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Finally, to examine factors associated with missing weight classification data, we compared children with and without parent report-based weight classification on parent perception that their child was overweight; length of time since child's most recent height and weight measurements; parent who completed the questionnaire; and where relevant, child's sex, age group, and race/ethnicity.
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It is very unlikely that the seed weight classification of the accessions based on this standard would be affected by environmental effects among years and locations.
[ 2] Guidelines for body weight classification based on the World Health Organization recommendation to use BMI and waist circumference as indicators of health risk will soon be introduced.
We also compared children with and without parent-reported weight classification data on the following factors: whether height, weight, or both measures were unavailable; child weight classification status based on EHR; parent perception that the child is overweight; child sex; child age group; and length of time since child's weight and height were last measured (Table 5).
To do this, we compared the EHR-based prevalence of overweight/obesity and obesity for groups of children who did and did not have a usable weight classification based on parent-reported data.
Specifically, Cawley, Han and Norton use a large US dataset comprised of immigrants from developing countries to examine the effect of Body Mass Index (hereafter BMI) and indicator variables for the clinical weight classifications for overweight and obese on several labor market outcomes2.
But while the I.O.C. started women's wrestling with four weight classes, it reduced by one, to seven, the number of weight classifications for men.
This resulted in significantly lower percentages of Latino (45%) and Asian (43%) children compared to nonHispanic White children (68%) for whom a BMI-for-age percentile could be calculated and weight classification assigned based on parent-reported data.
The percentages of children whose parents thought they were overweight (14.0%) or very overweight (1.0%) were significantly lower than the percentages with those weight classifications based on EHR data.
However, this study aimed to characterize novel relationships between specific biomarkers and increasing obesity in the Canadian population, and therefore we employed the Health Canada weight classification scheme, which is based on BMI. 17 Future research efforts should be directed towards examining whether the observed associations differ across specific obesity types.
Most of those studies focused on accuracy of weight classification and did not provide information about the accuracy of parent-reported height and weight as separate outcomes, and most did not examine multi-ethnic populations.
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