Stratification of Fat‐Free Mass Index Percentiles for Body Composition Based on National Health and Nutrition Examination Survey III Bioelectric Impedance Data

Kudsk, Kenneth A.; Muñoz-del-Rio, Alejandro; Busch, Rebecca A.; Kight, Cassandra E.; Schoeller, Dale A.

doi:10.1177/0148607115592672

Cited by 19 publications

(12 citation statements)

References 31 publications

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“…Age may also be a confounding variable for the effect of BMI z-scores on PM in our study. Indeed, fat-free mass is known to increase with age, with adolescents typically having more fat-free mass than younger children [3,22,41]. The post hoc analysis confirmed that the positive effect of BMI on PM found in younger children (≤ 12 years) disappeared in adolescents.…”

Section: Discussionsupporting

confidence: 52%

Impact of body mass index and socio-economic status on motor development in children and adolescents

et al. 2021

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This study assessed the impact of body mass index (BMI) and socioeconomic status (SES) on the Zurich Neuromotor Assessment, second version (ZNA-2), a battery of tests of motor development in typically developing children between 3 and 18 years of age. BMI measurements and international socio-economic index data were taken from the normative sample of the ZNA-2 for 321 children (158 boys, 163 girls) with a median age of 9.3 years. The age- and gender-adjusted motor performance of these children was quantified and grouped into five components: fine, pure, and gross motor tasks, static balance, and contralateral associated movements. A total score was also calculated. The associations of BMI and SES with the motor scores contribute to less than 5.1% of the total variance.Conclusion: The ZNA-2 for motor development is suitable for measuring motor abilities’ development as it is largely independent of the BMI of the child and the SES of the family. What is Known:• Typical motor development, as measured with the Zurich Neuromotor Assessment, second edition (ZNA-2), is strongly dependent on age and gender.• The ZNA-2 focusses on motor performance, motor quality and simple motor skills. What is New:• Higher socio-economic status (SES) is associated with slightly better motor performance as measured by the ZNA-2 total score.• In the ZNA-2 less than 5.1% of the variability in motor performance is attributable to the combined effect of body mass index and SES.

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Section: Discussionsupporting

confidence: 52%

Impact of body mass index and socio-economic status on motor development in children and adolescents

et al. 2021

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“…Nutritional therapy should be introduced forth with if the patient is deemed to be at risk from malnutrition questionnaires or if low FFMI (< 15 kg/m 2 for females, < 17 kg/m 2 for men) is detected (16). Monitoring body composition regularly helps to personalize nutritional plans and reduce the risk of malnutrition and sarcopenia, resulting in a better quality of life for our patients (29). IBD patients therapy needs a multidisciplinary approach and individually tailored diagnostic and therapeutic decisions at the same time.…”

Section: Discussionmentioning

confidence: 99%

Malnutrition risk questionnaire combined with body composition measurement in malnutrition screening in inflammatory bowel disease

Csontos¹,

Molnár²,

Piri³

et al. 2016

Rev Esp Enferm Dig

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The purpose of malnutrition screening is to predict the probability of a worse outcome due to nutritional factors. The Malnutrition Universal Screening Tool (MUST) can be used for screening in inflammatory bowel disease (IBD); however, it does not provide details about body composition. Our aim was to assess the body composition and combine this with the MUST method to screen risk of malnutrition and sarcopenia. A total of 173 IBD outpatients were enrolled in this cross-sectional study. The MUST scale indicated 21.4% of IBD patients to be at risk of malnutrition. A risk of sarcopenia was detected in 27.7%. However, one third of these patients were not considered to be at risk by their MUST score. Furthermore, Crohn's disease (CD) patients had a strongly unfavorable fat-free mass index (FFMI) value compared to ulcerative colitis (UC) patients, and these differences were significant among men (FFMI: 18.62 ± 2.16 vs 19.85 ± 2.22, p = 0.02, in CD and UC males, respectively). As sarcopenia is a relevant prognostic factor, the MUST method should be expanded to include body composition analysis to detect more IBD patients at risk of malnutrition and sarcopenia in order to start their nutritional therapy immediately.

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“…For example, Harrington et al [38] used NHANES 2009-2010 to stratify the US population by demographic variables to investigate sitting behavior. Kudsk et al, [39] used NHANES 1988-1994 data to assess poor outcomes in hospitalized patients for demographic strata.…”

Section: Modeling Variability With Existing Human Datamentioning

confidence: 99%

Virtual Modeling of User Populations and Formative Design Parameters

Knisely

Vaughn-Cooke

2020

Systems

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Human variability related to physical, cognitive, socio-demographic, and other factors can contribute to large differences in human performance. Quantifying population heterogeneity can be useful for designers wishing to evaluate design parameters such that a system design is robust to this variability. Comprehensively integrating human variability in the design process poses many challenges, such as limited access to a statistically representative population and limited data collection resources. This paper discusses two virtual population modeling approaches intended to be performed prior to in-person design validation studies to minimize these challenges by: (1) targeting recruitment of representative population strata and (2) reducing the candidate design parameters being validated in the target population. The first approach suggests the use of digital human models, virtual representations of humans that can simulate system interaction to eliminate candidate design parameters. The second approach suggests the use of existing human databases to identify relevant human characteristics for representative recruitment strata in subsequent studies. Two case studies are presented to demonstrate each approach, and the benefits and limitations of each are discussed. This paper demonstrates the benefit of modeling prior to conducting in-person human performance studies to minimize resource burden, which has significant implications on early design stages.

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Stratification of Fat‐Free Mass Index Percentiles for Body Composition Based on National Health and Nutrition Examination Survey III Bioelectric Impedance Data

Cited by 19 publications

References 31 publications

Impact of body mass index and socio-economic status on motor development in children and adolescents

Impact of body mass index and socio-economic status on motor development in children and adolescents

Malnutrition risk questionnaire combined with body composition measurement in malnutrition screening in inflammatory bowel disease

Virtual Modeling of User Populations and Formative Design Parameters

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