Pattern and Predicting Risk Factors of Multi-Morbidity in the AzarCohort Population Using Structural Equation Model

Background: The co-existence of chronic diseases (CD), a condition defined as multimorbidity (MM), is becoming a major public health issue. Understanding the general framework of MM diseases according to the well-known risk factors can assist in finding direct and indirect relationships among them. Therefore, we aimed to determine pattern and predicting risk factors of multi-morbidity in the Azar Cohort population using Structural Equation Model (SEM). Methods: In this study, the prevalence of MM in 15006 XXX cohort population was evaluated. MM was defined as the co-existence of two or more CDs. The information regarding socio-economic, demographic, sleeping habits, and physical activity were collected by questionnaires. A multi-group SEM was employed to model complex relationships between directly- and indirectly-observed variables. Results: The overall MM was seen in 28.8% of the population. The most prevalent chronic diseases were obesity, hypertension, depression, and diabetes, respectively. Obesity, depression, and diabetes were the most co-occurring CDs in our population. The SEM diagram indicated the overall effect of socio-demographic (predictors) and sleep and physical activity (mediators) on the number of CDs. The number of CDs in the active participants and those who sleep 6.6-7.3 hours/day was lower than the inactive participants and those who sleep ≤6.5 hours/day. Conclusions: According to our results, it seems that the reduction of MM is possible through promoting public health from an early age and for a wide range of socio-economic conditions, provided that the necessary support for general health is offered for the aging population.

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Social Capital and Factors Related to Stroke Risk in Ponorogo Hospital: Structural Equation Model Application

Journal of Epidemiology and Public Health ◽

10.26911/jepublichealth.2020.05.03.01 ◽

2020 ◽

Vol 5 (3) ◽

pp. 258-269

Author(s):

Lailatul Rohmah ◽

◽

Setyo Sri Rahardjo ◽

Bhisma Murti ◽

◽

...

Keyword(s):

Physical Activity ◽

Risk Factors ◽

Social Capital ◽

Structural Equation Model ◽

Structural Equation ◽

Stroke Risk ◽

Dietary Habits ◽

Equation Model ◽

Workplace Stress ◽

Dietary Habit

Background: Stroke is a non-communicable disease that ranks the second leading cause of death in the world. As many as 17 million patients who suffered a stroke, 6.5 million died from a stroke. This disease cannot be cured but can be controlled. The increasing number of cases of non-communicable diseases is related to risk factors. This study aimed to analyze the effect of social capital and factors related to stroke risk. Subjects and Method: A case-control study was conducted at the Ponorogo District Hospital, East Java, from February to March 2020. A sample of 200 patients was taken through fixed disease sampling. The dependent variable was a stroke. The independent variables were social capital, hypertension, residence, workplace, stress, income, dietary habit, education, physical activity. The data was collected using a questionnaire. Data were analyzed using the Structural Equation Model run on Stata 13. Results: The increase in stroke was directly affected by hypertension (b= 2.90; 95% CI= 2.09 to 3.71; p <0.001). The risk of stroke was affected indirectly by social capital, hypertension, workplace, stress, income, dietary habit, education, physical activity. Trust, bonding, bridging, and linking indirectly affected stroke risk on the contribution of social capital measurement. Conclusion: Increased stroke is directly affected by hypertension. Stroke is indirectly affected by social capital, hypertension, workplace, stress, income, dietary habits, education, and physical activity. Trust, bonding, bridging, and linking indirectly affect stroke risk on the contribution of social capital measurement. Keywords:stroke, social capital, risk factors Correspondence: LailatulRohmah. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: [email protected]. Mobile: +62896- 91804847.

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A Structural Equation Model of the relationship between physical activity and quality of life

International Journal of Clinical and Health Psychology ◽

10.1016/j.ijchp.2015.11.001 ◽

2016 ◽

Vol 16 (2) ◽

pp. 147-156 ◽

Cited By ~ 6

Author(s):

María Carbó-Carreté ◽

Joan Guàrdia-Olmos ◽

Climent Giné ◽

Robert L. Schalock

Keyword(s):

Quality Of Life ◽

Physical Activity ◽

Structural Equation Model ◽

Structural Equation ◽

Equation Model ◽

The Relationship

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Decision letter for "Quality of life in patients with comorbid serious mental illness and chronic diseases: A structural equation model"

10.1111/jan.14663/v2/decision1 ◽

2020 ◽

Keyword(s):

Quality Of Life ◽

Mental Illness ◽

Chronic Diseases ◽

Structural Equation Model ◽

Serious Mental Illness ◽

Structural Equation ◽

Equation Model

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Decision letter for "Quality of life in patients with comorbid serious mental illness and chronic diseases: A structural equation model"

10.1111/jan.14663/v1/decision1 ◽

2020 ◽

Keyword(s):

Quality Of Life ◽

Mental Illness ◽

Chronic Diseases ◽

Structural Equation Model ◽

Serious Mental Illness ◽

Structural Equation ◽

Equation Model

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Individual, social and environmental correlates of physical activity in overweight and obese African American and Hispanic women: A structural equation model analysis

Preventive Medicine Reports ◽

10.1016/j.pmedr.2015.01.001 ◽

2015 ◽

Vol 2 ◽

pp. 57-64 ◽

Cited By ~ 26

Author(s):

Scherezade K. Mama ◽

Pamela M. Diamond ◽

Sheryl A. McCurdy ◽

Alexandra E. Evans ◽

Lorna H. McNeill ◽

...

Keyword(s):

Physical Activity ◽

African American ◽

Structural Equation Model ◽

Structural Equation ◽

Hispanic Women ◽

Model Analysis ◽

Equation Model ◽

Environmental Correlates

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On Risk Factors of Inventory Finacing Based on Structural Equation Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.58-60.674 ◽

2011 ◽

Vol 58-60 ◽

pp. 674-679

Author(s):

Juan He ◽

Xin Wang ◽

Zhong Hua Ma

Keyword(s):

Risk Factors ◽

Credit Risk ◽

Structural Equation Model ◽

Structural Equation ◽

Equation Model ◽

Path Diagram ◽

Financing Risk ◽

Operation Status ◽

Inventory Financing ◽

The Empirical Analysis

This paper analyses the risk factors of inventory finacing, establishes path diagram and the structural equation model on relations between inventory financing risk factors and makes the empirical analysis. The results indicate the operation status of the company and the characteristics of the inventory pledged have a significant effect on credit risk, and so of the level of company management on company operation.Based on this, banks should take relative measures while developing the inventory finacing.

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Physical Fitness Plays a Crucial Mediator Role in Relationships Among Personal, Social, and Lifestyle Factors With Adolescents' Cognitive Performance in a Structural Equation Model. The Cogni-Action Project

Frontiers in Pediatrics ◽

10.3389/fped.2021.656916 ◽

2021 ◽

Vol 9 ◽

Author(s):

Vanilson Lemes ◽

Anelise R. Gaya ◽

Kabir P. Sadarangani ◽

Nicolas Aguilar-Farias ◽

Fernando Rodriguez-Rodriguez ◽

...

Keyword(s):

Physical Activity ◽

Physical Fitness ◽

Cognitive Performance ◽

Structural Equation Model ◽

Structural Equation ◽

Sleep Problems ◽

Equation Model ◽

Cognitive Tasks ◽

Fitness Components ◽

Mediator Role

Background: The beneficial relationship between physical fitness and cognitive performance is affected and modulated by a wide diversity of factors that seem to be more sensitive during the development stage, particularly during early adolescence. This study aimed to examine the role of physical fitness considering the multivariate association between age, health-related quality of life (HRQOL), school vulnerability index (SVI), body mass index z-score (BMIz), physical activity, and sleep problems with the cognitive performance in boys and girls.Method: Participants were 1,196 adolescents aged 10–14 years (50.7% of boys) from Chile. Three physical fitness components and eight cognitive tasks were measured. BMIz was determined using growth references by age and sex, whereas questionaries were used to assess sleep problems, physical activity, and HRQOL. SVI was established according to the score given by the Chilean Government to educational establishments. We performed a structural equation model (SEM) to test multivariate associations among study' variables by sex.Results: Fitness was positively associated with boys' and girls' cognitive performance (β = 0.23 and β = 0.17; p = 0.001, respectively). Moreover, fitness presented a significant mediator role in the relationships between BMIz, SVI, and physical activity with cognitive performance (indirect effect). Additionally, SVI showed a negative association both direct and indirect effect in all three fitness components and all cognitive tasks, being this relationship stronger in girls than in boys.Conclusion: Our findings suggest that physical fitness and all its components play a crucial mediator role in the associations between several factors associated with adolescents' cognitive performance. Thereby, educational and health strategies should prioritise improving physical fitness through physical activity. They also should address other factors such as school vulnerability, obesity, and the early gender gap in a comprehensive approach boosting cognitive performance among early adolescents.Trial registration: Research Registry (ID: researchregistry5791).

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Analysis of the Risk Factors Affecting the Size of Fatal Accidents Involving Trucks Based on the Structural Equation Model

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119841042 ◽

2019 ◽

Vol 2673 (8) ◽

pp. 112-124 ◽

Cited By ~ 2

Author(s):

Yalong Yuan ◽

Min Yang ◽

Zuoxian Gan ◽

Jingxian Wu ◽

Chengcheng Xu ◽

...

Keyword(s):

Risk Factors ◽

Structural Equation Model ◽

Structural Equation ◽

Structural Model ◽

Equation Model ◽

Body Type ◽

Fatal Accidents ◽

Fatal Accident ◽

Accident Severity ◽

Occupant Injury

For decreasing the casualties and property losses in truck-involved fatal accidents, efforts to identify risk factors and their impacts on the fatal accidents are urgently needed. First, for scaling damage extent in fatal accident, truck occupant injury factor and accident size were selected from occupant- and crash- levels respectively. Then, a general structural model was built to explore the relationships between environmental, roadway, vehicle, driver factors and fatal accident severity. Afterwards, by analyzing 2010 data from the Trucks Involved in Fatal Accidents (TIFA) database, a weighted least squares (WLS) based structural equation model (SEM) was adopted to estimate the parameters of the general structural model. Significant differences between various risk factors determining truck occupant injury factors and accident severity were identified. The results indicate that environmental, roadway, vehicle, and driver factors all have statistically significant effects on the accident size and truck occupant injury factors. However, the extent to which these risk factors impact these two latent endogenous variables differ significantly. Measurement models including different latent risk factors and the corresponding observed variables are then analyzed. The results show that main indicators affecting accident severity are: environmental and roadway factors such as weather, surface conditions; vehicle factors such as truck weight and body type; and driver factors such as age, driving experience, and history of crashes or convictions. Finally, several countermeasures are suggested for truck manufactures and safety planners with the goal of reducing the number and severity of fatal accidents involving trucks.

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