Nicole Bender

Alzheimer's disease (AD) is an important, non‐curable disease today. Several possible risk factors have been discussed, among others sleep. Evolutionary hypotheses were proposed to explain sleep variation and AD risk, such as a potential advantage of short or interrupted sleep in ancient insecure environments, the evolution of increased plasticity of the human brain, or antagonistic pleiotropy with increased AD risk. The aim of this systematic review was to investigate in which way sleep is associated with AD risk, in the light of evolutionary hypotheses. Following PRISMA guidelines, the databases PubMed and Embase were searched for longitudinal observational studies on the association between sleep and incident AD in cognitively healthy people at baseline. Potential confounders were assessed (e.g., age, sex, country, etc.). Search results were deduplicated and assessed for inclusion or exclusion by two independent reviewers. We summarized the results in tables and performed meta‐analyses in risk factor subgroups where appropriate. Out of 5800 studies, 39 were suitable for this review and 35 were meta‐analyzed. Long sleep duration showed a positive association with AD (HR = 1.35, 95% CI = 1.12–1.63) that was not significant after accounting for heterogeneity using prediction intervals (95% CI = 0.74–2.49). Short sleep duration showed a weak, non‐significant association with AD risk (HR = 1.07, 95% CI = 0.98–1.18). Several measures of sleep quality (hypnotics use, daytime sleepiness, bad overall sleep quality, and early bedtime) showed an increased risk for AD, while others (e.g., late bedtime) showed a protective effect. This systematic review showed possible associations between sleep characteristics and the risk for AD. However, several results showed heterogeneity that we could not explain with the information given in the publications. More work is therefore needed to assess the risk factors for AD connected to sleep.

The Sustainable Development Goals (SDGs) were formulated in 2015 by the United Nations to improve human health and achieve sustainable existence at a global level. Failure to reach the SDGs will cause not only increased morbidity and mortality worldwide but also a depletion of natural resources, loss of biodiversity, and irreversible climate warming. Apart from structural and financial barriers, human behavioral reluctance to implement the SDGs is a major challenge. We narratively reviewed and analyzed such behavioral barriers from an evolutionary perspective. One potential explanation of the reluctance to implement the SDGs might be evolved behavioral predispositions that are not consistent with modern, indirectly perceivable threats such as pandemics and climate change. Furthermore, human cooperative behavior did not evolve for long‐term cooperation on a global scale. To improve the implementation of the SDGs, it is necessary to develop strategies that are consistent with evolved human behavioral traits.

Humans adapt their life history strategy and lifestyle behavior to the environment. The social restrictions during the COVID-19 pandemic in the years 2020–2021 led to changes in diet and physical activity habits in large parts of populations worldwide. Additionally, many people reported an increase in body weight during the pandemic. We investigated how diet quality, physical activity, and BMI changed since the end of the COVID-19 restrictions in Switzerland (2019–2023). We assessed diet and physical activity using a standardized questionnaire. We measured anthropometry and BMI using a stadiometer and a balance of a medical bioimpedance analyzer. Our results show a stable BMI in men and women during the pandemic. In both sexes, diet quality and physical activity levels did not change significantly during this time. Among women, physical activity and age were associated with BMI, while in men, apart from physical activity, high diet quality and living in the agglomeration were associated with BMI. Overall, we did not find evidence for a transient “unhealthier” lifestyle immediately after the COVID-19 pandemic. However, we found constituent sex differences in BMI determinants. Our results could indicate a higher resilience in highly educated persons and might contribute to more personalized approaches to prevent obesity.

Background: 3D laser-based photonic scanners are increasingly used in health studies to estimate body composition. However, too little is known about whether various 3D body scan measures estimate body composition better than single standard anthropometric measures, and which body scans best estimate it. Furthermore, little is known about differences by sex and age. Methods: 105 men and 96 women aged between 18 and 90 years were analysed. Bioelectrical Impedance Analysis was used to estimate whole relative fat mass (RFM), visceral adipose tissue (VAT) and skeletal muscle mass index (SMI). An Anthroscan VITUSbodyscan was used to obtain 3D body scans (e.g. volumes, circumferences, lengths). To reduce the number of possible predictors that could predict RFM, VAT and SMI backward elimination was performed. With these selected predictors linear regression on the respective body compositions was performed and the explained variations were compared with models using standard anthropometric measurements (Body Mass Index (BMI), waist circumference (WC) and waist-to-height-ratio (WHtR)). Results: Among the models based on standard anthropometric measures, WC performed better than BMI and WHtR in estimating body composition in men and women. The explained variations in models including body scan variables are consistently higher than those from standard anthropometrics models, with an increase in explained variations between 5% (RFM for men) and 10% (SMI for men). Furthermore, the explained variation of body composition was additionally increased when age and lifestyle variables were added. For each of the body composition variables, the number of predictors differed between men and women, but included mostly volumes and circumferences in the central waist/chest/hip area and the thighs. Conclusions: 3D scan models performed better than standard anthropometric measures models to predict body composition. Therefore, it is an advantage for larger health studies to look at body composition more holistically using 3D full body surface scans.

Virtual teaching tools have gained increasing importance in recent years. In particular, the COVID-19 pandemic has reinforced the need for media-based and self-regulated tools. What is missing are tools that allow us to interlink highly interdisciplinary fields such as evolutionary medicine and, at the same time, allow us to adapt content to different lectures. We designed an interactive online teaching tool, namely, the Mummy Explorer, using open-access software (Google Web Designer), and we provided a freely downloadable template. We tested the tool on students and lecturers of evolutionary medicine using questionnaires and improved the tool according to their feedback. The tool has a modular design and provides an overview of a virtual mummy excavation, including the subfields of paleopathology, paleoradiology, cultural and ethnographic context, provenance studies, paleogenetics, and physiological analyses. The template allows lecturers to generate their own versions of the tool for any topic of interest by simply changing the text and pictures. Tests undertaken with students of evolutionary medicine showed that the tool was helpful during their studies. Lecturers commented that they appreciated having a similar tool in other fields. Mummy Explorer fills a gap in the virtual teaching landscape of highly interdisciplinary fields such as evolutionary medicine. It will be offered for free download and can be adapted to any educational topic. Translations into German and possibly other languages are in progress.

Owing to the coronavirus disease pandemic, the Swiss goverment imposed a shutdown twice in 2020, which may have changed diet and physical activity. Regarding the question of weight change during the pandemic, little information based on measured weight data is available. We aimed to investigate whether the body mass indices (BMIs) of young Swiss men after the two shutdowns in spring and fall 2020 differed from those of young men examined before the shutdowns. We analysed young Swiss men’s BMIs taken during mandatory recruitment for the Swiss Armed Forces at the cross-sectional (not individual longitudinal) monitoring level and across weeks of conscription between January 2010 and July 2021 (n = 373 016). These data allow for continuous health monitoring of young men at almost the population level (coverage, >90%). For statistical modelling, we used the generalized additive model (GAM) framework. We showed that the BMIs of the conscripts examined in the 15 weeks after the two shutdowns in spring and autumn 2020 were not or only slightly different from their baseline values. Sensitivity analyses revealed that this conclusion also holds if the BMI distribution or prevalence of excess weight is assessed. The GAM further showed the significant effects of individual and area-based measures of socioeconomic position and age on BMI. Our results suggest that lifestyle changes during the pandemic in young men might have been too modest to be reflected in body weight. However, longitudinal data and/or data on women, children, or the elderly may lead to different conclusions.