ISAK Home

Vol. 5 No. 3 (2025): Volume 5, Issue 3, Year 2025

Articles

Anthropometry, Neck Posture and Smartphones: Exploring Interrelationships in Young College Students

  • Ankita R. Parkhe,
  • Lalli M. Singh,
  • Harsirjan Kaur
Ankita R. Parkhe
School of Physiotherapy, SGT University, Gurugram, Haryana, India
Lalli M. Singh
School of Physiotherapy, SGT University, Gurugram, Haryana, India
Harsirjan Kaur
School of Physiotherapy, SGT University, Gurugram, Haryana, India
PDF
DOI: https://doi.org/10.34256/ijk2534

Published 07-12-2025

Keywords

  • Smartphone,
  • Addiction,
  • Anthropometry,
  • Neck Posture

How to Cite

R. Parkhe, A., M. Singh, L., & Kaur, H. (2025). Anthropometry, Neck Posture and Smartphones: Exploring Interrelationships in Young College Students. International Journal of Kinanthropometry, 5(3), 30–37. https://doi.org/10.34256/ijk2534

Copyright (c) 2025 Ankita R. Parkhe, Lalli M. Singh, Harsirjan Kaur

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Dimensions

Crossref
Scopus
Google Scholar
Europe PMC

Abstract

Introduction: Smartphone addiction is increasingly common among young adults and tied to musculoskeletal problems, but we know little about how it connects to posture, body measurements, and composition. This study explores those links in university students. Methods: A cross-sectional study was done with 51 healthy students (18-25 years old) at SGT University. They completed the Smartphone Addiction Scale (SAS), Neck Disability Index (NDI), and a health assessment, plus measurements of craniovertebral angle (CVA) using Kinovea software, anthropometrics (like skinfolds, neck circumference, and shoulder width), and body composition via bioelectrical impedance analysis (BIA). We used Pearson correlations to spot relationships (p < 0.05). Results: Students had moderate SAS scores (27.88 ± 8.31), mild neck disability (7.71 ± 6.40), and average CVA of 54.79 ± 5.44°. Higher smartphone addiction linked to more body fat (r = 0.302, p = 0.031). Health scores dropped with higher BMI (r = -0.769, p < 0.001), body fat rate (r = -0.674, p < 0.001), body fat mass (r = -0.631, p < 0.001), and measures like neck circumference (r = -0.307, p = 0.029), shoulder width (r = -0.366, p = 0.008), and upper arm girth (r = -0.376, p = 0.007)—but rose with better hydration (r = 0.554, p < 0.001). Poorer posture (lower CVA) is related to higher body fat (r = -0.468, p = 0.043) and narrower shoulders (r = 0.461, p = 0.047). Smartphone addiction didn't strongly connect to posture, body measurements, or most metabolic factors. Conclusion: In young adults, body fat levels drive health and posture more than smartphone habits alone, though addiction does boost fat gain. Targeting sedentary habits and body composition could help prevent issues.

PDF

References

  1. Allam, M.M., Yousef, E., Tahoon, A. (2025). Cervical Posture Among Smart Phone Addictive with Cervicogenic Headache: Matched Case Control Study. Benha International Journal of Physical Therapy, 84-91.
  2. Ayvaz, D.N.Ç., Kilinc, F.N., PAÇ, F.A., Cakal, E. (2011). Anthropometric Measurements and Body Composition Analysis of Obese Adolescents with and Without Metabolic Syndrome. Turkish Journal of Medical Sciences, 41(2): 267-274. https://doi.org/10.3906/sag-0909-254
  3. Bennett, J.P., Lim, S. (2025). The Critical Role of Body Composition Assessment in Advancing Research and Clinical Health Risk Assessment across the Lifespan. Journal of Obesity & Metabolic Syndrome, 34(2): 120.https://doi.org/10.7570/jomes25010
  4. Bogduk, N. (2011). The anatomy and pathophysiology of neck pain. Physical Medicine and Rehabilitation Clinics, 22(3): 367-382.https://doi.org/10.1016/j.pmr.2011.03.008
  5. Bragança, S., Arezes, P., Carvalho, M., Ashdown, S. (2016). Effects of different body postures on anthropometric measures. In Advances in Ergonomics in Design: Proceedings of the AHFE 2016 International Conference on Ergonomics in Design, July 27-31, 2016, Walt Disney World®, Florida, USA Cham: Springer International Publishing,485: 313-322.https://doi.org/10.1007/978-3-319-41983-1_28
  6. Esparza-Ros, F., Vaquero-Cristóbal, R., Marfell-Jones, M. (2019). International Standards for Anthropometric Assessment. International Society for the Advancement of Kinanthropometry (ISAK).
  7. Faber, A., Bee, C., Girju, M., Onel, N., Rossi, A. M., Cozac, M., Lutz, R.J., Nardini, G., Song, C.E. (2022). The paradoxes of smartphone use: Understanding the user experience in today's connected world. Journal of Consumer Affairs, 56(3): 1260-1283.https://doi.org/10.1111/joca.12472
  8. Frank, A.P., de Souza Santos, R., Palmer, B.F., Clegg, D.J. (2019). Determinants of Body Fat Distribution In Humans May Provide Insight About Obesity-Related Health Risks. Journal of Lipid Research, 60(10): 1710-1719.https://doi.org/10.1194/jlr.R086975
  9. Gill, E., Chung, W. (2025). The Effect of Smartphone Addiction on Obesity in Children and Adolescents. Psychology, Health & Medicine, 1-15.https://doi.org/10.1080/13548506.2025.2561741
  10. Heitmayer, M., Lahlou, S. (2021). Why Are Smartphones Disruptive? An Empirical Study of Smartphone Use in Real-Life Contexts. Computers in Human Behavior, 116: 106637. https://doi.org/10.1016/j.chb.2020.106637
  11. Izzo, R., Guarnieri, G., Guglielmi, G., Muto, M. (2013). Biomechanics of the Spine. Part I: Spinal Stability. European journal of radiology, 82(1): 118-126.https://doi.org/10.1016/j.ejrad.2012.07.024
  12. Jéquier, E., Constant, F. (2010). Water as an essential nutrient: the physiological basis of hydration. European journal of clinical nutrition, 64(2): 115-123.https://doi.org/10.1038/ejcn.2009.111
  13. Kwon, M., Lee, J.Y., Won, W.Y., Park, J.W., Min, J.A., Hahn, C., Gu, X., Choi, J.H., Kim, D. J. (2013). Development and validation of a Smartphone Addiction Scale (SAS). PloS one, 8(2): e56936. https://doi.org/10.1371/journal.pone.0056936
  14. Limanan, D., Santoso, A., Teguh, S., Jap, A. (2025). Correlation between Anthropometry and Fat Caliper Measurements with Triglyceride Ratios and Blood Pressure: Korelasi antara Pengukuran Antropometri dan Pengukuran Kaliper Lemak dengan Rasio Trigliserida dan Tekanan Darah.n Jurnal Keperawatan Bunda Delima, 7(2): 135-149.https://doi.org/10.59030/jkbd.v7i2.178
  15. Ling, F.P., Chevillotte, T., Leglise, A., Thompson, W., Bouthors, C., Le Huec, J.C. (2018). Which Parameters Are Relevant In Sagittal Balance Analysis of The Cervical Spine? A Literature Review. European spine journal, 27(Suppl 1): 8-15.https://doi.org/10.1007/s00586-018-5462-y
  16. MacDermid, J.C., Walton, D.M., Avery, S., Blanchard, A., Etruw, E., McAlpine, C., Goldsmith, C.H. (2009). Measurement Properties of the Neck Disability Index: A Systematic Review. Journal of Orthopaedic & Sports Physical Therapy, 39(5): 400-417.https://www.jospt.org/doi/10.2519/jospt.2009.2930
  17. Vannajak, K., Muanjai, P., Wawnatde, N., Snieckus, A., Taweekarn, P. (2025). Effectiveness of Home-Based Corrective Exercises on Posture and Neck Strength in Older Adults with Smartphone Addiction: A Randomized-Controlled Trial. Sport Sciences for Health, 21(4): 3141-3155.https://doi.org/10.1007/s11332-025-01524-5
  18. Wasie, T. (2024). Screen to green: Navigating the Digital Dilemma. Teshome Wasie, 1.
  19. Xie, Y. (2016). A Study of Musculoskeletal Loading in Using a Touchscreen Smartphone among Young People with and Without Chronic Neck-Shoulder Pain. Physiotherapy, 101:e1668-e1669. https://doi.org/10.1016/j.physio.2015.03.068
  20. Yasshwi, U., Dhande, S., Dhale, T., Deshmukh, S., Verma, P. (2025). A Review of Musculoskeletal Disorders In Young People Associated With Excessive Use Of Smartphone. In AIP Conference Proceedings, AIP Publishing LLC, 3227(1): 060008.https://doi.org/10.1063/5.0242531
  21. Zárate-Tejero, C.A., Rodríguez-Rubio, P.R., Brandt, L., Krauss, J., Hernández-Secorún, M., Hidalgo-García, C., Lucha-López, O. (2024). Measuring Craniovertebral Angle Reference Values in Adults Using Kinovea Software. Applied Sciences, 14(19): 8639.https://doi.org/10.3390/app14198639