RESUMEN
BACKGROUND: Bioimpedance devices are practical for measuring body composition in preschool children, but their application is limited by the lack of validated equations. OBJECTIVES: To develop and validate fat-free mass (FFM) bioimpedance prediction equations among New Zealand 3.5-year olds, with dual-energy X-ray absorptiometry (DXA) as the reference method. METHODS: Bioelectrical impedance spectroscopy (SFB7, ImpediMed) and DXA (iDXA, GE Lunar) measurements were conducted on 65 children. An equation incorporating weight, sex, ethnicity, and impedance was developed and validated. Performance was compared with published equations and mixture theory prediction. RESULTS: The equation developed in ~70% (n = 45) of the population (FFM [kg] = 1.39 + 0.30 weight [kg] + 0.39 length2/resistance at 50 kHz [cm2/Ω] + 0.30 sex [M = 1/F = 0] + 0.28 ethnicity [1 = Asian/0 = non-Asian]) explained 88% of the variance in FFM and predicted FFM with a root mean squared error of 0.39 kg (3.4% of mean FFM). When internally validated (n = 20), bias was small (40 g, 0.3% of mean FFM), with limits of agreement (LOA) ±7.6% of mean FFM (95% LOA: -0.82, 0.90 kg). Published equations evaluated had similar LOA, but with marked bias (>12.5% of mean FFM) when validated in our cohort, likely due to DXA differences. Of mixture theory methods assessed, the SFB7 inbuilt equation with personalized body geometry values performed best. However, bias and LOA were larger than with the empirical equations (-0.43 kg [95% LOA: -1.65, 0.79], p < 0.001). CONCLUSIONS: We developed and validated a bioimpedance equation that can accurately predict FFM. Further external validation of the equation is required.
RESUMEN
BACKGROUND: Longitudinal assessment of the determinants of obesogenic growth trajectories in childhood can suggest appropriate developmental windows for intervention. METHODS: Latent class growth mixture modelling was used to identify body mass index (BMI) z-score trajectories from birth to age 6 years in 994 children from a prospective mother-offspring cohort (Chinese, Indian and Malay ethnicities) based in Singapore. We evaluated the early-life determinants of the trajectories as well as their associations with cardiometabolic risk markers at age 6 years. RESULTS: Five BMI z-score trajectory patterns were identified, three within the healthy weight range, alongside early-acceleration and late-acceleration obesogenic trajectories. The early-acceleration pattern was characterized by elevated fetal abdominal circumference growth velocity, BMI acceleration immediately after birth and crossing of the obesity threshold by age 2 years. The late-acceleration pattern had normal fetal growth and BMI acceleration after infancy, and approached the obesity threshold by age 6 years. Abdominal fat, liver fat, insulin resistance and odds of pre-hypertension/hypertension were elevated in both groups. Indian ethnicity, high pre-pregnancy BMI, high polygenic risk scores for obesity and shorter breastfeeding duration were common risk factors for both groups. Malay ethnicity and low maternal educational attainment were uniquely associated with early BMI acceleration, whereas nulliparity and obesogenic eating behaviours in early childhood were uniquely associated with late BMI acceleration. CONCLUSION: BMI acceleration starting immediately after birth or after infancy were both linked to early cardiometabolic alterations. The determinants of these trajectories may be useful for developing early risk stratification and intervention approaches to counteract metabolic adversities linked to childhood obesity.
