scholarly journals Pathways Leading to Prevention of Fatal and Non Fatal CVDs: An Interaction Model on 15 years Population-Based Cohort study

2020 ◽  
Author(s):  
Najmeh Shakibaei ◽  
Razieh Hassannejad ◽  
Noushin Mohammadifard ◽  
Hamid Reza Marateb ◽  
Marjan Mansourian ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Lipid Profile ◽  
Life Style ◽  
Latent Variables ◽  
Equation Modeling ◽  
Causal Network ◽  
Coronary Syndrome ◽  
Wide Range

Abstract Background An extensive study on cardiovascular risk factors interaction seems to be of crucial importance in order to prevent cardiovascular (CVD) events. The main focus of this study is understanding direct and indirect relationships between different CVDs risk factors. Methods A longitudinal data on adults aged ≥ 35 years, who were free of CVD at baseline, were used to study. The endpoints were CVD events, while their measurements were demographic, socio-economics, life-style components, laboratory findings, anthropometric measures, psychological factors, and quality of life status. A Bayesian structural equation modeling (BSEM) was used to determine the relationships among 21 relevant factors associated with total CVD, stroke, acute coronary syndrome (ACS), and fatal CVDs. Results In this study a total of 3161 individuals with complete information were included in the study. Total 407 CVD events were occurred during follow-up. The causal associations between 6 latent variables were identified in the causal network for fatal and non-fatal CVDs. Lipid profile influences the occurrence of CVD events as the most important, but it did so indirectly mediate through the risky behaviors and comorbidities. Lipid profile at baseline was influenced by a wide range of other protective factors, such as quality of life and healthy life style components. Conclusions Analyzing a causal network on risk factors reveals the flow of information in direct and indirect paths, as well as determining predictors and demonstrate the utility of integrating multi-factor data in a complex framework to identify novel candidate preventable pathways to lower risk of CVDs.

scholarly journals Pathways Leading to Prevention of Fatal and Non-Fatal Cardiovascular Disease: An Interaction Model on 15 years Population-Based Cohort study

2020 ◽  
Author(s):  
Najmeh Shakibaei ◽  
Razieh Hassannejad ◽  
Noushin Mohammadifard ◽  
Hamid Reza Marateb ◽  
Marjan Mansourian ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Cardiovascular Disease ◽  
Lipid Profile ◽  
Causal Network ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Coronary Syndrome ◽  
Wide Range

Abstract Background: A comprehensive study on the interaction of cardiovascular disease (CVD) risk factors is critical to prevent cardiovascular events. The main focus of this study is thus to understand direct and indirect relationships between different CVD risk factors. Methods: A longitudinal data on adults aged ≥35 years, who were free of CVD at baseline, were used in this study. The endpoints were CVD events, whereas their measurements were demographic, lifestyle components, socio-economics, anthropometric measures, laboratory findings, quality of life status, and psychological factors. A Bayesian structural equation modelling was used to determine the relationships among 21 relevant factors associated with total CVD, stroke, acute coronary syndrome (ACS), and fatal CVDs. Results: In this study, a total of 3161 individuals with complete information were involved in the study. A total of 407 CVD events, with an average age of 54.77(10.66) years, occurred during follow-up. The causal associations between six latent variables were identified in the causal network for fatal and non-fatal CVDs. Lipid profile, with the coefficient of 0.26 (0.01), influenced the occurrence of CVD events as the most critical factor, while it was indirectly mediated through risky behaviours and comorbidities. Lipid profile at baseline was influenced by a wide range of other protective factors, such as quality of life and healthy lifestyle components. Conclusions: Analysing a causal network of risk factors revealed the flow of information in direct and indirect paths. It also determined predictors and demonstrated the utility of integrating multi-factor data in a complex framework to identify novel preventable pathways to reduce the risk of CVDs.

scholarly journals Analysis of risk factors for vitamin D deficiency by results of the first stage of Russian non-interventional register study

2021 ◽  
pp. 109-118
Author(s):  
L. A. Suplotova ◽  
V. A. Avdeeva ◽  
L. Y. Rozhinskaya ◽  
E. A. Pigarova ◽  
E. A. Troshina
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Vitamin D ◽  
Vitamin D Deficiency ◽  
Russian Federation ◽  
Direct Sunlight ◽  
Cross Sectional ◽  
Wide Range ◽  
Smoking Duration

Introduction. In Russian Federation, there are no comprehensive studies assessing the quality of life and risk factors for vitamin D deficiency and insufficiency, taking into account its status in different geographic latitudes.Aim. To assess the quality of life and risk factors for vitamin D deficiency and insufficiency among the population living in the regions of the Russian Federation located at latitudes from 45 ° to 70 °.Materials and methods. The first stage of the Russian multicenter non-interventional registry study using the “cross-sectional” method was carried out from March 2020 to May 2020.Results and discussion. According to the results of the correlation analysis, qualitative and quantitative factors were identified, presumably being risk factors for vitamin D deficiency and deficiency. Qualitative risk factors include: education; alcohol consumption; being in direct sunlight for more than 30 minutes a day; visit to the solarium; using sunscreen; drinking coffee; taking medications (not vitamin-mineral complexes). Quantitative factors include: visits to specialists (total per year); smoking (duration, years); exercise for more than 30 minutes a day, once a week; being in direct sunlight for more than 30 minutes a day.Conclusion. A wide range of risk factors for vitamin D deficiency dictates the need for their further study to clarify the category of persons who are shown targeted biochemical screening with subsequent drug correction.

Risk Factors and Coping Style Affect Health Outcomes in Adults With Type 2 Diabetes

2015 ◽  
Vol 18 (1) ◽  
pp. 82-89 ◽  
Author(s):  
Chiung-Yu Huang ◽  
Hui-Ling Lai ◽  
Yung-Chuan Lu ◽  
Wen-Kuei Chen ◽  
Shu-Ching Chi ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Coping Style ◽  
Coping Styles ◽  
Equation Modeling ◽  
Duration Of Diabetes ◽  
And Coping

Objective: Most psychosocial interventions among individuals with Type 2 diabetes mellitus (T2DM) target depressive symptoms (DSs) rather than causal antecedents that lead to DSs or affect health-related quality of life (HrQoL). This research investigated a conceptual model of the effects of risk factors and coping styles on HrQoL and DSs in patients with T2DM. Method: A descriptive, correlational design was used with a convenience sample of 241 adults with T2DM aged ≥ 20 years recruited from a hospital metabolic outpatient department. Data were collected using a demographic questionnaire, the modified Ways of Coping Checklist, the Center for Epidemiological Studies Depression Scale, the Short Form 36 Health Survey, and physiological examination. HbA1C was collected from participants’ medical records. Structural equation modeling techniques were used to analyze relationships among risk factors, mediators, and HrQoL. Results: Younger age, more education, and longer duration of diabetes predicted better physical quality of life. Duration of diabetes and three coping styles predicted DSs. Longer duration of diabetes and lower fasting glucose predicted better mental quality of life. Three coping styles acted as mediators between risk factors and health, that is, active and minimizing styles promoted positive outcomes, while avoidance promoted negative outcomes. Conclusions: This integrated model provides a holistic picture of how risk factors and coping style influence HrQoL and DSs in individuals with T2DM. Nurses could use active coping strategies in cognitive behavioral therapy to enhance glycemic control in patients with T2DM.

scholarly journals Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252205
Author(s):  
Mahalingam Vasantha ◽  
Malaisamy Muniyandi ◽  
Chinnaiyan Ponnuraja ◽  
Ramalingam Srinivasan ◽  
Perumal Venkatesan
Keyword(s):  
Quality Of Life ◽  
Latent Variables ◽  
Structural Equation ◽  
Well Being ◽  
Monte Carlo Algorithm ◽  
Equation Modeling ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

Background The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied. Objective To identify the factors that contribute to the HRQoL of TB patients using BSEM. Methods This is a latent variable modeling with Bayesian approach using secondary data. HRQoL data collected after one year from newly diagnosed 436 TB patients who were registered and successfully completed treatment at Government health facilities in Tiruvallur district, south India under the National TB Elimination Programme (NTEP) were used for this analysis. In this study, the four independent latent variables such as physical well–being (PW = PW1-7), mental well-being (MW = MW1-7), social well-being (SW = SW1-4) and habits were considered. The BSEM was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment. Results Bayesian estimates were obtained using 46,300 observations after convergence and the standardized structural regression estimate of PW, MW, SW on HRQoL were 0.377 (p<0.001), 0.543 (p<0.001) and 0.208 (p<0.001) respectively. The latent variables PW, MW and SW were significantly associated with HRQoL of TB patients. The age was found to be significantly negatively associated with HRQoL of TB patients. Conclusions The current study demonstrated the application of BSEM in evaluating HRQoL. This methodology may be used to study precise estimates of HRQoL of TB patients in different time points.

A Theoretical Approach to Measuring Quality of Life

2002 ◽  
Vol 10 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Karen H. Sousa ◽  
Fang Fang Chen
Keyword(s):  
Quality Of Life ◽  
Theoretical Approach ◽  
Latent Variables ◽  
Structural Equation ◽  
Factor Model ◽  
Measurement Model ◽  
Equation Modeling ◽  
Related Quality ◽  
Health Related

The purpose of this article is to discuss conceptual issues surrounding health-related quality of life (HRQOL) and to provide an example of how structural equation modeling can address some of these conceptual issues. This article reports the development of the measurement model for overall quality of life, a dimension of HRQOL as conceptualized by Wilson and Cleary (1995). The sample (N = 1410) is from the AIDS Time-Oriented Health Outcome Study (ATHOS) databank, a longitudinal observational database of persons with HIV-associated illness. The hypothesized second-order factor model consists of 5 latent variables and 17 measured items. The fit indicators (RMSEA = .0717; SRMR = .0450; CFI = .951) suggest that the model provides an adequate description of the pattern of relationships in the data. A theoretical approach to HRQOL will expand its clinical use as an outcome measure and increase its relevance.

Sign in / Sign up

Export Citation Format

Share Document