Literature DB >> 15033843

A multicentre randomised controlled trial of an intervention to improve the accuracy of linear growth measurement.

T H Lipman1, K D Hench, T Benyi, J Delaune, K A Gilluly, L Johnson, M G Johnson, H McKnight-Menci, D Shorkey, J Shults, F L Waite, C Weber.   

Abstract

AIMS: To evaluate linear growth assessment and the effect of an intervention on measurement accuracy in primary care practices (PCP) within eight US geographical areas.
METHODS: In this multicentre randomised controlled intervention study, paediatric endocrine nurses as site coordinators (SC) visited 55 randomly assigned PCP to evaluate growth assessment of staff performing linear measurements. SC observed 127 measurers assessing a total of 878 children: 307 (baseline), 282 (3 months), and 289 (6 months). Accuracy was determined by SC re-measuring each child with correct technique and equipment. State of the art equipment and a standardised growth training session were provided to the intervention group (IG) following the baseline visit. SC repeated data collection at all PCP at 3 and 6 months.
RESULTS: There were no baseline differences between IG and CG equipment, technique, or accuracy; only 30% of measurements were accurate (< or =0.5 cm from SC). Post-intervention, significantly more IG measurements were accurate: IG = 55%, CG = 37% at 3 months; IG = 70%, CG = 34% at 6 months. Odds ratio of accuracy for IG versus CG was 2.1 at 3 months and 4.5 at 6 months. At 6 months, mean difference from the SC measurements was 0.5 cm in IG and 1.1 cm in CG.
CONCLUSIONS: In PCP, children are measured inaccurately. Our intervention significantly improved measurement accuracy. Improved accuracy could yield more rapid detection and diagnosis of paediatric growth disorders.

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Mesh:

Year:  2004        PMID: 15033843      PMCID: PMC1719855          DOI: 10.1136/adc.2003.030072

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  12 in total

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Journal:  Arch Dis Child       Date:  1994-06       Impact factor: 3.791

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  20 in total

1.  Misdiagnosis of overweight and underweight children younger than 2 years of age due to length measurement bias.

Authors:  Sheryl L Rifas-Shiman; Janet W Rich-Edwards; Kelley S Scanlon; Ken P Kleinman; Matthew W Gillman
Journal:  MedGenMed       Date:  2005-11-29

Review 2.  Dance for Health: An Intergenerational Program to Increase Access to Physical Activity.

Authors:  Krista Schroeder; Sarah J Ratcliffe; Adriana Perez; David Earley; Cory Bowman; Terri H Lipman
Journal:  J Pediatr Nurs       Date:  2017-07-18       Impact factor: 2.145

3.  An observational cohort study of weight- and length-derived anthropometric indicators with body composition at birth and 5 mo: the Healthy Start study.

Authors:  Wei Perng; Brandy M Ringham; Deborah H Glueck; Katherine A Sauder; Anne P Starling; Mandy B Belfort; Dana Dabelea
Journal:  Am J Clin Nutr       Date:  2017-06-28       Impact factor: 7.045

Review 4.  Dilemmas of growth hormone treatment for GH deficiency and idiopathic short stature: defining, distinguishing, and deciding.

Authors:  Julia G Halas; Adda Grimberg
Journal:  Minerva Pediatr       Date:  2020-04-09       Impact factor: 1.312

5.  Validity of child anthropometric measurements in the Special Supplemental Nutrition Program for Women, Infants, and Children.

Authors:  Catherine M Crespi; Vivian H Alfonso; Shannon E Whaley; May C Wang
Journal:  Pediatr Res       Date:  2012-01-11       Impact factor: 3.756

6.  Social jet lag, chronotype and body mass index in 14-17-year-old adolescents.

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Journal:  Chronobiol Int       Date:  2016-08-11       Impact factor: 2.877

7.  Anthropometric measures of abdominal adiposity for the identification of cardiometabolic risk factors in adolescents.

Authors:  David R Weber; Lorraine E Levitt Katz; Babette S Zemel; Paul R Gallagher; Kathryn M Murphy; Susan M Dumser; Terri H Lipman
Journal:  Diabetes Res Clin Pract       Date:  2014-01-08       Impact factor: 5.602

8.  Early growth faltering in healthy term infants predicts longitudinal growth.

Authors:  Erin S Ross; Nancy F Krebs; A Laurie W Shroyer; L Miriam Dickinson; Paul H Barrett; Susan L Johnson
Journal:  Early Hum Dev       Date:  2009-07-15       Impact factor: 2.079

9.  Electronic Health Record Mid-Parental Height Auto-Calculator for Growth Assessment in Primary Care.

Authors:  Terri H Lipman; Pamela Cousounis; Robert W Grundmeier; James Massey; Andrew J Cucchiara; Virginia A Stallings; Adda Grimberg
Journal:  Clin Pediatr (Phila)       Date:  2015-10-27       Impact factor: 1.168

10.  The role and impact of community health workers in childhood obesity interventions: a systematic review and meta-analysis.

Authors:  K Schroeder; R McCormick; A Perez; T H Lipman
Journal:  Obes Rev       Date:  2018-08-29       Impact factor: 9.213

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