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.

This review examines disparities in access to urban green space (UGS) based on socioeconomic status (SES) and race-ethnicity in Global South cities. It was motivated by documented human health and ecosystem services benefits of UGS in Global South countries and UGS planning barriers in rapidly urbanizing cities. Additionally, another review of Global North UGS studies uncovered that high-SES and White people have access to a higher quantity of higher quality UGSs than low-SES and racial-ethnic minority people but that no clear differences exist regarding who lives closer to UGS. Thus, we conducted a systematic review to uncover (1) whether UGS inequities in Global North cities are evident in Global South cities and (2) whether inequities in the Global South vary between continents. Through the PRISMA approach and five inclusion criteria, we identified 46 peer-reviewed articles that measured SES or racial-ethnic disparities in access to UGS in Global South cities. We found inequities for UGS quantity (high-SES people are advantaged in 85% of cases) and UGS proximity (74% of cases). Inequities were less consistent for UGS quality (65% of cases). We also found that UGS inequities were consistent across African, Asian, and Latin American cities. These findings suggest that Global South cities experience similar inequities in UGS quantity and quality as Global North cities, but that the former also face inequities in UGS proximity.

Is the amount of “greenness” within a 250-m, 500-m, 1000-m or a 2000-m buffer surrounding a person’s home a good predictor of their physical health? The evidence is inconclusive. We reviewed Web of Science articles that used geographic information system buffer analyses to identify trends between physical health, greenness, and distance within which greenness is measured. Our inclusion criteria were: (1) use of buffers to estimate residential greenness; (2) statistical analyses that calculated significance of the greenness-physical health relationship; and (3) peer-reviewed articles published in English between 2007 and 2017. To capture multiple findings from a single article, we selected our unit of inquiry as the analysis, not the article. Our final sample included 260 analyses in 47 articles. All aspects of the review were in accordance with PRISMA guidelines. Analyses were independently judged as more, less, or least likely to be biased based on the inclusion of objective health measures and income/education controls. We found evidence that larger buffer sizes, up to 2000 m, better predicted physical health than smaller ones. We recommend that future analyses use nested rather than overlapping buffers to evaluate to what extent greenness not immediately around a person’s home (i.e., within 1000–2000 m) predicts physical health.

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Widespread vaccination against COVID-19 is critical for controlling the pandemic. Despite the development of safe and efficacious vaccinations, low-and lower-middle income countries (LMICs) continue to encounter barriers to care owing to inequitable access and vaccine apprehension. This study aimed to summarize the available data on COVID-19 vaccine acceptance rates and factors associated with acceptance in LMICs. A comprehensive search was performed in PubMed, Scopus, and Web of Science from inception through August 2021. Quality assessments of the included studies were carried out using the eight-item Joanna Briggs Institute Critical Appraisal tool for cross-sectional studies. We performed a meta-analysis to estimate pooled acceptance rates with 95% confidence intervals (CI). A total of 36 studies met the inclusion criteria and were included in the review. A total of 83,867 respondents from 33 countries were studied. Most of the studies were conducted in India (n = 9), Egypt (n = 6), Bangladesh (n = 4), or Nigeria (n = 4). The pooled-effect size of the COVID-19 vaccine acceptance rate was 58.5% (95% CI: 46.9, 69.7, I2 = 100%, 33 studies) and the pooled vaccine hesitancy rate was 38.2% (95% CI: 27.2–49.7, I2 = 100%, 32 studies). In country-specific sub-group analyses, India showed the highest rates of vaccine acceptancy (76.7%, 95% CI: 65.8–84.9%, I2= 98%), while Egypt showed the lowest rates of vaccine acceptancy (42.6%, 95% CI: 16.6–73.5%, I2= 98%). Being male and perceiving risk of COVID-19 infection were predictors for willingness to accept the vaccine. Increasing vaccine acceptance rates in the global south should be prioritized to advance global vaccination coverage.