emphasizing the critical role of lifestyle choices and risk factor management. It underscores that a well-balanced diet, regular physical activity, abstaining from tobacco, prioritizing quality sleep, weight maintenance, and effective management of blood lipids, blood glucose, and blood pressure are interconnected elements pivotal for cardiovascular well-being[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The adoption of these principles has the potential to significantly reduce the risk of heart disease and elevate overall quality of life. Notably, research exploring the correlation between LE8 and Cognitive function remains limited at present.\u003c/p\u003e \u003cp\u003eThe intricate relationship between cognitive function and cardiovascular health in older adults underscores their reciprocal influences on overall well-being[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Cardiovascular health, including key factors such as blood pressure, blood lipid profiles, and vascular function, plays a pivotal role in sustaining optimal cerebral blood flow. Conditions like hypertension and atherosclerosis, prevalent in poor cardiovascular health, can compromise cerebral perfusion, potentially leading to cognitive decline[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Conversely, cognitive function and mental health significantly influence one's capacity to adhere to heart-healthy lifestyle choices. The adoption of healthy habits, including regular exercise, smoking cessation, and a balanced diet, not only reduces cardiovascular risks but also correlates with enhanced cognitive function[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These interconnections emphasize the importance of a comprehensive health approach addressing both cognitive well-being and cardiovascular health in older adults. However, it is worth noting that the association between Life's Essential 8, the latest metric for comprehensively assessing cardiovascular health, and altered cognitive function in older adults requires further research validation. Therefore, this study aims to estimate the correlation between Life's Essential 8 and cognitive function in older adults using data from the National Health and Nutrition Examination Survey (NHANES).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e The analysis in this study strictly adhered to the NHANES analytic guidelines, which are overseen by the National Center for Health Statistics at the Centers for Disease Control and Prevention in Maryland. NHANES employs a meticulously designed stratified multi-stage sampling approach, and comprehensive documentation of the sampling and testing procedures can be found in previously published articles[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In summary, systematic health-related interviews and examinations occurred in 2-year cycles, ensuring the inclusion of participants from diverse geographical regions and various racial/ethnic backgrounds, thereby guaranteeing comprehensive representation in the survey. Notably, NHANES protocols have obtained ethical approval from the National Center for Health Statistics research ethics review board, and written informed consent was obtained from all enrolled participants. Cognitive testing was specifically administered to participants aged 60 years and older during the period of 2011\u0026ndash;2014[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The data utilized in this study were extracted from NHANES surveys conducted between 2011 and 2014. Among the 19,931 subjects who participated in NHANES from 2011 to 2014, individuals were excluded based on the following criteria: (1) those under the age of 60 (n\u0026thinsp;=\u0026thinsp;16,299), (2) those with incomplete cognitive testing data (n\u0026thinsp;=\u0026thinsp;698), and (3) those with missing data on LS8 and covariates (n\u0026thinsp;=\u0026thinsp;221). Consequently, a total of 2,279 subjects met the inclusion criteria for this research. The detailed flowchart illustrating this process is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCognitive function\u003c/h2\u003e \u003cp\u003eCognitive functioning was evaluated during an interview conducted at a Mobile Examination Center and assessed by skilled interviewers. This assessment comprised three distinct tests: the CERAD Word Learning sub-test (CERAD W-L), which measured immediate and delayed recall of new verbal information (a memory sub-domain); the Animal Fluency test, designed to evaluate categorical verbal fluency (a component of executive function); and the Digit Symbol Substitution Test (DSST), which gauged processing speed, sustained attention, and working memory. The CERAD test involved three consecutive learning trials and a delayed recall task. Consequently, the results are reported as three individual trial scores, each ranging from 0 to 10, a total score that combines performance across all three trials, ranging from 0 to 30, and a single score for delayed recall, ranging from 0 to 10. While there is no upper limit, in practical terms, scores for the Animal Fluency test typically range from 3 to 39, and scores for the digit symbol test range from 0 to 105. All results were recorded on the CFQ questionnaire\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of Life's Essential 8\u003c/h2\u003e \u003cp\u003eThe LE8 score comprises four health behaviors (diet, physical activity, nicotine exposure, and sleep duration) and four health factors (body mass index, non-HDL cholesterol, blood glucose, and blood pressure)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Detailed scoring criteria for each item can be found in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Dietary parameters were evaluated using the Healthy Eating Index (HEI) 2015, calculated based on the subject's 24-hour dietary recall[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The HEI score was computed as the average of two recall periods, or if only data from the first day was available, that value was used. Information regarding physical activity, nicotine exposure, sleep patterns, diabetes history, and medication history was collected through a self-report questionnaire. Physical examinations included height, weight, and blood pressure measurements, from which body mass index (BMI) was derived by dividing weight (in kilograms) by the square of height (in meters). Non-HDL(high-density lipoprotein) cholesterol and hemoglobin A1c levels were determined from collected blood samples. Each of the 8 CVH indicators received a score ranging from 0 to 100, and the total LE8 score was calculated as the unweighted average of these 8 indicators. Moreover, participants exhibiting high CVH were classified with LE8 scores between 80 and 100, those with moderate CVH fell within the 50\u0026ndash;79 range, and individuals with low CVH were situated between 0 and 49[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In our study, we utilized these same cutoff points to categorize health behavior and health factor scores, enabling further exploration of the relationship between LE8 subscales and cognitive function.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy covariates\u003c/h2\u003e \u003cp\u003eThe study's covariates encompassed gender (male and female), age, categorized into age groups (60\u0026ndash;69, 70\u0026ndash;79, and 80\u0026thinsp;+\u0026thinsp;years), race/ethnicity (non-hispanic white, non-hispanic black, other hispanic, mexican american, non-hispanic asian, and others), educational attainment (less than 9th grade, college graduate or above, high school graduate/GED or equivalent, less than 9th grade, and some college or AA degree), the family income-to-poverty ratio, and alcohol consumption.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eGiven the intricate NHANES sampling design, we employed appropriate weights for the sample analysis. For initial characterization, we utilized weighted means (IQR) for continuous variables and sample sizes (weighted percentages) for categorical variables. To assess disparities in variable characteristics among the low, moderate, and high CVH groups, we applied ANOVA for differences in weighted means regarding continuous variables and the Rao\u0026mdash;Scott χ2 test for distinctions in weighted percentages for categorical variables. Weighted linear regression was employed to investigate the correlation between LE8 scores and cognitive test results (including CERAD: Trial 1\u0026ndash;3 Score, CERAD: Total Score (3 Recall trials), CERAD: Delayed Recall Score, Animal Fluency: Total Score, and Digit Symbol: Score), as well as the association between various CVH levels and cognitive tests. Crude models did not incorporate any potential confounding factors, whereas age-adjusted models were adjusted solely for age. Fully-adjusted models included adjustments for age, sex, race, education level, the family income-to-poverty ratio, and alcohol consumption. Furthermore, we explored the correlations between health behavior, health factor scores, and each of the LE8 scores with cognitive tests using weighted linear regression analyses, while accounting for all confounding variables. To further validate the link between LE8 scores and cognitive tests, we employed Restricted Cubic Spline (RCS). All analyses were conducted in the overall population, as well as in subgroups based on sex (women and men) and age groups (60\u0026ndash;69 years, 70\u0026ndash;79 years, and 80\u0026thinsp;+\u0026thinsp;years), respectively. Statistical tests were two-sided, with statistical significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed using R software, version 4.2.0 (R Core Team, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive statistics\u003c/h2\u003e \u003cp\u003eThe characteristics of the study population according to CVH status were shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 2279 adults aged 60 years or older were included for analysis. Moderate CVH status group contained 76% of all participants. The mean age was 69.01 years, and 47% of the participants were male. Participants with high CVH status were more likely to be Non-Hispanic White, higher educational levels, to have higher PIR, and more alcohol consumption (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the NHANES Participants Selected by Life\u0026rsquo;s Essential 8\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall, N\u0026thinsp;=\u0026thinsp;2279 (100%)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eLife\u0026rsquo;s Essential 8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP Value\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLow CVH (0\u0026ndash;49 points)\u003c/b\u003e, N\u0026thinsp;=\u0026thinsp;359 (12%)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eModerate CVH (50\u0026ndash;79 points)\u003c/b\u003e, N\u0026thinsp;=\u0026thinsp;1717 (76%)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eHigh CVH (80\u0026ndash;100 points)\u003c/b\u003e, N\u0026thinsp;=\u0026thinsp;203 (11%)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.01 (63.00, 74.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.78 (62.00, 72.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.22 (64.00, 74.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.94 (63.00, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,156 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210 (59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e854 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (55%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e633 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e487 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51 (24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e490 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e376 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,149 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e854 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,130 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e863 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,165 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e899 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e130 (88%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e356 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e171 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e195 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Asian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e119 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther/multiracial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 9th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9-11th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e221 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate/GED or equivalent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e535 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e416 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college or AA degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e672 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e510 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59 (24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege graduate or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e544 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e408 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100 (59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePIR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.17 (1.71, 5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.42 (1.12, 3.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.18 (1.74, 5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.94 (3.06, 5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e687 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e523 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59 (23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;5 drinks/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,118 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e198 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e829 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91 (46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;10 drinks/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026thinsp;+\u0026thinsp;drinks/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e288 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 (24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eN not Missing (unweighted), \u003csup\u003e2\u003c/sup\u003emedian (IQR) for continuous; n (%) for categorical, \u003csup\u003e3\u003c/sup\u003eWilcoxon rank-sum test for complex survey samples; chi-squared test with Rao \u0026amp; Scott's second-order correction; CVH, cardiovascular health; PIR, Poverty Impact Ratio.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between Life\u0026rsquo;s Essential 8 and cognitive function\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presented the associations between Life\u0026rsquo;s Essential 8 and cognitive performance. High CVH group had a higher score in Life\u0026rsquo;s Essential 8 total score, health behaviors score, diet score, physical activity score, sleep health score, tobacco exposure score, health factors score, BMI score, BP score, Blood glucose score and blood lipids (non-HDL cholesterol) score (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). High CVH group also showed better performance in cognitive outcomes including CERAD: trial 1\u0026ndash;3, CERAD: delayed recall, animal fluency test, and gigit symbol test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between cognitive tests scores and CVH status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003csup\u003e, N = 2279 (100%)2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow CVH (0\u0026ndash;49 points)\u003csup\u003e, N = 359 (12%)2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate CVH (50\u0026ndash;79 points)\u003csup\u003e, N = 1717 (76%)2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHigh CVH (80\u0026ndash;100 points)\u003csup\u003e, N = 203 (11%)2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP Value\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLife\u0026rsquo;s Essential 8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.65 (55.63, 73.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.92 (40.63, 46.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.21 (58.75, 72.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.48 (81.25, 86.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth behaviors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.52 (56.25, 81.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.57 (35.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.92 (56.25, 81.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.08 (81.25, 87.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiet\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.22 (25.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.53 (25.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.24 (25.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.37 (50.00, 50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.78 (0.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.72 (0.00, 0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.31 (0.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.87 (100.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep health\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.96 (70.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.84 (40.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.25 (70.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.69 (100.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTobacco exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.12 (75.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.18 (0.00, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.87 (75.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.40 (75.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.78 (50.00, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.27 (32.94, 52.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.50 (52.50, 72.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e85.89 (80.00, 90.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.16 (30.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.79 (15.00, 70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.05 (30.00, 70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.47 (70.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.12 (25.00, 80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.80 (5.00, 55.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.63 (25.00, 75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.95 (55.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood glucose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.80 (60.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.64 (30.00, 60.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.14 (60.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.56 (100.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood lipids (non-HDL cholesterol)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.05 (40.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.86 (30.29, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.17 (40.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.57 (60.00, 100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCognitive tests\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERAD: Trial 1 Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.01 (4, 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.75 (4, 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.00 (4, 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.31 (4, 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERAD: Trial 2 Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.04 (6, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.84 (6, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.99 (6, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.55 (6, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERAD: Trial 3 Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.80 (7, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.58 (7, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.77 (7, 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.26 (7, 10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERAD: Total Score (3 Recall trials)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.84 (17, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.17 (17, 22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.76 (17, 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.12 (19, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERAD: Delayed Recall Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.31 (5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.02 (5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.28 (5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.84 (5, 8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnimal Fluency: Total Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.30 (14, 22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.71 (13, 20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.26 (14, 22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.25 (16, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDigit Symbol: Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.84 (42, 64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.86 (34, 58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.91 (42, 64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.90 (49, 69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eN not Missing (unweighted), \u003csup\u003e2\u003c/sup\u003emedian (IQR) for continuous; n (%) for categorical, \u003csup\u003e3\u003c/sup\u003eWilcoxon rank-sum test for complex survey samples; chi-squared test with Rao \u0026amp; Scott's second-order correction; CVH, cardiovascular health; BMI, body mass index; BP, blood pressure; HDL, high-density lipoprotein; CERAD, Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen treating Life\u0026rsquo;s Essential 8 as a continuous measure, each 1-unit increase in Life\u0026rsquo;s Essential 8 score was associated with higher CERAD: delayed recall score (Beta: 0.02; 95%CI: 0.01, 0.03; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CERAD: total score (3 recall trials) (Beta: 0.04; 95%CI: 0.02, 0.06; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), animal fluency: total score (Beta: 0.09; 95%CI: 0.05, 0.12; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and digit symbol: score (Beta: 0.29; 95%CI: 0.18, 0.41; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similar results were obtained after adjusting for age (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). After fully adjusting, Life\u0026rsquo;s Essential 8 score was associated with higher CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.00, 0.04; P\u0026thinsp;=\u0026thinsp;0.035), animal fluency: total score (Beta: 0.04; 95%CI: 0.01, 0.07; P\u0026thinsp;=\u0026thinsp;0.007), and digit symbol: score (Beta: 0.11; 95%CI: 0.02, 0.19; P\u0026thinsp;=\u0026thinsp;0.015) but not CERAD: delayed recall score (Beta: 0.01; 95%CI: 0.00, 0.02; P\u0026thinsp;=\u0026thinsp;0.052) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). When grouped according to CVH status, High CVH was significantly associated with higher CERAD: delayed recall score (Beta: 0.82; 95%CI: 0.40, 1.2; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CERAD: total score (3 recall trials) (Beta: 1.9; 95%CI: 1.1, 2.8; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), animal fluency: total score (Beta: 3.5; 95%CI: 2.0, 5.1; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and digit symbol: score (Beta: 12; 95%CI: 7.0, 17; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared to Low CVH (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similar results were showed after adjusting for age or fully adjusted (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Beta coefficients and 95% confidence intervals of Life\u0026rsquo;s Essential 8 for CERAD: Trial1-3 were provided in Table S2.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBeta coefficients and 95% confidence intervals of Life\u0026rsquo;s Essential 8 for cognitive tests scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCERAD: Delayed Recall Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCERAD: Total Score (3 Recall trials)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eAnimal Fluency: Total Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eDigit Symbol: Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003eLife\u0026rsquo;s Essential 8\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.05, 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.18, 0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.06, 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.20, 0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFully adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.01, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.02, 0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCVH status (Based on Life\u0026rsquo;s Essential 8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow CVH (0\u0026ndash;49 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate CVH (50\u0026ndash;79 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.06, 1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.65, 2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.2, 9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh CVH (80\u0026ndash;100 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40, 1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1, 2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.0, 5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e7.0, 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow CVH (0\u0026ndash;49 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate CVH (50\u0026ndash;79 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13, 0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.32, 1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.0, 2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.1, 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh CVH (80\u0026ndash;100 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56, 1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3, 3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.4, 5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.0, 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFully adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow CVH (0\u0026ndash;49 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate CVH (50\u0026ndash;79 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.17, 0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.35, 1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.14, 1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.41, 5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh CVH (80\u0026ndash;100 points)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08, 0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11, 2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.41, 3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.56, 8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eCI = Confidence Interval; CVH, cardiovascular health; CERAD, Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease.\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eFully adjusted: adjusted for age, sex, race, education level, ratio of family income to poverty and alcohol consumption.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe dose-response relationship between Life\u0026rsquo;s Essential 8 and cognitive function after fully adjusting were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In restricted cubic spline models, Life\u0026rsquo;s Essential 8 scores were positively associated with CERAD: delayed recall score (P-overall\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, P-non-linear\u0026thinsp;=\u0026thinsp;0.3340; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), CERAD: total score (3 recall trials) (P-overall\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, P-non-linear\u0026thinsp;=\u0026thinsp;0.7709; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), animal fluency: total score (P-overall\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, P-non-linear\u0026thinsp;=\u0026thinsp;0.9974; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), digit symbol: score (P-overall\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, P-non-linear\u0026thinsp;=\u0026thinsp;0.3446; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) in a linear manner.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between Life\u0026rsquo;s Essential 8 components and cognitive function\u003c/h2\u003e \u003cp\u003eThe LE8 score comprises four health behaviors (diet, physical activity, nicotine exposure, and sleep duration) and four health factors (body mass index, non-HDL cholesterol, blood glucose, and blood pressure). Health behaviors score was associated with higher animal fluency: total score (Beta: 0.04; 95%CI: 0.02, 0.06; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and digit symbol: score (Beta: 0.10; 95%CI: 0.05, 015; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but not CERAD: delayed recall score (Beta: 0; 95%CI: 0.00, 0.01; P\u0026thinsp;=\u0026thinsp;0.2), CERAD: total score (3 recall trials) (Beta: 0.01; 95%CI: 0.00, 0.02; P\u0026thinsp;=\u0026thinsp;0.081), after fully adjusted (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Health factors score was associated with higher CERAD: delayed recall score (Beta: 0.01; 95%CI: 0.00, 0.01; P\u0026thinsp;=\u0026thinsp;0.003), CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.01, 0.03; P\u0026thinsp;=\u0026thinsp;0.002), animal fluency: total score (Beta: 0.03; 95%CI: 0.01, 0.05; P\u0026thinsp;=\u0026thinsp;0.006), and digit symbol: score (Beta: 0.12; 95%CI: 0.04, 0.20; P\u0026thinsp;=\u0026thinsp;0.003) after adjusting age (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). When fully adjusted, no significant association was found between health factors score and cognitive function scores. The dose-response relationship between health behaviors, health factors and cognitive function after fully adjusting were shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Beta coefficients and 95% confidence intervals of health behaviors and health factors for CERAD: Trial1-3 were provided in Table S3. Higher non-HLD cholesterol scores were associated with worse animal fluency: total score (Beta: -0.01; 95%CI: -0.02, 0.00; P\u0026thinsp;=\u0026thinsp;0.047), and digit symbol: score (Beta: -0.02; 95%CI: -0.04, 0.00; P\u0026thinsp;=\u0026thinsp;0.047), and BMI was not significantly correlated with cognitive function scores (Table S4). Association between all Life\u0026rsquo;s Essential 8 metric (diet, physical activity, nicotine exposure, sleep duration, body mass index, non-HDL cholesterol, blood glucose, and blood pressure) and cognitive function scores was provided in Table S4.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBeta coefficients and 95% confidence intervals of health behaviors and health factors for cognitive tests scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCERAD: Delayed Recall Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCERAD: Total Score (3 Recall trials)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eAnimal Fluency: Total Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eDigit Symbol: Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eHealth behaviors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.05, 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.15, 0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.05, 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.16, 0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFully adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.05, 0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.01, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.03, 0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.01, 0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.04, 0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFully adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00, 0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.02, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.04, 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eCI = Confidence Interval; \u003csup\u003e2\u003c/sup\u003eFully adjusted: adjusted for age, sex, race, education level, ratio of family income to poverty and alcohol consumption.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis of sex and age\u003c/h2\u003e \u003cp\u003eThe results of subgroup analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. In the male subgroup, LS8 showed a significant positive correlation with animal fluency score (Beta: 0.05; 95%CI: 0.01, 0.09; P\u0026thinsp;=\u0026thinsp;0.014) after fully-adjusted. LS8 was positive correlated with CERAD: total score (3 recall trials) (Beta: 0.02; 95%CI: 0.00, 0.04; P\u0026thinsp;=\u0026thinsp;0.036) and animal fluency score (Beta: 0.04; 95%CI: 0.00, 0.07; P\u0026thinsp;=\u0026thinsp;0.03) in the female subgroup. In the 60\u0026ndash;69 years age subgroup, LS8 showed a significant positive correlation with animal fluency score (Beta: 0.04; 95%CI: 0.01, 0.08; P\u0026thinsp;=\u0026thinsp;0.027) after fully-adjusted. In the 70\u0026ndash;79 years age subgroup, no significant correlation between LS8 and cognitive tests after fully-adjusted. But in the 80\u0026thinsp;+\u0026thinsp;years age subgroup, LS8 was positive correlated with animal fluency score (Beta: 0.05; 95%CI: 0.00, 0.09; P\u0026thinsp;=\u0026thinsp;0.036) and digit symbol score (3 recall trials) (Beta: 0.19; 95%CI: 0.09, 0.28; P\u0026thinsp;=\u0026thinsp;0.001). Subgroup analysis of sex and age for CERAD: Trial 1\u0026ndash;3 was showed in Table S5.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBeta coefficients and 95% confidence intervals of Life\u0026rsquo;s Essential 8 for cognitive tests scores by sex and age\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCERAD: Delayed Recall Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCERAD: Total Score (3 Recall trials)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eAnimal Fluency: Total Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eDigit Symbol: Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubgroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e95% CI1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e95% CI1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04, 0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.13, 0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05, 0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.19, 0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFully-adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01, 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.01, 0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03, 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05, 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.18, 0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.04, 0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.17, 0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFully-adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.01, 0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e60\u0026ndash;69 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.06, 0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.15, 0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFully-adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00, 0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01, 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.05, 0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e70\u0026ndash;79 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00, 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.02, 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.12, 0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFully-adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.02, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.02, 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.02, 0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e80\u0026thinsp;+\u0026thinsp;years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo-adjusted\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01, 0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01, 0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05, 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.25, 0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFully-adjusted\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02, 0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.03, 0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00, 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.09, 0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eCI = Confidence Interval; \u003csup\u003e2\u003c/sup\u003eFully adjusted: adjusted for age, race, education level, ratio of family income to poverty and alcohol consumption; \u003csup\u003e3\u003c/sup\u003eFully adjusted: adjusted for sex, race, education level, ratio of family income to poverty and alcohol consumption.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe global landscape is witnessing a significant demographic shift, with a burgeoning aging population. By 2050, it is projected that older adults aged 60 years and above will constitute 22% of the global population. This demographic transformation brings forth unique challenges, including the rising prevalence of cognitive impairments and neurodegenerative diseases[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Cognitive function, encompassing memory, attention, executive function, and other mental processes, is a fundamental component of an individual's ability to lead an independent and fulfilling life. Simultaneously, cardiovascular health remains a central concern, given its pervasive impact on mortality and morbidity worldwide[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Cardiovascular disease (CVD) is the leading cause of death globally, underlining the need for comprehensive strategies to mitigate risk factors and promote heart health. Life's Essential 8 (LE8), an innovative metric introduced by the AHA, offers a holistic approach to assess cardiovascular health, focusing on lifestyle choices and risk factor management[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this nationally representative cross-sectional study, we found that LE8 scores and its health behaviors scores and health factors scores showed a significant positive correlation with cognitive test scores of U.S. seniors aged 60 years and older.\u003c/p\u003e \u003cp\u003ePrevious study has explored the link between LS7 and cognitive functioning and found that maintaining good LS7 scores showed a significant positive correlation with better cognitive functioning[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our findings are similar to previous study. The CHV definitions of LS7 were categorized into ideal, intermediate, and poor CVH for each component. This definition is less sensitive to interindividual differences and is unable to be used to assess dose-response effects[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, we found a significant linear relationship between LS8 and cognitive test scores by RCS analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), further suggesting that maintaining good LS8 scores is beneficial to cognitive function.\u003c/p\u003e \u003cp\u003eThe use of LE8 as a definition of CVH in this study adds significant evidence of a relationship between CVH and cognitive function. High CVH group (based on LS8 score) was significantly associated with higher CERAD: delayed recall score, CERAD: total score (3 recall trials), animal fluency: total score, and digit symbol: score, compared to Low CVH group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Maintaining good cardiovascular status shows an important positive correlation with good cognitive function performance. One of the primary reasons for the strong connection between cardiovascular health and cognitive function is the presence of shared risk factors. Many risk factors that contribute to cardiovascular diseases, such as hypertension, diabetes, hyperlipidemia, and obesity, have also been implicated in the development of cognitive impairments and neurodegenerative diseases[\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This overlap in risk factors underscores the importance of addressing both cardiovascular health and cognitive function in tandem.\u003c/p\u003e \u003cp\u003eThe LE8 score comprises and four health factors: BMI, non-HDL cholesterol, blood glucose, and blood pressure, to assess individual cardiovascular health. And health factors score was associated with higher CERAD: delayed recall score, CERAD: total score (3 recall trials), animal fluency: total score, and digit symbol: score after adjusting age (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Although our study did not find a significant association between BMI and cognitive function, excessive BMI often represents obesity, obesity can lead to cardiovascular issues, inflammation, insulin resistance, and metabolic disruptions, all of which are associated with cognitive decline. Furthermore, obesity may trigger adverse changes in brain structure and function, increasing the risk of cognitive impairments and dementia[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Elevated blood glucose levels, such as in diabetes, are associated with an increased risk of cognitive decline and dementia. Prolonged high blood glucose can lead to nerve damage, vascular inflammation, and structural brain changes, all of which can impact cognitive function[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Optimal blood pressure levels are associated with improved cognitive resilience, while hypertension has been linked to an increased risk of cognitive impairments, including Alzheimer's disease and dementia[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Managing blood pressure is thus essential for maintaining cognitive function and overall well-being. Health factors not only affect cardiovascular health but also exert a substantial influence on cognitive function. Maintaining favorable health factors can contribute to the preservation of cognitive function.\u003c/p\u003e \u003cp\u003eInterestingly, our findings regarding the relationship between blood lipids and cognitive function revealed a noteworthy result: higher non-HDL cholesterol scores were inversely associated with cognitive function scores, suggesting that elevated non-HDL cholesterol levels in the serum may be indicative of better cognitive performance (Table S4). The brain is the body's highest cholesterol-containing organ, and the total serum cholesterol levels in the blood have a significant impact on brain aging and cognitive abilities[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. To date, evidence concerning the relationship between total cholesterol levels and cognitive function in the elderly has yielded ambiguous results without a definitive consensus, which may be influenced by the aging process. Our research results align with some previous studies regarding the association between cholesterol and cognitive function. One study involving 382 individuals examined the link between cholesterol concentration and cognitive abilities, finding that lower cholesterol levels were associated with poorer cognitive function in both non-dementia and dementia patients[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Another study involving 1,034 participants revealed that among participants aged 70, higher total cholesterol was associated with higher cognitive ability scores[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, there are also studies that have reported contrasting trends. A study of 1,159 Chinese adults aged 60 and older found that higher blood total cholesterol concentrations were associated with a faster decline in overall cognitive abilities[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. A meta-analysis based on eight studies and involving over 21,000 individuals aged 60 and above did not establish any relationship between cholesterol and cognitive decline or dementia in the elderly[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Cholesterol is traditionally regarded as a risk factor for cardiovascular diseases, and lower cholesterol levels are desirable for cardiovascular events[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Nevertheless, recent research has suggested that cholesterol has a protective effect against certain non-cardiovascular diseases and hemorrhagic strokes, particularly among older adults[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Given the complex role of cholesterol, further in-depth research is needed to ascertain the optimal cholesterol levels for individuals to attain maximum benefits.\u003c/p\u003e \u003cp\u003eThe LE8 score also includes four health behaviors: diet, physical activity, nicotine exposure, and sleep duration. Health behaviors score was associated with higher animal fluency: total score, and digit symbol: score but not CERAD: delayed recall score, CERAD: total score (3 recall trials), after fully adjusted (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Research has shown that diet has a significant impact on brain health. Adopting a balanced diet rich in antioxidants, including fruits, vegetables, whole grains, and healthy fats, can reduce inflammation, oxidative stress, and neuronal damage, thus contributing to the protection of cognitive function[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Conversely, high sugar, saturated fat, and processed food consumption have been linked to an increased risk of Alzheimer's disease and dementia[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Furthermore, diet can also influence cardiovascular health, which in turn affects cognitive function[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Poor cardiovascular health can lead to inadequate blood supply to the brain, impacting memory, thinking, and attention, among other blood supply abilities[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, adopting healthy dietary habits is not only beneficial for the heart but also helps maintain clear thinking and memory. Physical activity promotes increased blood flow to the brain, stimulates the release of neurotrophic factors, and enhances neuronal connectivity and communication, all of which contribute to the protection and promotion of cognitive function[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Moreover, physical activity holds significant potential for preventing cognitive impairments and dementia[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Studies have consistently shown that an active lifestyle can reduce the risk of cognitive impairments in older adults, enhancing cognitive reserve capacity and making the brain more resilient[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Nicotine, the addictive component of tobacco, acts on the brain's neurotransmitter systems, disrupting their normal functioning and potentially leading to cognitive deficits[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Long-term smoking has also been linked to an increased risk of neurodegenerative conditions such as Alzheimer's disease and dementia[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. It accelerates brain aging processes and may contribute to the accumulation of harmful proteins in the brain associated with these conditions. Quality sleep plays a crucial role in maintaining and enhancing cognitive abilities, including memory, attention, problem-solving, and decision-making[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. During sleep, the brain undergoes essential processes that consolidate and organize information acquired during wakefulness. It helps strengthen neural connections, optimize memory storage, and clear waste products from brain cells[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Insufficient or poor-quality sleep disrupts these processes, leading to cognitive impairments. Chronic sleep deprivation has been linked to decreased cognitive performance, mood disturbances, and increased risk of neurodegenerative conditions such as Alzheimer's disease[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Based on our findings, it is evident that maintaining healthy behaviors has a more significant impact on improving cognitive function. However, this should not overshadow the crucial role that healthy elements play in sustaining cognitive function at its current level.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first large-scale, nationally representative cohort study that delves into the relationship between Cardiovascular Health (CVH) and cognitive function using Life's Essential 8. Additionally, we examined the dose-response correlation between Life's Essential 8 and cognitive function scores. Nevertheless, it's crucial to acknowledge several potential limitations. Firstly, the four health behaviors, encompassing dietary intake, physical activity, nicotine exposure, and sleep health, rely on self-reported data, which could introduce recall bias. Secondly, despite making multivariate adjustments, unmeasured or residual confounding factors might impact the observed associations. Thirdly, our findings among U.S. adults may not be directly generalizable to other populations. Lastly, the cross-sectional study design prevents us from establishing causal and temporal relationships between CVH and cognitive function. Given the promising findings and the acknowledged limitations of this study, further validation through extensive prospective cohort studies is warranted.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo summarize, a higher level of adherence to the Life's Essential 8 (LE8) criteria is associated with improved cognitive function in older adults in the United States. Considering the reasonable findings and the various limitations of this study, it is imperative that these results undergo further validation through large prospective cohort studies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAHA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;American Heart Association\u003c/p\u003e\n\u003cp\u003eLS7 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Life\u0026apos;s Simple 7\u003c/p\u003e\n\u003cp\u003eCVH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cardiovascular health\u003c/p\u003e\n\u003cp\u003eLE8 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Life\u0026apos;s Essential 8\u003c/p\u003e\n\u003cp\u003eNHANES \u0026nbsp; \u0026nbsp;National Health and Nutrition Examination Survey\u003c/p\u003e\n\u003cp\u003eCERAD \u0026nbsp; \u0026nbsp; Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease.\u003c/p\u003e\n\u003cp\u003eDSST \u0026nbsp; \u0026nbsp; \u0026nbsp; Digit Symbol Substitution Test\u003c/p\u003e\n\u003cp\u003eHEI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Healthy Eating Index\u003c/p\u003e\n\u003cp\u003eBMI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Body mass index\u003c/p\u003e\n\u003cp\u003eHDL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;High-density lipoprotein\u003c/p\u003e\n\u003cp\u003eRCE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Restricted Cubic Spline\u003c/p\u003e\n\u003cp\u003eCVD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cardiovascular disease \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the National Center for Health Statistics of the Centers for Disease Control and Prevention for sharing the NHANES data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZL designed the study and is the principal investigator. WZ and JCT drafted the manuscript. HXZ conducted the data analysis. WZ, YYZ, JCT, and MHL critically revised the manuscript for important intellectual content and interpreted the data. ZL and HXZ accessed and verified the data. All authors approved the final version of the manuscript. MHL is the guarantor. The corresponding author (HXZ) has access to and responsibility for the raw data associated with the study. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the\u0026nbsp;the National Natural Science Foundation of China (NSFC) (No. 82260248).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from the National Health and Nutrition Examination Survey (NHANES) 2011–2014 are publicly available online (https://wwwn.cdc.gov/nchs/nhanes/ Default.aspx).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations Ethics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES was approved by the National Center for Health Statistics Research Ethics Review Board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLenze EJ, Voegtle M, Miller JP, Ances BM, Balota DA, Barch D, Depp CA, Diniz BS, Eyler LT, Foster ER, et al: Effects of Mindfulness Training and Exercise on Cognitive Function in Older Adults: A Randomized Clinical Trial. 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Int J Behav Nutr Phys Act 2022, 19:80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrivanek TJ, Gale SA, McFeeley BM, Nicastri CM, Daffner KR: Promoting Successful Cognitive Aging: A Ten-Year Update. J Alzheimers Dis 2021, 81:871\u0026ndash;920.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBliss ES, Wong RH, Howe PR, Mills DE: Benefits of exercise training on cerebrovascular and cognitive function in ageing. J Cereb Blood Flow Metab 2021, 41:447\u0026ndash;470.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaterhouse U, Brennan KA, Ellenbroek BA: Nicotine self-administration reverses cognitive deficits in a rat model for schizophrenia. Addict Biol 2018, 23:620\u0026ndash;630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDurazzo TC, Mattsson N, Weiner MW: Smoking and increased Alzheimer's disease risk: a review of potential mechanisms. Alzheimers Dement 2014, 10:S122-S145.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrande G, Qiu C, Fratiglioni L: Prevention of dementia in an ageing world: Evidence and biological rationale. Ageing Res Rev 2020, 64:101045.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaillard J, Sagaspe P, Philip P, Bioulac S: Sleep timing, chronotype and social jetlag: Impact on cognitive abilities and psychiatric disorders. Biochem Pharmacol 2021, 191:114438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoyce R, Williams S, Adamantidis A: REM sleep and memory. Curr Opin Neurobiol 2017, 44:167\u0026ndash;177.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrwin MR, Vitiello MV: Implications of sleep disturbance and inflammation for Alzheimer's disease dementia. Lancet Neurol 2019, 18:296\u0026ndash;306.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Life's Essential 8, Cognition, NHANES, Cardiovascular health, Aging","lastPublishedDoi":"10.21203/rs.3.rs-3929606/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3929606/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe American Heart Association(AHA) recently redefined cardiovascular health(CVH) with the introduction of Life's Essential 8(LE8). This study explores the relationships between both the aggregate and individual CVH metrics, as defined by Life's Essential 8, and cognitive function in older adults in the United States.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional, population-based study analyzed data from the National Health and Nutrition Examination Survey conducted between 2011 and 2014, focusing on individuals aged 60 years and older. CVH was categorized as low(0\u0026ndash;49), moderate(50\u0026ndash;79), or high(80\u0026ndash;100). Cognitive function was assessed through the CERAD tests, Animal Fluency test, and Digit Symbol Substitution test. Multivariable logistic models and restricted cubic spline models were employed to investigate these associations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThis study included a total of 2,279 older adults in the United States. Only 11% of adults achieved a high total CVH score, while 12% had a low score. After adjusting for potential confounding factors, higher LE8 scores were significantly associated with higher scores on CERAD: delayed recall score(0.02[0.01, 0.03]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CERAD: total score(3 recall trials)(0.04[0.02, 0.06]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), animal fluency: total score(0.09[0.05, 0.12]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and digit symbol: score(0.29[0.18, 0.41]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), demonstrating a linear dose-response relationship. Similar patterns were also observed in the associations between health behavior and health factor scores with cognitive function tests.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eLE8 scores exhibited positive linear associations with cognitive function. Promoting adherence to optimal CVH levels may prove beneficial in maintaining higher levels of cognitive function in older adults in the United States.\u003c/p\u003e","manuscriptTitle":"Association Between Life's Essential 8 and Cognitive Function Among US Older Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-23 19:05:27","doi":"10.21203/rs.3.rs-3929606/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-26T05:41:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-11T20:02:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0fb9c4f9-2fcf-4573-99db-8f9e2c7fe1c4","date":"2024-03-01T13:00:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-01T09:36:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-01T06:52:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-02-21T14:31:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-21T14:29:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-02-05T02:32:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e1196253-5067-4d9e-997b-ba4176d1a87c","owner":[],"postedDate":"February 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28894454,"name":"Health sciences/Health care"},{"id":28894455,"name":"Health sciences/Neurology"}],"tags":[],"updatedAt":"2024-09-02T16:02:54+00:00","versionOfRecord":{"articleIdentity":"rs-3929606","link":"https://doi.org/10.1038/s41598-024-70112-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-26 15:57:47","publishedOnDateReadable":"August 26th, 2024"},"versionCreatedAt":"2024-02-23 19:05:27","video":"","vorDoi":"10.1038/s41598-024-70112-3","vorDoiUrl":"https://doi.org/10.1038/s41598-024-70112-3","workflowStages":[]},"version":"v1","identity":"rs-3929606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3929606","identity":"rs-3929606","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}