724 - Exploring Clinical Factors Associated with the Skeletal Muscle Mass Index in Early Childhood and School-age Years of Preterm and Low Birth Weight Infants

Publication Number: 2706.724

Nobuhiko Nagano, Nihon University School of Medicine, Itabashi-ku, Tokyo, Japan; CHIHIRO MUKAI, Nihon University School of Medicine, Itabashi-ku, Tokyo, Japan; Hidetoshi Go, Nihon University School of Medicine, 30-1 Oyaguchi Kamicho Itabashi, Tokyo, Japan; Yuki Sato, Nihon University School of Medicine, Itabashi, Tokyo, Japan; Takayuki Imaizumi, Nihon University School of Medicine, Itabashi-ku, Tokyo, Japan; Ryoji Aoki, nihon university, Bunkyo-ku, Tokyo, Japan; Midori Hijikata, Nihon university school of medicine department of pediatrics and child health, Itabashi, Tokyo, Japan; Kazumasa Fuwa, Nihon University School of Medicine, Itabashi-ku, Tokyo, Japan; Aya Okahashi, Nihon University School of Medicine, Itanashi-ku, Tokyo, Japan; Ichiro Morioka, Nihon University School of Medicine, Itabashi, Tokyo, Japan

Background: Preterm and low-birth-weight (LBW) infants tend to have reduced skeletal muscle mass, even in adulthood, which may lower their basal metabolic rate and increase the risk of type 2 diabetes mellitus (T2DM). This phenotype differs from obesity-related T2DM, which results from excess energy intake. Recently, non-invasive medical body composition analyzers have enabled the detailed assessment of muscle mass in children.

Objective: To identify clinical factors associated with the skeletal muscle mass index (SMI) during early childhood and school age in preterm and LBW children.

Design/Methods: Preterm and LBW children aged ≥5 years who were followed in our outpatient clinic and who underwent body composition analysis using a medical device (InBody S10, bioelectrical impedance analysis) were included. The InBody S10 is rapid and radiation-free. The associations between the SMI (kg/m²) and clinical factors including sex, gestational age, birth weight standard deviation score (SDS), birth length SDS, age at measurement, height SDS, body mass index (BMI) SDS, obesity level, body fat mass, protein mass, body cell mass, basal metabolic rate, and phase angle, were determined.

Results: Seventy-four participants (40 girls and 34 boys) were included. The median gestational age and birth weight were 28 weeks (range, 23–36 weeks) and 939 g (range, 348–2,422 g), respectively. The median age at measurement was 7 years (range, 5–9 years). Median BMI was 14.3 (range, 10.8–20.1), and BMI SDS was −0.9 (range, −4.9 to 2.0); only two children (3%) met the criteria for obesity. Median SMI was 3.8 kg/m² (range, 2.0–5.5 kg/m2), lower than previously reported values in general children (5.0–6.0 kg/m²) (Table 1). In univariate analyses, SMI was significantly positively correlated with BMI SDS, obesity level, protein mass, body cell mass, basal metabolic rate, and phase angle, and significantly negatively correlated with age. In multivariate analysis, factors other than age remained independently associated with SMI (Table 2).

Conclusion(s): Preterm and LBW children had a lower SMI during early childhood and school-age than the general population of children. A low BMI SDS was independently associated with a lower SMI. Preterm and LBW children with a markedly low BMI SDS should be evaluated for muscle mass to guide long-term metabolic health management.

Subject backgrounds
PAS2026NaganoTable1.pdf

Multivariate analysis
PAS2026NaganoTable2.pdf