Physical activity as a protective factor for dementia and Alzheimer's disease: systematic review, meta-analysis and quality assessment of cohort and case-control studies

Physical activity alleviates negative effects of bedroom light pollution on blood pressure and hypertension in Chinese young adults

Excessive exposure to light at night (LAN) has become a serious public health concern. However, little is known about the impact of indoor LAN exposure on blood pressure, particularly among young adults. We aimed to investigate the effects of bedroom individual-level LAN exposure in real-world environment on blood pressure and hypertension among vulnerable young adults, and to evaluate the possible buffering effect of physical activity. In this cross-sectional study, a total of 400 healthy young adults aged 16-22 years were included. Bedroom LAN exposure was recorded at 1-min intervals for two consecutive nights using a TES-1339 R illuminance meter. Blood pressure was measured three times (8-11 a.m. in the physical examination day) in the seated position using an Omron HEM-7121 digital sphygmomanometer. A wrist-worn triaxial accelerometer (ActiGraph GT3X-BT) was used to assess physical activity for seven consecutive days. Each 1 lx increase of bedroom LAN intensity was associated with 0.55 mmHg-increase in SBP (95% CI: 0.15, 0.95), 0.30 mmHg-increase in DBP (95% CI: 0.06, 0.54), and 0.38 mmHg-increase in MAP (95% CI: 0.12, 0.65). Higher levels of LAN exposure were associated with increased risk of hypertension (LAN ≥ 3lx vs. LAN < 3lx: OR = 3.30, 95%CI = 1.19-9.19; LAN ≥ 5lx vs. LAN < 5lx: OR = 3.87, 95%CI = 1.37-10.98). However, these detrimental effects of bedroom LAN exposure on blood pressure and hypertension were not observed among young adults with high MVPA (≥2 h/day) level. MVPA can alleviate negative effects of bedroom LAN exposure on blood pressure and hypertension. Maintaining bedroom settings darkness at night may be an important strategy for reducing the risk of hypertension. Furthermore, for individuals living with high levels of indoor LAN exposure, regular physical activity may be a good option for preventing cardiovascular disease and hypertension.

The burden of mild cognitive impairment attributable to physical inactivity in Colombia

BACKGROUND

Mild cognitive impairment often precedes dementia. The purpose of this analysis was to estimate the population attributable fraction for physical activity in Colombia, which is the reduction in cases that would occur if all participants were physically active.

METHODS

The sample included 20,174 men and women aged 70.04 ± 7.68 years (mean ± SD) from the National Survey of Health, Wellbeing and Ageing. Trained interviewers administered a shorter version of the mini-mental state examination and mild cognitive impairment was defined as a score of 12 or less out of 19. Logistic regression models were fitted and population attributable fractions for physical activity were calculated. All analyses were adjusted for age, sex, height, education, income, civil status, smoking, and alcohol drinking.

RESULTS

The prevalence of physical activity was approximately 50% when defined as walking between 9 and 20 blocks at least three times per week. Theoretically, 19% of cases of mild cognitive impairment would be eliminated if all adults were to walk (95% confidence interval: 16%, 22%). The prevalence was approximately 20% when defined as taking part in vigorous sport or exercise at least three times per week. Theoretically, 23% of cases of mild cognitive impairment would be eliminated if all adults were to take part in vigorous sport or exercise (16%, 30%). Similar results were observed after removing those who reported mental health problems.

CONCLUSION

Physical activity, whether walking or vigorous sport and exercise, has the potential to substantially reduce the burden of mild cognitive impairment in Colombia.

Self-reported sleepiness associates with greater brain and cortical volume and lower prevalence of ischemic covert brain infarcts in a community sample

STUDY OBJECTIVES

We evaluated if self-reported sleepiness was associated with neuroimaging markers of brain aging and ischemic damage in a large community-based sample.

METHODS

Participants from the Framingham Heart Study Offspring cohort (n = 468, 62.5 ± 8.7 years old, 49.6%M) free of dementia, stroke, and neurological diseases, completed sleep questionnaires and polysomnography followed by magnetic resonance imaging (MRI), 3 years later on average. We used linear and logistic regression models to evaluate the associations between Epworth Sleepiness Scale (ESS) scores and total brain, cortical and subcortical gray matter, and white matter hyperintensities volumes, and the presence of covert brain infarcts.

RESULTS

Higher sleepiness scores were associated with larger total brain volume, greater cortical gray matter volume, and a lower prevalence of covert brain infarcts, even when adjusting for a large array of potential confounders, including demographics, sleep profiles and disorders, organic health diseases, and proxies for daytime cognitive and physical activities. Interactions indicated that more sleepiness was associated with larger cortical gray matter volume in men only and in APOE ε4 noncarriers, whereas a trend for smaller cortical gray matter volume was observed in carriers. In longitudinal analyses, those with stable excessive daytime sleepiness over time had greater total brain and cortical gray matter volumes, whereas baseline sleepiness scores were not associated with subsequent atrophy or cognitive decline.

CONCLUSION

Our findings suggest that sleepiness is not necessarily a marker of poor brain health when not explained by diseases or sleep debt and sleep disorders. Rather, sleepiness could be a marker of preserved sleep-regulatory processes and brain health in some cases.

Prediction of Alzheimer’s Disease by a Novel Image-Based Representation of Gene Expression

Early intervention can delay the progress of Alzheimer’s Disease (AD), but currently, there are no effective prediction tools. The goal of this study is to generate a reliable artificial intelligence (AI) model capable of detecting the high risk of AD, based on gene expression arrays from blood samples. To that end, a novel image-formation method is proposed to transform single-dimension gene expressions into a discriminative 2-dimensional (2D) image to use convolutional neural networks (CNNs) for classification. Three publicly available datasets were pooled, and a total of 11,618 common genes’ expression values were obtained. The genes were then categorized for their discriminating power using the Fisher distance (AD vs. control (CTL)) and mapped to a 2D image by linear discriminant analysis (LDA). Then, a six-layer CNN model with 292,493 parameters were used for classification. An accuracy of 0.842 and an area under curve (AUC) of 0.875 were achieved for the AD vs. CTL classification. The proposed method obtained higher accuracy and AUC compared with other reported methods. The conversion to 2D in CNN offers a unique advantage for improving accuracy and can be easily transferred to the clinic to drastically improve AD (or any disease) early detection.

Using a two-sample mendelian randomization analysis to explore the relationship between physical activity and Alzheimer's disease

Evidence from previous epidemiological studies on the effect of physical activity on the risk of Alzheimer's disease (AD) is conflicting. We performed a two-sample Mendelian randomization analysis to verify whether physical activity is causally associated with AD. This study used two-sample Mendelian randomization (MR) analysis to estimate the association between physical activity (including overall activity, sedentary behavior, walking, and moderate-intensity activity) and AD. Genetic instruments for physical activity were obtained from published genome-wide association studies (GWAS) including 91,105 individuals from UK Biobank. Summary-level GWAS data were extracted from the International Genomics of Alzheimer's Project IGAP (21,982 patients with AD and 41,944 controls). Inverse Variance Weighted (IVW) was used to estimate the effect of physical activity on AD. Sensitivity analyses including weighted median, MR-Egger, MR-PRESSO, and leave-one-out analysis were used to estimate pleiotropy and heterogeneity. Mendelian randomization evidences suggested a protective relationship between walking and AD (odds ratio (OR) = 0.30, 95% confidence interval (CI), 0.13-0.68, P = 0.0039). Genetically predicted overall activity, sedentary behavior, and moderate-intensity activity were not associated with AD. In summary, this study provided evidence that genetically predicted walking might associate with a reduced risk of AD. Further research into the causal association between physical activity and AD could help to explore the real relationship and provide more measures to reduce AD risk.

ICT-Based Individualized Training of Institutionalized Individuals With Dementia. Evaluation of Usability and Trends Toward the Effectiveness of the InCoPE-App

Physical activity interventions can alleviate the course of disease for individuals with dementia (IWD) who have been extraordinarily affected by the COVID-19 pandemic. Information and Communication Technology (ICT) provides new opportunities not only to mitigate negative effects of the pandemic but also to sustainably improve everyday life of IWD in nursing homes. The aim of the present study was to evaluate the ICT-based InCoPE-App, which was used to assess physical and cognitive performance and deliver individualized exercise for IWD, with regard to 1) user experience of nursing assistants, and 2) trends toward the effectiveness of the intervention on physical and cognitive performance of IWD. An 18-week individualized multidomain intervention (2 × 60 min/session) was delivered to an intervention group (IG; n = 10, mean age 88.4 ± 5.6, 70% female) by nursing assistants (n = 10, mean age 56.1 ± 10.4, 90% female) using the InCoPE-App. A control group (CG; n = 3, mean age 87.3 ± 3.5, 100% female) received conventional treatment. User experience was assessed among nursing assistants by different questionnaires, i.e., PSSUQ and ISONORM 9241/110-S for usability, and AttrakDiff2 for pragmatic (PQ), hedonic quality-identity and stimulation (HQI and HQS), and attractiveness (ATT). Trends toward the effectiveness of the intervention were assessed using MMSE (global cognitive function), FICSIT-4 (balance), 6MWT and TUG (mobility), and m30CST (function of lower limbs). Usability of the InCoPE-App was rated as high by nursing assistants (mean ± SD; overall PSSUQ 2.11 ± 0.75; overall ISONORM 9241/110-S 1.90 ± 0.88; ATT 1.86 ± 1.01; PQ 1.79 ± 1.03; HQI 1.8 ± 0.79; and HQS 1.37 ± 0.69). Dropout was high in the total sample (36.7%). Trends toward the effectiveness were observed within IG in nine IWD who showed positive or neutral trends in at least two physical performance outcomes. Seven participants had positive or neutral trends in the FICSIT-4, seven participants in m30CST, and four and seven participants in 6MWT and TUG, respectively. In conclusion, the InCoPE-App has good nursing assistant-rated usability, whereas training effects and intervention adherence were rather low most likely due to COVID-19 restrictions. Single-subject research revealed more positive than negative trends in IG of IWD. Further research is needed to evaluate feasibility, suitability, and effectiveness of the InCoPE-App.