Differences between recumbent length and stature measurement in groups of 2- and 3-y-old children and its relevance for the use of European body mass index references

Buyken, Anette E.; Hahn, Sebastian; Kroke, Anja

doi:10.1038/sj.ijo.0802738

Cited by 16 publications

(8 citation statements)

References 19 publications

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“…Unfortunately, height is not consistently recorded in many PICUs. Further, when height is measured in non-ambulatory patients, it is typically recumbent length which can underestimate height (4). The accuracy of measured height is also compromised by scoliosis, neuromuscular weakness, joint deformity, flexion contractures, and other syndromes (5, 6).…”

Section: Introductionmentioning

confidence: 99%

Predicting Body Height in a Pediatric Intensive Care Unit Using Ulnar Length

et al. 2018

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Objective: To determine if ulnar length obtained by the bedside nurse can be used to estimate patient length. To compare our findings to previous predictive equations of height and ulnar length. To evaluate the performance of predictive equations for height and ulnar length on patients with syndromes that affect height.Design: Retrospective observational study of prospectively collected data.Settings: Multidisciplinary Pediatric Intensive Care Unit in a university teaching hospital.Patients: 1,177 patients, ages 1 month to 23 years. Mean age was 79.7 months (1,3 IQR 19.5, 164.5 months) and 55.4% male.Measurements: Ulnar length was obtained using digital calipers by bedside nurses in PICU as well as height and weight. The electronic health care record was used to extract patient information.Main Results: The predictive equation for height for the entire group is: height (cm) = 0.59*ulnar length (mm) + 13.1 (r2 = 0.93). Bland Altman analysis of the derivation formula applied to the testing group did not show any systematic bias.Conclusions: Our study shows that ulnar length measurements can be used to predict height with a simple linear formula in a PICU setting. Not having specific individuals or specific training for ulnar measurement did not seem to alter the accuracy (r2 = 0.93). The robust nature of the measurement and ease of use may make this an unconventional but reasonable alternative to obtaining height when that cannot be measured directly.

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Section: Introductionmentioning

confidence: 99%

Predicting Body Height in a Pediatric Intensive Care Unit Using Ulnar Length

et al. 2018

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“…An early screening intended to diagnose the metabolic syndrome already in childhood would be very important, but unfortunately, criteria for this diagnosis have not been well established for children. Currently, different classifications are proposed in order to meet this diagnosis (8,9,10), but it seems difficult to establish a uniform classification system applicable universally, since many features of obesity change by ethnic group and also with the age of the patient (11). …”

Section: Introductionmentioning

confidence: 99%

Thyroid Function and Obesity

Longhi

Radetti²

2012

Jcrpe

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Nowadays, childhood obesity is one of the biggest health emergencies in the developed countries. Obesity leads to multiple metabolic alterations which increase the risk of developing diabetes and cardiovascular diseases. Thyroid function has been often described as altered in obese children, however, it is not clear whether the altered thyroid function is the cause or the consequence of fat excess. On the other hand, thyroid structure seems also to be affected. Nevertheless, both functional and structural alterations seem to improve after weight loss and therefore no treatment is needed.Conflict of interest:None declared.

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“…Owing to the differences between recumbent length and standing height (on average length is greater than height when measured at the same time), a mathematical correction was used to compute standing height for children age 3 and younger. 16 This correction factor is based on data from children who were measured successively in standing and lying positions, and leads to a series of smoothened BMI measurements. BMI was calculated as weight (kg) divided by height (m) 2 .…”

Section: Anthropometric Measurementsmentioning

confidence: 99%

A comparative evaluation of two different approaches to estimating age at adiposity rebound

et al. 2005

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Objective: To compare different approaches (visual estimation of individual BMI curves with polynomial models) to estimate age at adiposity rebound (AR), as different approaches might lead to different results. AR has been suggested as a critical period between intra-uterine life and early adulthood, and recent data showed that early age at AR is associated with higher body mass later in life. Methods: Longitudinal anthropometric data from the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study were used to obtain individual BMI growth curves. We then compared the visual estimation approach to polynomial models in three different scenarios reflected by different data sets: an idealistic, an realistic, and a realistic scenario with imputed values. Results: In all three scenarios, the visual estimation yielded significantly higher estimates than the polynomial models of 2nd or 3rd order. Cross-tabulations of groups of age at AR (early, medium, and late) showed that truly concordant classification was low, ranging only from 51 to 63%. A closer examination of the data indicated that the differences in estimates were mainly due to differences in the underlying definitions: the polynomial models select the nadir in the growth curve as the age at AR, whereas the visual estimation deviates from this concept in those cases where there is plateau in the growth curve. In the latter instance, the turning point of the growth curve before its increase is selected as the age at rebound. Only when the underlying criteria for the estimation of AR with the visual approach were modified, could concordant results between the two approaches be obtained. Considering the underlying physiological basis, it became clear that approaches which determine AR by simply identifying the nadir in the BMI curve do not reflect AR appropriately. This refers to those cases in which the nadir in the growth curve and the turning point at the onset of the adiposity increase are not identical. Conclusions: Estimating AR with the visual approach appears to best reflect the physiological basis of the AR, and is also preferable, because it resulted in the lowest number of children with missing estimates for age at AR.

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Differences between recumbent length and stature measurement in groups of 2- and 3-y-old children and its relevance for the use of European body mass index references

Cited by 16 publications

References 19 publications

Predicting Body Height in a Pediatric Intensive Care Unit Using Ulnar Length

Predicting Body Height in a Pediatric Intensive Care Unit Using Ulnar Length

Thyroid Function and Obesity

A comparative evaluation of two different approaches to estimating age at adiposity rebound

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