Ordinal Logistic Regression Models Research Articles

Examining travel mode preference for the COVID-19 Post-Vaccination Period: Insights from Dhaka, Bangladesh

This research investigates preferences of general public towards travel modes in the COVID-19 post-vaccination times. First, a questionnaire survey is conducted in Dhaka, Bangladesh, to gather information on people's socio-demographic characteristics, travel choices before, during, and after the pandemic, and attitudes towards public transit, active transport, and personal car. Next, three ordinal logistic regression models are developed to explore how mode preferences vary across socio-demographics, travel characteristics, and risk perceptions. This research identifies factors that contribute to commuters' travel mode preference as well as factors that act as deterrents. Analysis reveals that there will be a noticeable shift from public transport to private car and active transport. To be able to walk or bike to work, people may consider relocating closer to their workplaces. Individuals who used a private car before vaccination may continue to do so after being vaccinated. Additionally, women are more likely to prefer own vehicles while people aged more than 49 years are less likely to prefer public transport. Results also suggest that use of food delivery services, ridesharing, and working from home significantly affects travel mode preference. Individuals who never used ridesharing services are more likely to prefer walking and bicycling after vaccination. The outcomes of this study are expected to assist transport policymakers in the Global South to better understand COVID-19′s long-term influence on mode choice behavior and help in developing pragmatic policies to promote sustainable travel habits.

Does Climate Change Affect Health? Beliefs from the Health Information National Trends Survey.

Climate change is currently and will continue impacting human health, however, beliefs about the level of threat vary by demographics, region, and ideology. The purpose of this study was to assess factors related to climate change and health beliefs using cross-sectional data from the Health Information National Trends Survey (HINTS). Data from 5,075 respondents in the 2022 iteration of HINTS was used for this study. Chi-square tests were used to evaluate demographic differences among those who believe climate change will harm health a lot compared to some, a little, or not at all. Generalized ordinal logistic regression models were used to examine the relationship between the belief that climate change will harm health and independent variables regarding trust in scientists, health recommendations from experts, and demographic characteristics. Female, Black, Hispanic, and college graduate respondents had higher odds and people in the Southern U.S. those aged 35-49, 50-64, and 75years or older had significantly lower odds of believing climate change would harm their health. Those who trust information about cancer from scientists and those that believe health recommendations from experts conflict or change had higher odds of believing climate change would harm health. Our analysis highlights factors that impact climate change and health beliefs, which may provide targets for tailoring public health messages to address this issue.

Socio-demographic and infrastructural variables influencing maternal risk concentration among ever-married women of reproductive age in rural West Bengal, India.

The risk of a woman dying as a result of pregnancy or childbirth during her lifetime is about one in six in the poorest parts of the world. The present study aims to determine prevalence of maternal risk and the influencing variables among ever-married women belonging to the reproductive age group (15-49) of Birbhum district, West Bengal. A cohort-based retrospective cross-sectional study was carried out among the sample of 229 respondents through a purposive stratified random sampling method and a pre-designed semi-structured questionnaire. The ordinal logistic regression (OLR) model was taken as a tool of assessment. Before developing the proportional OLR model, we have checked the multicollinearity effect among the predictors and the first-order effect modifier was evaluated as well. We performed data analysis using SPSS version 26. The result shows that illiterate women (Odds ratios [OR]=2.81, 95% CI, 0.277-1.791), from lower standard of living (OR=1.14, 95% CI, -0.845-1.116), married before the age of 15years (OR=21.96, 95% CI, -0.55-6.73) and between the age of 15-18years (OR=24.51. 95% CI, -0.45-6.85) are more likely to be affected by the higher concentration of maternal risk. Other important predictor is the time of pregnancy registration. Considering the transport and related en-route causalities, the result portraying a clear picture where the distance and travel time becoming significant factors in determining the concentration of maternal risk. Incidences of child marriages should be restricted. Eradicating factors influencing an individual's decision to seek care would be an essential contribution in excluding the dominant maternal risk factors.

IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT

This research is primarily dedicated to providing a comprehensive exposition of the methodology applied in the deployment of a cartographic-based machine learning algorithm designed for the precise identification of areas susceptible to landslides within the geographical confines of the Takari District.This research delves into the application of mapping-based machine learning algorithms in the domain of non-structural disaster mitigation, with a specific emphasis on the detection of landslide susceptibility within the Takari District. A range of machine learning algorithms, including Support Vector Machine, Naive Bayes Classifier, Ordinal Logistic Regression, Random Forest, and Decision Tree, were harnessed to evaluate rainfall data within the context of landslide susceptibility. An evaluation of model performance, anchored in accuracy and Kappa metrics, unveiled that both the Ordinal Logistic Regression and Random Forest models exhibited noteworthy precision, reaching a commendable 74.36%. Nevertheless, a meticulous examination of Kappa values disclosed the ascendancy of the Random Forest model, which achieved a superior Kappa value of 0.5397. As portrayed in the visual representation provided, it becomes manifest that the Random Forest algorithm's prognostications yield 66 instances of cloudy atmospheric conditions, 48 occurrences of light precipitation, and 3 episodes of moderate rainfall. These predictions are influenced by several factors, including average temperature, humidity levels, wind speed, duration of sunlight, and wind direction at maximum speed. Consequently, this comprehensive analysis underscores the Random Forest algorithm as the most efficacious model for landslide susceptibility prediction. Furthermore, the study seamlessly integrated overlay maps, encompassing the Slope Inclination Map of the Takari District, Geological Map of the Takari District, and Soil Type Map of the Takari District, to contribute to the formulation of a definitive map delineating the susceptibility to landslides in the Takari District. Furthermore, further research could conduct spatial validation of the model predictions using additional datasets or remote sensing data to validate the accuracy of the landslide susceptibility map and ensure its applicability across different geographical regions.

Prediction of long-term functional outcome following different rehabilitation pathways after stroke unit discharge.

To investigate whether referral for different types of rehabilitation on discharge from Swedish stroke units can predict functional outcomes at 1 and 5 years after a stroke. A longitudinal and registry-based study. A total of 5,118 participants with index stroke in 2011 were followed-up at 1 and 5 years after the stroke. Ordinal logistic regression models were developed to predict the category of functional outcome: independent, dependent, or dead. The primary predictors were planned rehabilitation in a home setting, inpatient rehabilitation, and outpatient rehabilitation, with no planned rehabilitation as the reference category. Planned outpatient rehabilitation predicted independence (compared with death) at 1 year. Planned rehabilitation in the home setting predicted independence (compared with death) at 1 and 5years. Compared with other planned pathways, participants planned for inpatient rehabilitation had more severe conditions, and planned inpatient rehabilitation did not predict independence. Planning for outpatient or home-based rehabilitation appeared to lead more effectively to participants achieving independence over the course of 1-5 years. This may have been due to the less severe nature of these participants' conditions, compared with those requiring inpatient rehabilitation.

The effect of dietary diversity on anemia levels among children 6-23 months in sub-Saharan Africa: A multilevel ordinal logistic regression model.

Anemia is the most common hematologic disorder of children worldwide. Since dietary diversity is a main requirement of children is to get all the essential nutrients, it can thus use as one of the basic indicator when assessing the child's anemia. Although dietary diversity plays a major role in anemia among children in sub-Saharan Africa, there is little evidence of an association between the dietary diversity and anemia level to identified potential strategies for prevention of anemia level in sub-Saharan Africa. To examine the association between dietary diversity and anemia levels among children aged 6-23 months in sub-Saharan Africa. The most recent Demographic and Health Surveys from 32 countries in SSA were considered for this study, which used pooled data from those surveys. In this study, a total weighted sample of 52,180 children aged 6-23 months was included. The diversity of the diet given to children was assessed using the minimum dietary diversity (MDD), which considers only four of the seven food groups. A multilevel ordinal logistic regression model was applied due to the DHS data's hierarchical structure and the ordinal nature of anemia. With a p-value of 0.08, the Brant test found that the proportional odds assumption was satisfied. In addition, model comparisons were done using deviance. In the bi-variable analysis, variables having a p-value ≤0.2 were taken into account for multivariable analysis. The Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) was presented for potential determinants of levels of anemia in the multivariable multilevel proportional odds model. The overall prevalence of minimum dietary diversity and anemia among children aged 6-23 months were 43% [95% CI: 42.6%, 43.4%] and 72.0% [95% CI: 70.9%, 72.9%] respectively. Of which, 26.2% had mild anemia, 43.4% had moderate anemia, and 2.4% had severe anemia. MDD, being female child, being 18-23 months age, born from mothers aged ≥25, taking drugs for the intestinal parasite, higher level of maternal education, number of ANC visits, middle and richer household wealth status, distance of health facility and being born in Central and Southern Africa were significantly associated with the lower odds of levels of anemia. Contrarily, being 9-11- and 12-17-months age, size of child, having fever and diarrhea in the last two weeks, higher birth order, stunting, wasting, and underweight and being in West Africa were significantly associated with higher odds of levels of anemia. Anemia was a significant public health issue among children aged 6-23 months in sub-Saharan Africa. Minimum dietary diversity intake is associated with reduced anemia in children aged 6 to 23 months in sub-Saharan Africa. Children should be fed a variety of foods to improve their anemia status. Reducing anemia in children aged 6-23 months can be achieved by raising mother education levels, treating febrile illnesses, and improve the family's financial situation. Finally, iron fortification or vitamin supplementation could help to better reduce the risk of anemia and raise children's hemoglobin levels in order to treat anemia.

Mapping an intelligent algorithm for predicting female adolescents' cervical vertebrae maturation stage with high recall and accuracy.

The present study was designed to define a novel algorithm capable of predicting female adolescents' cervical vertebrae maturation stage with high recall and accuracy. A total of 560 female cephalograms were collected, and cephalograms with unclear vertebral shapes and deformed scales were removed. 480 films from female adolescents (mean age: 11.5 years; age range: 6-19 years) were used for the model development phase, and 80 subjects were randomly and stratified allocated to the validation cohort to further assess the model's performance. Derived significant predictive parameters from 15 anatomic points and 25 quantitative parameters of the second to fourth cervical vertebrae (C2-C4) to establish the ordinary logistic regression model. Evaluation metrics including precision, recall, and F1 score are employed to assess the efficacy of the models in each identified cervical vertebrae maturation stage (iCS). In cases of confusion and mispredictions, the model underwent modification to improve consistency. Four significant parameters, including chronological age, the ratio of D3 to AH3 (D3:AH3), anterosuperior angle of C4 (@4), and distance between C3lp and C4up (C3lp-C4up) were administered into the ordinary regression model. The primary predicting model that implements the novel algorithm was built and the performance evaluation with all stages of 93.96% for accuracy, 93.98% for precision, 93.98% for recall, and 93.95% for F1-score were obtained. Despite the hybrid logistic-based model achieving high accuracy, the unsatisfactory performance of stage estimation was noticed for iCS3 in the primary cohort (89.17%) and validation cohort (85.00%). Through bivariate logistic regression analysis, the posterior height of C4 (PH4) was further selected in the iCS3 to establish a corrected model, thus the evaluation metrics were upgraded to 95.83% and 90.00%, respectively. An unbiased and objective assessment of the cervical vertebrae maturation (CVM) method can function as a decision-support tool, assisting in the evaluation of the optimal timing for treatment in growing adults. Our novel proposed logistic model yielded individual formulas for each specific CVM stage and attained exceptional performance, indicating the capability to function as a benchmark for maturity evaluation in clinical craniofacial orthopedics for Chinese female adolescents.

Are the shoulder joint function, stability, and mobility tests predictive of handstand execution?

Handstand is a basic element common across gymnastic disciplines and physical education classes that is frequently evaluated for quality in competition or skill acquisition. The correct handstand execution relies on maintaining balance, for which the shoulders seem particularly important. This study explores the relationship between shoulder joint function and the quality of handstand execution in novice college athletes (n = 111; aged 19-23 years). We assessed the shoulder joint function using standardized field tests (Upper Quarter Y Balance Test and Closed Kinetic Chain Upper Extremity Stability Test) and evaluated handstand execution on official rating scale. Ordinal logistic regression models showed no relationship between the quality of handstand execution (E-score) and measures of shoulder joint stability or mobility in our sample (POR = 0.97 [0.91, 1.03] and 1.00 [0.91, 1.09] for E-score). Two major factors may have caused an observed pattern of results. Firstly, the standardized tests assess shoulder joints in different loads and ranges of motion compared to handstands. Secondly, our novice sample was not able to perform the handstand sufficiently well. In our sample of novice college athletes, shoulder function seems not related to handstand execution as other latent factors hindered their performance.

Chronic and Latent Viral Infections and Leukocyte Telomere Length across the Lifespan of Female and Male Individuals Living with or without HIV

Background: Chronic/latent viral infections may accelerate immunological aging, particularly among people living with HIV (PLWH). We characterized chronic/latent virus infections across their lifespan and investigated their associations with leukocyte telomere length (LTL). Methods: Participants enrolled in the CARMA cohort study were randomly selected to include n = 15 for each decade of age between 0 and >60 y, for each sex, and each HIV status. Cytomegalovirus (CMV), Epstein–Barr virus (EBV), human herpesvirus 8 (HHV-8), herpes simplex virus 1 (HSV-1), and HSV-2 infection were determined serologically; HIV, hepatitis C (HCV), and hepatitis B (HBV) were self-reported. LTLs were measured using monochrome multiplex qPCR. Associations between the number of viruses, LTL, and sociodemographic factors were assessed using ordinal logistic and linear regression modeling. Results: The study included 187 PLWH (105 female/82 male) and 190 HIV-negative participants (105 female/84 male), ranging in age from 0.7 to 76.1 years. Living with HIV, being older, and being female were associated with harbouring a greater number of chronic/latent non-HIV viruses. Having more infections was in turn bivariately associated with a shorter LTL. In multivariable analyses, older age, living with HIV, and the female sex remained independently associated with having more infections, while having 3–4 viruses (vs. 0–2) was associated with a shorter LTL. Conclusions: Our results suggest that persistent viral infections are more prevalent in PLWH and females, and that these may contribute to immunological aging. Whether this is associated with comorbidities later in life remains an important question.

A surge in food insecurity during the COVID-19 pandemic in a cohort in Mexico City.

The COVID-19 pandemic has not only caused tremendous loss of life and health but has also greatly disrupted the world economy. The impact of this disruption has been especially harsh in urban settings of developing countries. We estimated the impact of the pandemic on the occurrence of food insecurity in a cohort of women living in Mexico City, and the socioeconomic characteristics associated with food insecurity severity. We analyzed data longitudinally from 685 women in the Mexico City-based ELEMENT cohort. Food insecurity at the household level was gathered using the Latin American and Caribbean Food Security Scale and measured in-person during 2015 to 2019 before the pandemic and by telephone during 2020-2021, in the midst of the pandemic. Fluctuations in the average of food insecurity as a function of calendar time were modeled using kernel-weighted local polynomial regression. Fixed and random-effects ordinal logistic regression models of food insecurity were fitted, with timing of data collection (pre-pandemic vs. during pandemic) as the main predictor. Food insecurity (at any level) increased from 41.6% during the pre-pandemic period to 53.8% in the pandemic stage. This increase was higher in the combined severe-moderate food insecurity levels: from 1.6% pre-pandemic to 16.8% during the pandemic. The odds of severe food insecurity were 3.4 times higher during the pandemic relative to pre-pandemic levels (p<0.01). Socioeconomic status quintile (Q) was significantly related to food insecurity (Q2 OR = 0.35 p<0.1, Q3 OR = 0.48 p = 0.014, Q4 OR = 0.24 p<0.01, and Q5 OR = 0.17 p<0.01), as well as lack of access to social security (OR = 1.69, p = 0.01), and schooling (OR = 0.37, p<0.01). Food insecurity increased in Mexico City households in the ELEMENT cohort as a result of the COVID-19 pandemic. These results contribute to the body of evidence suggesting that governments should implement well-designed, focalized programs in the context of economic crisis such as the one caused by COVID-19 to prevent families from the expected adverse health and well-being consequences associated to food insecurity, especially for the most vulnerable.

Impacts of Streetscape Features on Individual Social Capital: Applying Korea’s Neighborhood Data to Street View Images to Improve Lives of the Socially Vulnerable

Neighborhood social vulnerability is a dimension of vulnerability that influences society’s response to external factors, encompassing various social factors tied to socioeconomic and demographic attributes at the neighborhood level. While previous studies have explored the associations between vulnerable neighborhoods and stressors like environmental hazards, understanding of their impact on residents’ social capital remains limited. Moreover, the role of built environments in mitigating these effects is uncertain. This study investigates the impact of neighborhood social vulnerability, alongside streetscape features, on individual social capital in Seoul, South Korea. Using a stratified random sampling method, we surveyed 1000 Seoul residents, assessing their social capital and demographics. In particular, six questionnaires based on a four-point Likert scale were used to measure the individual level of social capital: two questions for social networks, three questions for social participation, and one question for sense of community. Additionally, we employed a deep learning-based model to analyze Google Street View images for detailed streetscape features. Our analysis, utilizing multiple and ordinal logistic regression models, reveals that walkable environments and neighborhood prosperity, indicated by factors like income, education, and street greenery, are linked to higher social capital. Moreover, less urbanized areas with lower land prices and greater openness to the sky also show positive associations. These findings underscore the potential of improving streetscape features to mitigate the negative impacts of neighborhood vulnerability, particularly in neighborhoods where low-income and less-educated residents are concentrated, offering insights for urban planners and community leaders.

Determinants of nutritional status of children aged 6–59 months in the case of Itang special woreda, Gambella, Ethiopia

Nutritional status is one of the most important causes of improper physical and mental development in children. The study attempts to assess the factors affecting the severity status of children aged 6–59 months’ malnutrition based on the weight-for-age anthropometric index (z-score) and examine between-kebeles-level differences in determinants of the nutritional status of children. A community-based, cross-sectional study design was conducted from October 12 to November 12, 2022. A sample of 397 children aged 6–59 months primary data by applying multi–stage clustered sampling technique was used by considering their heterogeneity. The data were entered by SPSS and analyzed by using R version 3.4.0 and STATA 14.2 statistical software package using a multilevel ordinal logistic regression model and inferences were conducted at a 5% significance level. The results show that birth interval ≥ 24 months (OR = 1.431253, 95% CI 1.221337 1.6763421, P-value = 0.008), economic status of households medium (OR = 16.21466, 95% CI 1.221403 1.423929, P-value = 0.000), economic status of households rich (OR = 223.2856, 95% CI 1.34295 2.582325, P-value = 0.000), employment status of the mother unemployed (OR = 0.2291348, 95% CI 0.0529511 0.9966281, P-value = 0.049), No toilet facility (bush field) (OR = 0.3163329, 95% CI 0.1825356 0.5481975, P-value = 0.000), number of household members (OR = 0.9100682, 95% CI 0.8313481 0.9967315, P-value = 0.042), breastfeeding < 12 months (OR = 0.53803, 95% CI 0.322315 0.898135, P-value = 0.018), educational level of father Primary (OR = 4.601687, 95% CI 1.758009 2.22053, P-value = 0.000), educational level of father Secondary above (OR = 99.65229, 95% CI 2.533502 4.788896, P-value = 0.000) and geographical area (kebeles) were found to be important factors that affect a child's nutritional status between 6 and 59 months. 15% of the overall variation is attributable to the Kebeles level, according to two-level multilevel ordinal logistic regressions with estimates of the variation attributable to the Kebeles level equal to 0.569 and an intraclass correlation coefficient of 0.15. Due to the nature of the response variable random intercept model with random coefficients fitted the data adequately in predicting the severity status of children aged 6–59 months’ malnutrition for the multilevel ordinal logistic regression model analysis. So, the researcher recommended that implementing primary health care and nutrition programs that would fit each kebeles’ features in Itang Special Woreda to safeguard children from nutritional deficiency.

Country Differences in Older Men's Hearing Difficulty Disadvantage.

Objectives: Hearing difficulty is prevalent in older adulthood and projected to increase via global aging, particularly among men. Currently, there is limited research on how this gender disparity might vary by country. Methods: Using 2018 data (n = 29,480) from the Health and Retirement Study (HRS) international family of studies, we investigate gender disparities in hearing difficulty among respondents ages 55-89 from the United States (n = 12,566), Mexico (n = 10,762), and Korea (n = 6152) with country-specific ordinal logistic regression models that progressively adjust for demographic, social, and health indicators. Results: In the United States, men's hearing difficulty disadvantage was consistently observed. In Mexico, men's hearing difficulty disadvantage was explained by the interactive effect of gender and age group but resurfaced after adjusting for comorbidities. In Korea, there was consistently no gender difference in hearing difficulty. Discussion: Our results highlight the heterogeneity in older men's hearing difficulty disadvantage among a diverse group of aging countries.

Abstract PO5-11-07: Short- and long-term treatment-related effects on physical health in breast cancer survivors

Abstract Background. Breast cancer (BC) survivors experience greater physical health declines compared to cancer-free women of the same age, which is thought to be caused by their cancer and its treatment. However, the short- and long-term effects of different types of treatment on physical health are not well understood, especially for hormone therapy. Moreover, whether specific aspects of physical health, such as activities of daily living (ADL), are affected by treatment is unknown. Methods. This analysis was conducted in the Cancer Prevention Study 3 (CPS-3), a prospective cohort study with approximately 300,000 participants enrolled between 2006-2013. Participants returned a baseline survey and triennial follow-up surveys beginning in 2015. Incident, non-metastatic, female BC patients were included in this analysis if they returned a survey at least 90 days after their diagnosis through June 30, 2020, the end of follow-up for this analysis. All 2,551 BC patients included in this study had pre- and post-diagnostic surveys and underwent breast surgery if they were diagnosed with invasive disease. They were matched to up to five cancer-free women on age and year of survey returns (N=12,704). Self-reported physical health and ADL were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Scale instrument. Treatment information was obtained from cancer registries and self-report and included surgery, chemotherapy, radiation and hormonal therapy. Odds Ratios (OR) and 95% confidence intervals (CI) between treatment received and self-reported physical function were estimated using multivariable ordinal logistic regression models at three time points relative to the case’s diagnosis date: before diagnosis, within 90 days to 5 years after diagnosis, and more than 5 years after diagnosis. Results. Median age at diagnosis was 56 years (interquartile range (IQR): 50-62). Approximately 82% of the tumors were hormone-receptor positive. The median times from the three physical health measurements to diagnoses were 1.7 years before diagnosis (IQR: 0.9 – 2.7), 1.7 years (IQR: 0.9 – 2.5) from 90 days to 5 years post-diagnosis and 6.6 years (IQR: 5.5-7.0) for more than 5 years post-diagnosis. There was a significant risk of physical decline within 5 years of diagnosis for women who received chemotherapy or hormonal therapy compared to cancer-free women (Table 1). However, more than 5 years after diagnosis, the risk of physical decline was only observed among those who received chemotherapy. Treatment combinations that included chemotherapy were also associated with a decline in the ability to carry out ADL during the first 5 years. Patients who received hormonal therapy without chemotherapy were comparable to cancer-free women in their ability to carry out ADL during the post-diagnosis period. BC patients who received surgery only or surgery and radiation reported physical health and ADLs similar to cancer-free women within 5 and &amp;gt;5 years after diagnosis. Conclusions. Post-diagnosis physical health decline is time and treatment dependent. Patients receiving chemotherapy have the greatest overall physical health decline and it is long-lasting. Beyond five years from diagnosis, physical health of breast cancer patients who did not receive chemotherapy were similar to cancer-free women. Strategies are needed to help BC patients receiving chemotherapy overcome the long-term physical function limitations of their cancer treatment. Table. Associations between treatment received and physical health and ability to carry out activities of daily living. OR: Odds Ratio; CI: confidence interval; chemo: chemotherapy; radio: radiation therapy; horm: hormonal therapy. *Associations were adjusted for matching factors, which included age and time from diagnosis to measurement of physical health. Citation Format: Clara Bodelon, Matthew Masters, Lauren McCullough, Alpa Patel, Lauren Teras. Short- and long-term treatment-related effects on physical health in breast cancer survivors [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-11-07.

Left ventricular systolic dysfunction predicts clinical prognosis in patients with acute ischemic stroke after intravenous thrombolysis.

Although intravenous recombinant tissue plasminogen activator (rt-PA) thrombolysis is the most effective early treatment for acute ischemic stroke (AIS), outcomes vary greatly among patients. Left ventricular systolic dysfunction (LVSD) is prone to distant organ ischemia and may be a predictor for poor prognosis in AIS patients undergoing intravenous thrombolysis (IVT). Our aim was to investigate the predictivity of LVSD diagnosis (as measured by left ventricular ejection fraction (LVEF)) on 90-day clinical outcomes in AIS patients undergoing thrombolysis. The current prospective cohort study continuously enrolled 273 AIS patients from the National Stroke Prevention and Treatment Engineering Management Special Database who underwent IVT and completed echocardiography within 24 h of admission between 2021 and 2023. LVSD was examined by evaluation of the echocardiographic LVEF values using Simpson's biplane method of discs in line with international guidelines, and defined as a LVEF value < 50%. Multivariable ordinal logistic regression model was performed to analyze the association between LVEF and functional outcome at 3 months. Restricted cubic spline (RCS) was used to examine the shape of the dose-response association between reduced LVEF and poor functional outcomes. Subgroup analysis was also employed to further verify the reliability and practicability of the results. Baseline data analysis showed LVSD patients had more comorbidities including on multivariate analyses, LVSD (OR 2.78, 95% CI 1.23 to 6.24, P=0.014), pre-existing diabetes mellitus (OR 2.08, 95% CI 1.11 to 3.90, P=0.023) and NIHSS on arrival (OR 1.31, 95% CI 1.21 to 1.49, P<0.001) were independent predictors of poor functional outcomes (mRS ≥ 3) at 3 months. Multivariable-adjusted spline regression indicated a linear dose-response association between LVEF after IVT and poor functional outcomes (p for linearity < 0.001), with the optimal cutoff values of LVEF being 0.48. Our finding indicated that AIS patients with LVSD after IVT had poorer outcomes, suggesting the need to monitor and optimize LVEF in stroke management.

Cross-sectional evaluation of the multidimensional indicators of psychosocial functioning and its sociodemographic correlates among Indian adults: WHO SAGE Study (2007-2010).

This study examined the relationship between sociodemographic characteristics and psychosocial functioning (PF) among Indian adults. Data (N = 11,230) for this study came from the World Health Organization's SAGE (Longitudinal Study of Global Aging and Adult Health) Wave 1 2007-2010. First, multivariable regression analyses (logistic or linear regression depending on the outcome variable) were run to evaluate whether PF indicators varied by gender after controlling other sociodemographic characteristics. Next, the relationship between sociodemographic characteristics and PF indicators was examined using ordinary least square regression (OLS) models and logistic regression models, separately for men and women. Specifically, the PF indicators, including social indicators of interpersonal relationship difficulty, social connectedness, and personal indicators of sleep, affect, perceived quality of life, and cognition were each regressed on sociodemographic factors. All analyses in the study were cross-sectional in nature and conducted using STATA version 15.1. Overall, the study found significant sociodemographic differences in PF among Indian adults that also varied by gender. As such, social and/or economic disadvantage was associated with poorer PF. However, the results demonstrated that socioeconomic patterns in PF were much more nuanced among women than among men. This study adds to previous research on PF in India and provides new insights into how sociodemographic characteristics shape it. A major research implication of this finding is that inconsistent with assumptions of previous research, an increase in SES is not always linked to proportionate increases in PF among women. The study also makes a compelling case for separately examining multiple non-clinical outcomes of psychosocial health.

Evaluation of quality of life scores and family impact scales in pediatric patients with alopecia areata: a cross-sectional cohort study.

There are a limited number of studies evaluating the effects of alopecia areata (AA) on the health-related quality of life (HRQoL) of pediatric patients and their families. This study aimed to assess the HRQoL of pediatric patients with AA and their parents. This single-center cross-sectional cohort study included 72 pediatric patients diagnosed with AA. The study was conducted between December 2020 and December 2021 in the dermatology department of a single tertiary center in Turkey. The HRQoL index of the pediatric patients was assessed with the Children's Dermatology Life Quality Index (CDLQI). At the same time, their parents, who were primarily involved in the disease process, were evaluated using the Dermatological Family Impact Scale (DeFIS). An ordinal logistic regression model was used to detect predictors for CDLQI severity. The mean ± SD CDLQI of the pediatric patients who participated in our study was 8.4 ± 5.3, corresponding to moderate impairment. The highest impairment in CDLQI was observed in the symptoms and feelings domain, while the slightest impairment was observed in the domain of personal relationships (P < 0.001). There was a statistically significant positive correlation between the Severity of Alopecia Tool (SALT) score and all CDLQI domains, and the most substantial relationship was with the leisure domain (r = 0.78, P < 0.001). DeFIS scores of female patients were substantially higher than males (25.3 ± 8.6 vs. 17.6 ± 9, P = 0.001). Our study supports that AA is a disease that significantly impacts the HRQoL of affected children and their families.

On the association between dietary oily fish intake and bone mineral density in frequent fish consumers of Amerindian ancestry. The three villages study.

Oily fish is a major dietary source of omega-3 polyunsaturated fatty acids and other nutrients that may have a positive effect on bone health. However, this association is inconsistent and seems to be more evident in certain ethnic groups. We aimed to assess the association between oily fish intake and bone mineral density (BMD) in frequent fish consumers of Amerindian ancestry living in rural Ecuador. This study included 399 individuals aged ≥ 60years living in three neighboring rural villages of coastal Ecuador. Dietary oily fish intake was quantified systematically using validated surveys and BMD was determined by dual-energy x-ray absorptiometry. Ordinal logistic regression models, adjusted for demographics and cardiovascular risk factors, were fitted to assess the independent association between oily fish intake and bone health. Participants had a mean age of 68.8 ± 6.8years, and 58% were women. The mean intake of oily fish was 8.5 ± 4.7 servings/week, with 308 (77%) reporting high fish intake (≥ 5.2 servings/week [728g]). Ninety-four (24%) participants had normal BMD T-scores, 149 (37%) had osteopenia, and 156 (39%) had osteoporosis. Ordinal logistic regression models showed no association between high fish intake and bone health in the total population. When men and women were analyzed separately, the association became significant for women only in both unadjusted (OR: 2.52; 95% C.I.: 1.22 - 5.23) and fully-adjusted models (OR: 2.23; 95% C.I.: 1.03 - 4.81). Consumption of ≥ 5.2 oily fish servings/week is associated with lower prevalence of osteopenia and osteoporosis in elderly women of Amerindian ancestry.

Hospital managers' perspectives on pregnancy policy and work adjustments: A cross-sectional study.

Risk assessment and work adjustment according to EU legislation may safeguard pregnant employees and their offspring. Knowledge on management perspectives in relation to implementation of protective measures is limited. The primary aim was to describe Danish hospital managers' engagement in pregnancy policy and work adjustment for pregnant employees. The secondary aim was to investigate how managers' characteristics and the setting affect engagement and behaviour. This was a cross-sectional study of survey data from 212 managers. Outcomes were within dimensions of health promotion, pregnancy policy, work adjustment, collaboration, manager support, and sick leave. Logistic and ordinal logistic regression models were applied to identify associations between background information and outcomes. Of the managers included, 84% arranged meetings and 76% conducted occupational risk assessment. Most managers (96%) engaged in dialogue with the employees before sick leave. Most managers felt competent in providing guidance for pregnant employees and 99% considered work adjustment important, mainly to safeguard mothers and children. The self-reported data showed positive associations between female managers and feeling competent to guide the employee. Further, management training was associated with meetings with pregnant employees. Seniority was associated with feeling competent to guide and dialogue. Midwifery support was associated with competence in guiding employees about risk factors. Work adjustment and risk assessment for pregnant employees are considered a priority by Danish hospital managers. Overall, managers feel competent guiding pregnant employees. However, managers experience midwifery support beneficial for the guidance of pregnant employees.

Assessing health-related quality of life of Chinese population using CQ-11D

PurposeThis study aimed to assess the health-related quality of life (HRQoL) of the Chinese population by using the Chinese medicine quality of life-11 dimensions (CQ-11D) questionnaire and to identify factors associated with HRQoL.MethodsThe data was derived from a survey conducted by the Institute of Pharmacoeconomics Evaluation at Beijing University of Chinese Medicine on the quality of life of the Chinese population. The sex and age of respondents were considered through quota sampling. Demographic, socioeconomic, and health indicators were collected using the structured questionnaire. We performed bivariate analyses first to examine the associations between the above factors and the HRQoL of respondents measured by the CQ-11D. Multivariate linear regression and ordinal logistic regression models were established to analyze the factors (demographic, socioeconomic, and health indicators) differences in HRQoL, as well as the risk of each group reporting problems across the 11 dimensions of CQ-11D.ResultsFrom February 2021 to November 2022, a total of 7,604 respondents were involved and 7,498 respondents were included. The sample approximated the general adult Chinese population in terms of age, sex, and district of residence, and each geographic distribution ranged from 9.71 to 25.54%. Of the respondents, 45.84% were male, and 89.82% were Han ethnicity. The mean utility score ranged from 0.796 to 0.921 as age increased. According to the respondents, most health problems were identified in the PL (fatigue) (70.16%) and SM (quality of sleep) (63.63%) dimensions. The CQ-11D index scores varied with the demographic and socioeconomic characteristics of respondents, except for ethnicity (p > 0.05) and income (p > 0.05). The multivariate analysis revealed significant negative associations between health utility scores and various factors. These factors include sex (female), age over 65, belonging to ethnic minorities, rural household registration, being widowed or divorced, having a primary school education or below, being a student or unemployed, having a low income of 0–1,300, engaging in smoking or drinking, limited participation in physical activities, experiencing changes in self-perceived health status compared to the previous year, and having chronic diseases. The odds of respondents reporting problems in 11 dimensions varied among different socio-demographic groups.ConclusionsThis study reports the first Chinese population norms for the CQ-11D derived using a representative sample of the Chinese general population. Self-reported health status measured by the CQ-11D varies among different socio-economic groups. In addition to participation a physical activity and the presence of chronic disease, smoking and drinking also significantly influence HRQoL.