Examining the mental health impacts of climate change on young people in Canada: a national cross-sectional survey.

BACKGROUND: Climate change poses a substantial threat to the mental wellbeing of young people. Population-level research is urgently needed to help inform policies and interventions to ensure that young people are not burdened by long-term mental health impacts from climate change. We sought to identify the prevalence, distribution, and factors associated with climate change-related mental and emotional health outcomes among young people (aged 13-34 years) in Canada. METHODS: This study is part of a larger cross-sectional survey, which examined mental and emotional health responses to climate change among individuals aged 13 years or older from across Canada. We used a multi-stage, multi-stratified random probability sampling procedure. Participants were randomly recruited through either an addressed letter or a telephone call. Online and telephone questionnaires were used to interview individuals in English, French, or Inuktitut between April 1, 2022, and March 31, 2023. Data were weighted by age and province using population estimates from Statistics Canada and analysed using descriptive statistics, factor analyses, and multivariable regression analyses. FINDINGS: The full survey included 2476 participants, with a subgroup of 409 young people. Of the 401 respondents who provided their gender identity, 215 (54%) identified as cisgender women, 167 (42%) identified as cisgender men, and 19 (5%) identified as non-binary. Preliminary results suggest that young people in Canada experience a wide range of climate-related emotional and mental health outcomes. More than 70% of respondents in the young people subgroup reported having at least mild levels of sadness, anger, worry, anxiety, concern, helplessness, hopelessness, or powerlessness related to climate change. The severity of climate-related emotional responses differed by gender, with non-binary respondents and cisgender women reporting higher average levels of distress than cisgender men. Regional differences were also observed, with northern regions and urban locations reporting more severe reactions. INTERPRETATION: This study builds on the understanding of the burden of climate change on the mental health of young people. If unaddressed, the impact of this burden could have long-standing and wide-reaching public health and related socioeconomic effects. FUNDING: Canadian Institutes of Health Research, ArcticNet, Social Sciences and Humanities Research Council Doctoral Fellowship, Izaak Walton Killam Memorial Scholarship, and Alberta Innovates Graduate Student Scholarship.

A systematic review of ambient heat and sleep in a warming climate.

Climate change is elevating nighttime and daytime temperatures worldwide, affecting a broad continuum of behavioral and health outcomes. Disturbed sleep is a plausible pathway linking rising ambient temperatures with several observed adverse human responses shown to increase during hot weather. This systematic review aims to provide a comprehensive overview of the literature investigating the relationship between ambient temperature and valid sleep outcomes measured in real-world settings, globally. We show that higher outdoor or indoor temperatures are generally associated with degraded sleep quality and quantity worldwide. The negative effect of heat persists across sleep measures, and is stronger during the hottest months and days, in vulnerable populations, and the warmest regions. Although we identify opportunities to strengthen the state of the science, limited evidence of fast sleep adaptation to heat suggests rising temperatures induced by climate change and urbanization pose a planetary threat to human sleep, and therefore health, performance, and wellbeing.

Estimating climate change and mental health impacts in Canada: A cross-sectional survey protocol.

Climate change has severe and sweeping impacts on mental health. Although research is burgeoning on mental health impacts following climate and weather extremes, less is known about how common these impacts are outside of extreme events. Existing research exploring the prevalence of psychosocial responses to climate change primarily examines university students and uses non-random sampling methods. Herein, our protocol outlines an approach to data collection, processing, and analysis to estimate the population prevalence, magnitude, and distribution of mental health responses to climate change in Canada. A cross-sectional survey of youth and adults aged 13 years and older in Canada will be administered over the course of one year. The questionnaire will take approximately 10 minutes to complete orally and will be administered in English, French, and Inuktitut. The survey will consist of six sections: (1) self-reported past experiences of climate change; (2) self-reported climate-related emotions; (3) self-reported past and current impacts, anticipatory impacts, and vicarious experiences; (4) self-reported subclinical outcomes; (5) self-reported behavioural responses; and (6) demographics. A multi-stage, multi-stratified random probability sampling method will be used to obtain a sample representative of the Canadian population. We will use two different modes of recruitment: an addressed letter sent by postal mail or a telephone call (landlines and cellular). Population-weighted descriptive statistics, principal component analysis, and weighted multivariable regression will be used to analyse the data. The results of this survey will provide the first national prevalence estimates of subclinical mental health responses to climate change outcomes of people living in Canada.

The global human day.

The daily activities of ≈8 billion people occupy exactly 24 h per day, placing a strict physical limit on what changes can be achieved in the world. These activities form the basis of human behavior, and because of the global integration of societies and economies, many of these activities interact across national borders. Yet, there is no comprehensive overview of how the finite resource of time is allocated at the global scale. Here, we estimate how all humans spend their time using a generalized, physical outcome-based categorization that facilitates the integration of data from hundreds of diverse datasets. Our compilation shows that most waking hours are spent on activities intended to achieve direct outcomes for human minds and bodies (9.4 h/d), while 3.4 h/d are spent modifying our inhabited environments and the world beyond. The remaining 2.1 h/d are devoted to organizing social processes and transportation. We distinguish activities that vary strongly with GDP per capita, including the time allocated to food provision and infrastructure, vs. those that do not vary consistently, such as meals and transportation time. Globally, the time spent directly extracting materials and energy from the Earth system is small, on the order of 5 min per average human day, while the time directly dealing with waste is on the order of 1 min per day, suggesting a large potential scope to modify the allocation of time to these activities. Our results provide a baseline quantification of the temporal composition of global human life that can be expanded and applied to multiple fields of research.

Climate Change and Substance-Use Behaviors: A Risk-Pathways Framework.

Climate change is undermining the mental and physical health of global populations, but the question of how it is affecting substance-use behaviors has not been systematically examined. In this narrative synthesis, we find that climate change could increase harmful substance use worldwide through at least five pathways: psychosocial stress arising from the destabilization of social, environmental, economic, and geopolitical support systems; increased rates of mental disorders; increased physical-health burden; incremental harmful changes to established behavior patterns; and worry about the dangers of unchecked climate change. These pathways could operate independently, additively, interactively, and cumulatively to increase substance-use vulnerability. Young people face disproportionate risks because of their high vulnerability to mental-health problems and substance-use disorders and greater number of life years ahead in which to be exposed to current and worsening climate change. We suggest that systems thinking and developmental life-course approaches provide practical frameworks for conceptualizing this relationship. Further conceptual, methodological, and empirical work is urgently needed to evaluate the nature and scope of this burden so that effective adaptive and preventive action can be taken.

Gender differences in nighttime sleep patterns and variability across the adult lifespan: a global-scale wearables study.

STUDY OBJECTIVES: Previous research on sleep patterns across the lifespan have largely been limited to self-report measures and constrained to certain geographic regions. Using a global sleep dataset of in situ observations from wearable activity trackers, we examine how sleep duration, timing, misalignment, and variability develop with age and vary by gender and BMI for nonshift workers. METHODS: We analyze 11.14 million nights from 69,650 adult nonshift workers aged 19-67 from 47 countries. We use mixed effects models to examine age-related trends in naturalistic sleep patterns and assess gender and BMI differences in these trends while controlling for user and country-level variation. RESULTS: Our results confirm that sleep duration decreases, the prevalence of nighttime awakenings increases, while sleep onset and offset advance to become earlier with age. Although men tend to sleep less than women across the lifespan, nighttime awakenings are more prevalent for women, with the greatest disparity found from early to middle adulthood, a life stage associated with child-rearing. Sleep onset and duration variability are nearly fixed across the lifespan with higher values on weekends than weekdays. Sleep offset variability declines relatively rapidly through early adulthood until age 35-39, then plateaus on weekdays, but continues to decrease on weekends. The weekend-weekday contrast in sleep patterns changes as people age with small to negligible differences between genders. CONCLUSIONS: A massive dataset generated by pervasive consumer wearable devices confirms age-related changes in sleep and affirms that there are both persistent and life-stage dependent differences in sleep patterns between genders.

The Negative Effect of Smartphone Use on Academic Performance May Be Overestimated: Evidence From a 2-Year Panel Study.

In this study, we monitored 470 university students' smartphone usage continuously over 2 years to assess the relationship between in-class smartphone use and academic performance. We used a novel data set in which smartphone use and grades were recorded across multiple courses, allowing us to examine this relationship at the student level and the student-in-course level. In accordance with the existing literature, our results showed that students' in-class smartphone use was negatively associated with their grades, even when we controlled for a broad range of observed student characteristics. However, the magnitude of the association decreased substantially in a fixed-effects model, which leveraged the panel structure of the data to control for all stable student and course characteristics, including those not observed by researchers. This suggests that the size of the effect of smartphone usage on academic performance has been overestimated in studies that controlled for only observed student characteristics.

Inferring transportation mode from smartphone sensors: Evaluating the potential of Wi-Fi and Bluetooth.

Understanding which transportation modes people use is critical for smart cities and planners to better serve their citizens. We show that using information from pervasive Wi-Fi access points and Bluetooth devices can enhance GPS and geographic information to improve transportation detection on smartphones. Wi-Fi information also improves the identification of transportation mode and helps conserve battery since it is already collected by most mobile phones. Our approach uses a machine learning approach to determine the mode from pre-prepocessed data. This approach yields an overall accuracy of 89% and average F1 score of 83% for inferring the three grouped modes of self-powered, car-based, and public transportation. When broken out by individual modes, Wi-Fi features improve detection accuracy of bus trips, train travel, and driving compared to GPS features alone and can substitute for GIS features without decreasing performance. Our results suggest that Wi-Fi and Bluetooth can be useful in urban transportation research, for example by improving mobile travel surveys and urban sensing applications.