Ordinal Regression Research Articles

Blood pressure variability in acute stroke: Risk factors and association with functional outcomes at 1 month.

Blood pressure variability, in acute stroke, may be an important modifiable determinant of functional outcome after stroke. In a large international cohort of participants with acute stroke, it was sought to determine the association of blood pressure variability (in the early period of admission) and functional outcomes, and to explore risk factors for increased blood pressure variability. INTERSTROKE is an international case-control study of risk factors for first acute stroke. Blood pressure was recorded at the time of admission, the morning after admission and the time of interview in cases (median time from admission 36.7 h). Multivariable ordinal regression analysis was employed to determine the association of blood pressure variability (standard deviation [SD] and coefficient of variance) with modified Rankin score at 1-month follow-up, and logistic regression was used to identify risk factors for blood pressure variability. Amongst 13,206 participants, the mean age was 62.19 ± 13.58 years. When measured by SD, both systolic blood pressure variability (odds ratio 1.13; 95% confidence interval 1.03-1.24 for SD ≥20 mmHg) and diastolic blood pressure variability (odds ratio 1.15; 95% confidence interval 1.04-1.26 for SD ≥10 mmHg) were associated with a significant increase in the odds of poor functional outcome. The highest coefficient of variance category was not associated with a significant increase in risk of higher modified Rankin score at 1 month. Increasing age, female sex, high body mass index, history of hypertension, alcohol use, and high urinary potassium and low urinary sodium excretion were associated with increased blood pressure variability. Increased blood pressure variability in acute stroke, measured by SD, is associated with an increased risk of poor functional outcome at 1 month. Potentially modifiable risk factors for increased blood pressure variability include low urinary sodium excretion.

Association Between Institution ZIP Code Characteristics and NIH Funding.

Introduction. While racial NIH funding disparities have been identified, little is known about the link between community demographics of institutions and NIH funding. We sought to evaluate the association between institution zip code characteristics and NIH funding. Methods. We linked the 2011-2021 NIH RePORTER database to Census data. We calculated the funding to each institution and stratified institutions into funding quartiles. We defined out independent variables as institution ZIP code level race/ethnicity (White, Black, and Hispanic), and socioeconomic status (household income, high school graduation rate, and unemployment rate). We used ordinal regression models to evaluate the association between institution ZIP code characteristics and grant funding quartile. Results. We included 731,548 grants (US$271,495,839,744) from 3,971 ZIP codes. The funding amounts in millions of U.S. dollars for the funding quartiles were fourth - 0.25, third - 1.1, second - 3.8, first - 43.5. Using ordinal regression, we found an association between increasing unemployment rate (OR = 1.03 [1.02, 1.05]), increasing high school graduation rate (OR = 3.6 [1.6, 8.4]), decreasing proportion of White people (OR = 0.4 [0.3, 0.5]), increasing proportion of Black people (OR = 1.3 [0.9, 1.8]), and increasing proportion of Hispanic/Latine people (OR = 2.5 [1.7, 3.5]) and higher grant funding quartiles. We found no association between household income and grant funding quartile. Conclusion. We found ZIP code demographics to be inadequate for evaluating NIH funding disparities, and the association between institution ZIP code demographics and investigator demographics is unclear. To evaluate and improve grant funding disparities, better grant recipient data accessibility and transparency are needed.

Determinants of Financial Inclusion in Kenya: A Demand-Side Perspective

This study sought to analyze the underlying financial inclusion determinants in Kenya. The study applies ordinal logit regression to examine the effect of the residential area, gender, education level, marital status, and employment type on financial inclusion. Financial inclusion is measured by developing a financial inclusion index for ten binary financial services variables. From the index, three financial inclusion levels are designed. These include low financial inclusion with scores of zero to three, medium with scores of four to six, and high level with scores of seven to ten. The estimates of the ordinal model are statistically significant for all factors considered except gender. Area of residence, age, education type, income, and marital status positively affect the log odds of financial inclusion, while employment is negatively linked. Education, employment, and marital status have interaction effects on financial inclusion. This study recommends that the Kenyan government formulate and strengthen policies to tackle challenges such as gender disparity, rural bank infrastructure development, fostering an environment conducive for entrepreneurship to address unemployment and income disparities, advocating for secondary school completion, and addressing social issues impacting family stability, including separation or the absence of marriage.

Two for One—Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform

Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: “MIX1”, combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and “MIX2”, combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

Racial and Ethnic Differences in Mortality and Functional Outcomes Following Aneurysmal Subarachnoid Hemorrhage.

Ischemic and hemorrhagic stroke incidence tends to be higher among minority racial and ethnic groups. The effect of race and ethnicity following an aneurysmal subarachnoid hemorrhage (aSAH) remains poorly understood. Thus, we aimed to explore the association between race and ethnicity and aSAH outcomes. Single-center retrospective review of patients with aSAH from January 2009 to March 2023. Primary outcome was in-hospital mortality. Secondary outcomes included delayed cerebral ischemia, cerebral infarction, radiographic and symptomatic vasospasm, pulmonary complications, epileptic seizures, external ventricular drain placement, and modified Rankin Scale score at discharge and 3-month follow-up. Associations between race and ethnicity and outcomes were assessed using binary and ordinal regression models, with multivariable models adjusted for significant covariates. A total of 1325 patients with subarachnoid hemorrhage presented to our center. Among them, 443 cases were excluded, and data from 882 patients with radiographically confirmed aSAH were analyzed. Distribution by race and ethnicity was 40.8% (n=360) White, 31.4% (n=277) Hispanic, 22.1% (n=195) Black, and 5.7% (n=50) Asian. Based on Hunt-Hess and modified Fisher grade, aSAH severity was similar among groups (P=0.269 and P=0.469, respectively). In-hospital mortality rates were highest for Asian (14.0%) and Hispanic (11.2%) patients; however, after adjusting for patient sex, age, health insurance, smoking history, alcohol and substance abuse, and aneurysm treatment, the overall likelihood was comparable to White patients. Hispanic patients had higher risks of developing cerebral infarction (adjusted odds ratio, 2.17 [1.20-3.91]) and symptomatic vasospasm (adjusted odds ratio, 1.64 [1.05-2.56]) than White patients and significantly worse discharge modified Rankin Scale scores (adjusted odds ratio, 1.44 [1.05-1.99]). Non-White patients also demonstrated a lower likelihood of 0 to 2 discharge modified Rankin Scale scores (adjusted odds ratio, 0.71 [0.50-0.98]). No significant interactions between race and ethnicity and age or sex were found for in-hospital mortality and functional outcomes. Our study identified significant differences in cerebral infarction and symptomatic vasospasm risk between Hispanic and White patients following aSAH. A higher likelihood of worse functional outcomes at discharge was found among non-White patients. These findings emphasize the need to better understand predisposing risk factors that may influence aSAH outcomes. Efforts toward risk stratification and patient-centered management should be pursued.

Association between COVID-19 severity and tobacco smoking status: a retrospective cohort study using propensity score matching weights analysis

IntroductionThe COVID-19 pandemic continues to be a global threat to public health, with over 766 million confirmed cases and more than 6 million reported deaths. Patients with a smoking history...

Exploring the Digital Frontier in Sports Training: Coach's Perspectives, Influential Factors, and Case Study in Indonesia

This study aims to determine the perception of coaches in the entry of digitalization of sports and the effect of gender, age, region, educational background, and training experience on the perception of the entry of digitalization of sports. This research is a quantitative research with a cross-sectional survey method. The data collection instrument uses a questionnaire that has been tested for validity and reliability using the corrected item-total correlation test and the Cronbach'Alpha test. Percentage analysis was used to determine the coach's perception, while ordinal regression was used to determine the effect of the independent variable on the dependent variable. The study results found that 39.9% of coaches agreed, and 39.4% strongly agreed with digital technology in sports. Two independent variable indicators influence coaches' perception of the inclusion of digitalization in the world of sports: the level of education and training experience. This study concludes that it is essential to develop the digitalization of training programs; this is related to the convenience of coaches and athletes in monitoring the development of student-athlete training programs. Keywords: digital, training program, coach's perception.

Understanding the mechanism of safety attitude mitigates the turnover intention novice nurses via the person-centred method: A theory-driven, deductive cross-sectional study.

Examine profiles of safety attitudes among novices and explore whether profiles moderate the occupational identity-turnover pathway. Novice nurses face unique challenges in adopting positive safety attitudes, which influence outcomes like turnover. However, past research found only average levels of safety attitudes among novices, ignoring possible heterogeneity. Exploring whether meaningful subgroups exist based on safety perspectives and factors shaping them can provide insights to improve safety attitudes and retention. This study was designed as a cross-sectional investigation. Data were collected through the distribution of questionnaires. Descriptive statistics were first conducted, followed by latent profile analysis. We then carried out univariate analysis and ordinal multinomial regression to explore the factors shaping the different profiles. Finally, we examine the moderating effect of nurses' safety attitudes with different latent profiles on the relationship between professional identification and turnover intention. A total of 816 novice nurses were included. Three profiles were identified: high, moderate and low safety attitudes - higher attitudes were associated with lower turnover intention. Interest in nursing, health status, identity and turnover predicted profile membership. Moderate profile had a stronger buffering effect on the identity-turnover link versus high profile. Multiple safety attitude profiles exist among novice nurses. Certain factors like interest in nursing and occupational identity are associated with more positive safety profiles. Targeting these factors could potentially improve safety attitudes and reduce turnover among novice nurses. The moderating effects suggest that tailored interventions matching specific subgroups may maximize impact. Assessing subgroup attitudes enables tailored training for novices' specific needs, nurturing continuous improvement. Supporting early career development and role identity may strengthen retention intentions.

Fecal calprotectin and platelet count predict histologic disease activity in pediatric ulcerative colitis: results from a projection-predictive feature selection.

Especially for pediatric patients, proxies of mucosal inflammation are needed. The Pediatric Ulcerative Colitis Activity Index (PUCAI) has been established to predict clinical and endoscopic disease activity. However, histologic inflammation might persist. We applied a special variable selection technique to predict histologic healing in pediatric ulcerative colitis (UC) as parsimoniously (but still as precisely) as possible. The retrospective analysis included data from two study cohorts, comprising 91 visits from 59 pediatric patients with UC. A Bayesian ordinal regression model was used in combination with a projection-predictive feature selection (PPFS) to identify a minimal subset of clinical and laboratory parameters sufficient for the prediction of histologic disease activity. Following the PPFS, CEDATA-GPGE patient registry data were analyzed to investigate the relevance of the selected predictors in relation to PUCAI and Physician Global Assessment (PGA) in up to 6697 patient visits. Fecal calprotectin (FC) and platelet count were identified as the minimal subset of predictors sufficient for prediction of histologic disease activity in pediatric UC. FC and platelet count also appeared to be associated with increasing disease activity as measured by PUCAI and PGA in the CEDATA-GPGE registry. Based on the selected model, predictions can be performed with a Shiny web app. Conclusion: Our statistical approach constitutes a reproducible and objective tool to select a minimal subset of the most informative parameters to predict histologic inflammation in pediatric UC. A Shiny app shows how physicians may predict the histologic activity in a user-friendly way using FC and platelet count. To generalize the findings, further prospective studies will be needed. What is Known: • Histologic healing is a major endpoint in the therapy of ulcerative colitis (UC). • The PUCAI score has been established to predict disease activity in pediatric UC but is not suitable for the prediction of histologic healing. What is New: • Our Bayesian ordinal regression model in combination with a projection-predictive feature selection is a reproducible and objective tool to select the minimal subset of clinical and laboratory parameters to predict histologic inflammation in pediatric UC. • Histologic inflammation in pediatric UC can be non-invasively predicted based on the combination of fecal calprotectin levels and platelet count.

Strong habitat and seasonal phenology effects on the evolution of self-compatibility, clonality and pollinator shifts in Lachenalia (Asparagaceae: Scilloideae).

Plants employ a diversity of reproductive safeguarding strategies to circumvent the challenge of pollen limitation. Focusing on southern African Lachenalia (Asparagaceae: Scilloideae), we test the hypothesis that the evolution of reproductive safeguarding traits (self-compatibility, autonomous selfing, bird pollination and clonal propagation) is favoured in species occupying conditions of low insect abundance imposed by critically infertile fynbos heathland vegetation and by flowering outside the austral spring insect abundance peak. We trace the evolution of these traits and selective regimes on a dated, multi-locus phylogeny of Lachenalia and assess their evolutionary associations using ordinary and phylogenetic regression. Ancestral state reconstructions identify an association with non-fynbos vegetation and spring flowering as ancestral in Lachenalia, the transition to fynbos vegetation and non-spring flowering taking place multiple times. They also show that self-compatibility, autofertility, bird pollination and production of multiple clonal offsets have evolved repeatedly. Regression models suggest that bird pollination and self-compatibility are selected for in fynbos and in non-spring flowering lineages, with autofertility being positively associated with non-spring flowering. These patterns support the interpretation of these traits as reproductive safeguarding adaptations under reduced insect pollinator abundance. We find no evidence to support the interpretation of clonal propagation as a reproductive safeguarding strategy.

Changes in mental distress among employees during the three years of the COVID-19 pandemic in Germany.

The COVID-19 pandemic changed the future of work sustainably and led to a general increase in mental stress. A study conducted during the second and third pandemic wave with a retrospective survey of the first wave among 1,545 non-healthcare workers confirmed an increase in anxiety and depression symptoms and showed a correlation with the occupational SARS-CoV-2 infection risk. This online follow-up survey aims to examine changes in mental distress as the pandemic progressed in Germany and to identify factors influencing potential changes. Longitudinal data from 260 subjects were available for this analysis. Mental distress related to anxiety and depression symptoms, assessed by the Patient Health Questionnaire-4 (PHQ-4), and occupational risk factors were solicited at the end of 2022 and retrospectively at the fifth wave. Categorized PHQ-4 scores were modelled with mixed ordinal regression models and presented with odds ratios (OR) and 95% confidence intervals (95% CI). A previous diagnosis of a depressive or anxiety disorder was a strong risk factor for severe symptoms (OR 3.49, 95% CI 1.71-7.11). The impact of occupational SARS-CoV-2 infection risk on mental distress was increased, albeit failing to reach the formal level of statistical significance (high risk OR 1.83, 95% CI 0.59-5.63; probable risk OR 1.72, 95% CI 0.93-3.15). Mental distress was more pronounced in those with a previous diagnosis of anxiety and depression. Confirmed occupational risk factors were protective measures against occupational SARS-CoV-2 infection perceived as inadequate, chronic work-related stress, overcommitment, reduced interactions with fellow-workers, and work-privacy conflicts. The pandemic had a negative impact on anxiety and depression symptoms among the studied non-healthcare workers, particularly early in the pandemic, although this effect does not appear to be permanent. There are modifiable risk factors that can protect workers' mental health, including strengthening social interactions among employees and reducing work-privacy conflicts.

Measuring Impact of CAMELS Model on Financial Performance of Indian Commercial Banks

The purpose of this study is to examine the effects of CAMELS components on the financial performance of Indian commercial banks. To fulfill the objectives of the study,secondary data were collectedfor the fiscal year 2016 to 2021 from four public sector and four private sector banks based on their market capitalization. To analyse the data two econometric models are constructed using return on assets (ROA) and return on equity (ROE) as proxies for commercial banks’ financial performance as dependent variables and six CAMELS’s key indicators (capital adequacy, asset quality, management efficiency, earning quality, liquidity, and sensitivity to market risk)as independent variables. To determine the extent to which the independent variables have an effect on the dependent variable, panel ordinal least square regression with their assumption has been used. The findings of the study revealed that the financial performance of Indian banking sector as evaluated by ROA and ROE is statistically and significantly affected by capital adequacy, liquidity and sensitivity to market risk, whereas asset quality, managerial efficiency and earning quality is found to have insignificant impact on the financial performance of Indian commercial banks. In order to perform better, it is suggested that the commercial banks should focus more on the variables that have a substantial impact on their financial performance. Keywords: Random effect, ROA, ROE, liquidity, sensitivity to market risk, CAMELS.

Bedtime Regularity and Sleep Sufficiency in Children with Tourette Syndrome

ObjectiveDespite research demonstrating sleep disturbance in children with Tourette Syndrome (TS), few studies have examined bedtime regularity and sleep sufficiency, two important sleep health dimensions. Therefore, this study examined bedtime regularity and sleep sufficiency in children with TS relative to matched healthy controls, and its associated demographic, clinical, and behavioral factors. MethodParticipants were 384 parents or caregivers of children aged 3 to 17 years, including 192 with current TS and 192 matched healthy controls drawn from the 2020-2021 cycle of the National Survey of Children’s Health. Parents completed questions assessing demographics (i.e., age, race, sex), clinical (i.e., ADHD, ASD, anxiety, depression, tic severity, behavioral or conduct problems, ADHD medication, health-condition related impairment), and behavioral (i.e., screen time) characteristics. Mann-Whitney U test and chi-square test of independence were performed to compare groups on bedtime regularity and sleep sufficiency, respectively. Ordinal regression and binary logistic regression without and with backward elimination were performed to evaluate indicators of bedtime regularity and sleep sufficiency, respectively, in children with TS. ResultsChildren with current TS had significantly poorer bedtime regularity, but not sleep sufficiency, relative to matched healthy controls. In children with TS, anxiety and two or more hours of daily screen time were associated with higher likelihood of poor bedtime regularity. Autism was associated with lower likelihood of insufficient sleep, and depression was associated with increased likelihood of insufficient sleep. ConclusionsFindings put forth screen time, anxiety, and depression as intervention targets to optimize sleep health in children with TS.

Urban inundation mapping by coupling 1D − 2D models and model comparison

Urban inundation mapping is important for early warning, management, and drainage network planning. Urban flood simulations typically utilize a 1D model focused on pipe nodes, whereas 2D simulations are required over a land area. In this paper, our focus is on their coupling, so that a dynamic 1D-2D model is obtained. We couple the Storm Water Management Model (SWMM), a widely utilized urban drainage model, with 2D models to simulate urban inundation. The 1D-2D coupled inundation model uses the 1D model output, which represents the overflow volume of sparsely distributed pipe nodes. After coupling, surface inundation distribution maps are obtained. We developed a physically-based 2D overflow diffusion model (2D-DM) and compared it with two geostatistical models: Ordinary co-kriging (OCK) and Regression Kriging (RK). The study area is the central area of Haining City in China, where a severe storm occurred on August 3, 2018. The 2D-DM performed best (RMSE = 0.232), followed by RK (RMSE = 0.286), and OCK (RMSE = 0.361), but did not provide uncertainty measures, in contrast to the geostatistical models. We conclude that 1D-2D coupling was done successfully, with the different 2D models showing different qualities. To enhance urban inundation mapping, it is suggested to couple the 1D model with both physical and statistically based 2D models for a more comprehensive assessment of potential inundation areas and depths.

The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.

Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratifying symptomatic paediatric patients with suspected Sjögren's disease. This cross-sectional study was done in symptomatic patients who visited the Department of Pediatric Rheumatology at the University of Florida, FL, USA. Eligible patients were younger than 18 years or had symptom onset before 18 years of age. Patients with confirmed diagnosis of another autoimmune condition or infection with a clear aetiological microorganism were excluded. Eligible patients underwent comprehensive examinations to rule out or diagnose childhood Sjögren's disease. We used latent class analysis with clinical and laboratory variables to detect heterogeneous patient classes. Machine learning models, including random forest, gradient-boosted decision tree, partial least square discriminatory analysis, least absolute shrinkage and selection operator-penalised ordinal regression, artificial neural network, and super learner were used to predict patient classes and rank the importance of variables. Causal graph learning selected key features to build the final Florida Scoring System. The predictors for all models were the clinical and laboratory variables and the outcome was the definition of patient classes. Between Jan 16, 2018, and April 28, 2022, we screened 448 patients for inclusion. After excluding 205 patients due to symptom onset later than 18 years of age, we recruited 243 patients into our cohort. 26 patients were excluded because of confirmed diagnosis of a disorder other than Sjögren's disease, and 217 patients were included in the final analysis. Median age at diagnosis was 15 years (IQR 11-17). 155 (72%) of 216 patients were female and 61 (28%) were male, 167 (79%) of 212 were White, and 20 (9%) of 213 were Hispanic, Latino, or Spanish. The latent class analysis identified three distinct patient classes: class I (dryness dominant with positive tests, n=27), class II (high symptoms with negative tests, n=98), and class III (low symptoms with negative tests, n=92). Machine learning models accurately predicted patient class and ranked variable importance consistently. The causal graphical model discovered key features for constructing the Florida Scoring System. The Florida Scoring System is a paediatrician-friendly tool that can be used to assist classification and long-term monitoring of suspected childhood Sjögren's disease. The resulting stratification has important implications for clinical management, trial design, and pathobiological research. We found a highly symptomatic patient group with negative serology and diagnostic profiles, which warrants clinical attention. We further revealed that salivary gland ultrasonography can be a non-invasive alternative to minor salivary gland biopsy in children. The Florida Scoring System requires validation in larger prospective paediatric cohorts. National Institute of Dental and Craniofacial Research, National Institute of Arthritis, Musculoskeletal and Skin Diseases, National Heart, Lung, and Blood Institute, and Sjögren's Foundation.

Long-term ambient air pollution and coronary atherosclerosis: Results from the Swedish SCAPIS study

Background and aimsDespite firm evidence for an association between long-term ambient air pollution exposure and cardiovascular morbidity and mortality, results from epidemiological studies on the association between air pollution exposure and atherosclerosis have not been consistent. We investigated associations between long-term low-level air pollution exposure and coronary atherosclerosis. MethodsWe performed a cross-sectional analysis in the large Swedish CArdioPulmonary bioImaging Study (SCAPIS, n = 30 154), a random general population sample. Concentrations of total and locally emitted particulate matter <2.5 μm (PM2.5), <10 μm (PM10), and nitrogen oxides (NOx) at the residential address were modelled using high-resolution dispersion models. We estimated associations between air pollution exposures and segment involvement score (SIS), coronary artery calcification score (CACS), number of non-calcified plaques (NCP), and number of significant stenoses, using ordinal regression models extensively adjusted for potential confounders. ResultsMedian 10-year average PM2.5 exposure was 6.2 μg/m3 (range 3.5–13.4 μg/m3). 51% of participants were women and 51% were never-smokers. None of the assessed pollutants were associated with a higher SIS or CACS. Exposure to PM2.5 was associated with NCP (adjusted OR 1.34, 95% CI 1.13, 1.58, per 2.05 μg/m3). Associations with significant stenoses were inconsistent. ConclusionsIn this large, middle-aged general population sample with low exposure levels, air pollution was not associated with measures of total burden of coronary atherosclerosis. However, PM2.5 appeared to be associated with a higher prevalence of non-calcified plaques. The results suggest that increased risk of early-stage atherosclerosis or rupture, but not increased total atherosclerotic burden, may be a pathway for long-term air pollution effects on cardiovascular disease.

Assessment of Fire Safety Management for Special Needs Schools in South Africa

The safety and well-being of learners with special educational needs in South Africa remain a paramount concern, significantly impacting their constitutional rights and dignity. Despite legislative commitments aimed at fostering inclusive education, a pervasive absence of adequate fire safety measures in special needs schools (SNSs) in South Africa has persisted, leading to the vulnerability of these learners. Tragic incidents, such as fatal fires in these schools, as reported in the literature, underscore the urgent need for immediate intervention to ensure the safety and security of these learners, especially with regards to fire hazards. This study, conducted within the Northwest Province of South Africa, assessed the state of fire safety management in SNSs by applying a series of chi-squared (χ2) tests of independence for categorical variables, descriptive statistics, and regression analysis using the Statistical Package for Social Scientists (SPSS), Version 20 and found that limited access to power is the potential root cause of fires in these schools; also, the limited amount of fire safety initiatives was a problem. In addition, the ordinal regression showed a statistically significant relationship when the question of to what extent the learners in the sampled schools are involved in fire safety programs was regressed with the questions of whether management and stakeholders were involved in fire safety programs and also on taking part in the physical fire safety programs (χ2 = 47.412; df = 2; p &lt; 0.001; R2 = 70.5%). Furthermore, fire safety management was not sufficiently implemented in the sampled schools and the safety legislations of the country were not implemented accordingly when it came to fire safety. This study identified root causes of fire risks, gauged stakeholders’ awareness and involvement in fire safety management, and advocated for more stringent safety policies and practices within the SNS based on the above findings.

Inferior Frontal Sulcal Hyperintensities on Brain MRI Are Associated with Amyloid Positivity beyond Age-Results from the Multicentre Observational DELCODE Study.

Inferior frontal sulcal hyperintensities (IFSHs) on fluid-attenuated inversion recovery (FLAIR) sequences have been proposed to be indicative of glymphatic dysfunction. Replication studies in large and diverse samples are nonetheless needed to confirm them as an imaging biomarker. We investigated whether IFSHs were tied to Alzheimer's disease (AD) pathology and cognitive performance. We used data from 361 participants along the AD continuum, who were enrolled in the multicentre DELCODE study. The IFSHs were rated visually based on FLAIR magnetic resonance imaging. We performed ordinal regression to examine the relationship between the IFSHs and cerebrospinal fluid-derived amyloid positivity and tau positivity (Aβ42/40 ratio ≤ 0.08; pTau181 ≥ 73.65 pg/mL) and linear regression to examine the relationship between cognitive performance (i.e., Mini-Mental State Examination and global cognitive and domain-specific performance) and the IFSHs. We controlled the models for age, sex, years of education, and history of hypertension. The IFSH scores were higher in those participants with amyloid positivity (OR: 1.95, 95% CI: 1.05-3.59) but not tau positivity (OR: 1.12, 95% CI: 0.57-2.18). The IFSH scores were higher in older participants (OR: 1.05, 95% CI: 1.00-1.10) and lower in males compared to females (OR: 0.44, 95% CI: 0.26-0.76). We did not find sufficient evidence linking the IFSH scores with cognitive performance after correcting for demographics and AD biomarker positivity. IFSHs may reflect the aberrant accumulation of amyloid β beyond age.

Postharvest practices and loss determinants for interventions among smallholder potato farmers in Tiyo district, Arsi zone, Ethiopia

Postharvest loss reduction, which will contribute to several sustainable development goals (SDGs) including SDG 1, 2, 3, 9, 12 and 13, is an important strategy for food and nutrition security. It requires interventions designed based on timely and reliable statistical data. However, lack of produce-specific loss data and associated factors along the postharvest value chain stages remains a challenge to implement appropriate interventions. Therefore, a survey was conducted on socio-demographic characteristics, postharvest practices, extent and causes of losses, and factors influencing postharvest loss of potato crops in Tiyo district of Arsi Zone, Ethiopia in 2022. A multistage sampling method was used to select a total of 209 smallholder potato farming household heads through a combination of purposive and simple random sampling techniques. Quantitative data collection was carried out online using computer-assisted personal interviewing (CAPI) by programming a semi-structured questionnaire in KoboCollect software for tablets. Descriptive statistics and ordinal probit regression model were used to analyze the collected data and determinant factors influencing postharvest loss of potatoes at various farm-level stages, respectively. An aggregate of 15-46% loss exists between harvesting and marketing. Losses during harvesting, sorting, cleaning, packaging, field-to-storage transport, storage, and storage-to-market transport were 58.9%, 6.2%, 2.9%, 2.4%, 3.8%, 20.1%, and 5.7%, respectively. Elevated loss during harvesting and storage in the area is likely to reflect poor handling and storage practices. The primary causes of losses were poor harvesting and handling techniques, poor storage facility, and insects and worms. Moreover, regression model estimations of categorical losses, as perceived by farmers, reveal that socio-demographic variables and postharvest factors influenced potato loss. During the harvest stage, working family members significantly (p&lt;0.01) increased loss while years of schooling (p&lt;0.05) significantly reduced loss. In addition, harvesting using leaf color change observation as a criterion had significantly (p&lt;0.01) mitigated potato loss. In storage, female respondents (p&lt;0.05), land size (p&lt;0.05), and lack of training (p&lt;0.1) had accentuated loss. During transport, the age of household reduced (p&lt;0.1) loss whereas farming experience promoted (p&lt;0.1) it. To reduce the existing losses, farmers’ awareness should be increased concerning each stage. The study recommends the need for stakeholders’ intervention focusing on postharvest knowledge and skill capacity building, demonstration of simple innovative ventilated storage construction using locally available materials, appropriate packaging (such as reusable plastic crates) and transport methods, and simple value addition methods (such as potato drying using indirect solar dryers and potato flour processing for fortifying local cereals). Key words: CAPI, Ethiopia, ordinal probit regression, postharvest practices, potato loss determinants

High School Students' Health Literacy Related to the COVID-19 Pandemic in Indonesia

The global crisis due to COVID-19 demanded changes in people’s behavior to adapt to the pandemic. One factor that determined behaviors was literacy skills, especially in the health sector. A study related to the COVID-19 pandemic was carried out on high school students to assess students’ health literacy and determine related factors. Data collection was carried out from December 2021 to February 2022 by dividing urban areas, developing districts, and remote regions. The Health Literacy Questionnaire (HLQ) was adapted to suit the conditions of the COVID-19 pandemic. The data was interpreted as descriptive-narrative. Differences in literacy ability and the relationship with influencing factors were analyzed using ordinal regression and SEM-AMOS analysis. Limited health literacy was found in students from remote areas. A significant relationship was found between health literacy and class interest based on the ordinal regression test results. In contrast, health literacy was not related to gender, grade level, infected experience, and domicile. It was found that the ability to navigate health system information had a significant effect on students’ understanding of health literacy. Health literacy, which was low and unequal, is expected to improve strategic and sustainable education programs through science learning and physical health. Keywords: Health Literacy, COVID-19, Indonesia