In this study, we established an overweight prediction model using standardized deviation scores of anthropometric parameters collected during the first 5 years of life.
BMI values were calculated from these weight and height measurements and transformed to standardized deviation scores (z-scores) according to the sex- and age-specific 'WHO-Child-Growth-Standards' for children.
Expressed as relative to the standard deviation, the difference found in the adjusted model corresponds with a standardized effect size in DNA methylation of −0.13 standard deviation score (SDS).
SDS, standard deviation score.
Results are presented for both unstandardized and standardized (by mean and standard deviation) scores.
The most common statistics used in this model are infit and outfit statistics (the information-weighted average of the squared standardized deviation of observed score with respect to expected score).
The pathways are ranked based on a standardized difference score (z-score) using the expected value and standard deviation of the number of differentially expressed genes in a pathway under a hypergeometric distribution.
† Odds ratio for one standardized deviation increase in each cognition score using logistic regression.
When the standardized deviation of the average PCA score for each population from the overall average across all populations for the three axes was calculated, it ranged from 1.19 (Skinny Lake) to 5.35 (Murray Creek, Fig. 3B).
When the standardized deviation of the average FCA score for each population from the overall average across all populations for the three axes was calculated it ranged from 1.05 (Blackwater River) to 4.90 (Murray Creek, Fig. 3A).
Standardized difference scores (the s-score or normal score) were also calculated by subtracting the mean scores of the patients from the mean scores of the general population, followed by the division of these deviations by each scale's standard deviation in the general population.
