Notes

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Only a small proportion of homeless individuals reported fear of COVID-19 in mid-2021 in Germany. Such knowledge about the correlates of higher levels of fear of COVID-19 may be helpful for addressing certain risk groups (e.g., homeless individuals aged 50-64 years). In a further step, avoiding extraordinarily high levels of fear of COVID-19 may be beneficial to avoid irrational thinking and acting regarding COVID-19 in this group.
Only a small proportion of homeless individuals reported fear of COVID-19 in mid-2021 in Germany. Such knowledge about the correlates of higher levels of fear of COVID-19 may be helpful for addressing certain risk groups (e.g., homeless individuals aged 50-64 years). In a further step, avoiding extraordinarily high levels of fear of COVID-19 may be beneficial to avoid irrational thinking and acting regarding COVID-19 in this group.Amidst the COVID-19 vaccination, Twitter is one of the most popular platforms for discussions about the COVID-19 vaccination. These types of discussions most times lead to a compromise of public confidence toward the vaccine. The text-based data generated by these discussions are used by researchers to extract topics and perform sentiment analysis at the provincial, country, or continent level without considering the local communities. The aim of this study is to use clustered geo-tagged Twitter posts to inform city-level variations in sentiments toward COVID-19 vaccine-related topics in the three largest South African cities (Cape Town, Durban, and Johannesburg). VADER, an NLP pre-trained model was used to label the Twitter posts according to their sentiments with their associated intensity scores. The outputs were validated using NB (0.68), LR (0.75), SVMs (0.70), DT (0.62), and KNN (0.56) machine learning classification algorithms. The number of new COVID-19 cases significantly positively correlated with tts can be used to better analyse the dynamics in sentiments toward community-based infectious diseases-related discussions, such as COVID-19, Malaria, or Monkeypox. This can provide additional city-level information to health policy in planning and decision-making regarding vaccine hesitancy for future outbreaks.
Currently, longitudinal studies on frailty are in an early stage, particularly in low- and middle-income countries. Only one study was conducted in Hong Kong to examine age-period-cohort effects on the prevalence of frailty among Chinese older adults.

This study aims to shed light on the prevalence trajectory of frailty among older adults in mainland China through the APC model and to analyze the effects of age, period, and cohort on the prevalence trajectory.

The sample for this study was older adults aged 65-109 years old from the 2002 to 2014 Chinese Longitudinal Healthy Longevity Survey (CLHLS). Frailty status was measured by Rockwood FI. An age-period-cohort model was used to describe the effects of age, period, and cohort on the prevalence trajectory of frailty.

The prevalence of frailty among Chinese older adults changed significantly with age, period, and cohort. Furthermore, the effect of age was much stronger than the effect of period and cohort. The prevalence of frailty in the 101-103 and 104-106 age groups was 8.998 (95% CI 13.667-5.924) and 8.699 (95% CI 13.037-5.805) times higher than the in the 65-67 age group, respectively. The sensitivity analysis based on Fried's frailty phenotype showed similar results, confirming the robustness of our findings.

All of the age effect reflecting the individual aging process, period effect reflecting change in the social environment, and birth cohort effect reflecting different generations could influence the prevalence of frailty at the population level. In contrast, the age effect was the main effect.
All of the age effect reflecting the individual aging process, period effect reflecting change in the social environment, and birth cohort effect reflecting different generations could influence the prevalence of frailty at the population level. In contrast, the age effect was the main effect.
The American Indian/Alaska Native (AI/AN) population in the U.S. is thriving in spite of settler colonialist efforts of erasure. AI/AN people, however, continue to experience persistent health disparities including a disproportionate burden of substance use and sexually transmitted diseases/infections (STDs/STIs), as well as a disproportionate lack of public health STD screening services and STD prevention interventions grounded in AI/AN social contexts, experiences, and epistemologies. The present study explored how stressors and protective factors based on the Indigenist Stress Coping framework predict STD screening outcomes among Native adults.

We analyzed baseline self-report data from 254 Native adults ages 18-55 years with recent binge substance use who were enrolled in an evaluation of "EMPWR," a two-session STD risk reduction program in a rural, reservation-based community in the U.S. Southwest. Logistic regression models with robust variance were used to estimate odds ratios of lifetime STD testi such as lifetime discrimination encounters and how these interact to drive or discourage sexual health services at local clinics. In addition, larger household size may be a protective factor functioning as a form of social support, and the extended family's role should be taken into consideration. Future research should consider improvement in measurements of AI/AN enculturation constructs.
Our findings suggest that STD prevention programs should take into consideration AI/AN-specific historical traumatic stressors such as lifetime discrimination encounters and how these interact to drive or discourage sexual health services at local clinics. In addition, larger household size may be a protective factor functioning as a form of social support, and the extended family's role should be taken into consideration. Future research should consider improvement in measurements of AI/AN enculturation constructs.
Antidepressants have aroused wide public concern due to their widespread presence in water and their harm to human health and environment. This study was designed to evaluate the contribution of wastewater treatment plants (WWTPs) to the presence of antidepressants in the surface water.

Data was evaluated by analyzing water samples collected from the influent, effluent, upstream and downstream of the WWTPs on the rivers of interest in Hangzhou, Zhejiang Province, China. Besides, the study also assessed the impact of the release of antidepressants from WWTPs to the surface water on the drinking water. An automatic solid-phase extraction combined with ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-MS/MS) was used to detect antidepressants.

The most abundant compound was venlafaxine, followed by citalopram, sertraline, and fluvoxamine with concentrations between 0.6 and 87 ng/L. Antidepressants showed maximum concentrations at the effluent outlets of the WWTPs, and greater concentrations were found downstream than upstream of the WWTPs in Qiantang River. The results of source water and finished water showed that the detection concentration was lower than the detection limit of the method.

The less impact of the release of antidepressants from WWTPs to the surface water on the drinking water was identified. Nevertheless, these compounds were hardly removed by wastewater treatment processes. Thus, their risks deserve close attention.
The less impact of the release of antidepressants from WWTPs to the surface water on the drinking water was identified. Nevertheless, these compounds were hardly removed by wastewater treatment processes. Thus, their risks deserve close attention.
In an era of increasingly expensive intensive care costs, it is essential to evaluate early whether the length of stay (LOS) in the intensive care unit (ICU) of obesity patients with sepsis will be prolonged. On the one hand, it can reduce costs; on the other hand, it can reduce nosocomial infection. Therefore, this study aimed to verify whether ICU prolonged LOS was significantly associated with poor prognosis poor in obesity patients with sepsis and develop a simple prediction model to personalize the risk of ICU prolonged LOS for obesity patients with sepsis.

In total, 14,483 patients from the eICU Collaborative Research Database were randomized to the training set (3,606 patients) and validation set (1,600 patients). The potential predictors of ICU prolonged LOS among various factors were identified using logistic regression analysis. For internal and external validation, a nomogram was developed and performed.

ICU prolonged LOS was defined as the third quartile of ICU LOS or more for all sepsis patm to predict the risk of ICU prolonged LOS. This prediction model is accurate and reliable, and it can assist patients and clinicians in determining prognosis and making clinical decisions.
In developing countries, adverse pregnancy outcomes are major public health issues. It is one of the leading causes of neonatal morbidity and mortality worldwide. Despite the fact that ending prenatal mortality and morbidity is one of the third Sustainable Development Goals (SDG), the burden of the problem continues to be a huge concern in developing countries, including Ethiopia. Hence, this study aimed to determine the prevalence and associated factors of lifetime adverse pregnancy outcomes among antenatal care (ANC) booked women in Northwest Ethiopia.

An institutional-based cross-sectional study design was conducted in Northwest Ethiopia, between March 2021 and June 2021. A multi-stage stratified random sampling technique was employed to recruit participants. An interviewer-administered and checklist questionnaire were used to collect the data. The data were entered into Epi-data version 4.6 software and exported to Stata version 16 for analysis. check details The binary logistic regression model was fitted to identtheir life. Road access to health facilities and husband-supported pregnancy were statistically significant factors for adverse events in pregnancy. Therefore, it is better to give more attention to expanding infrastructure like road accessibility and increasing husband-supported pregnancy to reduce adverse pregnancy outcomes.Globally, the demand for masks has increased due to the COVID-19 pandemic, resulting in 490,201 tons of waste masks disposed of per month. Since masks are used in places with a high risk of virus infection, waste masks retain the risk of virus contamination. In this study, a 1 kg/h lab-scale (diameter 0.114 m, height 1 m) bubbling fluidized bed gasifier was used for steam gasification (temperature 800 °C, steam/carbon (S/C) ratio 1.5) of waste masks. The use of a downstream reactor with activated carbon (AC) for tar cracking and the enhancement of hydrogen production was examined. Steam gasification with AC produces syngas with H2, CO, CH4, and CO2 content of 38.89, 6.40, 21.69, and 7.34 vol%, respectively. The lower heating value of the product gas was 29.66 MJ/Nm3 and the cold gas efficiency was 74.55 %. This study showed that steam gasification can be used for the utilization of waste masks and the production of hydrogen-rich gas for further applications.
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