The COVID-19 pandemic and its associated stressors have impacted the daily lives and sleeping patterns of many individuals, including university students. Dreams may provide insight into how the mind processes changing realities; dreams not only allow consolidation of new information, but may give the opportunity to creatively “play out” low-risk, hypothetical threat simulations. While there are studies that analyze dreams in high-stress situations, little is known of how the COVID-19 pandemic has impacted dreams of university students. The aim of this study was to explore how the dream content of students was affected during the university COVID-19 lockdown period (March–July, 2020). Using online survey methods, we analyzed dream recall content (n = 71) using the Hall-Van de Castle dream coding system and Fisher's exact tests for sex comparisons. Preliminary results indicate that female students experienced more nightmares as compared to male students. Dream analysis found that, relative to normative American College Student (ACS) samples generated pre-COVID-19, women were more likely to experience aggressive interactions in their dream content, including increased physical aggression. Results indicate that university students did experience changes in dream content due to the pandemic lockdown period, with women disproportionally affected. These findings can aid universities in developing support programs for students by bringing forth an understanding of students' concerns and anxieties as they process the “new normal” of social distancing.

Background and objectives Sleep is a vulnerable state in which individuals are more susceptible to threat, which may have led to evolved mechanisms for increasing safety. The sentinel hypothesis proposes that brief awakenings during sleep may be a strategy for detecting and responding to environmental threats. Observations of sleep segmentation and group sentinelization in hunter-gatherer and small-scale communities support this hypothesis, but to date it has not been tested in comparisons with industrial populations characterized by more secure sleep environments. Methodology Here, we compare wake after sleep onset (WASO), a quantitative measure of nighttime awakenings, between two nonindustrial and two industrial populations: Hadza hunter-gatherers (n=33), Malagasy small-scale agriculturalists (n=38), and Hispanic (n=1,531) and non-Hispanic White (NHW) (n=347) Americans. We compared nighttime awakenings between these groups using actigraphically-measured sleep data. We fit linear models to assess whether WASO varies across groups, controlling for sex and age. Results We found that WASO varies significantly by group membership, and is highest in Hadza (2.44 hours) and Malagasy (1.93 hours) and lowest in non-Hispanic Whites (0.69 hours). Hispanics demonstrate intermediate WASO (0.86 hours), which is significantly more than NHW participants. After performing supplementary analysis within the Hispanic sample, we found that WASO is significantly and positively associated with increased perception of neighborhood violence. Conclusions and implications Consistent with principles central to evolutionary medicine, we propose that evolved mechanisms to increase vigilance during sleep may now be mismatched with relatively safer environments, and in part responsible for driving poor sleep health.

Sleep duration, quality, and rest-activity pattern—a measure for inferring circadian rhythm—are influenced by multiple factors including access to electricity. Recent findings suggest that the safety and comfort afforded by technology may improve sleep but negatively impact rest-activity stability. According to the circadian entrainment hypothesis, increased access to electric lighting should lead to weaker and less uniform circadian rhythms, measured by stability of rest-activity patterns. Here, we investigate sleep in a Maya community in Guatemala who are in a transitional stage of industrialization. We predicted that (i) sleep will be shorter and less efficient in this population than in industrial settings, and that (ii) rest-activity patterns will be weaker and less stable than in contexts with greater exposure to the natural environment and stronger and more stable than in settings more buffered by technologic infrastructure. Our results were mixed. Compared to more industrialized settings, in our study population sleep was 4.87% less efficient (78.39% vs 83.26%). We found no significant difference in sleep duration. Rest-activity patterns were more uniform and less variable than in industrial settings (interdaily stability = 0.58 vs 0.43; intradaily variability = 0.53 vs 0.60). Our results suggest that industrialization does not inherently reduce characteristics of sleep quality; instead, the safety and comfort afforded by technological development may improve sleep, and an intermediate degree of environmental exposure and technological buffering may support circadian rhythm strength and stability.

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Introduction Menarcheal timing is associated with growth, development, health, wellbeing, and reproduction across the lifespan. Although sexual orientation is a known correlate of health and developmental inequities, relatively little evolutionarily framed research has investigated sexual orientation‐based variation in maturational timing. To improve our understanding of menarcheal timing among sexual minority (SM) people, we use a biocultural‐evolutionary life history lens that takes into account the stresses of minoritization to examine the relationship between sexual orientation and self‐reported age at menarche in a sample of American adults. Methods Using the U.S. National Health and Nutrition Examination Survey (NHANES), a large, nationally representative dataset (n = 9757), we fit multiple logistic regression models and survival curves to evaluate associations between sexual orientation, indicators of somatic and material resources during adolescence (e.g., education, citizenship, upper arm length), and self‐reported menarche. Results SM respondents were more likely to report earlier (by 4–5 months) ages of menarche (p < .001). Post‐hoc tests revealed that these differences were driven by bisexual (p < .001) and same‐sex experienced (p < .001) relative to heterosexual and lesbian/gay respondents. Earlier menarcheal timing among SM respondents persisted after adjusting for socio‐demographic factors and proxies of developmental conditions. Discussion Our findings reveal that SM status is associated with earlier ages of menarche, an important social and reproductive milestone. We argue that uniting life history theory with the minority stress hypothesis better explains differences in menarcheal timing by sexual orientation than previous paradigms. Investigators should attend to sexual orientation‐based variation in maturational timing using holistic, inclusive approaches.