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Table 2 Exploratory analyses performed on satiety, outcome and dietary variables

From: Subjective satiety and other experiences of a Paleolithic diet compared to a diabetes diet in patients with type 2 diabetes

 

Bivariate correlation P*

Pearson correlation r

Linear regression P§

Adjusted R2

∆SQ for energy per meal versus outcome variables

   ∆ TG (mmol/l)

0.03

0.60

0.03

0.30

∆SQ for energy per meal versus dietary variables

   ∆Vitamin B6 (mg)

0.02

0.64

0.02

0.35

   ∆Potassium (mg)

0.03

0.60

NS

 

   ∆Total energy (MJ)

0.049

0.55

NS

 

∆SQ for energy density per meal versus outcome variables

   No correlations

∆SQ for energy density per meal versus dietary variables

   ∆Water from food (g)

0.01

0.71

0.01

0.45

   ∆Phosphorus (mg)

0.01

0.67

NS

 

   ∆Potassium (mg)

0.01

0.66

NS

 

   ∆Vitamin B6 (mg)

0.02

0.64

NS

 

   ∆Calcium (mg)

0.03

0.59

NS

 

   ∆Fiber (g)

0.04

0.58

NS

 

   ∆Total energy (MJ)

0.046

0.56

NS

 

   ∆Carbohydrate (g)

0.047

0.56

NS

 

∆SQ for glycemic load per meal versus outcome variables

   ∆BMI (kg/m2)

0.0003

−0.84

0.0003

0.69

   ∆Weight (kg)

0.03

−0.59

NE

 

   ∆Waist (cm)

0.02

−0.63

NS

 

∆SQ for glycemic load per meal versus dietary variables

   ∆Spirits (g)

0.03

0.59

0.03

0.29

  1. Exploratory analyses performed on satiety, outcome and dietary variables with significant effects from a Paleolithic diet as compared to a diabetes diet plus water from food and energy-containing beverages (spirits, wine, beer, sweet beverages and juice). Analyses consisted of bivariate correlations between within-subject differences (∆, value during Paleolithic diet minus value during diabetes diet) in satiety quotients (SQ) for energy, energy density and glycemic load per meal versus within-subject differences in outcome and dietary variables. Significantly correlating variables were entered into a stepwise forward linear regression analyses. *P for bivariate correlation between variables in a two-sided t-test. §Stepwise forward linear regression analyses entering significantly correlated variables. NS Not Significant, NE Weight and BMI not entered in same regression analysis due to calculatory relatedness.