Finally, to examine possible threshold and nonlinear relationships that might cut across current overweight and
obese cut points, locally weighted regression techniques were used to generate lines of best fit for the relationships between BMI z scores and PedsQL total, summary, and subscale scores that differed significantly by weight category; P <.05 was considered significant.
Not exact matches
Of these children, 15 % could be considered overweight or
obese according to the
cut - off
points of the International Obesity Task Force [34].
Using
cut - off
points derived from internationally collected data, BMI values can be used to indicate the proportion of children who are underweight, normal weight, overweight and
obese.
We dichotomized weight status as overweight /
obese or normal weight based on the International Obesity Task Force
cut -
points [50].