Multivariable Approach Research Articles

Prognostic Factors for Postoperative Bleeding Complications and Prolonged Intensive Care after Percutaneous Hepatic Chemosaturation Procedures with Melphalan.

Percutaneous hepatic melphalan perfusion (chemosaturation) in patients with liver metastases is known to be associated with procedure-related hemodynamic depression and coagulation impairment, which may cause bleeding complications and/or a prolonged intensive care unit length of stay (ICU LOS). We retrospectively analyzed possible predictive factors for bleeding complications and an ICU LOS > 1 d in a cohort of 31 patients undergoing 90 chemosaturation procedures. Using a multivariable mixed-model approach, we identified the amount of perioperative fluid volume (OR 12.0, 95% CI 2.3-60.0, p = 0.003) and protamine (OR 0.065, 95% CI 0.007-0.55, p = 0.012) to be associated with bleeding complications. Furthermore, the amount of perioperative fluid volume was associated with an ICU LOS > 1 d (OR 5.2, 95% CI 1.4-19.0, p = 0.011). Heparin dosage, melphalan dosage, extracorporeal circulation time, and noradrenaline dosage had no significant effects on outcomes. Protamine use was not associated with anaphylactic or thromboembolic complications. Despite the limited sample size, these results suggest a restrictive perioperative fluid regime to be beneficial, and support the use of protamine for heparin reversal after chemosaturation procedures. Further prospective randomized trials are needed to confirm these findings.

The Application of an Inverse Methodology to Predict Nonlinear Thermal Properties in Laser Beam Welding

Modern engineering applications use processes that submit materials to high-temperature gradients. However, the traditional experimentation methods applied to determine thermal properties often do not provide reliable data when working temperatures are up to extreme conditions. Hence, the present work demonstrates the use of an inverse heat conduction problem methodology for estimating the thermal properties of a laser beam welding (LBW) process. The applied technique is the quadrilateral optimization method (QOM), which consists of a multivariable estimation approach developed to calculate the function’s parameters. Additionally, the future time regularization scheme was implemented in the objective function to regularize the results. The applied numerical process solved the energy equation using the finite volume method implemented in an in-house CUDA-C language code. The software is a multi-thread application run in a graphics processing unit for enhanced computational time efficiency. A validation study compared the estimated results with LBW simulated data. The QOM estimates the parameters of a function representing the range of thermal conductivity values. The proposed method is expected to lower experimental costs for obtaining thermal properties at high temperatures by eliminating the need for sophisticated technical equipment and skilled labor required by traditional direct measurements.

Evaluating the spatial application of multivariable flood damage models

AbstractFlood damage arises from complex interactions between flooding processes and socio‐economic elements. Damage assessments for elements such as residential buildings rely on a modelled representation of local damage factors. Multivariable model approaches are well suited for damage prediction using detailed information on flood hazard and building characteristics. While broad explanatory variable ranges can improve model prediction performance, model transfer across geographical contexts often causes performance loss. This study aims to determine if increasing explanatory damage variables in a multivariable model improves residential building damage prediction and whether models based on local variables transfer between locations. We used empirical damage observations from six flood events to train and evaluate random forest regression model prediction performance. Spatial transfer is tested by splitting event datasets with trained models applied to original and external events. Variable analysis demonstrates model performance improvement with up to seven flood hazard and building characteristics, decreasing thereafter. Event models showed highest prediction precision for the original event, while models trained on all events transfer with comparable predictions for urban stormwater flooding. Prediction precision reduces when models transfer between locations affected by different flood types. This indicates flood damage models must replicate variability in local damage factors for reliable spatial transfer.

Subjective and Performance-Based Cognition and Their Associations with Head Injury History in Older Former National Football League Players.

Investigate the association between self-reported subjective and performance-based cognition among older (50-70 years) former professional American football players, as well as the relationship of cognitive measures with concussion history and years of football participation, as a proxy for repetitive head impact exposure. Among older former National Football League (NFL) players ( N = 172; mean age = 60.69 ± 5.64), associations of subjective (Patient Reported Outcome Measurement Information System Cognitive Function-Short Form) and performance-based cognitive measures (Brief Test of Adult Cognition by Telephone [BTACT] Executive Function and Episodic Memory indices) were assessed via univariable and multivariable regression models, with a priori covariates of depression and race. A similar univariate and multivariable regression approach assessed associations between concussion history and years of football participation with subjective and performance-based cognitive measures. In a sample subset ( n = 114), stability of subjective cognitive rating was assessed via partial correlation. Subjective ratings of cognition were significantly associated with performance-based assessment, with moderate effect sizes (episodic memory ηp2 = 0.12; executive function ηp2 = 0.178). These associations were weakened, but remained significant ( P s < 0.05), with the inclusion of covariates. Greater concussion history was associated with lower subjective cognitive function ( ηp2 = 0.114, P < 0.001), but not performance-based cognition. The strength of association between concussion history and subjective cognition was substantially weakened with inclusion of covariates ( ηp2 = 0.057). Years of participation were not associated with measures of subjective or objective cognition ( P s > 0.05). These findings reinforce the importance of comprehensive evaluation reflecting both subjective and objective measures of cognition, as well as the consideration of patient-specific factors, as part of a comprehensive neurobehavioral and health assessment of older former contact sport athletes.

P-616 Evaluation of salivary ELISA for Oestradiol and Progesterone monitoring in IVF patients

Abstract Study question How do salivary E2 and P correlate with serum determinations across ovarian stimulation (OS) for IVF and artificial endometrial preparation cycles for embryo transfer? Summary answer Saliva-blood correlations were higher for E2 than for P. E2 saliva-blood ratios were patient-dependent. High serum P cases on trigger day could be identified. What is known already Steroid hormone concentrations in saliva are lower than in serum, even if the hormone is predominantly free. Therefore, quantitative assays need to be as sensitive as possible. Saliva-based assessments are a reliable and proven method for quantifying female hormone levels in premenopausal women during the natural cycle while being very precise and painless for patients. However, the cumulative experience in ovarian stimulation is relatively low. A recent study including 652 pairs of saliva-serum E2 samples reported correlations between 0.68 and 0.91, while 237 pairs of samples for P showed correlations ranging from -0.02 to 0.22 (Sakkas et al, 2020). Study design, size, duration Prospective cohort study including 300 saliva-blood pair samples from 120 patients undergoing OS for IVF (n = 90) or artificial endometrial preparation for embryo transfer (n = 30) between February and October 2022. Data were collected at each of 3 points of OS: early (days 1-5), mid (days 6-9), and trigger. Patients following endometrial preparation collected just one sample on the day of embryo transfer Participants/materials, setting, methods Thirty expected poor responders, 30 normal, and 30 expected high responders according to ovarian reserve evaluation were included. Two saliva samples per blood sample were collected: immediately after waking up, and at the clinic just before or after the blood sample was taken. Saliva samples were stored at -20ºC and shipped to Mint Diagnostics (Kent, UK) for analysis of salivary E2 and P4 Main results and the role of chance Saliva-blood E2 correlations (Spearman) were 0.68 (fasting) and 0.69 (clinic). 72% of individuals showed saliva-serum correlations &amp;gt; 0.8. Correlations improved when controlling for subgroup (low, normal, high responders). P4 saliva-blood correlations (Spearman) were 0.44 (fasting) and 0.29 (clinic). 41% of individuals showed correlations &amp;gt;0.8 on fasting samples, and 33% on clinic samples. There was a high variance of individual correlations (0-1), which were dependent on ovarian response subgroups (p &amp;lt; 0.05). A multivariable approach was developed to identify patients with a serum P4&amp;gt;1.5 ng/mL the day of trigger (n = 11) with clinic samples showing 81% sensitivity and 91% specificity and fasting samples showing 83% and 91% respectively demonstrating the possibility of shifting hormone analysis to the home rather than the clinic. Eighteen of 30 (60%) saliva samples collected on the day of ET on patients under hormonal replacement therapy showed values out of the assay range (&amp;gt;5000 pg/mL). Therefore, no correlations could be estimated. Limitations, reasons for caution Detection of patients with high P4 on the day of trigger was limited due to a short number of cases. No conclusions could be drawn in HRT patients for embryo transfer due to high salivary P4 values. Wider implications of the findings The current study shows that salivary monitoring of E2 and P4 is feasible. This more friendly non-invasive method could allow frequent hormone monitoring without the need for appointments at the clinic and for phlebotomy, thus resulting in more convenience for both the clinics and the patients. Trial registration number NCT05184777

Analyzing the influence of geopolitical risks on European power prices using a multiresolution causal neural network

This paper presents a rigorous investigation into the multiresolution cross-correlation and causality between European energy markets and geopolitical risk (GPR). Using daily electricity spot prices from January 2015 to January 2023, the study employs the variational mode decomposition (VMD) method to uncover the underlying patterns and reveal the interaction between European power prices and GPR. The paper further develops a VMD-assisted multi-scaled causal neural network (VMD-M-CNN) as a multivariable forecasting approach, benchmarking it against other competing models. The results demonstrate a strong dependence between electricity markets and GPR across different investment time-scale horizons. Additionally, the relationship between the two has taken different forms over the crisis period in contrast with calm periods. The proposed VMD-M-CNN approach proves to be more effective than other benchmark models, providing valuable insights for market participants and policymakers to make informed decisions. The rigorous methodology employed and the novel approach developed enhance the credibility and robustness of the study, contributing to the growing body of literature on energy markets and GPR.

A Multi-Variable Sentinel-2 Random Forest Machine Learning Model Approach to Predicting Perennial Ryegrass Biomass in Commercial Dairy Farms in Southeast Australia

One of the most valuable and nutritionally essential agricultural commodities worldwide is milk. The European Union and New Zealand are the second- and third-largest exporting regions of milk products and rely heavily on pasture-based production systems. They are comparable to the Australian systems investigated in this study. With projections of herd decline, increased milk yield must be obtained from a combination of animal genetics and feed efficiencies. Accurate pasture biomass estimation across all seasons will improve feed efficiency and increase the productivity of dairy farms; however, the existing time-consuming and manual methods of pasture measurement limit improvements to utilisation. In this study, Sentinel-2 (S2) band and spectral index (SI) information were coupled with the broad season and management-derived datasets using a Random Forest (RF) machine learning (ML) framework to develop a perennial ryegrass (PRG) biomass prediction model accurate to +/−500 kg DM/ha, and that could predict pasture yield above 3000 kg DM/ha. Measurements of PRG biomass were taken from 11 working dairy farms across southeastern Australia over 2019–2021. Of the 68 possible variables investigated, multiple simulations identified 12 S2 bands and 9 SI, management and season as the most important variables, where Short-Wave Infrared (SWIR) bands were the most influential in predicting pasture biomass above 4000 kg DM/ha. Conditional Latin Hypercube Sampling (cLHS) was used to split the dataset into 80% and 20% for model calibration and internal validation in addition to an entirely independent validation dataset. The combined internal model validation showed R2 = 0.90, LCCC = 0.72, RMSE = 439.49 kg DM/ha, NRMSE = 15.08, and the combined independent validation had R2 = 0.88, LCCC = 0.68, RMSE = 457.05 kg DM/ha, NRMSE = 19.83. The key findings of this study indicated that the data obtained from the S2 bands and SI were appropriate for making accurate estimations of PRG biomass. Furthermore, including SWIR bands significantly improved the model. Finally, by utilising an RF ML model, a single ‘global’ model can automate PRG biomass prediction with high accuracy across extensive regions of all seasons and types of farm management.

A multivariable mendelian randomisation study of serum lipids and dementia risk within the UK Biobank

AbstractBackgroundAn unfavourable lipid profile has been associated with the increased risk of dementia or Alzheimer’s disease in both observational and genetic studies1,2. However, it is challenging to investigate each serum lipid measure individually due to the high correlation between the lipid traits. We aimed to discover causal associations between genetically instrumented serum lipid measures (low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), triglycerides, apolipoprotein‐A1 (apoA) and apolipoprotein‐B (apoB)) and the risk of dementia.MethodWe conducted multivariable and univariable Mendelian randomisation (MR) analyses on 329,896 UK Biobank participants (age 37‐73 years) to examine the associations between each serum lipid measure and the risk of dementia. The multivariable approach allows us to assess the association of each lipid measure with the outcome, in cases where the genetic variants used to estimate the exposures are mediated by one another.ResultIn the univariable MR analyses, we found that genetically determined higher LDL‐C and apoB were both associated with increased risk of dementia, while higher HDL‐C and apoA were associated with decreased risk of dementia. Meanwhile, using multivariable MR analyses, in a model containing LDL‐C, triglycerides and apoB, only apoB remained significantly associated with increased risk of dementia.ConclusionOur findings suggests that when considering the correlation between lipid measures, apoB plays an important role in the previously reported association between serum lipids and increased risk of dementia.

The importance of discriminative power rather than significance when evaluating potential clinical biomarkers in epilepsy research.

The quest for epilepsy biomarkers is on the rise. Variables with statistically significant group-level differences are often misinterpreted as biomarkers with sufficient discriminative power. This study aimed to demonstrate the relationship between significant group-level differences and a variable's power to discriminate between individuals. We simulated normal-distributed datasets from hypothetical populations with varying sample sizes (25-800), effect sizes (Cohen's d: .25-2.50), and variability (standard deviation: 10-35) to assess the impact of these parameters on significance and discriminative power. The simulation data were illustrated by assessing the discriminative power of a potential real-case biomarker-the EEG beta band power-to diagnose generalized epilepsy, using data from 66 children with generalized epilepsy and 385 controls. Additionally, we evaluated recently reported epilepsy biomarkers by comparing their effect sizes to our simulation-derived effect size criterion. Group size affects significance but not discriminative power. Discriminative power is much more related to variability and effect size. Our real data example supported these simulation results by demonstrating that group-level significance does not translate, one to one, into discriminative power. Although we found a significant difference in the beta band power between children with and without epilepsy, the discriminative power was poor due to a small effect size. A Cohen's d of at least 1.25 is required to reach good discriminative power in univariable prediction modeling. Slightly over 60% of the biomarkers in our literature search met this criterion. Rather than statistical significance of group-level differences, effect size should be used as an indicator of a variable's biomarker potential. The minimal required effects size for individual biomarkers-a Cohen's d of 1.25-is large. This calls for multivariable approaches, in which combining multiple variables with smaller effect sizes could increase the overall effect size and discriminative power.

Association between serum iron markers, iron supplementation and cardiovascular morbidity in pre-dialysis chronic kidney disease.

The optimal range of serum iron markers and usefulness of iron supplementation are uncertain in patients with pre-dialysis chronic kidney disease (CKD). We investigated the association between serum iron indices and risk of cardiovascular disease (CVD) events and the effectiveness of iron supplementation using Chronic Kidney Disease Japan Cohort data. We included 1416 patients ages 20-75years with pre-dialysis CKD. The tested exposures were serum transferrin saturation and serum ferritin levels and the outcome measures were any cardiovascular event. Fine-Gray subdistribution hazard models were used to examine the association between serum iron indices and time to events. The multivariable fractional polynomial interaction approach was used to evaluate whether serum iron indices were effect modifiers of the association between iron supplementation and cardiovascular events. The overall incidence rate of CVD events for a median of 4.12years was 26.7 events/1000 person-years. Patients with serum transferrin saturation <20% demonstrated an increased risk of CVD [subdistribution hazard ratio (HR) 2.13] and congestive heart failure (subdistribution HR 2.42). The magnitude of reduction in CVD risk with iron supplementation was greater in patients with lower transferrin saturations (P=.042). Maintaining transferrin saturation >20% and adequate iron supplementation may effectively reduce the risk of CVD events in patients with pre-dialysis CKD.

Causal relationships between the gut microbiome, blood lipids, and heart failure: a Mendelian randomization analysis.

Studies have linked gut microbiome and heart failure (HF). However, their causal relationships and potential mediating factors have not been well defined. To investigate the causal relationships between the gut microbiome and HF and the mediating effect of potential blood lipids by using genetics. We performed a bidirectional and mediation Mendelian randomization (MR) study using summary statistics from the genome-wide association studies of gut microbial taxa (Dutch Microbiome Project, n = 7,738), blood lipids (UK Biobank, n = 115,078), and a meta-analysis of HF (115,150 cases and 1,550,331 controls). We applied the inverse-variance weighted estimation method as the primary method, with several other estimators as complementary methods. The multivariable MR approach based on Bayesian model averaging (MR-BMA) was used to prioritize the most likely causal lipids. Six microbial taxa are suggestively associated with HF causally. The most significant taxon was the species Bacteroides dorei (odds ratio = 1.059, 95% confidence interval [CI] = 1.022 - 1.097, P value = 0.0017). The MR-BMA analysis showed that apolipoprotein B (ApoB) was the most likely causal lipid for HF (the marginal inclusion probability = 0.717, P value = 0.005). The mediation MR analysis showed that ApoB mediated the causal effects of species Bacteroides dorei on HF (proportion mediated = 10.1%, 95% CI = 0.2% - 21.6%, P value = 0.031). The study suggested a causal relationship between specific gut microbial taxa and HF and that ApoB might mediate this relationship as the primary lipid determinant of HF.

Determination of 24,25-dihydroxyvitamin D3 in Vitamin D External Quality Assessment Scheme samples using a reference measurement procedure

Ninety archived human serum samples from the Vitamin D External Quality Assessment Scheme (DEQAS) were analyzed using a reference measurement procedure (RMP) based on isotope dilution liquid chromatography – tandem mass spectrometry (ID LC-MS/MS) for the determination of 24,25-dihydroxyvitamin D3 [24,25(OH)2D3]. These 24,25(OH)2D3 results, in conjunction with concentration values assigned using RMPs for 25-hydroxyvitamin D2 [25(OH)D2] and 25-hydroxyvitamin D3 [25(OH)D3], provide a valuable resource for assessing the accuracy of measurements for 24,25(OH)2D3 and for investigating the relationship between 24,25(OH)2D3 and 25(OH)D3. Results for 24,25(OH)2D3 using the RMP were compared to DEQAS consensus values demonstrating that the consensus values were not sufficient to assess the accuracy of measurements among different laboratories and methods. A multivariable regression analysis approach using historical DEQAS consensus values for various total 25(OH)D assays was used to assess the contribution of 24,25(OH)2D3 concentration on the assay response. The response of several ligand binding assays for total 25(OH)D was shown to be impacted by the presence of 24,25(OH)2D3.

Humoral response after a BNT162b2 heterologous third dose of COVID-19 vaccine following two doses of BBIBP-CorV among healthcare personnel in Peru

BackgroundThe inactivated virus vaccine, BBIBP-CorV, was principally distributed across low- and middle-income countries as primary vaccination strategy to prevent poor COVID-19 outcomes. Limited information is available regarding its effect on heterologous boosting. We aim to evaluate the immunogenicity and reactogenicity of a third booster dose of BNT162b2 following a double BBIBP-CorV regime. MethodsWe conducted a cross-sectional study among healthcare providers from several healthcare facilities of the Seguro Social de Salud del Perú - ESSALUD. We included participants two-dose BBIBP-CorV vaccinated who presented a three-dose vaccination card at least 21 days passed since the vaccinees received their third dose and were willing to provide written informed consent. Antibodies were determined using LIAISON® SARS-CoV-2 TrimericS IgG (DiaSorin Inc., Stillwater, USA). Factors potentially associated with immunogenicity, and adverse events, were considered. We used a multivariable fractional polynomial modeling approach to estimate the association between anti-SARS-CoV-2 IgG antibodies’ geometric mean (GM) ratios and related predictors. ResultsWe included 595 subjects receiving a third dose with a median (IQR) age of 46 [37,54], from which 40% reported previous SARS-CoV-2 infection. The overall geometric mean (IQR) of anti-SARS-CoV-2 IgG antibodies was 8,410 (5,115 – 13,000) BAU/mL. Prior SARS-CoV-2 history and full/part-time in-person working modality were significantly associated with greater GM. Conversely, time from boosting to IgG measure was associated with lower GM levels. We found 81% of reactogenicity in the study population; younger age and being a nurse were associated with a lower incidence of adverse events. ConclusionsAmong healthcare providers, a booster dose of BNT162b2 following a full BBIBP-CorV regime provided high humoral immune protection. Thus, SARS-CoV-2 previous exposure and working in person displayed as determinants that increase anti-SARS-CoV-2 IgG antibodies.

Academic cheating as planned behavior: the effects of perceived behavioral control and individualism-collectivism orientations

AbstractTo inform interventions against academic cheating among college students, the study tests the moderating role of the construct of perceived behavioral control as originally proposed yet seldom tested in the Theory of Planned Behavior, and further tests the cultural boundary conditions for this moderating role with a focus on the four horizontal-vertical individualism-collectivism orientations. Using multicampus survey data collected from 2293 Chinese undergraduate students, the moderation analyses suggest a significant and negative joint effect of perceived behavioral control with the construct of subjective norm and a positive yet insignificant joint effect with the construct of attitude towards cheating. Further moderated moderation analyses identify a pattern from comparing the four significant three-way interactions: the positive effects of attitude towards cheating and subjective norm on academic cheating are stronger under the conditions of a combination of low subjective norm with low horizontal individualism and horizontal collectivism, respectively. The study contributes to a nuanced understanding of the utility of Theory of Planned Behavior in predicting academic cheating and supports a multivariable intervention approach that closely integrates administrative measures with students’ attitudinal and normative beliefs with a concern for the subtle yet significant influences of cultural orientations.

Multi-variable approach to groundwater vulnerability elucidation: A risk-based multi-objective optimization model

Groundwater vulnerability mapping is essential in environmental management since there is an increase in contamination caused by excessive population growth. However, to our knowledge, there is rare research dedicated to optimizing the groundwater vulnerability models, considering risk conditions, using a robust multi-objective optimization algorithm coupled with a multi-criteria decision-making model (MCDM). This study filled this knowledge gap by developing an innovative hybrid risk-based multi-objective optimization model using three distinguished models. The first model generated two series of scenarios for rate modifications associated with two common contaminations, Nitrate and Sulfate, based on susceptibility index (SI) and DRASTICA models. The second model was a multi-objective optimization framework using non-dominated sorting genetic algorithms- II and III (NSGA-II and NSGA-III), considering uncertainties in the input rates by the conditional value-at-risk (CVaR) technique. Finally, the third model was a well-known MCDM model, the COmplex PRoportional ASsessment (COPRAS), which identified the best compromise solution among Pareto-optimal solutions for weights of the contaminations. Regarding the Sulfate's results, although the optimized DRASTICA model led to the same correlation as the initial model, 0.7, the optimized SI model increased the correlation to 0.8 compared to the initial model as 0.58. For the Nitrate, both the optimized SI and the optimized DRASTICA models raised the correlation to 0.6 and 0.7 compared to the initial model with a correlation value of 0.36, respectively. Hence, the best and the lowest correlation among the optimized models were between SI and Sulfate concentration and SI and Nitrate concentration, respectively.

Modelling of salt intake reduction by incorporation of umami substances into Japanese foods: a cross-sectional study

BackgroundEvidence has demonstrated that excess sodium intake is associated with development of several non-communicable diseases. The main source of sodium is salt. Therefore, reducing salt intake in foods is an important global public health effort to achieve sodium reduction and improve health. This study aimed to model salt intake reduction with 'umami' substances among Japanese adults. The umami substances considered in this study include glutamate or monosodium glutamates (MSG), calcium diglutamate (CDG), inosinate, and guanylate.MethodsA total of 21,805 participants aged 57.8 years on average from the National Health and Nutrition Survey was used in the analysis. First, we employed a multivariable linear regression approach with overall salt intake (g/day) as a dependent variable, adjusting for food items and other covariates to estimate the contribution of salt intake from each food item that was selected through an extensive literature review. Assuming the participants already consume low-sodium products, we considered three scenarios in which salt intake could be reduced with the additional umami substances up to 30%, 60% and 100%. We estimated the total amount of population-level salt reduction for each scenario by age and gender. Under the 100% scenario, the Japan’s achievement rates against the national and global salt intake reduction goals were also calculated.ResultsWithout compromising the taste, the 100% or universal incorporation of umami substances into food items reduced the salt intake of Japanese adults by 12.8–22.3% at the population-level average, which is equivalent to 1.27–2.22 g of salt reduction. The universal incorporation of umami substances into food items changed daily mean salt intake of the total population from 9.95 g to 7.73 g: 10.83 g to 8.40 g for men and 9.21 g to 7.17 g for women, respectively. This study suggested that approximately 60% of Japanese adults could achieve the national dietary goal of 8 g/day, while only 7.6% would meet the global recommendation of 5.0 g/day.ConclusionsOur study provides essential information on the potential salt reduction with umami substances. The universal incorporation of umami substances into food items would enable the Japanese to achieve the national dietary goal. However, the reduced salt intake level still falls short of the global dietary recommendation.

Adolescent suicidal behaviour in Namibia: a cross-sectional study of prevalence and correlates among 3,152 school learners aged 12–17 years

BackgroundWhile adolescent suicidal behaviour (ideation, planning, and attempt) remains a global public health concern, available county-specific evidence on the phenomenon from African countries is relatively less than enough. The present study was conducted to estimate the 12-month prevalence and describe some of the associated factors of suicide behaviour among school-going adolescents aged 12–17 years old in Namibia.MethodsParticipants (n = 4531) answered a self-administered anonymous questionnaire developed and validated for the nationally representative Namibia World Health Organization Global School-based Student Health Survey conducted in 2013. We applied univariate, bivariable, and multivariable statistical approaches to the data.ResultsOf the 3,152 analytical sample, 20.2% (95% confidence interval [CI]: 18.3–22.2%) reported suicidal ideation, 25.2% (95% CI: 22.3–28.4%) engaged in suicide planning, and 24.5% (95% CI: 20.9–28.6%) attempted suicide during the previous 12 months. Of those who attempted suicide, 14.6% (95% CI: 12.5–16.9%) reported one-time suicide attempt, and 9.9% (95% CI: 8.1–12.1%) attempted suicide at least twice in the previous 12 months. The final adjusted multivariable models showed physical attack victimisation, bullying victimisation, loneliness, and parental intrusion of privacy as key factors associated with increased likelihood of suicidal ideation, planning, one-time suicide attempt, and repeated attempted suicide. Cannabis use showed the strongest association with increased relative risk of repeated attempted suicide.ConclusionThe evidence highlights the importance of paying more attention to addressing the mental health needs (including those related to psychological and social wellness) of school-going adolescents in Namibia. While the current study suggests that further research is warranted to explicate the pathways to adolescent suicide in Namibia, identifying and understanding the correlates (at the individual-level, family-level, interpersonal-level, school context and the broader community context) of adolescent suicidal ideations and non-fatal suicidal behaviours are useful for intervention and prevention programmes.

Consumer perception of plant-based yoghurt: Sensory drivers of liking and emotional, holistic and conceptual associations

Plant-based (PB) yoghurts is a rapidly expanding food category with the potential to reduce many of the negative environmental impacts associated with the farming of dairy cattle and related greenhouse gas emissions. Within the context of growing consumer demand for PB products, this research aimed to identify the main drivers of consumer acceptance of PB yoghurts through data drawn from a consumer study of 113 adult New Zealand participants who tasted a representative range of commercially available vanilla-flavoured PB yoghurts, and provided sample evaluations using a multi-variable measurement approach comprised of liking ratings, emotional responses, sensory characterisations, and holistic / conceptual perceptions. The primary finding of this study was that the overall acceptability of currently available PB yoghurts is low, leading to poor attitudes and low willingness to consume PB yoghurts. The examined products were characterised by the presence of several sensory attributes that negatively impacted consumer liking, either because they were unexpected or because their intensity level was too high. Among the main sensory issues identified were perceived sourness (acidity), lumpy appearance and non-white colour. In contrast, vanilla flavour and a creamy/smooth texture were identified as the main drivers of liking. The multi-response approach used in this study enabled a comprehensive characterisation of the products. One of the key insights gained was that negative emotional activation, caused by the presence of unexpected sensory attributes in the samples, was the main driver of product rejection. This was likely due to the disparity between consumers’ sensory expectations, formed primarily based on their experience with dairy yoghurts, and the actual experience upon tasting the PB yoghurts. Overall, the findings indicate that the sensory properties of currently available PB yoghurts are a significant barrier to their adoption by most consumers and that addressing these sensory deficiencies is essential to achieving mainstream market acceptance of these products.

Is Economic Growth Good for Population Health? A Critical Review.

The online version contains supplementary material available at 10.1007/s42650-023-00072-y.

Stability Augmentation in Lateral Directional Dynamics: A Multivariable Approach

This paper delves into the concept of stability augmentation in lateral-directional dynamics, focusing on a multivariable approach. In aircraft control systems, ensuring lateral-directional stability is crucial for safe and efficient flight. The primary objective is to examine the feedback control system's role in enhancing stability and how it interacts with the aircraft's inherent dynamics. We begin by exploring the basic augmentation system for lateraldirectional dynamics, which includes the feedback of body-axis roll rate to ailerons and yaw rate to the rudder, commonly referred to as the yaw damper. One of the key challenges addressed in this paper is the need to overcome the interference caused by the yaw damper when coordinating turns. This interference results from the constant nonzero yaw rate present during coordinated turns. To address this issue, the concept of "transient rate feedback" is introduced, which uses a washout filter to differentiate the feedback signal and minimize its effect during steady-state conditions. The paper presents mathematical models and transfer functions that describe the behavior of the lateral-directional augmentation system. It discusses the impact of different parameters, such as the time constants of actuators and washout filters, on the system's performance. The design of the feedback loops for roll and yaw control is elaborated upon, emphasizing the trade-offs between roll response, dutch roll damping, and roll-yaw coupling. Simulation results are used to evaluate the effectiveness of the stability augmentation system in improving the aircraft's roll response and dutch roll damping under varying flight conditions. The paper concludes with insights into the challenges and benefits of multivariable control system design for lateral-directional stability augmentation in aircraf