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

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.

• 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.

• 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.

• 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.

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%.

• 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.

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.

• 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.

Items Strongly

agreeAgree Disagree

Strongly Disagree

diet may reduce psychological stress 61.4 22.5 5.2 10.9I figure it is better to fit the diet 29.8 59.3 5.8 5.2the diet does not need to visit the doctor frequently.

0 32.2 43.2 24.6

the recommended diet does not cost much money.

61.4 7.6 11.6 19.5

I follow the recommended diet is easy. 9.7 70.8 5.8 13.7diet is recommended for the control of hyperglycemia.

42.6 57.4 0 0

I will be following a diet recommended for longer life.

81.5 18.5 0 0

diet will improve daily functioning. 35.3 64.7 0 0

Table 1: The frequency distribution of perceived benefits questions

scores regarding the nutritional behavior in the studied group

Table 2: The frequency distribution of perceived barriers questions

scores regarding the nutritional behavior in the studied group

 ItemsStrongly

agreeAgree Disagree

Strongly Disagree

Two things I can not cook due to busy life. 61.7 29.5 8.8 0Follow the diet requires a lot of time during the day.

63.2 28 8.8 0

Follow the diet deprives me of the pleasure of food.

61.7 37.7 0.6 0

Follow the diet makes me tired. 59.9 31.3 8.8 0Buying food diet is costly. 91.2 0 8.8 0My diet is not going to a party. 80.2 10.9 0.3 8.5Follow the diet has prompted me to do some of life's responsibilities.

72.6 18.5 0.3 8.5

I too agree that the diet is not followed. 9.7 81.5 0.3 8.5

• 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.

Table 3: Correlation matrix between the perceived benefit

and barriers with the intake of macronutrients in the

studied group

Studied variable energy protein carbohydrate fat

Perceived

benefits

r -0.549 -0.119 -0.504 -0.663

P 0.002 0.003 <0.001 <0.001

Perceived

barriers

r 0.571 0.238 0.578 0.691

P 0.009 0.031 <0.001 <0.001

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 indexRecommended

valueTheoretical

modelFinal model

Conclusions

Chi-square statistic 0.05 ≤ 0 0.962 FittedDegrees of freedom of the Chi-square statistic

3.00≥ 0.059 0.012 Fitted

Goodness of fit index (GFI) ≤0.90 0.928 0.997 FittedAdjusted goodness of fit index (AGFI)

≤0.80 0.5 0.951 Fitted

Normed fit index (NFI) ≤0.90 0.808 0.996 FittedComparative fit index (CFI) ≤0.90 0.808 0.953 FittedRoot mean square residual (RMR)

≥0.09 0.262 0.021 Fitted

Root mean square error of approximation (RMSEA)

≥0.10 0.217 0.041 Fitted

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 indexRecommended

valueTheoretical

modelFinal model

Conclusions

Chi-square statistic 0.05 ≤ 0 0.973 FittedDegrees of freedom of the Chi-square statistic

3.00≥ 0.060 0.012 Fitted

Goodness of fit index (GFI) ≤0.90 0.922 0.998 FittedAdjusted goodness of fit index (AGFI)

≤0.80 0.5 0.962 Fitted

Normed fit index (NFI) ≤0.90 0.817 0.996 FittedComparative fit index (CFI) ≤0.90 0.817 0.953 FittedRoot mean square residual (RMR)

≥0.09 0.253 0.020 Fitted

Root mean square error of approximation (RMSEA)

≥0.10 0.217 0.031 Fitted

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

variables Direct effect Indirect effect Total 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

energy 0.409 0.123 0.532

protein 0.145 0.021 0.166

carbohydrate 0.293 0.064 0.357

fat 0.471 0.217 0.688

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

model

Energy intake

Protein intake

Carbohydrate intake

Fat intake

Social support

Commitment to plan of action

Immediate competing demands

& preferences

Situational influences

Perceived benefits

Perceived barriers

Perceived self-efficacy

Activity related affect

0.35

-0.30

-0.45

-0.24

0.75

-0.51

-0.55

0.72

0.18

0.71

0.13

-0.11

-0.63

-0.33

-0.82

-0.08

-0.02

-0.33 -0.40 0.41

0.15 0.29

0.47

• 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.

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.

• 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.

متشکرم