A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals

Abstract

Background: Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modeling (SEM) to assess the association of adherence to a healthy eating index (HEI)-2015 with socio-demographic factors, psychological characteristics, metabolic syndrome (MetS) and other cardio-metabolic risk factors among obese individuals.

Methods: This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM.

Results: The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p<0.05, for age) and quantitative insulin sensitivity check index (p<0.05, for age and depression) via HEI. High adherence to HEI was found to be inversely associated with MetS risk (p<0.05).

Conclusion: Adherence to HEI-2015 seems to mediate the effect of socio-demographic parameters and mental health on cardio-metabolic risk factors as well as MetS risk. Further studies are needed to confirm these findings.

Fig 1. Hypothesized models in which HEI as a mediating variable relates socio-demographic variables and mental health to insulin resistance indices.

Abbreviations: HEI, healthy eating index; HOMA, homeostasis model assessment; QUICKI, quantitative insulin sensitivity check index; SES, socio-economic status; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite.

Fig 2. Hypothesized models in which HEI as a mediating variable relates socio-demographic variables and mental health to cardio-metabolic risk factors.

Abbreviations: HEI, healthy eating index; WHR, waist–hip ratio; BMI, body mass index; WC, waist circumference; FM, fat mass; FFM, fat free mass; SES, socio-economic status; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL, high-density lipoprotein; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite.

Fig 3. Hypothesized models in which HEI as a mediating variable relates socio-demographic variables and mental health to metabolic syndrome.

Abbreviations: HEI, healthy eating index;FM, fat mass; FFM, fat free mass; SES, socio-economic status; MetS, metabolic syndrome; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite.

Fig 4. Path analysis diagram with standardized estimates illustrating the total effects of socio-demographic and psychological parameters and diet on insulin resistance indices.

Abbreviations: HEI, healthy eating index; HOMA, homeostasis model assessment; QUICKI, quantitative insulin sensitivity check index; SES, socio-economic status; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite. *All path coefficients are standardized. Red arrows mean p.value ≤ 0.05. ^£Total effect is defined as the sum of direct and indirect effects.

Fig 5. Path analysis diagram with standardized estimates illustrating the total effects of socio-demographic and psychological parameters and diet on cardio-metabolic risk factors.

Abbreviations: HEI, healthy eating index; WHR, waist–hip ratio; BMI, body mass index; WC, waist circumference; FM, fat mass; FFM, fat free mass; SES, socio-economic status; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL, high-density lipoprotein; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite. *All path coefficients are standardized. Red arrows mean p.value ≤ 0.05. ^£Total effect is defined as the sum of direct and indirect effects.

Fig 6. Structural equation model diagram with standardised estimates for total effects of socio-demographic and psychological parameters and diet on Mets.

Abbreviations: HEI, healthy eating index;FM, fat mass; FFM, fat free mass; SES, socio-economic status; MetS, metabolic syndrome; PA, Physical activity; MS, marital status; Anx, anxiety; Dep, depression; Appe, appetite. *All path coefficients are standardized. Red arrows mean p.value ≤ 0.05. ^£Total effect is defined as the sum of direct and indirect effects.