Public Health Nutrition (Dec 2023)

Evaluating preschool linear growth velocities: an interim reference illustrated in Nepal

  • Swetha Manohar,
  • Elizabeth Colantuoni,
  • Andrew Lucian Thorne-Lyman,
  • Binod Shrestha,
  • Ramesh Kant Adhikari,
  • Angela KC,
  • Abhigyna Bhattarai,
  • Keith Parker West

DOI
https://doi.org/10.1017/S1368980023002409
Journal volume & issue
Vol. 26
pp. 2704 – 2716

Abstract

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Abstract Objective: An annualised linear growth velocity (LGV) reference can identify groups of children at risk of growing poorly. As a single velocity reference for all preschool ages does not exist, we present an interim tool, derived from published, normative growth studies, for detecting growth faltering, illustrating its use in Nepali preschoolers. Design: The WHO Child Growth Velocity Standard was adapted to derive 12-month increments and conjoined to the Tanner-Whitehouse Height Velocity Reference data yielding contiguous preschool linear growth annualised velocities. Linear restricted cubic spline regressions were fit to generate sex-specific median and standard normal deviate velocities for ages 0 through 59 months. LGV Z-scores (LGVZ) were constructed, and growth faltering was defined as LGVZ < –2. Setting: Use of the reference was illustrated with data from Nepal’s Tarai region. Participants: Children contributing the existing growth references and a cohort of 4276 Nepali children assessed from 2013 to 2016. Results: Fitted, smoothed LGV reference curves displayed monotonically decreasing 12-month LGV, exemplified by male/female annual medians of 26·4/25·3, 12·1/12·7, 9·1/9·4, 7·7/7·8 and 7/7 cm/years, starting at 0, 12, 24, 36 and 48 months, respectively. Applying the referent, 31·1 %, 28·6 % and 29·3 % of Nepali children <6, 6–11 and 12–23 months of age, and ∼6 % of children 24–59 months, exhibited growth faltering. Under 24 months, faltering velocities were more prevalent in girls (34·4 %) than boys (25·3 %) (P < 0·05) but comparable (∼6 %) in older preschoolers. Conclusions: A LGV reference, concatenated from extant data, can identify preschool groups at-risk of growth faltering. Application and limitations are discussed.

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