scholarly journals Impact of Sociodemographic Characteristics, Lifestyle, and Obesity on Coexistence of Diabetes and Hypertension: A Structural Equation Model Analysis amongst Chinese Adults

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenwen Wu ◽  
Jie Diao ◽  
Jinru Yang ◽  
Donghan Sun ◽  
Ying Wang ◽  
...  
Keyword(s):  
Structural Equation Model ◽  
Latent Variables ◽  
Structural Equation ◽  
Cross Sectional Study ◽  
Equation Model ◽  
Sociodemographic Characteristics ◽  
Chinese Adults ◽  
Cross Sectional ◽  
Total Prevalence ◽  
Confirmatory Factor

Background. In general, given the insufficient sample size, considerable literature has been found on single studies of diabetes and hypertension and few studies have been found on the coexistence of diabetes and hypertension (CDH) and its influencing factors with a large range of samples. This study aimed to establish a structural equation model for exploring the direct and indirect relationships amongst sociodemographic characteristics, lifestyle, obesity, and CDH amongst Chinese adults. Methods. A cross-sectional study was conducted in a representative sample of 25356 adults between June 1, 2015, and September 30, 2018, in Hubei province, China. Confirmatory factor analysis was initially conducted to test the latent variables. A structural equation model was then performed to analyse the association between latent variables and CDH. Results. The total prevalence of CDH was 2.8%. The model paths indicated that sociodemographic characteristics, lifestyle, and obesity were directly associated with CDH, and the effects were 0.187, 0.739, and 0.353, respectively. Sociodemographic characteristics and lifestyle were also indirectly associated with CDH, and the effects were 0.128 and 0.045, respectively. Lifestyle had the strongest effect on CDH (β = 0.784, P < 0.001 ), followed by obesity (β = 0.353, P < 0.001 ) and sociodemographic characteristics (β = 0.315, P < 0.001 ). All paths of the model were significant ( P < 0.001 ). Conclusion. CDH was significantly associated with sociodemographic characteristics, lifestyle, and obesity amongst Chinese adults. The dominant predictor of CDH was lifestyle. Targeting these results might develop lifestyle and weight loss intervention to prevent CDH according to the characteristics of the population.

scholarly journals Prevention of Children’s Burnout at School through the Tutoring and Guidance Process. A Structural Equation Model Analysis

2020 ◽  
Vol 10 (12) ◽  
pp. 356
Author(s):  
Jorge Expósito-López ◽  
Ramón Chacón-Cuberos ◽  
José Javier Romero-Díaz de la Guardia ◽  
Noelia Parejo-Jiménez ◽  
Sonia Rodríguez-Fernández ◽  
...  
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Mean Squared Error ◽  
Well Being ◽  
Cross Sectional Study ◽  
Equation Model ◽  
Fit Indices ◽  
Cross Sectional ◽  
Analytical Technique ◽  
Fit Index

The school burnout of children, defined as physical and mental exhaustion due to a lack of adjustment to the educational context, constitutes a serious problem in contemporary education. Thus, the determination of the elements that influence it and the possible strategies for avoiding it are key in the process of improving children’s well-being. A descriptive and cross-sectional study was conducted with a sample of 569 children aged 8 to 13 at eight primary education schools in Granada (Spain). With the aim of examining the association between the possible exhaustion of children and planned tutoring and guidance activities, a structural equation model (SEM) as the analytical technique was used. The results show good fit indices for the model (comparative fit index (CFI) = 0.955; normalised fit index (NFI) = 0.956; incremental fit index (IFI) = 0.946; root mean squared error approximation (RMSEA) = 0.089), which reflects the need for tutoring and guidance activities that are infused throughout the entire teaching process in order to preserve children’s well-being.

scholarly journals A Structural Equation Model of Social Support, Stress and Depression in Pregnant Women During Epidemic Period

2020 ◽  
Author(s):  
Yi Liang ◽  
Shengfeng Dong ◽  
Liling Zhu ◽  
Danqing Zhao ◽  
Liming Shen
Keyword(s):  
Social Support ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Cross Sectional Study ◽  
Equation Model ◽  
Guizhou Province ◽  
Cross Sectional ◽  
Auxiliary Condition ◽  
Condition Model ◽  
Epidemic Period

Objective: To investigate the connections among social support, stress, and depression. Design: Cross-sectional study. Setting: Guizhou Province in China. Population or Sample: An aggregate of 1,056 expectant ladies, had finished our questionnaire during pregnancy from March to April in 2020. Methods: The Edinburgh prenatal sadness scale, an independent pressure scale, and social support scale evaluated the downturn, stress, and social support of pregnant people during the pestilence. An auxiliary condition model was utilized to examine the immediate and aberrant connection between social support and prenatal misery. Main Outcome Measures: Incidence of depression. Results: During the pandemic time, 73.01% of pregnant ladies experienced prenatal misery. The model is suitable (chi-square = 11.96, CFI = 0.97, RMSEA = 0.07, RMR = 0.03). The auxiliary condition model indicated that the immediate pathway of social support to depression was critical (normalized pathway coefficient = - 0.34), and the aberrant pathway of stress to depression via social support was additionally huge (normalized pathway coefficient = 0.50). Stress partially intercedes the connection between social support and depression. Conclusion: Our discoveries posit that social support is related to an expanded danger of depression. Stress is decidedly corresponding to depression and assumes an interceding position between social support and stress. Thusly, directed mediation ought to be completed to lessen the depression of pregnant ladies and improve their psychological wellness status. Keywords: stress, depression, social support, structural equation model

scholarly journals Interrelationships between obesity, blood pressure and metabolic profile in climacteric women

2021 ◽  
Vol 34 ◽  
Author(s):  
Vivianne Margareth Chaves Pereira REIS ◽  
Rafael Silveira FREIRE ◽  
Maria Fernanda Santos Figueiredo BRITO ◽  
Lucinéia de PINHO ◽  
Josiane Santos Brant ROCHA ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Structural Equation ◽  
Metabolic Profile ◽  
Family Health ◽  
Cross Sectional Study ◽  
Equation Model ◽  
Cross Sectional ◽  
Measurement Models ◽  
Menopausal Women ◽  
Confirmatory Factor

ABSTRACT Objective This study aimed to evaluate the interrelationships between obesity, blood pressure and metabolic profile in climacteric women. Methods This is a cross-sectional study with a random sample of 874 women, aged 40 to 65 years, assisted in Family Health Strategies units in Montes Claros, Minas Gerais, Brazil. A structural equation model was used to assess the interrelationships between obesity, blood pressure and metabolic profile, adjusted for age. The variables blood pressure, obesity and metabolic profile were treated as constructs, which measurement models were developed using confirmatory factor analysis. Results It was observed that age has a positive and significant effect on blood pressure (β=0.20; p<0.001) and obesity (β=0.10; p=0.004). There was a direct and positive effect of obesity on blood pressure (β=0.26; p<0.001) and on the metabolic profile (β=0.10; p=0.037), adjusted for physical activity. Conclusions The simultaneous analysis of the relationships between age, obesity, blood pressure and metabolic profile in menopausal women suggests that, ageing has an effect on the increase of obesity and blood pressure, just as obesity increases blood pressure and changes the metabolic profile.

Upaya Preventif, Mutu, Kepuasan Dan Loyalitas Ibu Hamil Terhadap Minat Kunjungan Ulang di Klinik Abdi Persada Banjarmasin

2019 ◽  
Vol 2 (1) ◽  
pp. 69-84
Author(s):  
Nur Cahyani Ari Lestari
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Equation Model ◽  
Cross Sectional

Upaya preventif dalam kesehatan dan peningkatan mutu pelayanan merupakan salah satu ukuran dari kepuasan pasien dan loyalitas pasien yang mempengaruhi keinginan pasien untuk melakukan kunjungan ulang kembali terhadap penyedia jasa layanan kesehatan tersebut. Penelitian ini bertujuan untuk mengetahui pengaruh langsung maupun tidak langsung serta besaran antara upaya preventif, mutu pelayanan kepuasaan dan loyalitas ibu hamil terhadap minat kunjungan ulang ibu hamil di Klinik Abdi Persada Banjarmasin Tahun 2018. Penelitian ini, menggunakan metode cross sectional. Populasinya adalah ibu hamil yang memeriksakan kehamilannya di Klinik Abdi Persada Banjarmasin. Sampel penelitian ini berjumlah 90 orang ibu hamil. Penelitian ini menggunakan metode analisis Structural Equation Model menggunakan Smart PLS 2.0 dan SPSS 18. Hasil pengujian hipotesis dengan Structural Equation Model (SEM) dengan metode smartPLS menghasilkan temuan penelitian yaitu upaya preventif (24,56%), mutu pelayanan (26,89%), kepuasan (8,13%) dan loyalitas (38,33%). Loyalitas ibu hamil merupakan faktor dominan yang mempengaruhi minat kunjungan ulang ibu hamil di Klinik Abdi Persada Banjarmasin. Model - Model hasil analisis dapat menjelaskan 99,9% keragaman data dan mampu mengkaji fenomena yang dipakai dalam penelitian, sedangkan 0,1% dijelaskan komponen lain yang tidak ada dalam penelitian ini. Dapat disimpulkan bahwa terdapat pengaruh antara upaya preventif, mutu pelayanan, kepuasan dan loyalitas tehadap minat kunjungan ulang ibu hamil. Sarannya sebagai masukkan untuk lebih meningkatkan pelayanan kepada ibu hamil dalam pemeriksaan kehamilannya sehingga memberikan kepuasan ibu hamil agar dapat berkunjung kembali. Kata Kunci: Preventif, Mutu Pelayanan, Kepuasaan, Loyalitas, Kunjungan Ulang

scholarly journals The Role of Managerial Commitment and TPM Implementation Strategies in Productivity Benefits

2018 ◽  
Vol 8 (7) ◽  
pp. 1153 ◽  
Author(s):  
José Díaz-Reza ◽  
Jorge García-Alcaraz ◽  
Liliana Avelar-Sosa ◽  
José Mendoza-Fong ◽  
Juan Sáenz Diez-Muro ◽  
...  
Keyword(s):  
Least Squares ◽  
Structural Equation Model ◽  
Preventive Maintenance ◽  
Latent Variables ◽  
Structural Equation ◽  
Manufacturing Industry ◽  
Implementation Strategies ◽  
Equation Model ◽  
Total Productive Maintenance

The present research proposes a structural equation model to integrate four latent variables: managerial commitment, preventive maintenance, total productive maintenance, and productivity benefits. In addition, these variables are related through six research hypotheses that are validated using collected data from 368 surveys administered in the Mexican manufacturing industry. Consequently, the model is evaluated using partial least squares. The results show that managerial commitment is critical to achieve productivity benefits, while preventive maintenance is indispensable to total preventive maintenance. These results may encourage company managers to focus on managerial commitment and implement preventive maintenance programs to guarantee the success of total productive maintenance.

Big Data Analytics in the Agribusiness Supply Chain Management

2021 ◽  
Vol 9 (3) ◽  
pp. 32-42
Author(s):  
Marisol Valencia-Cárdenas ◽  
Jorge Anibal Restrepo-Morales ◽  
Francisco Javier Día-Serna
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Structural Equation Model ◽  
Inventory Management ◽  
Latent Variables ◽  
Structural Equation ◽  
Big Data Analytics ◽  
Equation Model ◽  
Chain Management

Importance and impact of the systems related to Agribusiness and Agri-food, are increasing around the world and demand a paramount attention. Collaboration in the inventory management is an integral part of the supply chain management, related to proactive integration among the chain actors facilitating production and supply, in especial in the agroindustrial sector of the Departamento de Antioquia, Colombia. This research establishes the main relationships between latent variables as collaboration, technology, models, optimization and inventory management, based on a literature review and applying a Structural Equation Model to a survey data of a sample of agribusiness companies. The results show that Available Technologies associated with Big Data, generates improvement of Collaboration Strategies, improving also Forecasting and Optimization; besides, Inventory Planning and Collaboration are related to Available Technologies associated with Big Data. A Poisson regression model and a Structural Equation Model estimations detect that the increasing strategies of technologies and Big Data are favorable to apply collaboration in the supply chain management, increasing possibilities to the enterprise competitiveness.

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