[Bone mineral density in nursing infants and young children (0-4 years old) at the level of the lumbar spine. The normal patterns]

An Esp Pediatr. 1998 Sep;49(3):248-52.
[Article in Spanish]

Abstract

Objective: A cross-sectional study of bone mineral density was conducted in a normal population of children with ages ranging from the neonatal period to 4 years with the aim of establishing normal bone mineral density (BMD) patterns.

Patients and methods: Bone mineral content density was measured by dual-energy X-ray absorptiometry at the level of the lumbar spine (L2-L4) in 147 normal children (69 boys, 78 girls, age range: 15 days to 4 years) randomly selected from the urban area of Barcelona.

Results: Weight, length and height were in the normal age distribution. Bone mineral content values were corrected by the vertebral surface area scanned and expressed as bone mineral density values (grams of hydroxyapatite/cm2). Bone mineral density values increased progressively from birth to 4 years and values were similar in both sexes. A statistically significant correlation was found between BMD values and age (r = 0.82, p < 0.001), weight (r = 0.87, p < 0.001) and length or height (r = 0.79, p < 0.001). Lumbar bone mineral density values increased annually, but the periods of higher increase were observed during the first 2 years of life. Bone mineral density values showed a similar pattern to height growth velocity.

Conclusions: We report normative data for bone mineral density at the lumbar spine in our normally-growing pediatric population from the neonatal period to 4 years. These data provide a tool for the study and follow-up of pediatric populations at risk for low bone mineralization during early childhood.

MeSH terms

  • Absorptiometry, Photon / methods
  • Absorptiometry, Photon / statistics & numerical data
  • Aging / physiology*
  • Bone Density*
  • Child, Preschool
  • Female
  • Humans
  • Infant
  • Infant, Newborn
  • Lumbar Vertebrae / diagnostic imaging*
  • Male
  • Reference Values
  • Regression Analysis
  • Sex Characteristics
  • Statistics, Nonparametric