A structural equation model to assess the pathways of body adiposity and inflammation status on dysmetabolic biomarkers via red cell distribution width and mean corpuscular volume: a cross-sectional study in overweight and obese subjects

Rondanelli, Mariangela; Perna, Simone; Alalwan, Tariq A.; Cazzola, Roberta; Gasparri, Clara; Infantino, Vittoria; Perdoni, Federica; Iannello, Giancarlo; Pepe, Daniele; Guido, Davide

doi:10.1186/s12944-020-01308-5

Lipids in Health and Disease

Table 2 Effect estimates of the path analysis of the conceptual model

From: A structural equation model to assess the pathways of body adiposity and inflammation status on dysmetabolic biomarkers via red cell distribution width and mean corpuscular volume: a cross-sectional study in overweight and obese subjects

	Estimate (β)	Standardized Estimate (β)^a	P (\|Z\| > z)	95% CI
Direct effect
BMI → CRP	0.050	0.342	0.008	0.013; 0.087
BMI → ROS	0.415	0.242	0.047	0.006; 0.825
BMI → Slope	− 0.012	− 0.153	0.192	− 0.031; 0.006
BMI → Lag-time	− 0.108	− 0.020	0.873	−1.432; 1.216
BMI → RDW	−0.132	− 0.229	0.022	− 0.244; − 0.019
BMI → MCV	0.078	0.070	0.574	−0.194; 0.350
WC → CRP	−0.002	−0.044	0.682	−0.012; 0.008
WC → ROS	−0.078	− 0.136	0.283	−0.220; 0.064
WC → Slope	0.000	0.003	0.975	−0.005; 0.006
WC → Lag-time	−0.292	− 0.160	0.143	− 0.684; 0.099
WC → RDW	0.122	0.640	< 0.001	0.089; 0.155
WC → MCV	−0.061	− 0.165	0.148	− 0.143; 0.022
CRP → RDW	0.302	0.077	0.085	−0.042; 0.646
CRP → MCV	−1.446	−0.190	< 0.001	−2.170; − 0.721
ROS → Slope	0.012	0.263	0.006	0.004; 0.021
ROS → Lag-time	−1.276	−0.399	< 0.001	−1.867; − 0.685
ROS → RDW	− 0.017	− 0.052	0.548	−0.074; 0.039
ROS → MCV	−0.003	− 0.005	0.943	− 0.097; 0.091
Slope→RDW	0.090	0.013	0.868	−0.971; 1.150
Slope→MCV	1.264	0.091	0.256	−0.917; 3.444
Lag-time→RDW	−0.001	−0.009	0.920	−0.019; 0.017
Lag-time→MCV	0.017	0.086	0.292	−0.015; 0.050
RDW → HOMA	0.081	0.168	0.016	0.015; 0.146
RDW → SBP	−0.206	−0.037	0.656	−1.115; 0.702
RDW → DBP	0.080	0.033	0.660	−0.277; 0.438
RDW → TGL	−0.007	−0.021	0.762	−0.049; 0.036
RDW → CHL	−0.009	−0.016	0.831	−0.089; 0.072
RDW → LDL	0.035	0.071	0.331	−0.036; 0.106
RDW → HDL	−0.037	−0.192	0.007	−0.065; − 0.010
RDW → CHL/HDL	0.071	0.117	0.096	−0.012; 0.154
RDW → BGL	0.044	0.096	0.070	−0.004; 0.091
RDW → Insulin	0.320	0.153	0.030	0.030; 0.609
MCV → HOMA	−0.028	−0.112	0.149	−0.066; 0.010
MCV → SBP	−0.081	−0.028	0.748	−0.576; 0.414
MCV → DBP	−0.071	−0.057	0.419	−0.244; 0.101
MCV → TGL	−0.013	−0.081	0.270	−0.036; 0.010
MCV → CHL	0.037	0.132	0.103	−0.008; 0.082
MCV → LDL	0.028	0.109	0.122	−0.007; 0.062
MCV → HDL	0.014	0.136	0.048	0.000; 0.027
MCV → CHL/HDL	−0.004	−0.014	0.834	−0.044; 0.035
MCV → BGL	0.007	0.029	0.514	−0.014; 0.027
MCV → Insulin	−0.160	−0.148	0.050	−0.320; 0.000

In bold:P < 0.05; in italic: 0.05 ≤ P < 0.10
Goodness of fit indexes: chi-square = 168.107 (P < 0.001), baseline chi-square = 1906.191 (P < 0.001), SRMR = 0.091, RMSEA =0.102 (90%CI = 0.084; 0.121), CFI = 0.940, TLI = 0.847
→ = effect, BMI = Body Mass Index, WC = Waist Circumference, CRP = C-Reactive Protein, ROS = Reactive Oxygen Species, RDW = Red Cell Distribution Width, MCV = Mean Corpuscular Volume, HOMA = Homeostasis Model Assessment, SBP = Systolic Blood Pressure, DBP = Diastolic Blood Pressure, TGL = Triglycerides, CHL = total cholesterol, LDL = low-density lipoprotein cholesterol, HDL = high-density lipoprotein cholesterol, BGL = Blood Glucose Level
^aSince the variables are measured on various scales, standardized estimates (β*) rather than raw effects (β) are shown using the standard deviations as measurement units for the variables. Therefore, these are standardized partial regression coefficients are effects of explanatory variable on response variable, controlling for the other variables of the model

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