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Linear hair growth rates in preschool children

Pediatric Research volume 95, pages 359–366 (2024)Cite this article

Abstract

Background

Human scalp hair is a validated bio-substrate for monitoring various exposures in childhood including contextual stressors, environmental toxins, prescription or non-prescription drugs. Linear hair growth rates (HGR) are required to accurately interpret hair biomarker concentrations.

Methods

We measured HGR in a prospective cohort of preschool children (N = 266) aged 9–72 months and assessed demographic factors, anthropometrics, and hair protein content (HPC). We examined HGR differences by age, sex, race, height, hair pigment, and season, and used univariable and multivariable linear regression models to identify HGR-related factors.

Results

Infants below 1 year (288 ± 61 μm/day) had slower HGR than children aged 2–5 years (p = 0.0073). Dark-haired children (352 ± 52 μm/day) had higher HGR than light-haired children (325 ± 50 μm/day; p = 0.0019). Asian subjects had the highest HGR overall (p = 0.016). Younger children had higher HPC (p = 0.0014) and their HPC-adjusted HGRs were slower than older children (p = 0.0073). Age, height, hair pigmentation, and HPC were related to HGR in multivariable regression models.

Conclusions

We identified age, height, hair pigment, and hair protein concentration as significant determinants of linear HGRs. These findings help explain the known hair biomarker differences between children and adults and aid accurate interpretation of hair biomarker results in preschool children.

Impact

  • Discovery of hair biomarkers in the past few decades has transformed scientific disciplines like toxicology, pharmacology, epidemiology, forensics, healthcare, and developmental psychology.

  • Identifying determinants of hair growth in children is essential for accurate interpretation of hair biomarker results in pediatric clinical studies.

  • Childhood hair growth rates define the time-periods of biomarker incorporation into growing hair, essential for interpreting the biomarkers associated with environmental exposures and the mind-brain-body connectome.

  • Our study describes age-, sex-, and height-based distributions of linear hair growth rates and provides determinants of linear hair growth rates in a large population of children.

  • Age, height, hair pigmentation, and hair protein content are determinants of hair growth rates and should be accounted for in child hair biomarkers studies.

  • Our findings on hair protein content and linear hair growth rates may provide physiological explanations for differences in hair growth rates and biomarkers in preschool children as compared to adults.

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Fig. 1: Statistical analyses to test the normality and equal variance assumptions for the two linear regression models.
Fig. 2: Whisker plots for HPC, HGR, and HPC:HGR by age.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on request.

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Acknowledgements

We thank Grace K-Y. Tam, Clinical Research Coordinator, Pain/Stress Neurobiology Laboratory, and Dr. Sukyung Chung, Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA for their contributions to this study and to earlier versions of this manuscript.

Funding

Grants from the Eunice Kennedy Shriver National Institute for Child Health & Human Development (R01 HD099296) and the Maternal & Child Health Research Institute to KJSA supported this study. Study sponsors had no role in the design and conduct of the study; the collection, management, analysis, or interpretation of the data; the preparation, review, approval, or decision to publish this manuscript.

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Author notes

  1. Mónica O. Ruiz

    Present address: Department of Pediatrics, Brown University School of Medicine, Rhode Island Hospital & Hasbro Children’s Hospital, Providence, RI, USA

Authors and Affiliations

  1. Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA

    Mónica O. Ruiz, Cynthia R. Rovnaghi & Kanwaljeet J. S. Anand

  2. Stanford Child Wellness Lab, Maternal & Child Health Research Institute, Stanford, CA, USA

    Mónica O. Ruiz, Cynthia R. Rovnaghi, Sahil Tembulkar, Leni Truong & Kanwaljeet J. S. Anand

  3. Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA

    FeiFei Qin & Sa Shen

  4. Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Kanwaljeet J. S. Anand

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Contributions

M.O.R.: substantial contributions to data analysis and interpretation; drafting the article and revising it critically for important intellectual content; and final approval of the version to be published. C.R.R.: substantial contributions to conception and design; data acquisition, analysis, and interpretation; drafting the article and revising it critically for important intellectual content; and final approval of the version to be published. S.T.: substantial contributions to conception and design; acquisition of data; and final approval of the version to be published. F.Q.: substantial contributions to data analysis and interpretation; and final approval of the version to be published. S.S.: substantial contributions to data analysis and interpretation; and final approval of the version to be published. L.T.: substantial contributions to data acquisition and analysis; and final approval of the version to be published. K.J.S.A.: Substantial contributions to conception and design; data acquisition, analysis and interpretation; drafting the article and revising it critically for important intellectual content; securing grant funding for the project; and final approval of the version to be published.

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Correspondence to Mónica O. Ruiz.

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Ruiz, M.O., Rovnaghi, C.R., Tembulkar, S. et al. Linear hair growth rates in preschool children. Pediatr Res 95, 359–366 (2024). https://doi.org/10.1038/s41390-023-02791-z

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