A pilot study exploring the relationship between urban greenspace accessibility and mental health prevalence in the City of San Diego in the context of socioeconomic and demographic factors

The connection between urban greenspace and mental health is a robust but unsettled area of research in the public health and urban planning literatures. Inconsistent findings in prior studies are mostly due to differences in greenspace measurements and interrelations with socio-demographic factors. This study examines the relationships of mental health prevalence (MHP) with health prevention, socioeconomic and race-ethnicity factors, and proximity to greenspace at the census-tract level in the City of San Diego, California, using data from the CDC 500 Cities Project and US Census Bureau. We considered three greenspace proximity measures: distances to specified vegetation types, parks, and tree cover. Spear-man’s rank correlation showed that MHP was significantly correlated to distances to greenspace (rho = 0.480), parks (rho = 0.234), and tree cover (rho = 0.342), and greenspace proximity plus crime occurrence explained 37.8% of the variance in MHP in regression analysis. Further analysis revealed that socioeconomic status, race-ethnicity, and health prevention explained more than 93% of the variance in MHP, while greenspace proximity did not enter the regression model with statistical significance. We discovered that certain socioeconomic and race-ethnicity variables, such as proportion of Hispanic population, poverty, and regular checkup, may fully represent the effects of greenspace on MHP in the City of San Diego. Regression analysis for three subsections of the city suggested that different predictors of MHP should be considered in formulating intervention measures. Our results indicate the need to improve mental health conditions through a range of interventions that address the disparities experienced by racial-ethnic minorities and those in lower-socioeconomic classes.

Exploring the role of City Networks in supporting urban resilience to COVID-19 in conflict-affected settings

Background: It is estimated that by 2050, almost 70 percent of the global population will be residing in urban areas. In recent years, cities have become central in tackling key urban challenges and have demonstrated greater flexibility in policymaking and innovation than national governments. Cities are currently more inclined to learn from each other via networks, partnerships, and pairings to develop solutions to many global challenges including pandemics such as COVID-19. Aim: To explore the role cities and city networks present in supporting urban resilience to pandemics focusing on conflict-affected settings. Methods: A desk-based literature review of academic and grey sources was conducted followed by thematic analysis. Results: Although most COVID-19 response plans have been developed and implemented by governments, the pandemic has revealed the significant potential for city networks in providing platforms for knowledge sharing and coordination of mitigation plans to address pandemic-specific interventions. We found that in conflict settings, city networks continue to play only a minor role, if any, compared to humanitarian and informal actors. Conclusion: City networks have the potential to contribute to strengthening global collaborative approaches to pandemic responses, but this has not been given sufficient investment and even less so in conflict-affected settings. It is essential for these networks to be integrated within a wider multidisciplinary and multisectoral platform that includes academics, humanitarian and informal actors.

Structural equation modeling of mental health in gentrifying neighborhoods in Austin, Texas

Having poor mental health can be life-threatening, and problems tied to it are prevalent in communities across the United States (US). The city of Austin is one of the ten cities in the US undergoing rapid urban gentrification; however, there is insufficient empirical evidence on the impact of this process on residents’ health. Consequently, this study explored the concept of weathering and life course perspective using data of 331 residents recruited from two regions endemic with gentrification to assess the health impacts of gentrification. We used a triangulation method including univariate, bivariate correlation, and multiple linear regression implemented through the structural equation model to examine the complex pathways to three health outcomes—measured stress, self-rated mental health, and depression symptoms. Bivariate Pearson’s correlation indicated a significant positive association between gentrification score and mental health symptoms and stress. However, the direct association between gentrification and depression disappeared in the causal/path model. In support of the weathering hypothesis, this study found that stress score was directly related to the adulthood depression score. Therefore, this research builds on the accumulating evidence of environmental stress and mental health in the US’s rapidly changing physical and sociocultural environment. Hence, implementing and guaranteeing social equity of resources will improve residents’ health and reduce the cost of health care spending at both the household level and the city government level.

COVID-19 and the 1918 influenza pandemics: a concise overview and lessons from the past

The coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first reported in December, 2019, in Wuhan, China. Even the public health sector experts could not anticipate that the virus would spread rapidly to create the worst worldwide crisis in more than a century. The World Health Organization (WHO) declared COVID-19 a public health emergency on January 30, 2020, but it was not until March 11, 2020 that the WHO declared it a global pandemic. The epidemiology of SARS-CoV-2 is different from the SARS coronavirus outbreak in 2002 and the Middle East Respiratory Syndrome (MERS) in 2012; therefore, neither SARS nor MERS could be used as a suitable model for foreseeing the future of the current pandemic. The influenza pandemic of 1918 could be referred to in order to understand and control the COVID-19 pandemic. Although influenza and the SARS-CoV-2 are from different families of viruses, they are similar in that both silently attacked the world and the societal and political responses to both pandemics have been very much alike. Previously, the 1918 influenza pandemic and unpredictability of the second wave caused distress among people as the first wave of that outbreak (so-called Spanish flu) proved to be relatively mild compared to a much worse second wave, followed by smaller waves. As of April, 2021, the second wave of COVID-19 has occurred around the globe, and future waves may also be expected, if the total population of the world is not vaccinated. This article aims to highlight the key similarities and differences in both pandemics. Similarly, lessons from the previous pan-demics and various possibilities for the future course of COVID-19 are also highlighted.

Fighting COVID-19 in Freetown, Sierra Leone: the critical role of community organisations in a growing pandemic

As the COVID-19 pandemic spreads in Africa, attention is increasingly shifting to the potential and ongoing impact on informal settlements, which face considerable challenges around the implementation of conventional control measures of social distancing, hand washing and self-isolation. In Freetown, Sierra Leone, residents of informal settlements have relied on local community organisations and groups, and their resourcefulness to provide essential preparedness, response and on-going support to alleviate the public health and economic risks associated with the effects of the COVID-19 outbreak. This is also premised on lessons drawn from dealing with previous epidemics, notably the Ebola virus disease in 2014–2015.This paper will explain the nature and form of community organisation that can be galvanised and leveraged for COVID-19 preparedness and responses that are suited for informal settlements. Secondly, it highlights the critical contribution of community organisations in social protection measures that tackle deeply entrenched inequalities in rapidly urbanising contexts. Finally, the cases examined seek to provide evidence of the value of processes of continuous learning within community organisation that are essential for both humanitarian assistance and emergency management. Although situated in Freetown, the broad lessons drawn are relevant for urban-poor communities and informal settlements in many urban African centres.

Mask material: challenges and virucidal properties as an effective solution against coronavirus SARS-CoV-2

COVID-19 viruses are primarily transmitted between people via respiratory droplets generated from an infected person while coughing, sneezing, exhaling or close contact. Hence, the use of masks are part of prevention and control measures to limit the spread of COVID-19. A comprehensive study on various materials used in masks is required. The filtration efficiency of cotton masks increases with increase in thread count and number of layers, but breathability is affected and therefore a risk for longer durations. Cotton-based masks have filtration efficiency ranging from 5% to 80% depending on the number of layers. Combinations of different hybrid fabric materials and design have an efficiency ranging from 37% to 97%. Bio-cellulose, which is derived from cellulosic biomass by synthesis techniques involving various physical and chemical processes followed by refining techniques, possesses remarkable properties including biodegradability, biocompatibility, low toxicity, etc., making it the most suitable mask material. Masks made of bio-cellulose have an important property of hydrophilicity which makes it adhere to the face tightly, giving a cooling effect to the face. Use of nanocellulose masks can help attaining filtration efficiency up to 99.9980–99.9995% along with other desirable properties. Hence, there is an immediate need to address the issues and challenges of mask materials and work towards the design and development of low cost masks to overcome these shortcomings by the researchers and manufacturers.

Social context affects mental health stigma

Prior research shows mental health stigma is context-dependent and blocks help-seeking behaviors. Any applied solutions will require basic research to understand these contextual nuances. The present paper presents two timed Likert-type rating studies in which participants scored photographs of individuals with mental health diagnoses and other control condition labels in different social contexts. In the first study (N = 99), participants rated the individuals in a professional context and in a non-professional context. The second study (N = 99) systematically manipulated the attractiveness of the individuals depicted. Professional context moderated mental health stigma, indicating that, relative to control label conditions, participants were less accepting of an individual with a mental health diagnosis label as a medical clinician than as a next-door neighbor. Attractiveness had a uniform effect across all the label conditions, which produced a compounding additive effect in which a mental health diagnosis and low attractiveness negatively impacted the ratings simultaneously. The study used timed implicit judgments to demonstrate empirically how previously unstudied social contexts can affect mental health stigma. Understanding how such contextual effects affect stigma is a prerequisite for the development of interventions to overcome the barriers stigma creates for access to treatment and prevention.

Depression among patients admitted to medical wards: comparison between a university hospital and regional hospital

Objective: We aimed to determine the prevalence of depression and to find factors associated with depression in admitted medical patients. The differences in the pattern of depression between a university hospital (UH) and a regional hospital (RH) were determined as well.Methods: This is a cross-sectional study. The Patient Health Questionnaire-9 (PHQ-9) was administered among hospitalized patients in medical wards. PHQ-9 could not differentiate between the type of depressive disorder that could be from medical conditions, adjustment disorder with depressed mood, major depressive disorder, or dysthymia.Results: A total of 343 patients (191 in UH, 152 in RH group) with age of 52.1 ± 16.9 years were included. Timing of interview was 4.3 ± 1.4 days after admission. The prevalence of depression (PHQ-9 score ≥ 9) was 12% (7.3% in UH vs 17.8% in RH, p < 0.005). According to PHQ-9 scoring, the prevalence of moderate-to-severe depression was 3.8%. Mean PHQ-9 score in RH was significantly higher than in UH (p < 0.001). Multiple baseline characteristics were analyzed by logistic regression and found no factors associated with depression. There was no difference in baseline characteristics of UH patients with depression compared to RH, except for universal health coverage plan.Conclusions: The prevalence of depression was 1 in 10 patients and was found to be more frequent and severe in RH than UH. All patients were at equal risk to develop depression during admission.

Expressing the quantity of urinary analytes: a discussion of some issues arising from the monitoring of the menstrual cycle

Practical domestic monitoring of the menstrual cycle requires measurements of urinary metabolites of reproductive hormones: oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG). Data reported in the literature are expressed as (i) concentration, without or with either creatinine- or specific gravity correction, or (ii) excretion rates. This variation in such a fundamental issue prompts consideration of the relationships between the four measures. Because the menstrual cycle kinetics of E1G and PdG are complex, we consider measurements of urinary creatinine, urea, galactose, xylose and inulin which tend to be more stable. We show that uncorrected concentration measurements of these urinary analytes can be positively correlated, negatively correlated or uncorrelated with the serum concentration. Based on measurements of urinary creatinine concentrations, urinary specific gravity and creatinine excretion rates, we conclude that urinary analyte concentration are likely to be more reliable when creatinine-corrected rather than corrected using specific gravity, but that both are less reliable than measurements of the excretion rate. This has implications for the quantitation of any urinary analyte, but especially for the monitoring of the menstrual cycle in which changes in E1G and PdG from one day to the next can be physiologically significant for a woman monitoring her fertility.