Social support and frailty progression in community-dwelling older adults.

Objectives: Despite the growing evidence regarding the influence of social factors on frailty in older adults, the effect of social support remains unclear. This study aims to assess the association between social support and frailty progression (transition and incidence) in a sample of community-dwelling older adults. Methods: Using a cohort study design, 1,059 older adults from the Berlin Initiative Study were followed up for 2.1 years. Multinomial and logistic regression analyses were performed to assess the association of social support using Oslo Social Support Scale-3 with frailty transition and incidence, respectively. Gender differences were explored using stratified analyses. Results: At baseline, frailty prevalence in the study population [mean (SD) age 84.3 (5.6) years; 55.8% women] reached 33.1% with 47.0, 29.4 and 23.6% of the participants reporting moderate, strong and poor social support, respectively. Over the follow-up period, social support was not significantly associated with the frailty transition categories in the adjusted model. Conversely, the adjusted logistic regression analysis showed that participants with poor social support had twice the odds of becoming frail compared to those with strong social support (OR 2.07; 95% CI 1.08-3.95). Gender-stratified analyses showed comparable estimates to the main analysis but were statistically non-significant. Discussion: Our study results underpin the role of social factors in frailty incidence and highlight social support as a potential target for frailty-preventing interventions in older adults. Therefore, it is important to adopt a biopsychosocial model rather than a purely biomedical model to understand and holistically improve the health of community-dwelling older adults.

Risk factors for breast cancer among women in Freetown, Sierra Leone, 2017: a case-control study.

Introduction: breast cancer is the most commonly diagnosed malignancy and an important cause of cancer death among females worldwide. The disease accounted for 25% (1.67 million) of new cancer cases and the fifth cause of cancer deaths. Incidence of all types of cancers is approximately 25% in Sierra Leone. However, there was no documented evidence on risk factors for breast cancer among women in the country. The main aim of this study was to assess risk factors associated with breast cancer among women screened for breast cancer in Freetown Sierra Leone. Methods: we conducted a case-control study on breast cancer involving 116 confirmed breast cancer cases and 116 controls. Questionnaire was designed to collect data on socio-demographic, reproductive and behavioral risk factors. Analysis was carried using logistic regression to assess the associations between breast cancer and the risk factors. Results: in the final multiple logistic regression, had formal educational level, (aOR 0.1, 0.03-0.26, p= 0.001) physical activity for more than 30 minutes per week (aOR 0.5 (0.9- 0.7, p=0.001). Cigarette smoking (aOR 4.8, 1.2-18.5, p=0.023) and family history of breast cancer (aOR 9.9 cigarette smoking (OR 4.4, 1.2-18.5, p=0.023) and family history of breast cancer (OR 9.9, 2.7-36.45, p=0.040) were identified as the main risk factors for breast cancer. This study did not find any statistically significant associations between reproductive risk factors and breast cancer. Conclusion: risk factors for breast cancer among women in Sierra Leone include educational level, physical activity, cigarette smoking and family history of breast cancer. We recommended screening program for women above 40 years and had history of breast cancer. Also, to establish breast cancer registry.

Can supervised deep learning architecture outperform autoencoders in building propensity score models for matching?

PURPOSE: Propensity score matching is vital in epidemiological studies using observational data, yet its estimates relies on correct model-specification. This study assesses supervised deep learning models and unsupervised autoencoders for propensity score estimation, comparing them with traditional methods for bias and variance accuracy in treatment effect estimations. METHODS: Utilizing a plasmode simulation based on the Right Heart Catheterization dataset, under a variety of settings, we evaluated (1) a supervised deep learning architecture and (2) an unsupervised autoencoder, alongside two traditional methods: logistic regression and a spline-based method in estimating propensity scores for matching. Performance metrics included bias, standard errors, and coverage probability. The analysis was also extended to real-world data, with estimates compared to those obtained via a double robust approach. RESULTS: The analysis revealed that supervised deep learning models outperformed unsupervised autoencoders in variance estimation while maintaining comparable levels of bias. These results were supported by analyses of real-world data, where the supervised model's estimates closely matched those derived from conventional methods. Additionally, deep learning models performed well compared to traditional methods in settings where exposure was rare. CONCLUSION: Supervised deep learning models hold promise in refining propensity score estimations in epidemiological research, offering nuanced confounder adjustment, especially in complex datasets. We endorse integrating supervised deep learning into epidemiological research and share reproducible codes for widespread use and methodological transparency.

The influence factors on pit and fissure sealing behavior of 12-year-old children: a cross-sectional study in Zhejiang, China.

BACKGROUND: In the 21st century, dental caries remains a global burden, particularly severely affecting the growth and quality of life of 12-year-old children. Fortunately, pit and fissure sealing (PFS) procedures can effectively prevent molars from caries. Hence, this study focused on the relationship between PFS and oral epidemiological factors in 12-year-old children. METHODS: A cross-sectional survey was conducted in 12-year-old children from 11 cities in Zhejiang Province. Their dental conditions were collected through questionnaires, as well as basic information such as relevant family information, oral health knowledge and behavior. Then, logistic regression analysis was used to identify the influencing factors associated with PFS. RESULTS: A total of 1204 children were included, with 252 in the PFS group and 952 in the non-PFS group. There were significant differences between the two groups in terms of decayed, missing and filled teeth (DMFT) score, first permanent molar DMFT score, residential area, educational level of parents, tooth-brushing frequency, use of dental floss, oral examination in a medical institution, having taken courses on oral health care, as well as having knowledge that tooth brushing could effectively prevent gingival inflammation, PFS could protect teeth, and oral disease may affect general health. According to further logistic regression analysis, the independent factors influencing PFS included use of dental floss [odds ratios (OR) = 1.672, 95% confidence intervals (CI) = 1.235-2.263, P = 0.001], having taken courses on oral health care (OR = 0.713, 95% CI = 0.515-0.988, P = 0.042), having knowledge that tooth brushing is effective in preventing gingival inflammation (OR = 0.627, 95% CI = 0.389-0.987, P = 0.044) and having knowledge that PFS can protect teeth (OR = 0.589, 95% CI = 0.438-0.791, P < 0.001). CONCLUSION: PFS can reduce the mean DMFT score of 12-year-old children. Independent influencing factors of PFS consist of use of dental floss, having taken courses on oral health care, oral health behavior and knowledge level.

Health literacy and its associated factors among the population in two schistosomiasis-endemic villages in Jiangxi Province, China.

This cross-sectional study aimed to assess the levels of health literacy and the associated factors among the general population living in 2 schistosomiasis-endemic villages in Jiangxi Province, China. Multistage stratified random sampling was used to select participants, and a face-to-face survey was conducted from July to August 2021 to collect participants' socio-demographic characteristics and levels of overall health literacy (HL) and its 3 subscales: health literacy of basic knowledge and concepts (HL-BKC), health literacy of behavior and lifestyle (HL-BAL), and health literacy of health-related skills (HL-HRS). The Chi-square test and logistic regression models were used to assess the association between socio-demographic characteristics and low HL levels. The prevalence rates of low overall HL, HL-BKC, HL-BAL, and HL-HRS were 84.3%, 61.8%, 82.6%, and 86%, respectively. In addition, no significant differences (P > .05) were noted between the 2 villages regarding overall HL scores and the 3 subscales of health literacy scores. Older age (P < .001), occupation (P < .001), lower educational level (P < .001), and lower annual household income (P < .05) were associated with an increased risk of low HL. Multivariate logistic regression revealed that occupation as a student (OR = 32.289, 95% CI:1.965-530.462, P < .05) and fishermen (OR = 27.902, 95%CI:1.91-407.642, P < .05), lower education level (OR = 0.384, 95%CI:0.149-0.99, P < .05), older age (OR = 5.228, 95%CI:1.458-18.75, P < .001), and lower annual household income (OR = 0.452, 95%CI:0.24-0.851, P < .05) were independently associated with low HL. The prevalence of low HL is high among the population in the schistosomiasis-endemic villages of Jiangxi Province, China. Age, education level, occupation, and annual household income were all independent factors associated with HL levels. Health educational interventions to improve HL should be simultaneously conducted in health promotion work to reduce risky habits.

Changes in unmet need for family planning among married women of reproductive age in Nigeria: A multilevel analysis of a ten-year DHS wave.

INTRODUCTION: Unmet need for family planning [UNFP] remains a serious public health concern in Nigeria. Evidence suggests that UNFP remains high over the last fifteen years despite numerous policies and programmes aimed at generating demand for family planning. This study used three Demographic and Health Survey (DHS) conducted over a ten-year period (2008-2018) to assess the changes in unmet need for family planning and associated contextual determinants. Understanding changes in unmet need for family planning among women and its associated contextual factors is crucial for designing appropriate interventions. METHODS: We analysed datasets the Nigeria Demographic and Health Surveys of 2008, 2013 and 2018 to assess changes and contextual determinants of unmet need for family planning. Data were analysed using frequency distribution, chi-square statistical test and multilevel binary logistic regression models. Due to the hierarchical structure of the data in which individuals are nested within households, multilevel mixed-effect logistic regression models were constructed. We used a multilevel binary logistic regression model after adjusting for variables not significant at the bivariate level. An adjusted odds ratio with 95% confidence interval was reported, with a p-value less than 0.05 declared to be significant predictors of unmet need for family planning. RESULTS: Unmet need for family planning decreased from 20.21% to 16.10% between 2008 and 2013 but subsequently rose later from 16.10% to 18.89% between 2013 and 2018. The pattern of changes in unmet need for either limiting or spacing was consistently high over the 10-year period, with the highest rate of each of the indicators of unmet need for family planning occurring in 2018 while the lowest rate was in 2008, thus indicating an increase in the proportion of respondents having unmet need for family planning over the referenced period. Age of respondents, educational level, wealth status, religious affiliation, parity, sex of head of household, partner educational level, region of residence, and community socioeconomic status were significant factors associated with the unmet need for family planning across the different data waves in Nigeria (p < 0.05). An intraclass correlation (ICC) of 4.9% showed that the individual and household level factors had a greater influence on the variation in the unmet need for family planning than did community factors in Nigeria. CONCLUSION: The overall prevalence of unmet need for family planning was consistently high over the ten-year period and community-level factors had lowest influence on the variation in unmet need for family planning compared to household and individual-level factors in Nigeria. Policies and interventions should focus on improving women's socio-economic and demographic characteristics at individual, household, and community levels to improve unmet need for family planning.

Predictive value of flexible proctosigmoidoscopy and laboratory findings for complete clinical responses after neoadjuvant chemoradiotherapy in patients with locally advanced primary rectal cancer: a retrospective cohort study.

PURPOSE: Colorectal cancer is the second leading cause of cancer death worldwide. Standard treatments for locally advanced rectal cancer include neoadjuvant chemoradiotherapy and total mesorectal excision (TME), which are associated with significant morbidity. After neoadjuvant therapy, one-third of patients achieve a pathological complete response (pCR) and are eligible for a watch-and-wait approach without TME. The purpose of this study was to determine the potential predictors of pCR before surgery. METHODS: The demographic, clinical, and endoscopic data of 119 patients with primary locally advanced rectal cancer without distant metastasis who underwent restaging endoscopy and TME 6-8 weeks after the end of neoadjuvant therapy were collected. The absence of tumor cells in the histological examination of the TME specimen after neoadjuvant therapy was considered pCR. Binary logistic regression and receiver operating characteristic curves were utilized for analysis. RESULTS: According to the multivariate logistic regression analysis, flattening of marginal tumor swelling (p value < 0.001, odds ratio = 100.605) emerged as an independent predictor of pCR in rectal cancer patients. Additionally, receiver operating characteristic curve analysis revealed that lower preoperative carcinoembryonic antigen and erythrocyte sedimentation rate levels predict pCR, with cutoffs of 2.15 ng/ml and 19.0 mm/h, respectively. CONCLUSION: Carcinoembryonic antigen and erythrocyte sedimentation rate, along with the presence of flattening of marginal tumor swelling, can predict pCR after neoadjuvant chemoradiotherapy in patients with primary rectal cancer. These factors offer a potential method for selecting candidates for conservative treatment based on endoscopic and laboratory findings.

Association between maternal multimorbidity and neurodevelopment of offspring: a prospective birth cohort study from the Japan Environment and Children's Study.

OBJECTIVES: To investigate the association between multimorbidity during pregnancy and neurodevelopmental delay in offspring using data from a Japanese nationwide birth cohort study. DESIGN: This study was a prospective birth cohort study. SETTING: This study population included 104 059 fetal records who participated in The Japan Environment and Children's Study from 2011 to 2014. PARTICIPANTS: Pregnant women whose children had undergone developmental testing were included in this analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Neurodevelopment of offspring was assessed using the Japanese version of the Ages and Stages Questionnaire, third edition, comprising five developmental domains. The number of comorbidities among the pregnant women was categorised as zero, single disease or multimorbidity (two or more diseases). Maternal chronic conditions included in multimorbidity were defined as conditions with high prevalence among women of reproductive age. A multivariate logistic regression analysis was conducted to examine the association between multimorbidity in pregnant women and offspring development. RESULTS: Pregnant women with multimorbidity, single disease and no disease accounted for 3.6%, 30.6% and 65.8%, respectively. The ORs for neurodevelopmental impairment during the follow-up period were similar for infants of mothers with no disease comorbidity and those with a single disease comorbidity. However, the ORs for neurodevelopmental impairment were significantly higher for children born to mothers with multimorbidity compared with those born to healthy mothers. CONCLUSION: An association was observed between the number of comorbidities in pregnant women and developmental delay in offspring. Multimorbidity in pregnant women may be associated with neurodevelopmental delay in their offspring. Further research is required in this regard in many other regions of the world.

Prevalence of childhood hypertension and associated factors in Zhejiang Province: a cross-sectional analysis based on random forest model and logistic regression.

With childhood hypertension emerging as a global public health concern, understanding its associated factors is crucial. This study investigated the prevalence and associated factors of hypertension among Chinese children. This cross-sectional investigation was conducted in Pinghu, Zhejiang province, involving 2,373 children aged 8-14 years from 12 schools. Anthropometric measurements were taken by trained staff. Blood pressure (BP) was measured in three separate occasions, with an interval of at least two weeks. Childhood hypertension was defined as systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) ≥ age-, sex-, and height-specific 95th percentile, across all three visits. A self-administered questionnaire was utilized to collect demographic, socioeconomic, health behavioral, and parental information at the first visit of BP measurement. Random forest (RF) and multivariable logistic regression model were used collectively to identify associated factors. Additionally, population attributable fractions (PAFs) were calculated. The prevalence of childhood hypertension was 5.0% (95% confidence interval [CI]: 4.1-5.9%). Children with body mass index (BMI) ≥ 85th percentile were grouped into abnormal weight, and those with waist circumference (WC) > 90th percentile were sorted into central obesity. Normal weight with central obesity (NWCO, adjusted odds ratio [aOR] = 5.04, 95% CI: 1.96-12.98), abnormal weight with no central obesity (AWNCO, aOR = 4.60, 95% CI: 2.57-8.21), and abnormal weight with central obesity (AWCO, aOR = 9.94, 95% CI: 6.06-16.32) were associated with an increased risk of childhood hypertension. Childhood hypertension was attributable to AWCO mostly (PAF: 0.64, 95% CI: 0.50-0.75), followed by AWNCO (PAF: 0.34, 95% CI: 0.19-0.51), and NWCO (PAF: 0.13, 95% CI: 0.03-0.30). Our results indicated that obesity phenotype is associated with childhood hypertension, and the role of weight management could serve as potential target for intervention.

Predictors for acute exacerbation of interstitial pneumonia following lung cancer surgery: a multicenter study.

BACKGROUND: Acute exacerbation (AE) of interstitial lung disease (ILD) is one of the most serious complications during perioperative period of lung cancer resection. This study aimed to investigate the correlation between preoperative 2- deoxy-2-[18F]fluoro-D-glucose (18F-FDG) PET/CT findings and AE in lung cancer patients with ILD. METHODS: We retrospectively reviewed the data of 210 patients who underwent lung resection for non-small cell lung cancer. Relationships between clinical data and PET images and AE were evaluated. The patients were divided into an AE(+) and an AE(-) group for multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was conducted and the area under curve (AUC) was used to assess the predictive values. RESULTS: Among 210 patients, 48 (22.8%) were diagnosed with ILD based on chest CT. Among them, 9 patients (18.75%) developed AE after lung resection and were defined as AE(+) group. The course of ILD was longer in AE(+) group compared to AE(-) group. More patients in AE(+) group had a history of AE and chronic obstructive pulmonary disease (COPD) than in AE(-) group. The maximum standardized uptake value (SUVmax) of the noncancerous interstitial pneumonia (IP) area and cancers in AE(+) group was significantly higher compared to AE(-) group. Univariate logistic regression analysis showed that AE, COPD, SUVmax of the noncancerous IP area, SUVmax of cancer, surgical method were significantly correlated with AE. The course of ILD[OR(95%CI) 2.919; P = 0.032], SUVmax of the noncancerous IP area[OR(95%CI) 7.630;P = 0.012] and D-Dimer level[OR(95%CI) 38.39;P = 0.041] were identified as independent predictors for AE in patients with ILD after lung cancer surgery. When the three indicators were combined, we found significantly better predictive performance for postoperative AE than that of SUVmax of the noncancerous IP area alone [0.963 (95% CI 0.914-1.00); sensitivity, 100%, specificity 87.2%, P < 0.001 vs. 0.875 (95% CI 0.789 ~ 0.960); sensitivity, 88.9%, specificity, 76.9%, P = 0.001; difference in AUC = 0.088, Z = 1.987, P = 0.04]. CONCLUSION: The combination of the course of ILD, SUVmax of the noncancerous IP area and D-Dimer levels has high predictive value for the occurrence of AE in patients with concomitant interstitial lesions.

Random forests for the analysis of matched case-control studies.

BACKGROUND: Conditional logistic regression trees have been proposed as a flexible alternative to the standard method of conditional logistic regression for the analysis of matched case-control studies. While they allow to avoid the strict assumption of linearity and automatically incorporate interactions, conditional logistic regression trees may suffer from a relatively high variability. Further machine learning methods for the analysis of matched case-control studies are missing because conventional machine learning methods cannot handle the matched structure of the data. RESULTS: A random forest method for the analysis of matched case-control studies based on conditional logistic regression trees is proposed, which overcomes the issue of high variability. It provides an accurate estimation of exposure effects while being more flexible in the functional form of covariate effects. The efficacy of the method is illustrated in a simulation study and within an application to real-world data from a matched case-control study on the effect of regular participation in cervical cancer screening on the development of cervical cancer. CONCLUSIONS: The proposed random forest method is a promising add-on to the toolbox for the analysis of matched case-control studies and addresses the need for machine-learning methods in this field. It provides a more flexible approach compared to the standard method of conditional logistic regression, but also compared to conditional logistic regression trees. It allows for non-linearity and the automatic inclusion of interaction effects and is suitable both for exploratory and explanatory analyses.

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabetes. Early and accurate identification of individuals at risk for MetS is essential. Various machine learning approaches have been employed to predict MetS, such as logistic regression, support vector machines, and several boosting techniques. However, these methods use MetS as a binary status and do not consider that MetS comprises five components. Therefore, a method that focuses on these characteristics of MetS is needed. In this study, we propose a multi-task deep learning model designed to predict MetS and its five components simultaneously. The benefit of multi-task learning is that it can manage multiple tasks with a single model, and learning related tasks may enhance the model's predictive performance. To assess the efficacy of our proposed method, we compared its performance with that of several single-task approaches, including logistic regression, support vector machine, CatBoost, LightGBM, XGBoost and one-dimensional convolutional neural network. For the construction of our multi-task deep learning model, we utilized data from the Korean Association Resource (KARE) project, which includes 352,228 single nucleotide polymorphisms (SNPs) from 7729 individuals. We also considered lifestyle, dietary, and socio-economic factors that affect chronic diseases, in addition to genomic data. By evaluating metrics such as accuracy, precision, F1-score, and the area under the receiver operating characteristic curve, we demonstrate that our multi-task learning model surpasses traditional single-task machine learning models in predicting MetS.

Rupture risk of intracranial aneurysms: Comparison between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms.

To compare the differences in clinical and morphological features between small ruptured intracranial aneurysms and large unruptured intracranial aneurysms to evaluate the risk factors for the rupture of IAs. The clinical data of 189 consecutive patients with 193 IAs were reviewed. The patients and IAs were divided into ruptured (<5 mm) and unruptured groups (>10 mm). The characteristics of the patients and the intracranial aneurysms (IAs) were compared between the 2 groups, and the risk factors for rupture of IAs were assessed using multiple logistic regression. Patient age (odds ratio [OR], 0.955), IA located at the internal carotid artery (ICA, OR, 0.202), irregular shape (OR, 0.083) and parent vessel diameter (OR, 0.426) were negatively correlated with the risk of IA rupture. IAs located at bifurcations (OR, 6.766) were positively correlated with the risk of IA rupture. In addition to the size of the IAs, regardless of IAs shape, other factors, such as younger age (<63.5 years), location at a bifurcation, IAs located at the ICA and a small parent vessel diameter (<3.25 mm), can influence the risk of IA rupture.

Tinea capitis and its associated factors among school children in Gondar town northwest, Ethiopia.

INTRODUCTION: Tinea capitis is a global public health concern with a unique therapeutic challenge and mostly affects children. The burden is double in developing countries. There is no study on school-going children from the urban residence in Ethiopia. OBJECTIVE: To determine the prevalence of Tinea capitis and its associated factors among school children in Gondar town northwest, Ethiopia 2021. METHODS: An institution-based cross-sectional study was conducted among school children in Gondar town from November 20 to December 20, 2021. Data was collected through an interviewer-administered structured questionnaire. A stratified simple random sampling technique was employed. Then data were entered into EPI Info version 7.22 and transferred to Statistical package for social science (SPSS) version 22 for further analysis. The binary logistic regression model was employed to identify factors associated with tinea capitis, and the strength of association and statistical significance was declared using the adjusted odds ratios with its corresponding 95% CI, and p-value ≤ 0.05 respectively. RESULT: The prevalence of tinea capitis among school children in Gondar town was found to be 29.4%. Public school student (AOR = 2.79 95% CI: 1.34-5.87), widowed mother (AOR = 6.09, 95% CI: 1.83-11.23), students in the age group of 5-8 years (AOR = 3.79 95% CI: 1.68-8.55), animal contact (AOR = 2.61 95% CI: 1.15-5.90), and family similar illness category (AOR = 8.49 95% CI: 3.73-11.39) have risen the likelihood of tinea capitis among school children. CONCLUSIONS: The prevalence of tinea capitis was higher. Young age, children from widowed marital status, illiterate mother, history of share blades, animal contact, a family similar illness, and lower number of living rooms are important factors contributing to tinea capitis among school children. Health education for the mother on the mode of transmission, prevention, and improve the low socioeconomic status of the parent is crucial. KEY TERMS: Children, Ethiopia, Gondar, School age, Tinea capitis.

Potentially Inappropriate Use of Medication and Its Determinants Among Ambulatory Older Adults in Six Community Chain Pharmacies in Asmara, Eritrea: A Cross-Sectional Study Using the 2023 American Geriatric Society Beers Criteria®.

Background: Potentially inappropriate medication (PIM) use is one of the main drug-related problems encountered in older adults. It is associated with adverse drug events, morbidity, mortality, increased economic costs, and negative effects on the quality of life that requires strict monitoring of prescriptions in older adults. Thus, the study aimed to assess potentially inappropriate medication use and its determinants among older adults. Methods: A cross-sectional study was conducted among all outpatient prescriptions dispensed to older adults (aged 65 years and above) in six community chain pharmacies in Asmara, Eritrea. Data were collected retrospectively, between June 16 and July 16, 2023. PIMs were detected using the 2023 American Geriatric Society (AGS) Beers Criteria®. Descriptive statistics and logistic regression analysis were performed using IBM SPSS® (Version-26.0). Results: A total of 2680 outpatient prescriptions dispensed to older adults were included in this study. The prevalence of PIM among prescriptions was 18.1% (95% CI: 16.7, 19.6). Moreover, a total of 470 medications were found to be avoided in older adults. The most commonly prescribed PIMs were sulfonylureas (27.2%) and substituted alkylamines (16.2%). The prevalence of prescriptions containing medications to be used with caution in older adults was 13.2% (95% CI: 12.0, 14.5). Age (Adjusted Odds Ratio (AOR))=0.98, 95% CI: 0.97, 0.99), polypharmacy (AOR=2.77, 95% CI: 1.49, 5.15), and general practitioner prescriber (AOR=1.38, 95% CI: 1.11, 1.70) were significantly associated with PIMs. Conclusion: A considerable number of ambulatory older adults were exposed to PIMs which require a close attention by policymakers, program managers, and healthcare professionals.

Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET.

Purpose: The aim of this study was to evaluate the association between computed tomography (CT) quantitative pulmonary vessel morphology and lung function, disease severity, and mortality risk in patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: Participants of the prospective nationwide COSYCONET cohort study with paired inspiratory-expiratory CT were included. Fully automatic software, developed in-house, segmented arterial and venous pulmonary vessels and quantified volume and tortuosity on inspiratory and expiratory scans. The association between vessel volume normalised to lung volume and tortuosity versus lung function (forced expiratory volume in 1 sec [FEV1]), air trapping (residual volume to total lung capacity ratio [RV/TLC]), transfer factor for carbon monoxide (TLCO), disease severity in terms of Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D, and mortality were analysed by linear, logistic or Cox proportional hazard regression. Results: Complete data were available from 138 patients (39% female, mean age 65 years). FEV1, RV/TLC and TLCO, all as % predicted, were significantly (p < 0.05 each) associated with expiratory vessel characteristics, predominantly venous volume and arterial tortuosity. Associations with inspiratory vessel characteristics were absent or negligible. The patterns were similar for relationships between GOLD D and mortality with vessel characteristics. Expiratory venous volume was an independent predictor of mortality, in addition to FEV1. Conclusion: By using automated software in patients with COPD, clinically relevant information on pulmonary vasculature can be extracted from expiratory CT scans (although not inspiratory scans); in particular, expiratory pulmonary venous volume predicted mortality. Trial Registration: NCT01245933.

Impact of Dementia in Colorectal Cancer Patients: United States Population-Based Cohort Study.

Background/Aims: Various socioeconomic and racial disparities are well-documented for colon cancer. However, the association of dementia, which is a growing cause of mortality in the elderly, remains unexplored. We aim to understand the association between these two conditions, in the elderly population group. Methods: We utilized the 2020 National Inpatient Sample to investigate records admitted for colorectal cancer identified through ICD-10 CM codes. We divided records by the presence of dementia. Adjusted odds ratios (aORs) for predefined outcomes were determined using multivariable logistic and linear regression models, adjusting for comorbidities. The primary outcome assessed was inpatient mortality, while secondary outcomes include other inpatient complications. Results: We identified 33,335 hospitalizations with ages more than 60. The mean age was 75.2 and males constituted 50.4%. In a survey multivariable logistic and linear regression model adjusting for patient and hospital factors, utilizing propensity score matching, the presence of dementia is associated with lower inpatient mortality (aOR 0.49, 95% confidence interval [CI] [0.26, 0.92], p=0.03), lower hospitalization costs (beta coefficient -2,823, 95% CI [-5,266, -440], p=0.02), lower odds of acute respiratory failure (aOR 0.54, p=0.01), lower mechanical ventilation usage (aOR 0.26, p<0.01) but higher odds of mental status change (aOR 1.97, 95% CI [1.37, 2.84], p<0.01). Conclusions: The presence of dementia is associated with a lower risk of inpatient mortality, and other clinical outcomes, in colorectal cancer cases admitted for hospitalization. Etiologies behind this relationship should be explored to understand this inverse relationship.

Susceptibility to e-cigarette among high school students: a study based on the ecological model of health behavior.

Introduction: Youth e-cigarette (EC) use has rapidly increased in the last few years. It is crucial to identify the susceptible youth and prevent them from EC uptake. This study was conducted to investigate factors that affect youth susceptibility to EC use. Methods: This study employed a cross-sectional survey design, utilizing multi-center stratified cluster sampling method to select two junior high schools and two senior high schools in Shanghai, Guangzhou, and Chengdu. One-third of classes of each grade in the selected schools were involved in this survey. After obtaining the informed consent of parents, an anonymous and self-administered questionnaire was distributed to students. Questionnaire was designed based on the Ecological Models of Health Behavior. Associations between EC susceptibility and covariates were identified using multivariate logistic regression. Results: Among 2,270 students who had never vaped, 38.0% were susceptible to ECs. Logistic regression analysis identified factors on different levels affecting the susceptibility. Individual factors included senior high school students (OR = 1.34, 95% CI: 1.08-1.65), sensation seeker (OR = 1.11, 95%CI: 1.08-1.14), poor academic performance (OR = 1.24, 95% CI: 1.01-1.54), ever cigarette user (OR = 2.27, 95% CI: 1.29-4.01), unaware of the second-hand smoke from vaping (OR = 1.56, 95% CI: 1.25-1.96), agreeable with "I do not want to hang around vapers" (OR = 0.79, 95% CI: 0.64-0.97), agreeable with "ECs are more fashionable than cigarette" (OR = 2.50, 95% CI: 1.72-3.62) and favorable attitudes toward vaping (OR = 5.09, 95% CI: 3.78-6.85) were significantly associated with susceptibility to ECs. At interpersonal level, students who believe they would not be punished by parents for vaping increased susceptibility (OR = 1.27, 95% CI:1.01-1.59). At community level, exposure of EC advertising (OR = 1.81, 95% CI:1.46-2.25), exposure to hazard information (OR = 0.76, 95% CI: 0.59-0.97) and seeing vaping in daily life (OR = 2.11, 95% CI: 1.62-2.74), were statistically significantly associated with youth susceptibility to ECs. Conclusion: EC susceptibility was observed in a substantial proportion of adolescents who had never vaped, influenced by factors on different levels. This research underscores the urgent need for comprehensive intervention strategies to prevent the youth susceptibility to ECs.

Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suicide attempt for intervention. In this study, six machine learning algorithms were employed to construct a predictive model for suicidal thinking and identify key variables. A traditional logistic regression analysis was supplementarily conducted to test the robustness of the results of machine learning. All analyses were conducted using a hierarchical approach to compare the model fit of each model in both machine learning and logistic regression. Three models were established for analysis. In Model 1, socioeconomic, residential, and health behavioral factors were incorporated. Model 2 expanded upon Model 1 by integrating physical health status, and Model 3 further incorporated mental health conditions. The results indicated that the gradient boosting algorithm outperformed the other machine learning techniques. Furthermore, the household income quintile was the most important feature in Model 1, followed by subjective health status, oral health, and exercise ability in Model 2, and anxiety and depression in Model 3. These results correspond to those of the hierarchical logistic regression. Notably, economic and residential vulnerabilities are significant factors in the mental health of the older population with higher instances of suicidal thoughts. This hierarchical approach could reveal the potential target population for suicide interventions.

Determinants of moderate-to-high physical activity levels in hemodialysis patients: A multicenter cross-sectional study.

Moderate physical activity is related to reduced mortality in hemodialysis patients. However, most hemodialysis patients have low physical activity levels for complex reasons. This study investigated the determinants of moderate-to-high physical activity levels and whether psychosocial correlates are associated with engagement in moderate-to-high physical activity among hemodialysis patients. A cross-sectional survey was conducted with 134 hemodialysis outpatients, aged 64.7 years, in three hemodialysis centers in Taiwan. Data on sociodemographics, comorbidities, lifestyles, and psychosocial correlates, including perceived benefits, barriers, and self-efficacy of physical activity, were collected. Multiple logistic regression analyses were performed. Results showed that patients with moderate-to-high physical activity levels constituted a significantly lower proportion of current smokers and had fewer perceived physical activity barriers and higher self-efficacy of physical activity compared with those with low levels. After adjusting for potential sociodemographic covariates, current employment, nonsmoking status, and high self-efficacy of physical activity were significantly associated with moderate-to-high physical activity levels. Developing strategies to improve the self-efficacy of physical activity, support employment, and enhance anti-smoking campaigns in hemodialysis patients can help them engage in moderate-to-high levels of physical activity.