1. Structural role of perceived benefits and barriers to receiving macronutrients in women with metabolic syndrome; a path analysis study Siamak Mohebi- Leila Azadbakht- Mohammad Hozoori- Mahmoud Parham- Aziz Kamran- Gholamreza Sharifirad

2. Introduction Metabolic syndrome is a set of metabolic abnormalities known through abdominal obesity, hypertension, insulin resistance and blood lipids abnormalities which is also considered as an independent risk factor for cardiovascular diseases and type 2 diabetes.

3. The prevalence of MetS in Asian population is estimated about 25.8%. The incidence of this syndrome increased from 30.1% to 34.7% in Iran during 2010- 2014.

4. Metabolic syndrome is associated with lifestyle factors such as diet, smoking and physical activity. Previous published papers in Iran showed that fruit, vegetable, dairy, whole grain and red meat are associated with MetS. The nutritional self-care is one of the most important approach for the control of MetS risk factors.

5. Nowadays, it is recognized that the feeding behavior of an individual is not only influenced by his nutritional knowledge but also can be influenced by several other factors. The perceived benefits and barriers are the two well- known structures in some of the health-related behaviors as central elements in most of the theories of behavior change such as Heath Belief Model and Pender's Health Promotion Model.

6. Materials and Methods A cross-sectional design was used for this study in 2012. Sample subjects were selected from among women with MetS who were referred to Isfahan's petroleum industry health care centers. In this study in order to fit the structural equation model (SEM) the number of samples obtained were 329 through observing 80% power, significance level of 0.05, 30 degrees of freedom and a maximum RMSE of 5%.

7. Two questionnaires were used to collect data: A researcher made questionnaire based on health promotion model which its validity and reliability was approved in a separate step after the design. Also, the feeding behaviors of the samples were checked through a 24 hour dietary recall for 3 days.

8. Results The mean age of patients was 44.8±8.1 years old and mean of suffering duration from the syndrome was 2.1± 0.9 years. Also, 1.2% had primary education, 8.2% guidance school, 56.2% high school and 34.3% had academic degree. The 41.3% were employed and 58.7% were housewives.

9. The mean and standard deviation of the perceived benefits scores of feeding behavior in this study were 24.3±3.3 and mean and standard deviation of perceived barriers scores were 28.1±4.8.

10. Items Strongly agree AgreeDisagree Strongly Disagree diet may reduce psychological stress61.422.55.210.9 I figure it is better to fit the diet29.859.35.85.2 the diet does not need to visit the doctor frequently. 032.243.224.6 the recommended diet does not cost much money. 61.47.611.619.5 I follow the recommended diet is easy.9.770.85.813.7 diet is recommended for the control of hyperglycemia. 42.657.400 I will be following a diet recommended for longer life. 81.518.500 diet will improve daily functioning.35.364.700 Table 1: The frequency distribution of perceived benefits questions scores regarding the nutritional behavior in the studied group

11. Table 2: The frequency distribution of perceived barriers questions scores regarding the nutritional behavior in the studied group Items Strongly agree AgreeDisagree Strongly Disagree Two things I can not cook due to busy life.61.729.58.80 Follow the diet requires a lot of time during the day. 63.2288.80 Follow the diet deprives me of the pleasure of food. 61.737.70.60 Follow the diet makes me tired.59.931.38.80 Buying food diet is costly.91.208.80 My diet is not going to a party.80.210.90.38.5 Follow the diet has prompted me to do some of life's responsibilities. 72.618.50.38.5 I too agree that the diet is not followed.9.781.50.38.5

12. The results showed that the mean of energy intake was 2512.4±344.2 kcal, protein intake was 70.9±27.2 gr, carbohydrate consumed was 420±89.3 gr and fat intake was 61.6±20.2 gr per day.

13. Table 3: Correlation matrix between the perceived benefit and barriers with the intake of macronutrients in the studied group Studied variableenergyproteincarbohydratefat Perceived benefits r-0.549-0.119-0.504-0.663 P0.0020.003<0.001 Perceived barriers r0.5710.2380.5780.691 P0.0090.031<0.001

14. Table 4: The value of model fitting in the path analysis in order to predict the intake of macronutrients in the studied group Model fit index Recommended value Theoretical model Final model Conclusions Chi-square statistic0.05 ≤00.962Fitted Degrees of freedom of the Chi-square statistic 3.00 ≥0.0590.012Fitted Goodness of fit index (GFI)≤0.900.9280.997Fitted Adjusted goodness of fit index (AGFI) ≤0.800.50.951Fitted Normed fit index (NFI)≤0.900.8080.996Fitted Comparative fit index (CFI)≤0.900.8080.953Fitted Root mean square residual (RMR) ≥0.090.2620.021Fitted Root mean square error of approximation (RMSEA) ≥0.100.2170.041Fitted

15. Table 5: The value of model fitting in the path analysis in order to predict the intake of macronutrients in the studied group Model fit index Recommended value Theoretical model Final model Conclusions Chi-square statistic0.05 ≤00.973Fitted Degrees of freedom of the Chi-square statistic 3.00 ≥0.0600.012Fitted Goodness of fit index (GFI)≤0.900.9220.998Fitted Adjusted goodness of fit index (AGFI) ≤0.800.50.962Fitted Normed fit index (NFI)≤0.900.8170.996Fitted Comparative fit index (CFI)≤0.900.8170.953Fitted Root mean square residual (RMR) ≥0.090.2530.020Fitted Root mean square error of approximation (RMSEA) ≥0.100.2170.031Fitted

16. Table 6: Direct, indirect and total impact coefficients of perceived benefits and barriers on energy, protein, carbohydrate and fat intake per day in the target group variablesDirect effectIndirect effectTotal effect perceived benefits energy-0.084-0.039-0.123 protein-0.029-0.020-0.049 carbohydrate-0.326-0.089-0.415 fat-0.401-0.104-0505 perceived barriers energy0.4090.1230.532 protein0.1450.0210.166 carbohydrate0.2930.0640.357 fat0.4710.2170.688

17. Figure 1: Diagram of path analysis to predict macronutrient intake in the final model

18. The final model showed that perceived barriers along with other investigated structures, can predict 72% of changes in energy intake, 51% of changes in protein intake, 42% of changes in carbohydrate intake and 88% of changes in lipid intake, and perceived benefits can predict 22% of changes in energy intake, 18% of protein, 35% of carbohydrates and 56% of lipid.

19. Conclusion The results of this study showed that the perceived benefits in patients with metabolic syndrome were in relatively good condition, but perceived barriers were in poor condition. In this study, confirmed the improper conditions of nutritional status in women, because of the macronutrients intake in the studied patients was more than RDA.

20. In this study, perceived barriers have a greater predictive ability to determine macronutrient intake than perceived benefits. So, according to many perceived barriers, we cannot expect proper nutritional care in these patients.

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