Can physical activity mitigate the effect of systemic inflammation on cognitive performance? Results from a large older community dwelling population in the Netherlands

Can physical activity mitigate the effect of systemic inflammation on cognitive performance? 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Results from a large older community dwelling population in the Netherlands Anne Fink, Constantin Reinke, Benjamin Aretz, Michael T. Heneka, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4761080/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Elevated systemic inflammation has been linked to poorer cognitive outcomes. Vigorous physical activity is associated with improved cognitive performance. This study investigates whether physical activity moderates the relationship between systemic inflammation and cognition. Methods Using the first wo waves from the Dutch Lifelines cohort study (N = 24,661, 50+), cognitive performance was assessed using a composite score from the Cogstate Brief Battery, with higher scores indicating lower cognitive performance. As a biomarker of systemic inflammation (SI), we used leukocyte count within the normal range of 3 to 11x10 9 cells per liter in EDTA blood samples in waves 1 and 2. We differentiated between low SI ( = 6.5x10 9 cells per liter) and distinguished between 4 groups: (1) Persons, who had low SI in both waves; (2) Persons, who had increased SI in wave 1, but low SI in wave 2; (3) Persons, who had low SI in wave 1, but increased SI in wave 2; and (4) Persons, who had increased SI in both waves. We performed linear regression models to examine the effect of inflammation and vigorous physical activity on cognition, adjusting for cognitive task accuracy, age, sex, physical activity, education, medical conditions, and smoking status associated with cognitive impairment. An interaction effect was used to analyze the potential moderation of physical activity. Results Individuals with high systemic inflammation (SI) levels in both waves exhibited significantly longer reaction times (b = 0.061 [0.001;0.121]) compared to those with low SI levels in both waves. Individuals who engage in vigorous physical activity had significantly faster reaction times (-0.152 [-0.198;-0.107]) compared to those who do not. The interaction term was insignificant meaning that all individuals benefit from vigorous physical activity in terms of their cognitive performance, regardless of their SI group. Conclusions Our findings suggest that elevated systemic inflammation is a risk factor for cognitive impairment in older adults, and that physical activity may mitigate this risk. Therefore, promoting physical activity among the aging population may be an effective strategy to prevent or delay cognitive decline and dementia by potentially preventing systemic inflammation. Cognitive performance systemic inflammation physical activity Figures Figure 1 BACKGROUND The increasing prevalence of dementia, both globally and particularly in Europe, poses a significant challenge to public health. As populations age, the number of individuals affected by this condition is expected to rise significantly from almost 50 million in 2015 to over 152 million in 2050 worldwide [ 1 ]. While the urgent need for effective strategies against cognitive impairment and the development of dementia is widely acknowledged, there is still a lack of understanding of the potential effectiveness of primary prevention interventions in the older population [ 2 ]. Newer studies revealed that systemic inflammation processes are one of the most important risk factors for neurodegeneration [ 3 ]. Several studies have shown that chronic systemic inflammation is associated with cognitive decline, affecting essential areas like memory, attention, and processing speed, as well as an increased risk of dementia [ 4 – 8 ]. One hypothesis is that inflammatory response causes the disruption of neuronal function and subsequent changes in brain structure [ 9 ]. Although systemic inflammation may be the response to the pathogenesis of cognitive decline or dementia, systemic inflammation may still influence the progression and clinical manifestation of the disease [ 10 ]. An elevated white blood cell count may serve as an early indicator of systemic inflammation and is associated with the progression of various diseases. A slightly elevated white blood cell count, even within the normal range, could indicate a higher likelihood of increased systemic inflammation and subclinical disease. In addition to an increased risk of developing cancer, cardiovascular diseases, type 2 diabetes, and other age-related diseases, as well as an increased risk of all-cause mortality [ 11 ] an elevated white blood cell count is also associated with reduced cognitive performance [ 12 ]. In contrast, physical activity is commonly linked to better cognitive performance. Regular exercise has been shown to improve several cognitive functions, including processing speed, memory, and executive function [ 13 ]. It is believed that the advantageous outcomes of physical activity on cognition are mediated through various mechanisms. These include promoting neuroplasticity, increasing brain-derived neurotrophic factor levels, improving cerebral blood flow, as well as reducing systemic chronic inflammation by reducing adipose tissue, enhancing the release of anti-inflammatory myokines, improving endothelial function, and modulating metabolic health [ 14 – 16 ]. Physical activity is therefore an important modifiable risk factor for cognitive decline and dementia in the absence of curative treatment options [ 17 ]. While it is clear that both systemic inflammation and physical activity independently affect cognitive performance, their interactions are less well understood. This large cohort study uses an older community-dwelling setting in the Netherlands to explore whether physical activity can mitigate the effect of systemic inflammation on cognitive performance. As shown in Fig. 1 , our hypothesis is that physical activity moderates the relationship between leukocyte count and cognitive performance by altering the strength of the relationship. We therefore theorize that elevated leukocyte counts affect active and inactive individuals differently (Fig. 1 ). METHODS Data The current study uses baseline and follow-up data (2006–2017) from the Lifelines Cohort Study and Biobank. Information on the study design and objectives of Lifelines has been previously described elsewhere [ 18 , 19 ]. In summary, Lifelines is a multi-disciplinary prospective population-based cohort study examining in a unique three-generation design the health and health-related behaviors of 167,729 persons living in the North of the Netherlands. It employs a broad range of investigative procedures in assessing the biomedical, socio-demographic, behavioral, physical and psychological factors which contribute to the health and disease of the general population, with a special focus on multi-morbidity and complex genetics. Lifelines was conducted in accordance with the guidelines of the Declaration of Helsinki. All procedures involving human subjects were approved by the Medical Ethics Committee of the University Medical Center Groningen (UMCG), and written informed consent was obtained from all participants. Our study included adults aged 50 years and above (N = 24,661), who had valid information on body height, body weight, systolic blood pressure, and physical activity at baseline (2006–2013), leukocyte count measurements at baseline (2006–2013) and follow-up (2014–2017), and cognitive performance measurements at follow-up (2014–2017). Outcome: Cognitive performance The CogState Brief Battery (CBB) is a computer-administered cognitive test battery that takes about 10 minutes to administer. It consists of four cognitive tasks that measure cognitive functions: Psychomotor function, attention, working memory, and memory [ 20 ]. The CBB has shown its effectiveness and sensitivity in detecting cognitive impairment in conditions like Alzheimer’s disease (AD) and mild cognitive impairment, and in assessing cognitive changes in the preclinical stages of AD [ 20 ]. This makes it a valuable tool in the field of cognitive neuroscience. We used two cognitive processing speed measures from the CBB. First, the Detection Task, which measures psychomotor function – the coordination of sensory or cognitive processes and motor activity. Second, the Identification Task, which measures attention. For both tasks, the primary outcome was reaction time in milliseconds (speed). A base 10 logarithmic transformation (log10) was used to normalize the distribution. The transformed values were z-standardized for 5-year age groups starting at age 50 and summed up to a composite score measuring cognitive performance. The resulting score ranged from − 8.21 to 13.24, with higher reaction times indicating poorer cognitive function. Detection Task and Identification Task were shown to have excellent specificity, validity and reliability [ 21 ]. Exposure: Marker of systemic inflammation (SI): Leukocyte count As a proxy biomarker of systemic inflammation (SI), we used leukocyte count within the normal range of 3 to 11x10 9 cells per liter in EDTA-blood samples at baseline (2006–2013) and follow-up (2014–2017). We excluded all individuals who had a leukocyte count of less than 3 or greater than 11 at either the baseline or at follow-up to reduce the possibility that conditions such as acute infections or leukemia, could bias the findings due to undetected and uncontrolled inflammation-related diseases and thus the computerized tests of the CBB [ 10 ]. The highest 25% of the leukocyte count ( > = 6.5x10 9 cells per liter) was defined as high SI levels [ 22 , 23 ] Values below this cut-off were defined as low SI levels. We performed four groups and distinguished between (1) individuals who had low SI at baseline and at follow-up (low-low), (2) individuals who had elevated SI at baseline but low SI at follow-up (high-low), (3) individuals who had low SI at baseline but elevated SI at follow-up (low-high), and (4) individuals who had elevated SI at baseline and at follow-up (high-high). Moderator variable: Physical activity Physical activity was assessed using the short questionnaire to assess health-enhancing physical activity (SQUASH), a questionnaire to measure the habitual physical activity level of adults, developed by the Dutch National Institute of Public Health and the Environment. The questionnaire consists of questions on four categories of activities: commuting, leisure time, household, and work/school. For each activity, the frequency, duration, and intensity are recorded [ 24 ]. For our analysis, we distinguished between people who did at least one minute of vigorous physical activity per week and people who did no vigorous physical activity at all at baseline Since high-intensity exercise has been shown to have the greatest impact on the inflammatory profile, we focus on vigorous physical activity [ 16 ]. Covariates The following covariates were measured at baseline: sex (male, female), age, education (low, medium, high, missing), smoking status (non-smoker, current smoker, missing), and self-reported diagnoses of diabetes, depression, stroke, myocardial infarction, heart failure, or Parkinson’s disease. Additionally, we included obesity (body mass index > 30 kg/m² derived from measured body height and weight during assessment) and systolic blood pressure measured during assessment. We used the speed measures recorded by the CBB as our primary outcome. This implies that participants who responded quickly to the tasks may still have provided inaccurate responses. To account for this possible response accuracy, we calculated a composite score of response accuracy measured by the number of correct responses divided by the number of total responses in the two CBB domains. Statistical analyses We used one-way analysis of variance and Bonferroni-corrected post hoc test (for covariates with more than two categories) to compare cognitive function scores between groups of SI levels, physical activity, and covariates. To estimate cognitive performance, we used a linear regression model with robust standard errors (Breusch-Pagan with p < 0.001) as a function of SI levels, physical activity, sex, age, education, smoking status, obesity, and self-reported diagnoses. A second model additionally included an interaction effect between physical activity and SI level groups (Fig. 1 ). To account for selection bias, we used inverse probability weighting. Stabilized weights were obtained from the quotient of a logistic response model as a function of all included variables of the association model and a logistic response model with age, sex, and education only [ 25 , 26 ]. RESULTS The study population consisted of 24,661 individuals. The cognitive performance score, measured as the combined z-standardized and log-transformed reaction times from the Detection and Identification tasks of CBB, had a mean value of -0.019 (95% confidence interval [-0.040;0.003]), and Figure S1 displays its distribution. Higher values correspond to poorer cognitive performance. Table 1 presents the characteristics of the study population and the associations between the dependent and independent variables. Individuals with low levels of inflammation in both waves (low-low) had an average cognitive function score of -0.051 [-0.078;-0.024]. In contrast, those with high levels of inflammation in both waves (high-high) had an average cognitive function score of 0.080 [0.027;0.134], indicating significantly poorer cognitive performance. Active individuals had a significantly better cognitive function (-0.214 [-0.251;-0.178]) compared to inactive individuals (0.071 [0.037;0.106]), and men had a better average cognitive function (-0.094 [-0.127;-0.062]) than women (0.042 [0.013;0.071]). Furthermore, there was an education gradient observed, as individuals with lower education exhibited significantly poorer cognitive function (0.307 [-0.270;0.343]) compared to those with middle (-0.037 [-0.076;0.001]) or high (-0.452 [-0.486;-0.418]) education. Individuals who reported having diabetes, stroke, or heart failure had significantly poorer cognitive function compared to those without these diseases. However, individuals with depression, myocardial infarction, or PD did not differ significantly from those without these diseases. We found a negative gradient between systolic blood pressure and cognitive performance. Specifically, individuals with a systolic blood pressure of over 140 mmHg had an average score of 0.085 [0.041;0.130], while those with a systolic blood pressure lower than 119 mmHg had an average score of -0.091 [-0.134;-0.049]. Additionally, we found that non-obese individuals had better cognitive function (-0.037 [-0.061;-0.014]) compared to obese individuals (0.079 [0.025;0.133]). There was no statistically significant difference in average cognitive function between non-smokers (-0.026 [-0.058;0.007]) and smokers (0.019 [-0.042;0.079]). Table 1 Characteristics of study participants and associations of predictor variables with mean of score of cognitive performance. Source: Lifelines data 2006–2015, own calculation. Variable Categories N % Mean of cognitive function 95% Confidence interval p-value Levels of systemic inflammation in wave 1 and 2 low-low 15,780 64.0 -0.051 -0.078 -0.024 < 0.001 high-low 1,977 8.0 -0.047 -0.122 0.028 low-high 2,756 11.2 0.036 -0.030 0.102 high-high 4,148 16.8 0.080 0.027 0.134 Vigorous physical activity inactive 16,888 68.5 0.071 0.037 0.106 < 0.001 active 7,773 31.5 -0.214 -0.251 -0.178 Sex male 10,988 44.6 -0.094 -0.127 -0.062 < 0.001 female 13,673 55.4 0.042 0.013 0.071 Education low 9,635 39.1 0.307 0.270 0.343 < 0.001 medium 7,453 30.2 -0.037 -0.076 0.001 high 7,062 28.6 -0.452 -0.486 -0.418 na 511 2.1 0.102 -0.057 0.261 Diabetes no 23,428 95.0 -0.031 -0.053 -0.009 < 0.001 yes 1,233 5.0 0.221 0.126 0.315 Depression no 22,311 90.5 -0.023 -0.046 -0.001 0.210 yes 2,350 9.5 0.024 -0.047 0.094 Stroke no 24,385 98.9 -0.022 -0.044 -0.001 0.002 yes 276 1.1 0.299 0.087 0.512 Myocardial infarction no 24,127 97.8 -0.021 -0.043 0.001 0.183 yes 534 2.2 0.079 -0.075 0.234 Heart failure no 24,379 98.9 -0.021 -0.043 0.000 0.038 yes 282 1.1 0.193 -0.030 0.417 Parkinson's disease no 24,642 99.9 -0.019 -0.041 0.002 0.377 yes 19 0.1 0.330 -0.367 1.027 Systolic blood pressure in quartiles < 119 6,187 25.1 -0.091 -0.134 -0.049 140 5,837 23.7 0.085 0.041 0.130 Obesity no 20,723 84.0 -0.037 -0.061 -0.014 < 0.001 yes 3,938 16.0 0.079 0.025 0.133 Smoking status no 21,259 86.2 -0.026 -0.058 0.007 0.343 yes 3,262 13.2 0.019 -0.042 0.079 na 140 0.6 0.160 -0.115 0.434 Total 24,661 100.0 -0.019 -0.040 0.003 na: not available Model results After adjusting for cognitive task accuracy, age, sex, physical activity, education, medical conditions, and smoking status, individuals with high systemic inflammation (SI) levels in both waves exhibited significantly longer reaction times (b = 0.061 [0.001;0.121]) compared to those with low SI levels in both waves. This suggests that consistently high levels of systemic inflammation are associated with poorer cognitive function (Table 2 , model 1). Individuals with a high level of SI at wave one but a low level at wave two and those with a low level of SI at wave one but a high level at wave two did not differ significantly from the reference group. However, the point estimates suggest that SI levels at wave two may be more critical for cognitive function, which was also measured at wave two. Individuals who engage in vigorous physical activity had significantly faster reaction times (b=-0.152 [-0.198;-0.107]) compared to those who do not, indicating a positive association between physical activity and cognitive function. Additionally, women exhibited significantly longer reaction times than men (b = 0.112 [0.069;0.156]), and those with medium or high education levels had faster reaction times than those with low education (medium: b=-0.247 [-0.300;-0.194], high: b=-0.556 [-0.607;-0.504]). In the adjusted analyses, only two reported comorbidities, diabetes, and stroke, were significantly associated with worse cognitive function. Diabetes had a coefficient of b = 0.131 [0.036;0.226], while stroke had a coefficient of b = 0.294 [0.084;0.503]. On the other hand, depression, myocardial infarction, heart failure, and PD did not show a significant association. A significant effect of systolic blood pressure was found, indicating that higher systolic blood pressure is associated with worse cognitive function, as reaction time increased by 0.003 [0.001;0.004] per unit increase in systolic blood pressure. When controlling for several comorbidities (e.g. hypertension, stroke, myocardial infarction) that are themselves associated with smoking and obesity, smoking and obesity were not significantly associated with cognitive function. Table 2 Results of linear regression models to identify impact of systemic inflammation (SI) and vigorous physical activity on cognitive performance including interaction terms in model 2. Source: Lifelines data 2006–2015, own calculation. Model 1 Model 2 Variable Categories Coefficient b p-value 95% Confidence interval Coefficient b p-value 95% Confidence interval Levels of SI in wave 1 and 2 low-low 0 0 high-low -0.025 0.538 -0.103 0.054 -0.046 0.340 -0.140 0.048 low-high 0.055 0.108 -0.012 0.123 0.035 0.409 -0.048 0.117 high-high 0.061 0.047 0.001 0.121 0.054 0.128 -0.015 0.124 Vigorous physical activity inactive 0 0 active -0.152 < 0.001 -0.198 -0.107 -0.167 < 0.001 -0.222 -0.113 Levels of SI # physical activity low-low # active 0 high-low # active 0.067 0.432 -0.100 0.234 low-high # active 0.064 0.377 -0.078 0.207 high-high # active 0.020 0.765 -0.110 0.149 Sex male 0 0 female 0.112 < 0.001 0.069 0.156 0.112 < 0.001 0.069 0.156 Education low 0 0 medium -0.247 < 0.001 -0.300 -0.194 -0.247 < 0.001 -0.300 -0.194 high -0.556 < 0.001 -0.607 -0.504 -0.556 < 0.001 -0.607 -0.504 na -0.138 0.077 -0.292 0.015 -0.139 0.076 -0.292 0.015 Diabetes no 0 0 yes 0.131 0.007 0.036 0.226 0.131 0.007 0.036 0.226 Depression no 0 0 yes 0.029 0.422 -0.042 0.101 0.030 0.417 -0.042 0.101 Stroke no 0 0 yes 0.294 0.006 0.084 0.503 0.294 0.006 0.084 0.503 Myocardial infarction no 0 0 yes 0.046 0.556 -0.108 0.201 0.046 0.559 -0.108 0.200 Heart failure no 0 0 yes 0.102 0.362 -0.117 0.321 0.102 0.361 -0.117 0.322 Parkinson's disease no 0 0 yes 0.261 0.416 -0.368 0.890 0.261 0.417 -0.369 0.891 Systolic blood pressure in mmHg 0.003 < 0.001 0.001 0.004 0.003 < 0.001 0.001 0.004 Obesity no 0 0 yes -0.036 0.232 -0.094 0.023 -0.035 0.237 -0.094 0.023 Smoking status no 0 0 yes -0.021 0.529 -0.087 0.045 -0.021 0.540 -0.087 0.045 na 0.110 0.410 -0.151 0.371 0.110 0.409 -0.151 0.371 Constant -0.140 0.275 -0.393 0.112 -0.134 0.299 -0.386 0.119 Adjusted R² 0.0866 0.0867 N 24,661 24,661 Models are adjusted for age and accuracy of cognitive tasks. SI: systemic inflammation; na: not available Interaction model The analysis including the interaction term of systemic inflammation and physical activity (model 2) showed that physical activity was associated with faster reaction times for individuals with low SI levels in both waves, which was the reference group. The interaction term itself did not show significant estimates, meaning that the main effect of the reference group can be applied to all SI groups. Therefore, all individuals benefit from vigorous physical activity in terms of their cognitive performance, regardless of their SI group. DISCUSSION Our study examined the potential moderator effect of vigorous physical activity on the relationship between the systemic inflammation levels within the normal range and cognition in individuals over two waves in an older community-dwelling population. In line with previous studies [ 4 – 6 , 12 ], we found that elevated levels of systemic inflammation are associated with poorer cognitive performance. Individuals with consistently high inflammation levels in both waves (high-high) had significantly worse cognitive function compared to those with consistently low levels of inflammation (low-low). This finding supports the hypothesis that chronic inflammation can have detrimental effects on cognitive health. Amongst other factors, chronic systemic inflammation can be promoted by a number of risk factors, including chronic infections, autoimmune diseases, an inflammatory diet (high in fat and sodium), physical inactivity, visceral obesity, microbiome dysbiosis, smoking, poor sleep, social isolation, chronic stress, and exposure to toxic substances such as air pollutants, pesticides, or industrial chemicals [ 10 , 27 ]. Also, the aging process itself may lead to elevated chronic systemic inflammation, which is referred to as immunosenescence [ 10 ]. Mechanistically, inflammatory cytokines may disrupt neuronal function and alter brain structure, impacting cognitive processes such as synaptic plasticity and neurotransmitter metabolism, or even drive neurodegenerative processes [ 3 , 9 ]. Our results underscore the importance of monitoring, preventing, or possibly treating systemic inflammation as it represents a potential risk factor for cognitive decline and age-related diseases. Further, we were able to confirm the positive impact of physical activity on cognitive performance. Vigorous physical activity was associated with faster reaction times, indicating better cognitive performance, even after adjusting for sociodemographics, lifestyle factors, and important comorbidities associated with cognitive performance. This aligns with the existing literature suggesting that physical activity promotes cognitive performance [ 13 , 28 ]. A study of a small number of institutionalized and cognitively impaired older women also showed that vigorous physical activity led to a reduction in inflammation and an improvement in global cognition within 28 weeks [ 29 ]. Regarding our hypothesis, our interaction analysis revealed no significant interaction terms, which means that the association between inflammation levels and cognitive performance is the same for active and inactive individuals. However, this also means that physical activity has a positive effect on cognitive performance independent of systemic inflammation levels. This suggests that physical activity is a universal protective factor that promotes cognitive health, irrespective of an individual's inflammation status. Thus, vigorous physical activity has a positive impact on cognitive performance beyond the potential to reduce the inflammatory level and emerges as a promising modifiable factor for mitigating cognitive decline. Our study has several strengths and limitations. One strength is the use of a large, population-based cohort with repeated measurements of leukocyte count. This allowed us to examine the temporal relationship between inflammation levels and cognition, and to control for potential confounding factors. Another strength is the use of a validated composite score from the CogState Brief Battery (CBB) that assessed the two domains attention and psychomotor function to measure cognitive performance, which has been shown to be more sensitive to both AD-related cognitive impairment and decline than scores from the individual CBB tasks [ 20 , 21 ]. A limitation of our study is the reliance on self-reported physical activity, which may be subject to recall bias and social desirability. In addition, we used leukocyte count as a proxy for systemic inflammation, which may not capture the complexity and heterogeneity of the inflammatory response. Future studies may benefit from using more specific biomarkers of inflammation, such as cytokines, chemokines, and complement factors. Furthermore, we only have information on the leukocyte count at the two-time points of the two waves. Therefore, we cannot rule out that critical events, such as severe acute infections or surgery [ 10 ], may have occurred in the meantime, which could influence cognitive performance at the time of the second wave. To measure physical activity, we only distinguished between people who are vigorously physically active and those who are not. The "inactive" group is therefore quite heterogeneous and consists of people who are not active at all and people who are only moderately active. Effect sizes may therefore be underestimated, especially for people who are not active at all. Another limitation is the relatively short time interval of a few years between the two waves, so that we cannot be sure that people had already reduced their physical activity level at the beginning of the study due to the onset of cognitive problems. We only have information on cognitive performance at the time of the second wave. The attrition rate between the first and second wave was significant, with almost 30% of respondents not participating in the second wave [ 18 ]. To address the issue of a higher drop-out probability for individuals with worse cognitive function at baseline, we applied inverse probability weighting. We lacked information on environmental factors that may also impact inflammation levels, cognitive performance, and the relationship between the two. Finally, our analyses were constrained to adjust for self-reported comorbidities, obesity, and smoking status. The implications of our study are relevant for public health and clinical practice. The results of our study indicate that elevated systemic inflammation is a risk factor for cognitive impairment in older adults. Furthermore, our findings suggest that physical activity may mitigate this risk, regardless of the individual’s inflammatory status. Therefore, promoting physical activity among the aging population may be an effective strategy to prevent or delay cognitive decline and dementia. Moreover, screening for systemic inflammation and monitoring cognitive function may help identify individuals who are at high risk of cognitive impairment and who may benefit from early intervention. CONCLUSIONS In conclusion, the results of this study highlight the complex interplay between systemic inflammation, physical activity, and cognitive performance. Regular physical activity emerges as an effective strategy to enhance cognitive health, even in the presence of high systemic inflammation. Simultaneously, the findings underscore the importance of controlling inflammation markers and cardiovascular risk factors to prevent cognitive impairments. Future research should continue to explore these relationships to develop targeted interventions for promoting cognitive health in the population. Abbreviations AD Alzheimer’s disease CBB CogState Brief Battery SI Systemic inflammation SQUASH Short questionnaire to assess health-enhancing physical activity UMCG University Medical Center Groningen Declarations Ethics declarations Ethics approval and consent to participate The LifeLines Cohort Study is being conducted according to the principles of the Declaration of Helsinki and in accordance with research code of the University Medical Center Groningen (UMCG). The LifeLines study has been approved by the medical ethical committee of the UMCG, The Netherlands. Consent for publication Not applicable. Availability of data and materials Data may be obtained from a third party and is not publicly available. Researchers may apply to use the Lifelines data used in this study. For information on how to request Lifelines data and terms of use are available on their website at (https://www.lifelines.nl/researcher/how-to-apply). The dataset supporting the conclusions of this article is stored at the LifeLines server, section OV21_00326, and available upon request. Competing interests None of the authors have any competing interests. Funding The Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen). Authors’ contribution AF wrote the manuscript and researched data. CR and GD contributed to concept and statistical design. 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Neurosci Biobehav Rev. 2017;75:114–28. https://doi.org/10.1016/j.neubiorev.2017.01.044 . Nimmo M, Leggate M, Viana J, King J. The effect of physical activity on mediators of inflammation. Diabetes Obes Metab. 2013;15(s3):51–60. https://doi.org/10.1111/dom.12156 . Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurol. 2014;13(8):788–94. http://dx.doi.org/10.1016/S1474-4422(14)70136-X . Sijtsma A, Rienks J, van der Harst P, Navis G, Rosmalen JG, Dotinga A. Cohort Profile Update: Lifelines, a three-generation cohort study and biobank. Int J Epidemiol. 2022;51(5):e295–302. 10.1093/ije/dyab257 . Scholtens S, Smidt N, Swertz MA, Bakker SJ, Dotinga A, Vonk JM, et al. Cohort Profile: LifeLines, a three-generation cohort study and biobank. Int J Epidemiol. 2015;44(4):1172–80. https://doi.org/10.1093/ije/dyu229 . Maruff P, Lim YY, Darby D, Ellis KA, Pietrzak RH, Snyder PJ, et al. Clinical utility of the cogstate brief battery in identifying cognitive impairment in mild cognitive impairment and Alzheimer’s disease. BMC Psychol. 2013;1(30). https://doi.org/10.1186/2050-7283-1-30 . White JP, Schembri A, Prenn-Gologranc C, Ondrus M, Katina S, Novak P, et al. Sensitivity of Individual and Composite Test Scores from the Cogstate Brief Battery to Mild Cognitive Impairment and Dementia Due to Alzheimer’s Disease. J Alzheimers Dis. 2023;96(4):1781–99. 10.3233/JAD-230352 . Chmielewski PP, Borysławski K, Chmielowiec K, Chmielowiec J, Strzelec B. The association between total leukocyte count and longevity: Evidence from longitudinal and cross-sectional data. Ann Anat. 2016;204:1–10. https://doi.org/10.1016/j.aanat.2015.09.002 . Nilsson G, Hedberg P, Öhrvik J. White blood cell count in elderly is clinically useful in predicting long-term survival. J Aging Res. 2014;2014(1):475093. https://doi.org/10.1155/2014/475093 . Wendel-Vos GW, Schuit AJ, Saris WH, Kromhout D. Reproducibility and relative validity of the short questionnaire to assess health-enhancing physical activity. J Clin Epidemiol. 2003;56(12):1163–9. https://doi.org/10.1016/S0895-4356(03)00220-8 . Metten M-A, Costet N, Multigner L, Viel J-F, Chauvet G. Inverse probability weighting to handle attrition in cohort studies: some guidance and a call for caution. BMC Med Res Methodol. 2022;22(1):45. https://doi.org/10.1186/s12874-022-01533-9 . Hernán MA, Hernández-Díaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004;15(5):615–25. 10.1097/01.ede.0000135174.63482.43 . Furman D, Campisi J, Verdin E, Carrera-Bastos P, Targ S, Franceschi C, et al. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25(12):1822–32. https://doi.org/10.1038/s41591-019-0675-0 . Fink A, Buchmann N, Tegeler C, Steinhagen-Thiessen E, Demuth I, Doblhammer G. Physical activity and cohabitation status moderate the link between diabetes mellitus and cognitive performance in a community-dwelling elderly population in Germany. PLoS ONE. 2017;12(10). https://doi.org/10.1371/journal.pone.0187119 . Chupel MU, Direito F, Furtado GE, Minuzzi LG, Pedrosa FM, Colado JC, et al. Strength training decreases inflammation and increases cognition and physical fitness in older women with cognitive impairment. Front Physiol. 2017;8:377. https://doi.org/10.3389/fphys.2017.00377 . Additional Declarations No competing interests reported. Supplementary Files floatimage3.jpeg Figure S1: Distribution of cognitive performance score. Higher values correspond to lower cognitive performance. Source: Lifelines data 2006-2015, own calculation. 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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-4761080","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":339845068,"identity":"8298b5c9-95c6-4713-a4bc-37b0d588e57d","order_by":0,"name":"Anne Fink","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYNACGwkGCfYGAxCTsYE4LWlALTwHSNPCwCAhkUCkFv7ZvQcfMCRY5EnOfLz5c0EFg2w/IS0Sd84lGzAkSBRLS6cVGM84w2A8k6A1N3LMJBh/SCTOk84xSOZtY0jccICADvkbOeY/gLYkzpM8Y3CY9x9D4n5CWgyAtjCAtMyW4DFs5m0A2kLIXYY3cowlEoBaZvakFTPzHJMwnkHIFrkbOYYfPiTUJc44fnjzZ54aG9n+BkLWgEACgilBjPpRMApGwSgYBYQAAHTDPQyTMnprAAAAAElFTkSuQmCC","orcid":"","institution":"German Center for Neurodegenerative Diseases","correspondingAuthor":true,"prefix":"","firstName":"Anne","middleName":"","lastName":"Fink","suffix":""},{"id":339845072,"identity":"276348d4-26f4-4ceb-ad8c-965152045e5b","order_by":1,"name":"Constantin Reinke","email":"","orcid":"","institution":"University of Rostock","correspondingAuthor":false,"prefix":"","firstName":"Constantin","middleName":"","lastName":"Reinke","suffix":""},{"id":339845074,"identity":"f95d6bd7-d6ca-48d4-86aa-1e37d0f24760","order_by":2,"name":"Benjamin Aretz","email":"","orcid":"","institution":"University of Bonn","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Aretz","suffix":""},{"id":339845076,"identity":"93463147-74ad-44ad-a566-535bb46d698e","order_by":3,"name":"Michael T. Heneka","email":"","orcid":"","institution":"University of Luxembourg","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"T.","lastName":"Heneka","suffix":""},{"id":339845078,"identity":"97b65c99-0b8c-4621-a2b6-d82c35b3442d","order_by":4,"name":"Gabriele Doblhammer","email":"","orcid":"","institution":"German Center for Neurodegenerative Diseases","correspondingAuthor":false,"prefix":"","firstName":"Gabriele","middleName":"","lastName":"Doblhammer","suffix":""}],"badges":[],"createdAt":"2024-07-18 08:35:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4761080/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4761080/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62661038,"identity":"386d3ec1-c5c9-439b-b7c0-5433eba7fd01","added_by":"auto","created_at":"2024-08-17 02:37:59","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":102784,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the moderator hypothesis: Physical activity as moderator of systemic inflammation effects on cognitive performance.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4761080/v1/e54e94ed8e4b9376d6a12726.jpeg"},{"id":81243652,"identity":"f7c2a2f2-b1bc-4f76-9c37-488d3281fe8b","added_by":"auto","created_at":"2025-04-24 00:46:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":917018,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4761080/v1/c7f6a97b-135f-4099-b70a-b3f9da1127a8.pdf"},{"id":62661722,"identity":"0aaf619f-19b6-4e88-a556-abc3689f4b36","added_by":"auto","created_at":"2024-08-17 02:45:59","extension":"jpeg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":189420,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S1: Distribution of cognitive performance score. Higher values correspond to lower cognitive performance. Source: Lifelines data 2006-2015, own calculation.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4761080/v1/9bfdabf3df381c28671a7af3.jpeg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can physical activity mitigate the effect of systemic inflammation on cognitive performance? Results from a large older community dwelling population in the Netherlands","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe increasing prevalence of dementia, both globally and particularly in Europe, poses a significant challenge to public health. As populations age, the number of individuals affected by this condition is expected to rise significantly from almost 50\u0026nbsp;million in 2015 to over 152\u0026nbsp;million in 2050 worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While the urgent need for effective strategies against cognitive impairment and the development of dementia is widely acknowledged, there is still a lack of understanding of the potential effectiveness of primary prevention interventions in the older population [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNewer studies revealed that systemic inflammation processes are one of the most important risk factors for neurodegeneration [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Several studies have shown that chronic systemic inflammation is associated with cognitive decline, affecting essential areas like memory, attention, and processing speed, as well as an increased risk of dementia [\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. One hypothesis is that inflammatory response causes the disruption of neuronal function and subsequent changes in brain structure [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although systemic inflammation may be the response to the pathogenesis of cognitive decline or dementia, systemic inflammation may still influence the progression and clinical manifestation of the disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn elevated white blood cell count may serve as an early indicator of systemic inflammation and is associated with the progression of various diseases. A slightly elevated white blood cell count, even within the normal range, could indicate a higher likelihood of increased systemic inflammation and subclinical disease. In addition to an increased risk of developing cancer, cardiovascular diseases, type 2 diabetes, and other age-related diseases, as well as an increased risk of all-cause mortality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] an elevated white blood cell count is also associated with reduced cognitive performance [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, physical activity is commonly linked to better cognitive performance. Regular exercise has been shown to improve several cognitive functions, including processing speed, memory, and executive function [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It is believed that the advantageous outcomes of physical activity on cognition are mediated through various mechanisms. These include promoting neuroplasticity, increasing brain-derived neurotrophic factor levels, improving cerebral blood flow, as well as reducing systemic chronic inflammation by reducing adipose tissue, enhancing the release of anti-inflammatory myokines, improving endothelial function, and modulating metabolic health [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Physical activity is therefore an important modifiable risk factor for cognitive decline and dementia in the absence of curative treatment options [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile it is clear that both systemic inflammation and physical activity independently affect cognitive performance, their interactions are less well understood. This large cohort study uses an older community-dwelling setting in the Netherlands to explore whether physical activity can mitigate the effect of systemic inflammation on cognitive performance. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, our hypothesis is that physical activity moderates the relationship between leukocyte count and cognitive performance by altering the strength of the relationship. We therefore theorize that elevated leukocyte counts affect active and inactive individuals differently (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eData\u003c/p\u003e \u003cp\u003eThe current study uses baseline and follow-up data (2006\u0026ndash;2017) from the Lifelines Cohort Study and Biobank. Information on the study design and objectives of Lifelines has been previously described elsewhere [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In summary, Lifelines is a multi-disciplinary prospective population-based cohort study examining in a unique three-generation design the health and health-related behaviors of 167,729 persons living in the North of the Netherlands. It employs a broad range of investigative procedures in assessing the biomedical, socio-demographic, behavioral, physical and psychological factors which contribute to the health and disease of the general population, with a special focus on multi-morbidity and complex genetics. Lifelines was conducted in accordance with the guidelines of the Declaration of Helsinki. All procedures involving human subjects were approved by the Medical Ethics Committee of the University Medical Center Groningen (UMCG), and written informed consent was obtained from all participants. Our study included adults aged 50 years and above (N\u0026thinsp;=\u0026thinsp;24,661), who had valid information on body height, body weight, systolic blood pressure, and physical activity at baseline (2006\u0026ndash;2013), leukocyte count measurements at baseline (2006\u0026ndash;2013) and follow-up (2014\u0026ndash;2017), and cognitive performance measurements at follow-up (2014\u0026ndash;2017).\u003c/p\u003e \u003cp\u003eOutcome: Cognitive performance\u003c/p\u003e \u003cp\u003eThe CogState Brief Battery (CBB) is a computer-administered cognitive test battery that takes about 10 minutes to administer. It consists of four cognitive tasks that measure cognitive functions: Psychomotor function, attention, working memory, and memory [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The CBB has shown its effectiveness and sensitivity in detecting cognitive impairment in conditions like Alzheimer\u0026rsquo;s disease (AD) and mild cognitive impairment, and in assessing cognitive changes in the preclinical stages of AD [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This makes it a valuable tool in the field of cognitive neuroscience. We used two cognitive processing speed measures from the CBB. First, the Detection Task, which measures psychomotor function \u0026ndash; the coordination of sensory or cognitive processes and motor activity. Second, the Identification Task, which measures attention. For both tasks, the primary outcome was reaction time in milliseconds (speed). A base 10 logarithmic transformation (log10) was used to normalize the distribution. The transformed values were z-standardized for 5-year age groups starting at age 50 and summed up to a composite score measuring cognitive performance. The resulting score ranged from \u0026minus;\u0026thinsp;8.21 to 13.24, with higher reaction times indicating poorer cognitive function. Detection Task and Identification Task were shown to have excellent specificity, validity and reliability [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExposure: Marker of systemic inflammation (SI): Leukocyte count\u003c/p\u003e \u003cp\u003eAs a proxy biomarker of systemic inflammation (SI), we used leukocyte count within the normal range of 3 to 11x10\u003csup\u003e9\u003c/sup\u003e cells per liter in EDTA-blood samples at baseline (2006\u0026ndash;2013) and follow-up (2014\u0026ndash;2017). We excluded all individuals who had a leukocyte count of less than 3 or greater than 11 at either the baseline or at follow-up to reduce the possibility that conditions such as acute infections or leukemia, could bias the findings due to undetected and uncontrolled inflammation-related diseases and thus the computerized tests of the CBB [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The highest 25% of the leukocyte count (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;6.5x10\u003csup\u003e9\u003c/sup\u003e cells per liter) was defined as high SI levels [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Values below this cut-off were defined as low SI levels. We performed four groups and distinguished between (1) individuals who had low SI at baseline and at follow-up (low-low), (2) individuals who had elevated SI at baseline but low SI at follow-up (high-low), (3) individuals who had low SI at baseline but elevated SI at follow-up (low-high), and (4) individuals who had elevated SI at baseline and at follow-up (high-high).\u003c/p\u003e \u003cp\u003eModerator variable: Physical activity\u003c/p\u003e \u003cp\u003ePhysical activity was assessed using the short questionnaire to assess health-enhancing physical activity (SQUASH), a questionnaire to measure the habitual physical activity level of adults, developed by the Dutch National Institute of Public Health and the Environment. The questionnaire consists of questions on four categories of activities: commuting, leisure time, household, and work/school. For each activity, the frequency, duration, and intensity are recorded [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. For our analysis, we distinguished between people who did at least one minute of vigorous physical activity per week and people who did no vigorous physical activity at all at baseline Since high-intensity exercise has been shown to have the greatest impact on the inflammatory profile, we focus on vigorous physical activity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCovariates\u003c/p\u003e \u003cp\u003eThe following covariates were measured at baseline: sex (male, female), age, education (low, medium, high, missing), smoking status (non-smoker, current smoker, missing), and self-reported diagnoses of diabetes, depression, stroke, myocardial infarction, heart failure, or Parkinson\u0026rsquo;s disease. Additionally, we included obesity (body mass index\u0026thinsp;\u0026gt;\u0026thinsp;30 kg/m\u0026sup2; derived from measured body height and weight during assessment) and systolic blood pressure measured during assessment. We used the speed measures recorded by the CBB as our primary outcome. This implies that participants who responded quickly to the tasks may still have provided inaccurate responses. To account for this possible response accuracy, we calculated a composite score of response accuracy measured by the number of correct responses divided by the number of total responses in the two CBB domains.\u003c/p\u003e \u003cp\u003eStatistical analyses\u003c/p\u003e \u003cp\u003eWe used one-way analysis of variance and Bonferroni-corrected post hoc test (for covariates with more than two categories) to compare cognitive function scores between groups of SI levels, physical activity, and covariates. To estimate cognitive performance, we used a linear regression model with robust standard errors (Breusch-Pagan with p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as a function of SI levels, physical activity, sex, age, education, smoking status, obesity, and self-reported diagnoses. A second model additionally included an interaction effect between physical activity and SI level groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To account for selection bias, we used inverse probability weighting. Stabilized weights were obtained from the quotient of a logistic response model as a function of all included variables of the association model and a logistic response model with age, sex, and education only [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe study population consisted of 24,661 individuals. The cognitive performance score, measured as the combined z-standardized and log-transformed reaction times from the Detection and Identification tasks of CBB, had a mean value of -0.019 (95% confidence interval [-0.040;0.003]), and Figure S1 displays its distribution. Higher values correspond to poorer cognitive performance. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the characteristics of the study population and the associations between the dependent and independent variables. Individuals with low levels of inflammation in both waves (low-low) had an average cognitive function score of -0.051 [-0.078;-0.024]. In contrast, those with high levels of inflammation in both waves (high-high) had an average cognitive function score of 0.080 [0.027;0.134], indicating significantly poorer cognitive performance. Active individuals had a significantly better cognitive function (-0.214 [-0.251;-0.178]) compared to inactive individuals (0.071 [0.037;0.106]), and men had a better average cognitive function (-0.094 [-0.127;-0.062]) than women (0.042 [0.013;0.071]). Furthermore, there was an education gradient observed, as individuals with lower education exhibited significantly poorer cognitive function (0.307 [-0.270;0.343]) compared to those with middle (-0.037 [-0.076;0.001]) or high (-0.452 [-0.486;-0.418]) education. Individuals who reported having diabetes, stroke, or heart failure had significantly poorer cognitive function compared to those without these diseases. However, individuals with depression, myocardial infarction, or PD did not differ significantly from those without these diseases. We found a negative gradient between systolic blood pressure and cognitive performance. Specifically, individuals with a systolic blood pressure of over 140 mmHg had an average score of 0.085 [0.041;0.130], while those with a systolic blood pressure lower than 119 mmHg had an average score of -0.091 [-0.134;-0.049]. Additionally, we found that non-obese individuals had better cognitive function (-0.037 [-0.061;-0.014]) compared to obese individuals (0.079 [0.025;0.133]). There was no statistically significant difference in average cognitive function between non-smokers (-0.026 [-0.058;0.007]) and smokers (0.019 [-0.042;0.079]).\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\u003eCharacteristics of study participants and associations of predictor variables with mean of score of cognitive performance.\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003eSource: Lifelines data 2006\u0026ndash;2015, own calculation.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean of cognitive function\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95% Confidence interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLevels of systemic inflammation in wave 1 and 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVigorous physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003einactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23,428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22,311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMyocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParkinson's disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSystolic blood pressure in quartiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e119\u0026ndash;128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129\u0026ndash;140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.7\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\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21,259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003ena: not available\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\u003eModel results\u003c/p\u003e \u003cp\u003eAfter adjusting for cognitive task accuracy, age, sex, physical activity, education, medical conditions, and smoking status, individuals with high systemic inflammation (SI) levels in both waves exhibited significantly longer reaction times (b\u0026thinsp;=\u0026thinsp;0.061 [0.001;0.121]) compared to those with low SI levels in both waves. This suggests that consistently high levels of systemic inflammation are associated with poorer cognitive function (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, model 1). Individuals with a high level of SI at wave one but a low level at wave two and those with a low level of SI at wave one but a high level at wave two did not differ significantly from the reference group. However, the point estimates suggest that SI levels at wave two may be more critical for cognitive function, which was also measured at wave two. Individuals who engage in vigorous physical activity had significantly faster reaction times (b=-0.152 [-0.198;-0.107]) compared to those who do not, indicating a positive association between physical activity and cognitive function. Additionally, women exhibited significantly longer reaction times than men (b\u0026thinsp;=\u0026thinsp;0.112 [0.069;0.156]), and those with medium or high education levels had faster reaction times than those with low education (medium: b=-0.247 [-0.300;-0.194], high: b=-0.556 [-0.607;-0.504]). In the adjusted analyses, only two reported comorbidities, diabetes, and stroke, were significantly associated with worse cognitive function. Diabetes had a coefficient of b\u0026thinsp;=\u0026thinsp;0.131 [0.036;0.226], while stroke had a coefficient of b\u0026thinsp;=\u0026thinsp;0.294 [0.084;0.503]. On the other hand, depression, myocardial infarction, heart failure, and PD did not show a significant association. A significant effect of systolic blood pressure was found, indicating that higher systolic blood pressure is associated with worse cognitive function, as reaction time increased by 0.003 [0.001;0.004] per unit increase in systolic blood pressure. When controlling for several comorbidities (e.g. hypertension, stroke, myocardial infarction) that are themselves associated with smoking and obesity, smoking and obesity were not significantly associated with cognitive function.\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\u003eResults of linear regression models to identify impact of systemic inflammation (SI) and vigorous physical activity on cognitive performance including interaction terms in model 2.\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003eSource: Lifelines data 2006\u0026ndash;2015, own calculation.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \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=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficient b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e95% Confidence interval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCoefficient b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e95% Confidence interval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLevels of SI in wave 1 and 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVigorous physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003einactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLevels of SI # physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-low # active\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\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-low # active\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\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow-high # active\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\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh-high # active\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\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.139\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 \u003cp\u003e-0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMyocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParkinson's disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure in mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \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 \u003cp\u003e0\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ena\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0866\u003c/p\u003e \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 \u003cp\u003e0.0867\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,661\u003c/p\u003e \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 \u003cp\u003e24,661\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eModels are adjusted for age and accuracy of cognitive tasks.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSI: systemic inflammation; na: not available\u003c/p\u003e \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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInteraction model\u003c/p\u003e \u003cp\u003eThe analysis including the interaction term of systemic inflammation and physical activity (model 2) showed that physical activity was associated with faster reaction times for individuals with low SI levels in both waves, which was the reference group. The interaction term itself did not show significant estimates, meaning that the main effect of the reference group can be applied to all SI groups. Therefore, all individuals benefit from vigorous physical activity in terms of their cognitive performance, regardless of their SI group.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study examined the potential moderator effect of vigorous physical activity on the relationship between the systemic inflammation levels within the normal range and cognition in individuals over two waves in an older community-dwelling population. In line with previous studies [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], we found that elevated levels of systemic inflammation are associated with poorer cognitive performance. Individuals with consistently high inflammation levels in both waves (high-high) had significantly worse cognitive function compared to those with consistently low levels of inflammation (low-low). This finding supports the hypothesis that chronic inflammation can have detrimental effects on cognitive health. Amongst other factors, chronic systemic inflammation can be promoted by a number of risk factors, including chronic infections, autoimmune diseases, an inflammatory diet (high in fat and sodium), physical inactivity, visceral obesity, microbiome dysbiosis, smoking, poor sleep, social isolation, chronic stress, and exposure to toxic substances such as air pollutants, pesticides, or industrial chemicals [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Also, the aging process itself may lead to elevated chronic systemic inflammation, which is referred to as immunosenescence [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Mechanistically, inflammatory cytokines may disrupt neuronal function and alter brain structure, impacting cognitive processes such as synaptic plasticity and neurotransmitter metabolism, or even drive neurodegenerative processes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Our results underscore the importance of monitoring, preventing, or possibly treating systemic inflammation as it represents a potential risk factor for cognitive decline and age-related diseases.\u003c/p\u003e \u003cp\u003eFurther, we were able to confirm the positive impact of physical activity on cognitive performance. Vigorous physical activity was associated with faster reaction times, indicating better cognitive performance, even after adjusting for sociodemographics, lifestyle factors, and important comorbidities associated with cognitive performance. This aligns with the existing literature suggesting that physical activity promotes cognitive performance [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A study of a small number of institutionalized and cognitively impaired older women also showed that vigorous physical activity led to a reduction in inflammation and an improvement in global cognition within 28 weeks [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding our hypothesis, our interaction analysis revealed no significant interaction terms, which means that the association between inflammation levels and cognitive performance is the same for active and inactive individuals. However, this also means that physical activity has a positive effect on cognitive performance independent of systemic inflammation levels. This suggests that physical activity is a universal protective factor that promotes cognitive health, irrespective of an individual's inflammation status. Thus, vigorous physical activity has a positive impact on cognitive performance beyond the potential to reduce the inflammatory level and emerges as a promising modifiable factor for mitigating cognitive decline.\u003c/p\u003e \u003cp\u003eOur study has several strengths and limitations. One strength is the use of a large, population-based cohort with repeated measurements of leukocyte count. This allowed us to examine the temporal relationship between inflammation levels and cognition, and to control for potential confounding factors. Another strength is the use of a validated composite score from the CogState Brief Battery (CBB) that assessed the two domains attention and psychomotor function to measure cognitive performance, which has been shown to be more sensitive to both AD-related cognitive impairment and decline than scores from the individual CBB tasks [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA limitation of our study is the reliance on self-reported physical activity, which may be subject to recall bias and social desirability. In addition, we used leukocyte count as a proxy for systemic inflammation, which may not capture the complexity and heterogeneity of the inflammatory response. Future studies may benefit from using more specific biomarkers of inflammation, such as cytokines, chemokines, and complement factors. Furthermore, we only have information on the leukocyte count at the two-time points of the two waves. Therefore, we cannot rule out that critical events, such as severe acute infections or surgery [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], may have occurred in the meantime, which could influence cognitive performance at the time of the second wave. To measure physical activity, we only distinguished between people who are vigorously physically active and those who are not. The \"inactive\" group is therefore quite heterogeneous and consists of people who are not active at all and people who are only moderately active. Effect sizes may therefore be underestimated, especially for people who are not active at all. Another limitation is the relatively short time interval of a few years between the two waves, so that we cannot be sure that people had already reduced their physical activity level at the beginning of the study due to the onset of cognitive problems. We only have information on cognitive performance at the time of the second wave. The attrition rate between the first and second wave was significant, with almost 30% of respondents not participating in the second wave [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. To address the issue of a higher drop-out probability for individuals with worse cognitive function at baseline, we applied inverse probability weighting. We lacked information on environmental factors that may also impact inflammation levels, cognitive performance, and the relationship between the two. Finally, our analyses were constrained to adjust for self-reported comorbidities, obesity, and smoking status.\u003c/p\u003e \u003cp\u003eThe implications of our study are relevant for public health and clinical practice. The results of our study indicate that elevated systemic inflammation is a risk factor for cognitive impairment in older adults. Furthermore, our findings suggest that physical activity may mitigate this risk, regardless of the individual\u0026rsquo;s inflammatory status. Therefore, promoting physical activity among the aging population may be an effective strategy to prevent or delay cognitive decline and dementia. Moreover, screening for systemic inflammation and monitoring cognitive function may help identify individuals who are at high risk of cognitive impairment and who may benefit from early intervention.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, the results of this study highlight the complex interplay between systemic inflammation, physical activity, and cognitive performance. Regular physical activity emerges as an effective strategy to enhance cognitive health, even in the presence of high systemic inflammation. Simultaneously, the findings underscore the importance of controlling inflammation markers and cardiovascular risk factors to prevent cognitive impairments. Future research should continue to explore these relationships to develop targeted interventions for promoting cognitive health in the population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Alzheimer\u0026rsquo;s disease\u003c/p\u003e\n\u003cp\u003eCBB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;CogState Brief Battery\u003c/p\u003e\n\u003cp\u003eSI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Systemic inflammation\u003c/p\u003e\n\u003cp\u003eSQUASH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Short questionnaire to assess health-enhancing physical activity\u003c/p\u003e\n\u003cp\u003eUMCG\u0026nbsp;University Medical Center Groningen\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics declarations\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe LifeLines Cohort Study is being conducted according to the principles of the Declaration of Helsinki and in accordance with research code of the University Medical Center Groningen (UMCG). The LifeLines study has been approved by the medical ethical committee of the UMCG, The Netherlands.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eData may be obtained from a third party and is not publicly available. Researchers may apply to use the Lifelines data used in this study. For information on how to request Lifelines data and terms of use are available on their website at (https://www.lifelines.nl/researcher/how-to-apply). The dataset supporting the conclusions of this article is stored at the LifeLines server, section OV21_00326, and available upon request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eNone of the authors have any competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen).\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contribution\u003c/p\u003e\n\u003cp\u003eAF wrote the manuscript and researched data. CR and GD contributed to concept and statistical design. CR, BA, MTH and GD contributed to the introduction and discussion and reviewed/edited the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all study participants.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGuerchet M, Prince M, Prina M. Numbers of people with dementia worldwide: An update to the estimates in the World Alzheimer Report 2015. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.alzint.org/resource/numbers-of-people-with-dementia-worldwide/\u003c/span\u003e\u003cspan address=\"https://www.alzint.org/resource/numbers-of-people-with-dementia-worldwide/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020). 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Front Physiol. 2017;8:377. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fphys.2017.00377\u003c/span\u003e\u003cspan address=\"10.3389/fphys.2017.00377\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cognitive performance, systemic inflammation, physical activity","lastPublishedDoi":"10.21203/rs.3.rs-4761080/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4761080/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eElevated systemic inflammation has been linked to poorer cognitive outcomes. Vigorous physical activity is associated with improved cognitive performance. This study investigates whether physical activity moderates the relationship between systemic inflammation and cognition.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing the first wo waves from the Dutch Lifelines cohort study (N\u0026thinsp;=\u0026thinsp;24,661, 50+), cognitive performance was assessed using a composite score from the Cogstate Brief Battery, with higher scores indicating lower cognitive performance. As a biomarker of systemic inflammation (SI), we used leukocyte count within the normal range of 3 to 11x10\u003csup\u003e9\u003c/sup\u003e cells per liter in EDTA blood samples in waves 1 and 2. We differentiated between low SI (\u0026lt;\u0026thinsp;6.5x10\u003csup\u003e9\u003c/sup\u003e cells per liter) and increased SI (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;6.5x10\u003csup\u003e9\u003c/sup\u003e cells per liter) and distinguished between 4 groups: (1) Persons, who had low SI in both waves; (2) Persons, who had increased SI in wave 1, but low SI in wave 2; (3) Persons, who had low SI in wave 1, but increased SI in wave 2; and (4) Persons, who had increased SI in both waves. We performed linear regression models to examine the effect of inflammation and vigorous physical activity on cognition, adjusting for cognitive task accuracy, age, sex, physical activity, education, medical conditions, and smoking status associated with cognitive impairment. An interaction effect was used to analyze the potential moderation of physical activity.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIndividuals with high systemic inflammation (SI) levels in both waves exhibited significantly longer reaction times (b\u0026thinsp;=\u0026thinsp;0.061 [0.001;0.121]) compared to those with low SI levels in both waves. Individuals who engage in vigorous physical activity had significantly faster reaction times (-0.152 [-0.198;-0.107]) compared to those who do not. The interaction term was insignificant meaning that all individuals benefit from vigorous physical activity in terms of their cognitive performance, regardless of their SI group.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings suggest that elevated systemic inflammation is a risk factor for cognitive impairment in older adults, and that physical activity may mitigate this risk. Therefore, promoting physical activity among the aging population may be an effective strategy to prevent or delay cognitive decline and dementia by potentially preventing systemic inflammation.\u003c/p\u003e","manuscriptTitle":"Can physical activity mitigate the effect of systemic inflammation on cognitive performance? Results from a large older community dwelling population in the Netherlands","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-17 02:37:54","doi":"10.21203/rs.3.rs-4761080/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1ed385c-c280-4fbe-b440-da11c3e225c0","owner":[],"postedDate":"August 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-24T00:38:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-17 02:37:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4761080","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4761080","identity":"rs-4761080","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}