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Accuracy of Parent-Reported Child Height and Weight and Calculated Body Mass Index Compared With Objectively Measured Anthropometrics: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND: Electronic health (eHealth) interventions for children often rely on parent-reported child anthropometric measures. However, limited studies have assessed parental accuracy in reporting child height and weight via Web-based approaches. OBJECTIVE: The objective of this study was to determ...

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Detalles Bibliográficos
Autores principales: Chai, Li Kheng, Collins, Clare E, May, Chris, Holder, Carl, Burrows, Tracy L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754693/
https://www.ncbi.nlm.nih.gov/pubmed/31538954
http://dx.doi.org/10.2196/12532
Descripción
Sumario:BACKGROUND: Electronic health (eHealth) interventions for children often rely on parent-reported child anthropometric measures. However, limited studies have assessed parental accuracy in reporting child height and weight via Web-based approaches. OBJECTIVE: The objective of this study was to determine the accuracy of parent-reported child height and weight, as well as body mass index and weight category that we calculated from these data. We also aimed to explore whether parent report was influenced by age, sex, weight status, or exposure to participation in a 12-week brief Web-based family lifestyle intervention. METHODS: This study was a secondary analysis of data from a 12-week childhood obesity pilot randomized controlled trial in families with children aged 4 to 11 years in Australia. We asked parents to report demographic information, including child height and weight, using an online survey before their child’s height and weight were objectively measured by a trained research assistant at baseline and week 12. We analyzed data using the Lin concordance correlation coefficient (ρc, ranging from 0 [poor] to ±1 [perfect] concordance), Cohen kappa coefficient, and multivariable linear regression models. RESULTS: There were 42 families at baseline and 35 families (83%) at week 12. Overall, the accuracy of parent-reported child height was moderate (ρc=.94), accuracy of weight was substantial (ρc=.96), and accuracy of calculated body mass index was poor (ρc=.63). Parents underreported child height and weight, respectively, by 0.9 cm and 0.5 kg at baseline and by 0.2 cm and 1.6 kg after participating in a 12-week brief Web-based family lifestyle intervention. The overall interrater agreement of child body mass index category was moderate at baseline (κ=.59) and week 12 (κ=.54). The weight category calculated from 74% (n=31) and 70% (n=23) of parent-reported child height and weight was accurate at baseline and week 12, respectively. Parental age was significantly (95% CI –0.52 to –0.06; P=.01) associated with accuracy of reporting child height. Child age was significantly (95% CI –2.34 to –0.06; P=.04) associated with reporting of child weight. CONCLUSIONS: Most Australian parents were reasonably accurate in reporting child height and weight among a group of children aged 4 to 11 years. The weight category of most of the children when calculated from parent-reported data was in agreement with the objectively measured data despite the body mass index calculated from parent-reported data having poor concordance at both time points. Online parent-reported child height and weight may be a valid method of collecting child anthropometric data ahead of participation in a Web-based program. Future studies with larger sample sizes and repeated measures over time in the context of eHealth research are warranted. Future studies should consider modeling the impact of calibration equations applied to parent-reported anthropometric data on study outcomes.