The transformative potential of digital anthropometry in pediatric health: mapping a decade of innovations in anthropometric assessment (2014–2023) 10.55131/jphd/2026/240224
Main Article Content
Abstract
Pediatric health is crucial for global well-being, as growth and development indicators significantly influence long-term outcomes. Traditional anthropometric methods often face inaccuracies. Digital anthropometry that uses technology like 3D scanners offers precise, efficient solutions that promise to enhance pediatric health monitoring. This review aims to explore the current state of digital anthropometry in pediatric health. The authors sourced articles from EBSCO, PubMed, ProQuest, ScienceDirect, and Scopus between 2014 and 2023. The studies were reviewed based on set criteria, synthesizing data according to technology types, measurement capabilities, contributions to pediatric health, and adoption challenges and opportunities. The use of digital technologies was highlighted using 32 studies, most of which used a 3D scanner. These technologies made significant contributions to pediatric health. For instance, 3D scanners were used to assess cranial deformation in infants, detect facial features associated with Williams Syndrome, and monitor body composition to identify risks of obesity. Digital anthropometry enhances measurement capabilities, particularly in assessing diverse body dimensions. It contributes to improved nutritional and growth assessment, diagnosis and management of health conditions, medical device design, and home use applications. Despite challenges such as technical failures in scan processing and measurement inaccuracies caused by child movement or suboptimal conditions, the non-invasive, portable, and automated nature of these technologies presents significant opportunities for advancing pediatric health. This review highlights the transformative potential of digital anthropometry in pediatric health, addressing a critical gap in previous literature, which has predominantly focused on adult populations or single technologies. By synthesizing diverse applications across digital tools specifically for children, this review helps clarify how these innovations can improve growth monitoring and promote global health equity. Despite adoption barriers, its integration into healthcare is crucial, and future research needs to address challenges and ensure sustainability.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Saavedra JM, Prentice AM. Nutrition in school-age children: a rationale for revisiting priorities. Vol. 81, Nutr Rev. Oxford University Press; 2023. p. 823–43.
Świąder-Leśniak A, Majcher A, Pyrżak B, Dziechciarz P. Consensus on the principles of physical development monitoring in children, possible or not? Pediatr Med Rodz. 2020; 16(3):268–74.
Gupta PM, Wieck E, Conkle J, Betters KA, Cooley A, Yamasaki S, et al. Improving assessment of child growth in a pediatric hospital setting. BMC Pediatr. 2020 Sep 3;20(1).
Casadei K, Kiel J. Anthropometric Measurement [Internet]. StatPearls [Internet]. StatPearls Publishing; 2019 [cited 2024 Dec 16]. Available from: http://europepmc.org/books/NBK537315
Sethi AK, Velarambath Manalil S, Das S, Singh S, Manu RM, Biswas R, et al. Quality improvement initiative to standardise the anthropometric assessment for children under the age of 5 years at an urban primary health centre in New Delhi. BMJ Open Qual. 2024 Jun 11;13(2).
Rosari A, Julianto J, Larasati AD, Pramesti LA, Triwiyanto, Lutfiyah S, et al. Developing a Nutritional Assessment Tool for Toddlers Using Anthropometry and IoT Technology. IJAHST. 2024 Apr 30;4(2):67–71.
Sofie M, Kusi Olla P, Kusumaningtyas P, Maduratni Chambali F. Stunting Monitoring in Indonesia. Indonesian JElectronicElectromedEngMedInform. 2023;5(4):217–23.
Hartati Y, Podojoyo, Agustini S, Nilawati NS, Telisa I, Siregar A. The effect of Clarias cookies on the growth and development of wasting children. J Public Hlth Dev. 2024 May 1;22(2): 154–66.
Soller T, Huang S, Horiuchi S, Wilson AN, Vogel JP. Portable digital devices for paediatric height and length measurement: A scoping review and target product profile matching analysis. PLoS One. 2023 Jul 1;18(7 JULY).
Mocini E, Cammarota C, Frigerio F, Muzzioli L, Piciocchi C, Lacalaprice D, et al. Digital Anthropometry: A Systematic Review on Precision, Reliability and Accuracy of Most Popular Existing Technologies. Vol. 15, Nutrients. MDPI; 2023.
Grange JM, Mock NB, Collins SM. Influence of non-directional errors in anthropometric measurements and age estimation on anthropometric prevalence indicators. PLoS One. 2024 Sep 1; 19(9).
Rumbo-Rodríguez L, Sánchez-Sansegundo M, Ferrer-Cascales R, García-D’urso N, Hurtado-Sánchez JA, Zaragoza-Martí A. Comparison of body scanner and manual anthropometric measurements of body shape: A systematic review. Vol. 18, Int. J. Environ. Res. Public Health. MDPI AG; 2021.
Wang M, Song Y, Zhao X, Wang Y, Zhang M. Utilizing Anthropometric Measurements and 3D Scanning for Health Assessment in Clinical Practice. Vol. 8, Phys. Act. Health. Ubiquity Press; 2024. p. 182–96.
Peters MD, Godfrey C, McInerney P, Munn Z, Tricco AC, Khalil H. Scoping reviews. In: JBI Manual for Evidence Synthesis. JBI; 2020.
Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Ann Intern Med. 2018 Oct 2;169(7):467–73.
Arksey H, O’Malley L. Scoping studies: Towards a methodological framework. Int J Soc Res Methodol: Theory Pract. 2005 Feb;8(1):19–32.
Gupta PM, Sivalogan K, Oliech R, Alexander E, Klein J, Addo OY, et al. Impact of anthropometry training and feasibility of 3D imaging on anthropometry data quality among children under five years in a postmortem setting. PLoS One. 2023 Sep 1;18(9 September).
Sacco R, Munoz MA, Billuart F, Lalevée M, Beldame J. Validation of an Automated Optical Scanner for a Comprehensive Anthropometric Analysis of the Foot and Ankle. Bioengineering. 2023 Aug 1;10(8).
Zhang L, Zhang T, Liu HJ, Xing DQ, Zhao YN, Zhang YB, et al. Body composition in healthy singleton term infants using the three-dimensional photonic scanning method: A multicenter cross-sectional study. Nutrition. 2023 Dec 1;116.
Bougma K, Mei Z, Palmieri M, Onyango D, Liu J, Mesarina K, et al. Accuracy of a handheld 3D imaging system for child anthropometric measurements in population-based household surveys and surveillance platforms: an effectiveness validation study in Guatemala, Kenya, and China. Am J Clin Nutr. 2022 Jul 1;116(1):97–110.
Jefferds MED, Mei Z, Palmieri M, Mesarina K, Onyango D, Mwando R, et al. Acceptability and Experiences with the Use of 3D Scans to Measure Anthropometry of Young Children in Surveys and Surveillance Systems from the Perspective of Field Teams and Caregivers. Curr Dev Nutr. 2022 Jun 1;6(6).
Kennedy S, Smith B, Sobhiyeh S, Dechenaud ME, Wong M, Kelly N, et al. Digital anthropometric evaluation of young children: comparison to results acquired with conventional anthropometry. Eur J Clin Nutr. 2022 Feb 1;76(2):251–60.
Leidman E, Jatoi MA, Bollemeijer I, Majer J, Doocy S. Accuracy of Fully Automated 3D Imaging System for Child Anthropometry in a Low-Resource Setting: Effectiveness Evaluation in Malakal, South Sudan. JMIR Biomed Eng. 2022 Oct 21;7(2): e40066.
Wu ZF, Fan QL, Ming L, Yang W, Lv KL, Chang Q, et al. A comparative study between traditional head measurement and structured light three-dimensional scanning when measuring infant head shape. Transl Pediatr. 2021 Nov 1;10(11):2897–906.
Ji C, Yao D, Li MY, Chen WJ, Lin SL, Zhao ZY. A study on facial features of children with Williams syndrome in China based on three-dimensional anthropometric measurement technology. Am J Med Genet A. 2020 Sep 1;182(9):2102–9.
Kennedy S, Hwaung P, Kelly N, Liu YE, Sobhiyeh S, Heo M, et al. Optical imaging technology for body size and shape analysis: evaluation of a system designed for personal use. Eur J Clin Nutr. 2020 Jun 1;74(6):920–9.
Wong MC, Ng BK, Kennedy SF, Hwaung P, Liu EY, Kelly NN, et al. Children and Adolescents’ Anthropometrics Body Composition from 3-D Optical Surface Scans. Obesity. 2019 Nov 1;27(11):1738–49.
Amirav I, Masumbuko CK, Hawkes MT, Solomon I, Aldar Y, Margalit G, et al. 3D analysis of child facial dimensions for design of medical devices in low-middle income countries (LMIC). PLoS One. 2019 May 1;14(5).
Andrews ET, Ashton JJ, Pearson F, Beattie RM, Johnson MJ. Handheld 3D scanning as a minimally invasive measuring technique for neonatal anthropometry. Clin Nutr ESPEN. 2019 Oct 1;33:279–82.
Pleuss JD, Talty K, Morse S, Kuiper P, Scioletti M, Heymsfield SB, et al. A machine learning approach relating 3D body scans to body composition in humans. Vol. 73, Eur J Clin Nutr. Nature Publishing Group; 2019. p. 200–8.
Conkle J, Suchdev PS, Alexander E, Flores-Ayala R, Ramakrishnan U, Martorell R. Accuracy and reliability of a low-cost, handheld 3D imaging system for child anthropometry. PLoS One. 2018 Oct 1;13(10).
Ganesan B, Luximon A, Al-Jumaily AA, Yip J, Gibbons PJ, Chivers A. Developing a three-dimensional (3D) assessment method for clubfoot-A study protocol. Front Physiol. 2018 Jan 4;8(JAN).
Loeffler-Wirth H, Vogel M, Kirsten T, Glock F, Poulain T, Körner A, et al. Longitudinal anthropometry of children and adolescents using 3D-body scanning. PLoS One. 2018 Sep 1;13(9).
Santos LP, Ong KK, Day F, Wells JCK, Matijasevich A, Santos IS, et al. Body shape and size in 6-year old children: Assessment by three-dimensional photonic scanning. Int J Obes. 2016 Jun 1;40(6):1012–7.
Soileau L, Bautista D, Johnson C, Gao C, Zhang K, Li X, et al. Automated anthropometric phenotyping with novel Kinect-based three-dimensional imaging method: Comparison with a reference laser imaging system. Eur J Clin Nutr. 2016 Apr 1;70(4):475–81.
Wells JCK, Stocks J, Bonner R, Raywood E, Legg S, Lee S, et al. Acceptability, precision and accuracy of 3D photonic scanning for measurement of body shape in a multi-ethnic sample of children aged 5-11 years? The SLIC study. PLoS One. 2015 Apr 28;10(4).
Burini S, Marchionni P, Scalise L, Spinsante S, Ferretti E, Carnielli VP. MeMeA 2020 conference proceedings : IEEE Medical Measurements & Applications : June 1-3, 2020, Bari, Italy. 2020;
Penders B, Dijk DR, Bocca G, Zimmermann LJI, van Ravenswaaij-Arts CMA, Gerver WJM. An analysis of body proportions in children with CHARGE syndrome using photogrammetric anthropometry. Am J Med Genet A. 2019 Aug 1;179(8):1459–65.
Affuso O, Pradhan L, Zhang C, Gao S, Wiener HW, Gower B, et al. A method for measuring human body composition using digital images. PLoS One. 2018 Nov 1;13(11).
Penders B, Brecheisen R, Gerver A, Van Zonneveld G, Gerver WJ. Validating Paediatric Morphometrics: Body proportion measurement using photogrammetric anthropometry. J Pediatr Endocrinol Metab. 2015 Nov 1;28(11–12):1357–62.
Sokolover N, Phillip M, Sirota L, Potruch A, Kiryati N, Klinger G, et al. A novel technique for infant length measurement based on stereoscopic vision. Arch Dis Child. 2014;99(7): 625–8.
Barbero-García I, Lerma JL, Mora-Navarro G. Fully automatic smartphone-based photogrammetric 3D modelling of infant’s heads for cranial deformation analysis. ISPRS J Photogramm Remote Sens. 2020 Aug 1;166:268–77.
Wetzel O, Schmidt AR, Seiler M, Scaramuzza D, Seifert B, Spahn DR, et al. A smartphone application to determine body length for body weight estimation in children: a prospective clinical trial. J Clin Monit Comput. 2018 Jun 1;32(3):571–8.
Fletcher R, Díaz XSoriano, Bajaj H, Ghosh-Jerath S. Development of Smart Phone-based Child Health Screening Tools for Community Health Workers. 2017 IEEE Global Humanitarian Technology Conference (GHTC). 2017;1–9.
Umiatin U, Indrasari W, Taryudi T, Dendi AF. Development of a Multisensor-Based Non-Contact Anthropometric System for Early Stunting Detection. J Sens Actuat Netw. 2022 Oct 24;11(4).
Bauman A, Ernst K, Hayden M, Roe DJ, Murray R, Agawo M, et al. Assessing community health: An innovative tool for measuring height and length. J Trop Pediatr. 2018 Apr 1;64(2):146–50.
Mayol-Kreiser SN, Garcia-Turner VM, Johnston CS. Examining the utility of a laser device for measuring height in free-living adults and children. Nutr J. 2015 Sep 8;14(1).
Huang S, Conkle J, Homer CSE, Kounnavong S, Phongluxa K, Vogel JP. Comparing the accuracy of an ultrasound height measurement device with a wooden measurement board among children aged 2–5 years in rural Lao People’s Democratic Republic: A methods-comparison study. PLoS One. 2023 Nov 1;18(11 November).
Tiwari M, Anand N. Validation and Reliability of Sizestream 3D Scanner for Human Body Measurement. Functional Textiles and Clothing 2020 [Internet]. 2021 Jan 1 [cited 2024 Dec 19];13–23. Available from: https:// link.springer.com/chapter/10.1007/978-981-15-9376-5_2
Major M, Mészáros B, Würsching T, Polyák M, Kammerhofer G, Németh Z, et al. Evaluation of a Structured Light Scanner for 3D Facial Imaging: A Comparative Study with Direct Anthropometry. Sensors. 2024 Aug 1;24(16).
Abdel-Alim T, Tio P, Kurniawan M, Mathijssen I, Dirven C, Niessen W, et al. Reliability and Agreement of Automated Head Measurements from 3-Dimensional Photogrammetry in Young Children. J Craniofac Surg. 2023 Sep 1;34(6):1629–34.
Smith B, McCarthy C, Dechenaud ME, Wong MC, Shepherd J, Heymsfield SB. Anthropometric evaluation of a 3D scanning mobile application. Obesity. 2022 Jun 1;30(6):1181–8.
Mueller J, Richter M, Schaefer K, Ganz J, Lohscheller J, Mueller S. How to measure children’s feet: 3D foot scanning compared with established 2D manual or digital methods. J Foot Ankle Res. 2023 Dec 1;16(1).
Cho SH, Cho YG, Park HA, Bong AR. Reliability and Validity of an Ultrasonic Device for Measuring Height in Adults. Korean J Fam Med. 2021;42(5):376–81.
Sørensen GVB, Riis J, Danielsen MB, Ryg J, Masud T, Andersen S, et al. Reliability and agreement of a novel portable laser height metre. PLoS One. 2020 Apr 1;15(4).
Lo AL, Hallac RR, Chen SH, Hsu KH, Wang SW, Chen CH, et al. Craniofacial Growth and Asymmetry in Newborns: A Longitudinal 3D Assessment. Int J Environ Res Public Health. 2022 Oct 1;19(19).
Goto L, Lee W, Huysmans T, Molenbroek JFM, Goossens RHM. The variation in 3D face shapes of dutch children for mask design. Appl Sci. 2021 Aug 1;11(15).
Yafie E, Pramono, Sutama IW, Samawi A, Khairuddin KFB, Asyhari R. Development and Validation of a Mobile Application for Early Childhood Nutrition Monitoring: A Multisensor-Based Non-Contact Anthropometric System. Golden Age: Jurnal Ilmiah Tumbuh Kembang Anak Usia Dini. 2024 Aug 22;9(3):421–33.
Pereira-da-Silva L, Henriques RB, Virella D, Mascarenhas A, Papoila AL, Alves M, et al. Laser-Based Length-Measuring Board for the Measurement of Infant Body Length from Outside an Incubator: Proposal and Assessment of a Model. Children [Internet]. 2024 Dec 19;11(12):1544. Available from: https://www.mdpi.com/2227-9067/11/12/154