Background University students are increasingly recognized as a vulnerable population, suffering from higher levels of anxiety, depression, substance abuse, and disordered eating compared to the general population. Therefore, when the nature of their educational experience radically changes—such as sheltering in place during the COVID-19 pandemic—the burden on the mental health of this vulnerable population is amplified. The objectives of this study are to 1) identify the array of psychological impacts COVID-19 has on students, 2) develop profiles to characterize students' anticipated levels of psychological impact during the pandemic, and 3) evaluate potential sociodemographic, lifestyle-related, and awareness of people infected with COVID-19 risk factors that could make students more likely to experience these impacts. Methods Cross-sectional data were collected through web-based questionnaires from seven U.S. universities. Representative and convenience sampling was used to invite students to complete the questionnaires in mid-March to early-May 2020, when most coronavirus-related sheltering in place orders were in effect. We received 2,534 completed responses, of which 61% were from women, 79% from non-Hispanic Whites, and 20% from graduate students. Results Exploratory factor analysis on close-ended responses resulted in two latent constructs, which we used to identify profiles of students with latent profile analysis, including high (45% of sample), moderate (40%), and low (14%) levels of psychological impact. Bivariate associations showed students who were women, were non-Hispanic Asian, in fair/poor health, of below-average relative family income, or who knew someone infected with COVID-19 experienced higher levels of psychological impact. Students who were non-Hispanic White, above-average social class, spent at least two hours outside, or less than eight hours on electronic screens were likely to experience lower levels of psychological impact. Multivariate modeling (mixed-effects logistic regression) showed that being a woman, having fair/poor general health status, being 18 to 24 years old, spending 8 or more hours on screens daily, and knowing someone infected predicted higher levels of psychological impact when risk factors were considered simultaneously. Conclusion Inadequate efforts to recognize and address college students’ mental health challenges, especially during a pandemic, could have long-term consequences on their health and education.

Abstract:Tracking the environmental impacts of production, use, and disposal of products (e.g., goods, and services) have been an important issue in the global economy. Although Life Cycle Assessment (LCA) is a widely applied method to track these environmental impacts and support policies, it has certain limitations and an isolated way of evaluating the environmental impacts with no consideration of social and economic impacts and mechanisms. To overcome the limits of current LCA, three mechanisms have been proposed in the literature: (1) broadening the indicators by including social and economic indicators in addition to the environmental impacts; (2) broadening the scope of analysis from product-level assessment to national and global levels; (3) deepening the assessment by inclusion of more mechanisms to account for interrelations among the system elements, uncertainty analysis, stakeholder involvement, etc. With these developments, LCA has been evolving into a new framework called Life Cycle Sustainability Assessment (LCSA). Practical application of LCSA requires integration of various methods, tools, and disciplines. In this study, a comprehensive literature review is conducted to investigate recent developments, current challenges, and future perspectives in the LCSA literature. According to the review, a high number (40%) of LCSA studies are from the environmental science discipline, while contributions from other disciplines such as economics (3%) and social sciences (9%) are very low. On broadening the scope of analysis, 58% of the studies are product-level works, while 37% quantified the impacts at national level and achieved an economy-wide analysis, and only 5% of the studies were able to quantify the global impacts of products using LCSA framework. Furthermore, current applications of LCSA have not considered the rebound effects, feedback mechanisms, and interrelations of the system of interest sufficiently. To address these challenges, we present a complete discussion about the overarching role of systems thinking to bring tools, methods and disciplines together, and provide practical examples from the earlier studies that have employed various system-based methods. We discuss the importance of integrated system-based methods for advancement of LCSA framework in the following directions: (1) regional and global level LCSA models using multi-region input-output analysis that is capable of quantitatively capturing macro-level social, environmental, and economic impacts; (2) dealing with uncertainties in LCSA during multi-criteria decision-making process and expert judgments in weighting of LCSA indicators; and (3) integration of system dynamics modeling to reveal complex interconnections, dependencies, and causal relationships between sustainability indicators.

Sustainable development efforts in urban areas often focus on understanding and managing factors that influence all aspects of health and wellbeing. Research has shown that public parks and green space provide a variety of physical, psychological, and social benefits to urban residents, but few studies have examined the influence of parks on comprehensive measures of subjective wellbeing at the city level. Using 2014 data from 44 U.S. cities, we evaluated the relationship between urban park quantity, quality, and accessibility and aggregate self-reported scores on the Gallup-Healthways Wellbeing Index (WBI), which considers five different domains of wellbeing (e.g., physical, community, social, financial, and purpose). In addition to park-related variables, our best-fitting OLS regression models selected using an information theory approach controlled for a variety of other typical geographic and socio-demographic correlates of wellbeing. Park quantity (measured as the percentage of city area covered by public parks) was among the strongest predictors of overall wellbeing, and the strength of this relationship appeared to be driven by parks’ contributions to physical and community wellbeing. Park quality (measured as per capita spending on parks) and accessibility (measured as the overall percentage of a city’s population within ½ mile of parks) were also positively associated with wellbeing, though these relationships were not significant. Results suggest that expansive park networks are linked to multiple aspects of health and wellbeing in cities and positively impact urban quality of life.

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