Metabolic risk factors associated with erosive esophagitis

2009 ◽  
Vol 24 (8) ◽  
pp. 1375-1379 ◽  
Author(s):  
Chian-Sem Chua ◽  
Yu-Min Lin ◽  
Fu-Chun Yu ◽  
Yi-Hsin Hsu ◽  
Jui-Hao Chen ◽  
...  
2007 ◽  
Vol 22 (10) ◽  
pp. 707-713 ◽  
Author(s):  
Jens Kronborg ◽  
Trond Jenssen ◽  
Inger Njølstad ◽  
Ingrid Toft ◽  
Bjørn O. Eriksen

2015 ◽  
Vol 76 (1) ◽  
pp. 33-37 ◽  
Author(s):  
Bohdan L. Luhovyy ◽  
Rebecca C. Mollard ◽  
Shirin Panahi ◽  
Maria Fernanda Nunez ◽  
France Cho ◽  
...  

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0161451 ◽  
Author(s):  
Anna S. Olafsdottir ◽  
Johanna E. Torfadottir ◽  
Sigurbjorn A. Arngrimsson

Obesity ◽  
2019 ◽  
Vol 27 (6) ◽  
pp. 982-988
Author(s):  
Emma Kjellberg ◽  
Josefine Roswall ◽  
Jonathan Andersson ◽  
Stefan Bergman ◽  
Ann‐Katrine Karlsson ◽  
...  

2019 ◽  
Author(s):  
Leila Sabzmakan ◽  
Mohammad Asghari Jafarabadi ◽  
Akbar Nikpajoh ◽  
Tahereh Kamalikhah

Abstract Background: Healthy eating plays a vital role in the management of metabolic risk factors, such as diabetes, hypertension, and dyslipidemia. The aim of this study was to investigate the factors associated with healthy eating among people with cardiovascular metabolic risk factors. Method: This study was a mixed method research (qualitative and quantitative). In the qualitative phase, 50 people who had at least a metabolic risk factor and referred to the Diabetes Centers of Karaj, Iran were interviewed based on PRECEDE framework to explain the causes of following/not following healthy eating. In the quantitative phase, first, we developed a questionnaire based on the findings of the qualitative phase, and its validity and reliability was assessed. Then 450 samples completed the questionnaire in order to identify factors related to healthy eating. The qualitative data analysis was done using directed content analysis. In addition, SPSS ver.17 and AMOS ver.18 software were used to analyze the quantitative data. Results: The results of quantitative part showed only 51.07% of participants followed healthy eating behaviors. Both the findings of the quantitative and qualitative indicated that predisposing factor was the most important determinant of healthy eating behaviors. There was a significant relationship with large effect size between predisposing factor and healthy eating behaviors (β=1, P=0.001). Among predisposing factors, self-efficacy (β=0.49, P=0.001) and perceived barriers (β=- 0.33, P=0.001) were the most significant predictors. However, the findings of quantitative and qualitative phases did not confirm each other for enabling and reinforcing factors. This means in the qualitative phase, enabling factor was perceived as a deep structural determinant of healthy eating, but in the quantitative phase, reinforcing factor (β=0.67, P=0.001) was reported as a significant social predictor. Conclusion: Although personal determinants were the most dominant determinants of healthy eating behaviors, not sufficient to explain eating behaviors. Therefore, social and structural factors have to be considered for promotion of healthy eating behaviors.


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