Economic factors affecting point-of-sale systems in Saudi Arabia’s food sectors by Mohamad Alnafissa, Yosef Alamri, Alaa Kotb, Emad S. Aljohani

“…The research utilized path regression analysis, following initial tests that revealed multicollinearity issues in a standard OLS model. …”
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Factors affecting oral frailty and nutritional status in older adults living alone by Ji-Min Cha, Dong Hoon Jung, Ha-neul Kim, Hee-Sook Lim

“…A survey of 606 adults aged 65 years and older examined their sociodemographic characteristics, health status, oral health, and nutritional status. Logistic regression analysis identified key factors affecting oral frailty and nutritional status.ResultsResults revealed a direct association between oral frailty and nutritional status, with loneliness emerging as a common factor influencing both variables.DiscussionThese findings highlight the importance of maintaining a balanced diet alongside proper oral hygiene and emphasize the need for integrated interventions including emotional support. …”
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Learned helplessness among vocational nursing students: current status and influencing factors by Yiheng Wang, Chunhong Zhou, Xihong Qian, Ying Zhao, Ling Gao, Wenlan Xu

“…Multivariate linear regression analysis revealed that the following factors were significantly associated with learned helplessness: low per capita household income (< 3000 yuan), non-voluntary choice of major (joint decision, parental preference, or other), non-passive future career orientation (further education or employment), low self-perceived major satisfaction, and poor interpersonal relationships with classmates (P < 0.05). …”
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The disease burden of gout in Asian countries and regions from 1990 to 2021, risk factors and forecast analysis: A systematic study of Asian disease burden in 2021. by Fuyu Yang, Runze Chen, Jun Xiong, Wenzhen Wang, Peng Yu, Huilin Wang

“…<h4>Methods</h4>Collect gout prevalence, incidence etc. from global burden of disease data in Asia, stratified by gender and age, analyze with statistical charts. Use Joinpoint regression model for trend analysis. …”
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Surgical Site Infections: Risk Factors for Multiple Antibiotic Resistance in Abdominal Surgery by D. S. Parshin, M. A. Topchiev, V. A. Astakhin, O. B. Chechukhina, E. O. Smirnyagina, E. N. Ravskiy

“…Single- and multivariate analysis was carried out, binary and multinomial logistic regression was performed. …”
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Factors Associated with Occupancy Level in a High- Complexity Emergency Department in Medellín by Estrada-Atehortúa, Andrés Felipe, Arroyave-Peña, Tatiana, Quiroz-Álvarez, Juan Esteban, Giraldo-Hoyos, Jaime Andrés, Bareño-Silva, José

“…Objectives: To determine the ED occupancy level at Hospital Pablo Tobón Uribe, Medellin, using the National Emergency Department Overcrowding Study (NEDOCS), analyzing hospital service factors, processes, physical capacity, and human resources. …”
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Investigating Factors Affecting Social Indifference among Female Teachers and Strategies for Mitigation by Azam Khatibi, Masoome Zand

“…Interestingly, neither socio-economic status nor age appeared to influence levels of social indifference. Stepwise regression analysis identified social satisfaction as the first variable to enter the model followed by social alienation and then social responsibility. …”
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Demographic characteristics and lifestyle related factors of depressive symptoms in Chinese children and adolescents by ZHAO Xia

“…The frequency of sugar-sweetened beverages (SSBs) consumption, exercise frequency, and daily internet usage on school days were significantly correlated with the prevalence and scores of depressive symptoms (P < 0.001). ④ Regression analysis identified that female, junior high school status, maternal military occupation, residence in the Western area, occasional or frequent SSBs consumption, and daily internet usage on school days were negative factors for depressive symptoms (P < 0.001); Whereas maternal education level of junior high school or over, family economic status of moderate or higher, adequate sleep duration, and regular exercise were positive factors (P < 0.001). …”
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Geographic patterns and environmental factors associated with human yellow fever presence in the Americas. by Patricia Najera Hamrick, Sylvain Aldighieri, Gustavo Machado, Deise Galan Leonel, Luz Maria Vilca, Sonia Uriona, Maria Cristina Schneider

“…Presence of yellow fever by county was used as the outcome variable and eight geo-environmental factors were used as independent variables. Spatial analysis was performed to identify and examine natural settings per county. …”
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Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach by Xiayuan Huang, Shushun Ren, Xinyue Mao, Sirui Chen, Elle Chen, Yuqi He, Yun Jiang

“…Their records were matched and combined with those of patients without cancer diagnoses using propensity scores based on demographic factors. Three advanced models, penalized logistic regression, random forest, and multilayer perceptron (MLP), were conducted to identify the rank of risk factors for each cancer type, with feature importance analysis for random forest and MLP models. …”
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Factors associated with loss and recovery of smell and taste after COVID‐19 infection by Diego E. Razura, Ido Badash, Bozena Wrobel, Kevin Hur

“…Methods The Integrated Public Use Microdata Series (IPUMS) 2021 National Health Interview Series (NHIS) database was used to analyze factors associated with loss and recovery of smell and taste in respondents who had a previous COVID‐19 infection. …”
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Telomere length in young and middle-aged patients: relationship with cardiovascular risk factors by V. I. Podzolkov, A. E. Bragina, N. A. Druzhinina, L. V. Vasilyeva, R. A. Shikhmagomedov, E. M. Averyeva

“…According to the multivariate regression analysis, LTL was associated with age (B=-0,04, Std. …”
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Occurrence and influencing factors of cardiovascular diseases in uremic patients after combined blood purification therapy by Shen Yu-xin, Zhang Qian-nan, Yu Ying-ji, Li Jun-hui

“…The general demographic data and clinical data of the two groups were compared. Logistic regression model was used to analyze the influencing factors of CVD occurrence after combined blood purification， and Spearman correlation analysis was used to analyze the correlation between each factor and CVD occurrence.ResultsA total of 122 uremia patients were included in the study， of which 20 had CVD， accounting for 16.39%， and the remaining 102 （83.61%） without CVD were included in the non-CVD group. …”
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Identifying Psychological and Sociological Factors Affecting Job Aspirations in Lower Secondary Students by Farid Ahmadi, Soheila Ahmadi

“…Additionally, Likert-type scales were used to collect data on academic self-concept, parental involvement, academic self-efficacy, socio-economic status, and student-teacher relationships. The data were analyzed using SPSS, utilizing descriptive statistics, correlation coefficients, and hierarchical regression techniques.   …”
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Analysis of risk factors of cholangiocarcinoma, role of diabetes mellitus and hepatitis B virus infection in the intrahepatic and extrahepatic cholangiocarcinoma: a retrospective c... by Hasan Md Rasadul, Peng-cheng Kang, Jing-lin Li, Shi-hui Ma, Cheng-hong Duan, Xu-dong Zhao, Yun-fu Cui

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Risk factors for linezolid - induced haematological toxicity in patients: a retrospective study by Kai Mo, Wen Cao, YaTing Lu, JuMan Li, RuHua Wei, MingWei Meng, YingE Liang, Hui Zhong, YanE Qin, XiaoBu Lan

“…Results: Binary logistic regression analysis revealed that creatinine clearance level (Ccr) < 50 mL/min/1.73 m2 (OR, 5.463; 95% CI, 1.249-23.888, p = 0.024) and Cmin > 7 mg/L (OR, 62.660; 95% CI, 14.293-274.708, p = 0.001) were risk factors associated with linezolid-induced thrombocytopenia. …”
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Occurrence and influencing factors of cardiovascular diseases in uremic patients after combined blood purification therapy by Shen Yu-xin, Zhang Qian-nan, Yu Ying-ji, Li Jun-hui

“…The general demographic data and clinical data of the two groups were compared. Logistic regression model was used to analyze the influencing factors of CVD occurrence after combined blood purification， and Spearman correlation analysis was used to analyze the correlation between each factor and CVD occurrence.ResultsA total of 122 uremia patients were included in the study， of which 20 had CVD， accounting for 16.39%， and the remaining 102 （83.61%） without CVD were included in the non-CVD group. …”
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Prevalence and determinants of clustering of adverse lifestyle behaviors among 35 – 75 years old residents at high cardiovascular disease risk in Hebei province: an analysis of dat... by Yuejing QIAO, Yuhuan LIU, Lijuan TANG, Dongsheng JIANG, Xiaoli LIU, Ze CUI

“…Multivariate unconditional logistic regression analysis revealed that being aged 45 – 64 years and having an agricultural household registration were risk factors for clustering of adverse lifestyle behaviors, but being female, having a junior high school education and above, having an annual household income of more than 25 000 Chinese yuan, being a laborer/private/commercial service worker/retired person/housewife/unemployed/and having other occupation were protective factors against the clustering for the residents. …”
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Analysis of the status and factors influencing the intrinsic capacity of hospitalized elderly patients (住院老年患者内在能力的现状和影响因素分析) by SUN Yutong (孙雨彤), ZHANG Jie (张洁), LI Hong (李虹), LI Jing (李晶), SHI Hong (施红), SHEN Ji (沈姞), ZHOU Jiao (周娇), DUAN Yuwei (段雨薇), ZHANG Dandan (张丹丹)

“…Methods Using a convenience sampling method, 264 elderly patients admitted to the geriatric ward from March 2020 to April 2022 were selected as the study population, and the WHO-recommended intrinsic capacity assessment tool, the Geriatric Index of Comorbidity (GIC) and the General Information Questionnaire were applied to analyze the status and factors influencing the intrinsic capacity of hospitalized elderly patients. …”
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Spatial Analysis of Rural Settlement Systems within the Framework of Land Use Planning Using Geographic Information Systems (Case Study: Aq Su Rural District) by Seyed Mohammad Mousavi Parsaei

“…To measure the impact of vulnerability factors on the spatial distribution of rural settlements, multiple regression analysis was utilized. …”
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