The association between student body mass index and tests of flexibility assessed by the FITNESSGRAM®: New York City public school students, 2017-18.
Hannah R Thompson, Andjelka Pavlovic, Emily D'Agostino and 3 more
PLoS ONE · 2021
doi:10.1371/journal.pone.0262083 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
FITNESSGRAM® is the most widely used criterion-referenced tool to assess/report on student health-related fitness across the US. Potential weight-related biases with the two most common tests of musculoskeletal fitness-the trunk extension and Back-Saver Sit-and-Reach (sit-and-reach)-have been hypothesized, though have not been studied. To determine the association between musculoskeletal fitness test performance and weight status, we use data from 571,133 New York City public school 4th-12th grade students (85% non-White; 75% qualified for free or reduced-price meals) with valid/complete 2017-18 FITNESSGRAM® data. Adjusted logistic mixed effects models with a random effect for school examined the association between weight status and whether a student was in the Healthy Fitness Zone (HFZ; met sex- and age-specific criterion-referenced standards) for the trunk extension and sit-and-reach. Compared to students with normal weight, the odds of being in the HFZ for trunk extension were lower for students with underweight (OR = 0.77; 95% CI: 0.741, 0.795) and higher for students with overweight (OR = 1.10; 95% CI: 1.081, 1.122) and obesity (OR = 1.11; 95% CI: 1.090, 1.13). The odds of being in the HFZ for sit-and-reach were lower for students with underweight OR = 0.85; 95% CI: 0.826, 0.878), overweight (OR = 0.83; 95% CI: 0.819, 0.844) and obesity (OR = 0.65; 95% CI: 0.641, 0.661). Students with overweight and obesity perform better on the trunk extension, yet worse on the sit-and-reach, compared to students with normal weight. Teachers, administrators, and researchers should be aware of the relationship of BMI with student performance in these assessments.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.