Time spent in physical activity, sedentary behavior, and sleep:Associations with self-rated sleep quality in middle-aged and older adults

Objectives: We examined the associations of estimated allocations of time spent in physical activity, sedentary behavior and sleep with self-rated sleep quality. Methods: Between 2011 and 2016, 1918 participants (mean age 71 ± 9 years, 51% women) from the population-based Rotterdam Study were included. Durations of light physical activity, moderate-to-vigorous physical activity, sedentary behavior, and sleep were assessed by accelerometry, self-rated sleep quality with the Pittsburgh Sleep Quality Index. Associations were assessed with compositional isotemporal substitution analyses. Results: Spending 30 minutes more in sedentary behavior (adjusted mean difference in PSQI score: 0.21, 95% confidence interval [0.15; 0.28] or in light physical activity (adjusted mean difference in PSQI score: 0.25 [0.03; 0.46], and 30 minutes less in sleep, was associated with poorer sleep quality. Conclusions: Our findings suggest reducing sedentary behavior and increasing sleep duration might be a potential intervention target to improve sleep quality in this population of middle-aged and older adults.</p

The bidirectional relationship between brain structure and physical activity:A longitudinal analysis in the UK Biobank

Physical activity is a protective factor against brain atrophy, while loss of brain volume could also be a determinant of physical activity. Therefore, we aimed to explore the bidirectional association of physical activity with brain structures in middle-aged and older adults from the UK Biobank. Overall, 3027 participants (62.45 ± 7.27 years old, 51.3% females) had data at two time points. Hippocampal volume was associated with total (β=0.048, pFDR=0.016) and household (β=0.075, pFDR&lt;0.001) physical activity. Global fractional anisotropy (β=0.042, pFDR=0.028) was also associated with household physical activity. In the opposite direction, walking was negatively associated with white matter volume (β=-0.026, pFDR=0.008). All these associations were confirmed by the linear mixed models. Interestingly, sports at baseline were linked to hippocampal and frontal cortex volumes at follow-up but these associations disappeared after adjusting for multiple comparisons (pall&gt;0.104). In conclusion, we found more consistent evidence that a healthier brain structure predicted higher physical activity levels than for the inverse, more established relationship.</p

Mechanisms Linking Physical Activity with Psychiatric Symptoms Across the Lifespan:A Systematic Review

Background: Physical activity has been suggested as a protective factor against psychiatric symptoms. While numerous studies have focused on the magnitude of physical activity’s effect on psychiatric symptoms, few have examined the potential mechanisms. Objective: The current review aimed to synthesize scientific evidence of the mechanisms through which physical activity might reduce psychiatric symptoms across the lifespan. Methods: We included articles that were published before March 2022 from five electronic databases (MEDLINE, Web of Science, PsycINFO, Embase, and Cochrane). A qualitative synthesis of studies was conducted. The risk of bias assessment was performed using The Joanna Briggs Institute Critical Appraisal Tool for Systematic Reviews. Studies were included if they explored the possible mechanisms through which physical activity influences psychiatric symptoms (i.e., internalizing and externalizing symptoms) across the lifespan. Results: A total of 22 articles were included (three randomized controlled trials, four non-randomized controlled trials, three prospective longitudinal studies, and 12 cross-sectional studies). Overall, most of the studies focused on children, adolescents, and young adults. Our findings showed that self-esteem, self-concept, and self-efficacy were the only consistent paths through which physical activity influences psychiatric symptoms (specifically depressive and anxiety symptoms) across the lifespan. There were insufficient studies to determine the role of neurobiological mechanisms. Conclusions: Overall, future physical activity interventions with the purpose of improving mental health should consider these mechanisms (self-esteem, self-concept, self-efficacy) to develop more effective interventions. Clinical Trial Registration: The protocol of this study was registered in the PROSPERO database (registration number CRD42021239440) and published in April 2022.</p

Mechanisms linking physical activity with psychiatric symptoms across the lifespan:A protocol for a systematic review

INTRODUCTION: Persistent psychiatric symptomatology during childhood and adolescence predicts vulnerability to experience mental illness in adulthood. Physical activity is well-known to provide mental health benefits across the lifespan. However, the underlying mechanisms linking physical activity and psychiatric symptoms remain underexplored. In this context, we aim to systematically synthesise evidence focused on the mechanisms through which physical activity might reduce psychiatric symptoms across all ages. METHODS AND ANALYSIS: With the aid of a biomedical information specialist, we will develop a systematic search strategy based on the predetermined research question in the following electronic databases: MEDLINE, Embase, Web of Science, Cochrane and PsycINFO. Two independent reviewers will screen and select studies, extract data and assess the risk of bias. In case of inability to reach a consensus, a third person will be consulted. We will not apply any language restriction, and we will perform a qualitative synthesis of our findings as we anticipate that studies are scarce and heterogeneous. ETHICS AND DISSEMINATION: Only data that have already been published will be included. Then, ethical approval is not required. Findings will be published in a peer-reviewed journal and presented at conferences. Additionally, we will communicate our findings to healthcare providers and other sections of society (eg, through regular channels, including social media). PROSPERO REGISTRATION NUMBER: CRD42021239440

Proteomic evidence of dietary sources in ancient dental calculus.

Archaeological dental calculus has emerged as a rich source of ancient biomolecules, including proteins. Previous analyses of proteins extracted from ancient dental calculus revealed the presence of the dietary milk protein β-lactoglobulin, providing direct evidence of dairy consumption in the archaeological record. However, the potential for calculus to preserve other food-related proteins has not yet been systematically explored. Here we analyse shotgun metaproteomic data from 100 archaeological dental calculus samples ranging from the Iron Age to the post-medieval period (eighth century BC to nineteenth century AD) in England, as well as 14 dental calculus samples from contemporary dental patients and recently deceased individuals, to characterize the range and extent of dietary proteins preserved in dental calculus. In addition to milk proteins, we detect proteomic evidence of foodstuffs such as cereals and plant products, as well as the digestive enzyme salivary amylase. We discuss the importance of optimized protein extraction methods, data analysis approaches and authentication strategies in the identification of dietary proteins from archaeological dental calculus. This study demonstrates that proteomic approaches can robustly identify foodstuffs in the archaeological record that are typically under-represented due to their poor macroscopic preservation

Implications of COVID-19 control measures for diet and physical activity, and lessons for addressing other pandemics facing rapidly urbanising countries.

At the time of writing, it is unclear how the COVID-19 pandemic will play out in rapidly urbanising regions of the world. In these regions, the realities of large overcrowded informal settlements, a high burden of infectious and non-communicable diseases, as well as malnutrition and precarity of livelihoods, have raised added concerns about the potential impact of the COVID-19 pandemic in these contexts. COVID-19 infection control measures have been shown to have some effects in slowing down the progress of the pandemic, effectively buying time to prepare the healthcare system. However, there has been less of a focus on the indirect impacts of these measures on health behaviours and the consequent health risks, particularly in the most vulnerable. In this current debate piece, focusing on two of the four risk factors that contribute to >80% of the NCD burden, we consider the possible ways that the restrictions put in place to control the pandemic, have the potential to impact on dietary and physical activity behaviours and their determinants. By considering mitigation responses implemented by governments in several LMIC cities, we identify key lessons that highlight the potential of economic, political, food and built environment sectors, mobilised during the pandemic, to retain health as a priority beyond the context of pandemic response. Such whole-of society approaches are feasible and necessary to support equitable healthy eating and active living required to address other epidemics and to lower the baseline need for healthcare in the long term

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Genetic Risk Score for Intracranial Aneurysms:Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

BACKGROUND: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. METHODS: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. RESULTS: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=-4.82×10(-3) per year [95% CI, -6.49×10(-3) to -3.14×10(-3)]; P=1.82×10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). CONCLUSIONS: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH

The complex genetics of gait speed:Genome-wide meta-analysis approach

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging