Fig 1.
Carbohydrate Z-scores and their corresponding percentiles after transformation using the standard normal distribution function.
Due to the usage of the standard normal distribution function by Shivappa et al. [17] to transform daily food parameter Z-scores (here carbohydrates of a simulated dataset of n = 32; Table 1) into percentiles, the resulting percentile scores are only scaled between [0.003, 0.409] and do not distribute across the entire unit interval.
Table 1.
Simulated data on daily consumption of food parameters and on a pro-inflammatory biomarker used for the Dietary Inflammatory Index (DII) calculation and analyses*.
Fig 2.
Daily saffron consumption Z-scores and their corresponding percentiles after transformation using the standard normal distribution function.
The standardized daily saffron consumption of the subjects (Z-scores of simulated data, n = 13) are scaled into percentiles [0.434, 0.584] when using the method by Shivappa et al. [17]. By using the values = 0.37, sdSaffron = 1.78 calculated by Shivappa et al. for the standardization, the percentiles cluster in the middle of the standard normal distribution function and do not fill the entire unit interval.
Table 2.
Differences in the Dietary Inflammatory Index (DII) calculated according to Shivappa et al. [17] or the Scaling-Formula With Outlier Detection (SFOD) method based on similar food consumption data between subject pairs.
Table 3.
Characteristics of TEENDIAB children/adolescents included in the present analysis.
Fig 3.
Boxplots of the dietary inflammatory index (DII) scores between the three different calculation methods.
Nutritional data from n = 193 subjects participating in the TEENDIAB study were used to calculate the DIIs according to the original method from Shivappa et al. [17] or the revised methods scaling-formula (SF) and scaling-formula with outlier detection (SFOD), respectively.
Table 4.
Associations between the Dietary Inflammatory Index (DII) calculated according to Shivappa, the Scaling-Formula (SF) and Scaling-Formula With Outlier Detection (SFOD) methods and cytokine levels*.