Binary Logistic Regression Model Research Articles

Hazard functioning modeling for dextrose fluids associated hemodilution; Cox-regressional analysis for patients’ Hematocrit Hemoglobin Ratio

Aims: This study looks at the cox-regressional relationships between hematocrit to hemoglobin ratio (HHR) and a group of outcomes of interest (cOI). These outcomes include death from any cause, acute myocardial infarction, stroke, and severe dilutional hyponatraemia incidence. Additionally other outcome of interest in this study will be prolongation of admission days, infection rate, acute kidney injury, and mandating the transition to the critical unit and mechanical ventilation intubation. The study also will investigate the performances of the tested ratio and will explore their sensitivity, specificity, and accuracy indexes. Methods: Between 2018 and 2022, a retrospective study was conducted at the King Hussein Medical Centre in Amman, Jordan, involving 926 patients. The study aimed to determine the potential risk of dilution of red blood cells in circulation caused by dextrose-containing fluids in patients with chronic kidney disease. The study aimed to determine the ideal threshold levels of the investigated ratio (HHR) to enhance clinical outcomes and safety margins, particularly in patients with severe renal impairment or chronic kidney disease in a hospital setting. The study included patients with fluctuating kidney function, renal replacement therapy, uncontrolled diabetes, and conditions necessitating specific fluid regimens. The study used binary logistic regression and cox-regression proportional hazard modelling to examine the correlation between the hematocrit to haemoglobin ratio and the composite outcomes of interest (cOI) in patients from Jordan. The findings suggest that higher cOI likelihood indicates a more advantageous condition, while lower values suggest a less advantageous condition. Results: A retrospective study at the KHMC in Amman, Jordan, involved 1306 patients from 2018 to 2022. The study focused on the hematocrit to haemoglobin ratio (HHR) and achieved correct classification rates of 70.8%. The best HHR was 2.555:1, with a 42.8% chance of occurring at this level. Cox-Regression Proportional Hazard Modelling revealed a censored percentage of 83.4% in HHR>2.555 stratum and 51.5% in HHR≤2.555 stratum. The study found a high percentage of HD patients processed in the analysis. Conclusion: Intravenous dextrose fluids associated hemodilutional state is linked to all-cause mortality in admitted medically and surgically patients and cardiovascular death. Low ratio increases the risk. Factors such as malnutrition and kidney function loss contribute to prognosis. Future studies should focus on mechanistic pathways, optimal targets, age, and sociodemographic factors.

A cross sectional study measuring injury mortality and its associated factors among adult patients in comprehensive specialized hospitals in Amhara National Regional State, Ethiopia

Background: Injury has become a life-threatening community health problem related to vital morbidity and mortality worldwide. Approximately 90% of injury-related deaths occurred in low- and middle-income countries. There is limited data that addresses the outcomes of injuries in adult trauma patients at the time of discharge to improve the outcome of trauma care in developing countries, including Ethiopia. Therefore, this study aimed to determine the mortality following injury and its associated factors among adult patients in comprehensive specialized hospitals in Amhara’s national regional state. Methods: An institution-based cross-sectional study was conducted among 596 adult trauma patients admitted between January 1, 2018 and December 30, 2020.. A systematic random sampling technique was employed to select the study participants. Data were collected from patient charts and registry books by using a data extraction tool. Data were entered into Epi-data version 4.6, and analysis was done using Stata version 16. The binary logistic regression model was fitted, and both bi-variable and multi-variable logistic regression analyses were employed. Result: A total of 581 adult trauma patient charts with a recorded rate of 97.5% were included in the final analysis. The overall mortality outcome of injury at discharge was found to be 8.3% (95% CI: 6%–10.5%). Age 26–40 years [AOR: 3.35 (95% CI: 1.35–8.33)], revised trauma score 10 [AOR: 3.11, (95% CI: 1.39–6.99)], duration of time before arrival in hospital >24 hours [AOR: 3.61 (95% CI: 1.18–11.02)], and surgical management in hospital [AOR: 0.25 (95% CI: 0.12–0.54)] were predictors of mortality in patients with injuries. Conclusion: In this study, the mortality outcome of injury is considerably high, and the middle age group, late presentation to the hospital, lower revised trauma score, and surgical management were significantly associated with the mortality outcome of injury on discharge from the hospital. Therefore, it is better if clinicians emphasize traumatically injured patients, especially for middle age groups, and lower revised trauma scores.

Willingness to join community-based health insurance and its associated factors among households in Nekemte City, Ethiopia. A community-based cross-sectional study

IntroductionEthiopia has been implementing community-based health insurance programs since 2011 to improve health care financing system. However, the prevalence of household willingness to join the community-based health insurance (CBHI) program and its associated factors are less explored in urban area. Therefore, this study was aimed to assess the prevalence of willingness to join community-based health insurance program and its associated factors among households in Nekemte City, Ethiopia.MethodsA community-based cross-sectional study was conducted on 422 randomly selected households in Nekemte City, Ethiopia. Bivariate and multivariable analyses were performed to see the association between the independent and outcome variables using binary logistic regression model. Association was described using an adjusted odd ratio (AOR) and a 95% confidence interval (CI). Finally, p-value < 0.05 was considered the cut-off point for declaring a significant.ResultsAmong 422 study participants, 320 (75.83%) [95% CI = 71.5-79.8%)] of the households were willing to join community-based health insurance program. The willingness to join for community-based health insurance was 3.11 times more likely among households who were in the richest quintile (AOR = 3.11; 95% CI = 1.08–8.93), 3.4 times more likely among those who were merchants (AOR = 3.40;1.33, 8.69), 2.52 times more likely among those who had history of chronic illness in the household (AOR = 2.52; 95% CI = 1.43–4.45), 4.09 times more likely among those who had the awareness about the scheme (AOR = 4.09; 95% CI = 1.97–8.47) and 3.29 times more likely among those who had the experience of borrow for medical care (AOR = 3.29; 95% CI = 1.48–7.30).ConclusionNearly three fourth of the households were willing to join community-based health insurance program, however, about one fourth of households were not willing, which is a significant public health problem. Being merchant, having awareness about the scheme, being in the richest wealth quintile, having experience of borrowing for medical care, and having history of chronic illness in the household were factors found to be significantly associated with willingness to join community based health insurance in the study area. Therefore, strengthening awareness creation at community level about the benefit package and principle of the program would increase their demand for the community-based health insurance scheme.

Nonlinear association of fibrinogen levels with functional prognosis in patients with acute ischemic stroke: a prospective cohort study

ObjectiveFibrinogen, essential in primary hemostasis, platelet aggregation, and leukocyte-endothelial interactions, is also associated with a heightened risk of acute ischemic stroke (AIS). However, its influence on AIS patient outcomes is unclear. This study examines the correlation between fibrinogen levels and the risk of unfavorable outcomes three months post-AIS.MethodsThis is a secondary analysis of a prospective cohort study conducted in Korea. The sample consisted of 1851 AIS patients who received treatment at a Korean hospital between January 2010 and December 2016. Statistical models were established to understand the relationship between fibrinogen levels(mg/dL) and unfavorable outcomes(mRs ≥ 3), including logistic regression models, Generalized Additive Models (GAM), and smooth curve fitting (penalized splines). The log-likelihood ratio test has been utilized to evaluate the best fit. To ensure the robustness of the results, sensitivity analyses were conducted by reanalyzing the relationship after excluding participants with TG > 200 mg/dl and BMI > 25 kg/m2. Subgroup analyses were also performed to assess whether influencing factors modify the association between fibrinogen levels and unfavorable outcomes.ResultsAfter adjusting for multiple covariates including age, BMI, sex, LDL-c, TG, HGB, HDL-c, BUN, FPG, ALB, PLT, AF, hypertension, smoking, DM, mRs score at admission, the binary logistic regression model demonstrated revealed a significant positive association between fibrinogen levels and the risk of unfavorable outcomes in AIS patients (OR = 1.215, 95% CI: 1.032–1.429, p = 0.019). Sensitivity analyses supported these findings, with similar ORs observed in subsets of patients with TG < 200 mg/dL (OR = 1.221, 95% CI: 1.036–1.440) and BMI < 25 kg/m2 (OR = 1.259, 95% CI: 1.051–1.509). Additionally, the relationship between fibrinogen levels and outcomes was nonlinear, with a critical threshold of 2.74 g/L. Below the inflection point, the OR for unfavorable outcomes was 0.666 ((95% CI: 0.360, 1.233, p = 0.196), whereas above it, the OR increased to 1.374 (95% CI: 1.138, 1.659).ConclusionsThis study has provided evidence of a positive and nonlinear correlation between fibrinogen levels and 3-month poor functional outcomes in patients with AIS. When fibrinogen levels exceeded 2.74 g/L, a significant and positive association was observed with the risk of poor outcomes. This study provides a further reference for optimizing rehabilitation exercises and facilitating clinical counseling in patients with acute ischemic stroke.

Comparative Analysis of the Predictive Performance of an ANN and Logistic Regression for the Acceptability of Eco-Mobility Using the Belgrade Data Set

To solve the problem of environmental pollution caused by road traffic, alternatives to vehicles with internal combustion engines are often proposed. As such, eco-mobility microvehicles have significant potential in the fight against environmental pollution, but only on the condition that they are widely accepted and that they replace the vehicles that predominantly pollute the environment. With this in mind, this study aims to elucidate the main variables that influence the acceptability of these vehicles, using prediction models based on binary logistic regression and a multilayer artificial neural network—a multilayer perceptron (ANN). The data of a random sample obtained via an online questionnaire, answered by 503 inhabitants of Belgrade (Serbia), were used for training and testing the model. A multilayer perceptron with 9 and 7 neurons in two hidden layers, a hyperbolic tangent activation function in the hidden layer, and an identity function in the output layer performed slightly better than the binary logistic regression model. With an accuracy of 85%, a precision of 79%, a recall of 81%, and an area under the ROC curve of 0.9, the multilayer perceptron model recognized the influential variables in predicting acceptability. The results of the model indicate that a respondent’s relationship to their current environmental pollution, the frequency of their use of modes of transport such as bicycles and motorcycles, their mileage for commuting, and their personal income have the greatest influence on the acceptability of using eco-mobility vehicles.

COVID-19 Associated Mucormycosis and Risk Factors: A Case-Control Study from Turkey

Background: Mucormycosis, a fatal fungal infection, has increased during the COVID-19 pandemic and posed significant challenges for clinicians. Objectives: Our research focused on identifying the clinical traits of patients with COVID-19-associated mucormycosis (CAM), comparing them with a control group, and identifying risk factors for the development of CAM. Methods: Our study was conducted on 39 CAM patients and 78 control patients from September 2020 to October 2022 at a tertiary education center and regional hospital. The control group was selected blindly in a 1:2 ratio among patients who did not develop mucormycosis, were hospitalized due to COVID-19, and were either discharged or deceased. The control group was matched to the case group regarding age and hospitalization date. To test potential risk factors for CAM, we performed a binary logistic regression analysis. The variables included in the multivariate binary logistic regression model were gender, diabetes, cumulative steroid dose (dexamethasone equivalent), duration of steroid treatment, and tocilizumab/anakinra treatment. Results: In our study, 39 patients were diagnosed with CAM. The average age of the patients was 66 ± 11.5 years. Of the patients, 54.7% (n = 64) were male, with a statistically significantly higher proportion of men in the CAM group (74.4% vs. 44.9%, P = 0.003). The diabetes rate was 51.3% (n = 60) among all patients, and it was higher in the CAM group (69.2% vs. 42.3%, P = 0.006). Regarding in-hospital mortality, the rate was higher in the CAM group (56.4% vs. 14.1%, P &lt; 0.001). The median length of stay in the hospital was 37 days for the CAM group and 10 days for the control group (P &lt; 0.001). The cumulative steroid dose was elevated in the CAM group compared to the control group (191 ± 61.4 mg vs. 117 ± 69.8 mg, P &lt; 0.001). The duration of steroid treatment was 16.5 ± 6.2 days in the CAM group, compared to 9.8 ± 4.7 days in the control group (P &lt; 0.001). Among CAM cases, paranasal involvement was the most common (56.4%), followed by rhino-orbital involvement (33.3%). In binary logistic regression analysis, male gender (OR, 3.9; 95% CI, 1.4 – 11.3), diabetes mellitus (OR, 4.4; 95% CI, 1.5 – 12.4), more than ten days of steroid use (OR, 5.5; 95% CI, 1.3 – 22.4), and tocilizumab/anakinra use (OR, 0.23; 95% CI, 0.06 – 0.8) were identified as risk factors for the development of CAM (p values 0.011, 0.005, 0.019, and 0.020, respectively). Conclusions: Male gender, diabetes mellitus, and steroid use for more than ten days were identified as positive risk factors, while tocilizumab/anakinra use was identified as a negative risk factor for the development of CAM.

Prevalence and determinants of moderate-to-severe anaemia in the third trimester of pregnancy: a multicenter cross-sectional study in Lagos, Nigeria

The high burden of anaemia during pregnancy underscores the urgent need to gain a comprehensive understanding of the factors contributing to its widespread occurrence. Our study assessed the prevalence and the trends of moderate-to-severe anaemia (MSA) in late pregnancy (28 to 36 weeks) and then investigated the key determinants driving this prevalence among women in Lagos, Nigeria. We conducted a secondary data analysis involving 1216 women enrolled in the Predict-PPH study between January and March 2023. We employed a multivariate binary logistic regression model with a backward stepwise selection approach to identify significant predictors of MSA. The study revealed a 14.5% prevalence of MSA during pregnancy. Independent predictors of MSA included having given birth to two or more children (adjusted odds ratio = 1.46, 95% confidence interval: 1.03–2.07), having a maternal body mass index (BMI) of 28 kg/m2 or higher (adjusted odds ratio = 1.84, 95% confidence interval: 1.29–2.61), having less than tertiary education (adjusted odds ratio = 1.51, 95% confidence interval: 1.08–2.11), and being unemployed (adjusted odds ratio = 1.97, 95% confidence interval: 1.19–3.26). It is crucial for pregnant women, particularly those with higher parities and elevated BMI, to be monitored regularly for anaemia and its consequences during their antenatal care. Additionally, addressing the link between low education, unemployment, and anaemia necessitates comprehensive strategies that empower women in terms of education and economic status to enhance the overall well-being of individuals and communities, ultimately reducing the prevalence of anaemia and associated health issues in pregnancy.

A non-destructive predictive model for estimating the freshness/spoilage of packaged chicken meat using changes in drip metabolites

This study investigates the possibility of utilizing drip as a non-destructive method for assessing the freshness and spoilage of chicken meat. The quality parameters [pH, volatile base nitrogen (VBN), and total aerobic bacterial counts (TAB)] of chicken meat were evaluated over a 13-day storage period in vacuum packaging at 4 °C. Simultaneously, the metabolites in the chicken meat and its drip were measured by nuclear magnetic resonance. Correlation (Pearson's and Spearman's rank) and pathway analyses were conducted to select the metabolites for model training. Binary logistic regression (model 1 and model 2) and multiple linear regression models (model 3-1 and model 3-2) were trained using selected metabolites, and their performance was evaluated using receiver operating characteristic (ROC) curves. As a result, the chicken meat was spoiled after 7 days of storage, exceeding 20 mg/100 g VBN and 5.7 log CFU/g TAB. The correlation analysis identified one organic acid, eight free amino acids, and five nucleic acids as highly correlated with chicken meat and its drip during storage. Pathway analysis revealed tyrosine and purine metabolism as metabolic pathways highly correlated with spoilage. Based on these findings, specific metabolites were selected for model training: ATP, glutamine, hypoxanthine, IMP, tyrosine, and tyramine. To predict the freshness and spoilage of chicken meat, model 1, trained using tyramine, ATP, tyrosine, and IMP from chicken meat, achieved a 99.9 % accuracy and had an ROC value of 0.884 when validated using drip metabolites. This model 1 was improved by training with tyramine and IMP from both chicken meat and its drip (model 2), which increased the ROC value for drip metabolites from 0.884 to 0.997. Finally, selected two metabolites (tyramine and IMP) can predict TAB and VBN quantitatively through models 3-1 and 3-2, respectively. Therefore, the model developed using metabolic changes in drip demonstrated the capability to non-destructively predict the freshness and spoilage of chicken meat at 4 °C. To make generic predictions, it is necessary to expand the model's applicability to various conditions, such as different temperatures, and validate its performance across multiple chicken batches.

Measles second dose vaccine uptake and its associated factors among children aged 24–35 months in Northwest Ethiopia, 2022

Measles is a major public health problem in under-five children, leading to lifelong complications. Therefore, the study aimed to assess the magnitude of measles second-dose vaccine uptake and its determinants among children aged 24–35 months in Northwest Ethiopia. A community-based cross-sectional study was conducted among 418 children aged 24–35 months in Northwest Ethiopia between January 2022 and February 2022. A simple random sampling technique was used to access study subjects. A binary logistic regression model was employed. An adjusted odd ratio with a 95% confidence interval (CI) and a p-value < 0.05 was used to declare significant predictors of measles second dose vaccine uptake. The magnitude of the measles second dose vaccine uptake among children aged 24–35 months was 41.39%. Postnatal care visits (AOR: 4.78, CI 1.49, 15.34), child vaccination status of other scheduled vaccines (AOR: 3.88, CI 2.23, 6.73), awareness of the measles second dose vaccine and its schedule (AOR: 8.924, CI 5.27, 15.09), and distance from the vaccination center (AOR: 0.21, CI 0.06, 0.77) were significantly associated with measles second dose vaccine uptake. The uptake of measles second dose vaccine in the study area was low. Therefore, health workers and other partners should initiate awareness creation programs for mothers/caretaker to improve the uptake of measles second dose vaccine.

Predictive modelling on the effects of the critical parameters in grain storage systems: A case study in the Philippines

Grain storage system plays a crucial role in preserving the quality and quantity of various grains including wheat kernels. Inefficient storage systems can result in spoilage, loss of quality, and reduction in quantity, leading to significant financial losses in the company. The quality of grains storage is influenced by several factors, including moisture content, protein content and falling number. In this study, the threshold, main, and interactions effects of critical parameters the identified critical parameters on grain storage quality were determined and modelled using ROC curve analysis and binary logistic regression analysis. The ROC curve analysis revealed a AUC of 0.992, 0.952, and 0.991 for moisture content, protein content, and falling number, respectively. Threshold values were also calculated and upon evaluation, the accuracies for all critical parameters yielded a significantly excellent result. The main effects of the critical parameters also significantly predicted the grain storage quality with χ2 of 353.26, p-value of 0.000, and R2 value of 61.81%. Furthermore, the interaction effects of the three critical parameters exhibited the greatest effect on grain storage quality. Through binary logistic regression model, the optimum quality grain storage is achieved at a moisture level of 11.42, protein level of 13.99, and a falling number of 443.55. These findings can be used as basis for the selected milling company and other grain storage companies to monitor these critical parameters and ensure a safe storage and quality grains. The study can be furthered improved by investigating other parameters that can determine grain storage quality.

Core characteristics of sublingual veins analysis and its relationship with hypertension.

The sublingual vein (SV) is a specialized diagnostic method used in Traditional Chinese Medicine (TCM). Despite its ability to objectively reflect blood flow, SV is often overlooked in clinical practice. This study aims to analyze the core characteristics of SV and investigate the in-depth relationship between its digital characteristics and hypertension. The goal is to find a link between SV and hypertension and break out of the current situation. Modern digital analysis techniques were applied to the traditional SV diagnostic theory. In a controlled study with 204 participants, the digital characteristics of SV were documented using TFDA-1, and its color value was analyzed using TDAS. Morphological characteristics of SV, such as trunklength, width, and tortuosity, were examined by combining computer vision with expert interpretation. This involved the application of automatic ranging methods and a rectangular approximation algorithm, which are novel approaches in the field of TCM. The t-test and Mann-Whitney U test were used to analyze the digital characteristics of SV in hypertension. Binary logistic regression and neural network models were established using machine learning to explore the deep relationship between SV characteristics and hypertension. There was a significant difference of the tortuosity of SV between the two groups (Z=-2.629, p= 0.009). The results revealed thick width of SV (OR = 2.64, 95% CI: 1.02-6.79) was the risk factor for hypertension. Addition of SV characteristics improved overall percent correct for hypertension prediction to 80%. TCM method of diagnosis of SV has been greatly expanded in terms of technical means, and the close relationship between SV and hypertension has been found in clinical data.

Attitudes towards snakebite health education and associated factors among residents in China: A national cross-sectional study.

This study aimed to investigate attitudes towards health education on snakebites and to identify the influencing factors among Chinese residents. Additionally, we proposed effective health education strategies for snakebite management. Between May 2022 and February 2023, we conducted a nationwide cross-sectional questionnaire survey using a multistage sampling method with supplementary snowball sampling. We used descriptive analysis, χ2 tests, and univariable and multivariable binary logistic regression models to analyse the data. We included 56 669 respondents in the analysis. The average score for snakebite knowledge was 12.13 ± 5.26 points, with a maximum score of 28. Among the respondents, 72.66 and 63.03% of the residents believed that it was necessary to disseminate knowledge about snakebites and expressed a willingness to receive snakebite training, respectively. Respondents from the northeast region, respondents with a higher education level, and respondents with higher scores for snakebite knowledge, health knowledge, health skills, and social-psychological adjustment skills exhibited more positive attitudes towards snakebite knowledge dissemination and training. Conversely, respondents from eastern or southern China, respondents older than 60, and respondents who lived in rudimentary housing conditions showed a lower perception of the need for snakebite knowledge dissemination and were less willing to participate in snakebite knowledge and skill training. Generally, Chinese residents have positive attitudes towards snakebite knowledge dissemination and training. However, the public lacks sufficient knowledge about snakebites. Therefore, we should pay close attention to areas south of the Yangtze River to strengthen snakebite health education using engaging formats that align with residents' interests, such as short videos or television programmes, in an attempt to and ultimately improve health literacy and prevention awareness.

Food Insecurity and Outpatient Care Utilization Among Indonesian Older Adults.

This study aims to examine the complex relationship between household food insecurity and outpatient care utilization among Indonesian older adults. Individual-level data from the 2020 National Socioeconomic Survey (SUSENAS; n = 29 950 older adults aged 60 and over in poor self-rated health who are unable to do daily activities) and environmental-level data (n = 84 096 villages in a data aggregation across 514 municipalities) from the 2021 Village Potential Data Census Collection Survey (PODES) are used in a two-level binary logistic regression model. Older adults who live in severely food insecure households (odds ratio [OR] 1.963; CI [1.658, 2.319]) and lack of health insurance (OR 1.654; CI [1.556, 1.747]) are more likely of not utilizing outpatient care. The interclass correlation coefficient value is 0.162, indicating that primary health care services in every village improve outpatient care utilization. Food insecurity is the major determinant of reduced likelihood of outpatient care utilization, which can be explained by household resource constraints.

COVID-19 vaccine hesitancy among adults in India: A primary study based on health behavior theories and 5C psychological antecedents model.

Despite the significant success of India's COVID-19 vaccination program, a sizeable proportion of the adult population remains unvaccinated or has received a single dose of the vaccine. Despite the recommendations of the Government of India for the two doses of the COVID-19 vaccine and the precautionary booster dose, many people were still hesitant towards the COVID-19 full vaccination. Hence, this study aimed to identify the primary behavioral and psychological factors contributing to vaccine hesitancy. Cross-sectional data was collected via a multi-stage sampling design by using a scheduled sample survey in the Gorakhpur district of Uttar Pradesh, India, between 15 July 2022 to 30 September 2022. This study has utilized three health behavior models-the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and the 5C Psychological Antecedents of vaccination, and employed bivariate and multivariable binary logistic regression model to assess the level of vaccine hesitancy and predictive health behavior of the respondents. Results indicate that among the constructs of the HBM and 5C Antecedents models, "perceived benefits", "confidence" and "collective responsibility" showed a lesser likelihood of COVID-19 vaccine hesitancy. However, in the TPB model constructs, a 'negative attitude towards the vaccine' showed a four times higher likelihood of COVID-19 vaccine hesitancy. From the future policy perspective, this study suggested that addressing the issue of 'negative attitudes towards the vaccine' and increasing the trust or confidence for the vaccine through increasing awareness about the benefits of the vaccination in India may reduce vaccine hesitancy.

The magnitude of stunting and its determinants among late adolescent girls in East Africa: Multilevel binary logistics regression analysis.

Stunting poses a significant health risk to adolescent girls aged 15-19 in low- and middle-income countries, leading to lower education levels, reduced productivity, increased disease vulnerability, and intergenerational malnutrition. Despite the inclusion of adolescent nutrition services in the Sustainable Development Goals, little progress has been made in addressing malnutrition among adolescent girls in several African nations. Limited evidence exists in East Africa due to small sample sizes and methodological limitations. To overcome these constraints, this study utilizes the latest Demographic and Health Survey data to estimate the prevalence and factors influencing stunting among late adolescent girls in ten East African countries. This study utilized the most recent Demographic and Health Survey (DHS) data from 10 East African countries, including a total sample weight of 22,504 late-adolescent girls. A multilevel mixed-effect binary logistic regression model with cluster-level random effects was employed to identify factors associated with stunting among these girls. The odds ratio, along with the 95% confidence interval, was calculated to determine individual and community-level factors related to stunting. A p-value less than 0.05 was considered statistically significant in determining the factors influencing stunting among late-adolescent girls. The prevalence of stunting among late adolescent girls in East Africa was found to be 13.90% (95% CI: 0.13-0.14). Religion, relationship to the head, presence of under-five children in the household, lactating adolescent, marital status, Time to get water source, and country of residence were significantly associated with Stunting. This study highlights the complexity of stunting in East Africa and identifies key factors that need attention to reduce its prevalence. Interventions should focus on improving water access, supporting lactating girls, addressing socioeconomic disparities, promoting optimal care practices, and implementing country-specific interventions to combat stunting and improve adolescent girls' nutrition.

Coffee consumption was associated with a lower prevalence of airflow limitation in postmenopausal women

BackgroundSeveral studies have suggested a potential correlation between menopause and airflow limitation. However, the presence of protective factors in postmenopausal women remains uncertain. Therefore, our study seeks to examine potential protective factors associated with a reduced prevalence of airflow limitation among postmenopausal women. MethodsPostmenopausal women were recruited from the Taiwan Biobank for this cross-sectional study. Airflow limitation was defined by a forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) ratio <0.7. The participants were categorized into two groups: non-coffee drinkers and coffee drinkers, and the association between coffee consumption and airflow limitation was examined using binary logistic regression models. ResultsA total of 8149 women with available information were enrolled. Compared to the non-coffee drinkers, the coffee drinkers had a significantly lower prevalence of airflow limitation (7% vs. 5%). The odds ratio (OR) for airflow limitation was lower in the coffee drinkers than in the non-coffee drinkers (OR = 0.77; 95% confidence interval [CI] = 0.63 to 0.94) after adjusting for confounding factors. We also examined the association between daily coffee consumption in cups and airflow limitation. The women who consumed ≥2 cups of coffee per day had an OR of 0.74 (95% CI = 0.59 to 0.94) compared to those who did not consume coffee. ConclusionsOur results suggest that habitual coffee consumption is associated with a reduction in the prevalence of airflow limitation in postmenopausal women, warranting further prospective studies to explore possible causal effects and mechanisms.

Association between food insecurity and edentulism for older adults: A pilot study.

This pilot study examined the association between food insecurity and edentulism among older adults in Washington State. This study focused on adults aged 50 years and older, who were recruited through seven community-based organizations in Washington State. The exposure variable was food security level (high, marginal, and low/very low food security) assessed using the 10-item U.S. Adult Food Security Survey. The outcome was edentulism, defined as having zero natural teeth. Confounder-adjusted odds ratios (OR) and 95% confidence intervals (CIs) were generated using binary logistic regression models (α = 0.05). Of the 216 participants, 28.7% (n = 62) had low/very low food security and 7.9% (n = 17) had zero teeth. Older adults with low or very low food security had greater odds of being edentulous compared to those with marginal or high food security, although the difference was not statistically significant (OR: 1.39; 95% CI: 0.46, 4.20; p = 0.56). Future research should explore food insecurity-focused interventions aimed at preventing edentulism in older adults in a broader effort to address oral health inequities.

Traditional Vs Modern English Language Teaching Methods: Study Based on a Survey

The study compares traditional and modern English language teaching methods and examines the prevalence and adoption of these methods by English language teachers. The sample consists of 100 English language teachers. The researchers use OLS regression, binary logistic regression and structural equation modelling to establish an association between adopting a particular language teaching method and the characteristics of the language teachers. Results indicate that experienced teachers prefer the social learning method, while less experienced teachers advocate the bilingual, experiential, and listening and observation methods. There are gender differences in accepting these language teaching methods. Female language teachers show an inclination towards the listening and observation method, whereas male teachers ardently favour the bilingual and experiential methods. Regression analysis reveals a higher probability of adoption of bilingual translation methods by non-English educational background teachers. Experienced teachers adopt the Social Learning Method, while less experienced teachers prefer experiential learning and bilingual translation methods more. Results of the path analysis using structural equation modelling indicate that the gender of the teachers mediates their educational background in the adoption of the particular language teaching method.

Phthalate exposure and subfecundity in preconception couples: A nested case-control study

BackgroundPhthalates (PAEs) are endocrine-disrupting chemicals ubiquitously found in the environment. This study aimed to examine the association between exposure of PAEs and subfecundity in preconception couples. MethodsThis is a nested case-control study based on preconception cohort. Preconception couples with intention to conceive were enrolled and followed up until a clinically confirmed pregnancy or 12 menstrual cycles of preparation for conception. A total of 107 couples with subfecundity- time to pregnancy (TTP) more than 12 menstrual cycles, and 144 couples ≤12 cycles were included in the analysis. The levels of PAE metabolites in one spot urine samples were detected and compared between the groups. The weighted quantile sum (WQS) regression model and Bayesian kernel machine regression (BKMR) model were used to examine the joint effects of couples’ exposure to PAEs on subfecundity. ResultsUsing the multivariate binary logistic regression model, compared to the lowest quartile of urinary ∑PAEs concentration group, both preconception females (aOR=2.42, 95% CI: 1.10–5.30, p=0.027) and males (aOR=2.99, 95% CI: 1.36–6.58, p=0.006) in the highest quartile group had an increased risk of subfecundity, and a dose-response relationship was observed between PAEs and the risk of subfecundity. The WQS analyses found that co-exposure to PAE mixture was a risk factor for subfecundity in preconception female (aOR=1.76, 95% CI: 1.38–2.26, p<0.001), male (aOR=1.58, 95% CI: 1.20–2.08, p=0.001), and couple (aOR=2.39, 95% CI: 1.61–3.52, p<0.001). The BKMR model found a positive combined effect of mixed exposure to PAEs on the risk of subfecundity. ConclusionsPAEs increase the risk of subfecundity in preconception couples. Our research reinforced the need of monitoring PAE exposure for the purpose of improving human reproductive health.

Activated clotting time value as an independent predictor of postoperative bleeding and transfusion.

Activated Clotting Time (ACT) is commonly used to monitor anticoagulation during cardiac surgeries. Final-ACT values may be essential to predict postoperative bleeding and transfusions, although ideal values remain unknown. Our aim was to evaluate the utility of ACT as a predictor of postoperative bleeding and transfusion use. Retrospective study (722 patients) submitted to surgery between July 2018-October 2021. We compared patients with Final-ACT<basal-ACT and Final-ACT≥basal-ACT; and Final-ACT < 140s with ≥140 s. Continuous variables were analyzed with Wilcoxon Rank-Sum test; categorical variables using Chi-square or Fisher's exact test. A Linear Mixed Regression model was used to analyze bleeding in patients with Final-ACT < 140s and ≥140 s.Independent variables were analyzed with Binary Logistic Regression models to investigate their association with bleeding and transfusion. Patients with Final-ACT ≥ 140s presented higher postoperative bleeding than Final-ACT < 140s at 12 h (P = 0.006) and 24 h (**P = 0.004). CPB time (OR 1.009,1.002-1.015,95% CI) and masculine sex (OR 2.842,1.721-4.821,95% CI) were significant predictors of bleeding. Patients with Final-ACT ≥ 140s had higher risk of UT (OR 1.81, 1.13-2.89, 95% CI; P = 0.0104), compared to Final-ACT < 140s. CPB time (OR 1.019,1.012-1.026,95% CI) and Final-ACT (OR 1.021,1.010-1.032,95% CI) were significant predictors of transfusion. Female sex was a predictor of UT, with a probability for use of 27.23% (21.84-33.39%,95% CI) in elective surgeries, and 60.38% (37.65-79.36%,95% CI) in urgent surgeries, higher than in males. Final-ACT has a good predictive value for the use of transfusion. Final-ACT ≥ 140s correlate with higher risk of transfusion and increased bleeding. The risk of bleeding and transfusion is higher with longer periods of CPB. Males have a higher risk of bleeding, but females have a higher risk of transfusion.