Scholarlink

Objective <p>To examine the associations between BMI trajectories and changes in fat-free mass index (FFMI) and fat mass index (FMI), assessed via bioelectrical impedance analysis (BIA) and skinfold thickness (ST).</p> Methods <p>The study included 4708 European children with BIA data and 3627 with ST data, aged 2–9.9 years at baseline, participating in two waves of the IDEFICS (IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants))/I.Family (I. Family (Determinants of eating behavior in European children, adolescents, and their parents)) studies (w0: 2007/08; w2: 2013/14). Children were classified into three BMI trajectory groups: retained normal weight (RNW), remained overweight/obese (ROO), and excessive weight gain (EWG). Analyses of covariance evaluated differences in BMI z-score changes, FFMI, and FMI across groups. Mixed-effects linear regression assessed associations between BMI z-score changes and FFMI/FMI over time.</p> Results <p>BMI z-score changes were more strongly associated with FMI (<i>β</i> = 1.16–1.70 in boys; 1.17–1.62 in girls, <i>p</i> &lt; 0.05) than with FFMI, for both BIA and ST. In ROO and EWG groups, associations with FMI were consistently stronger, except among girls &lt;6 years in the ROO group (BIA). In the RNW group, boys &gt;6 years showed stronger associations with FFMI.</p> Conclusions <p>Associations between BMI changes and FFMI/FMI vary by BMI trajectory and body composition method. BIA showed closer alignment with BMI changes than ST. These findings suggest that BMI alone may not adequately capture changes in specific body compartments. While convenient, BMI should be interpreted with caution, especially when fat or fat-free mass plays a differential role in disease risk or health outcomes.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Association between trajectories of body mass index and changes in fat free mass index and fat mass index in a cohort of European children. The IDEFICS/I.Family studies

  • 期刊论文

  • 发表日期：

    2026年3月19日

查看全文
  • Elizabeth Lizárraga,
  • Iris Iglesia-Altaba,
  • Javier Santabárbara,
  • Wolfgang Ahrens,
  • Claudia Börnhorst,
  • Annarita Formisano,
  • Toomas Veidebaum,
  • Michael Tornaritis,
  • Stefaan De Henauw,
  • Gabriele Eiben,
  • Monica Hunsberger,
  • Dénes Molnár,
  • Luis A. Moreno

摘要

Objective

To examine the associations between BMI trajectories and changes in fat-free mass index (FFMI) and fat mass index (FMI), assessed via bioelectrical impedance analysis (BIA) and skinfold thickness (ST).

Methods

The study included 4708 European children with BIA data and 3627 with ST data, aged 2–9.9 years at baseline, participating in two waves of the IDEFICS (IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants))/I.Family (I. Family (Determinants of eating behavior in European children, adolescents, and their parents)) studies (w0: 2007/08; w2: 2013/14). Children were classified into three BMI trajectory groups: retained normal weight (RNW), remained overweight/obese (ROO), and excessive weight gain (EWG). Analyses of covariance evaluated differences in BMI z-score changes, FFMI, and FMI across groups. Mixed-effects linear regression assessed associations between BMI z-score changes and FFMI/FMI over time.

Results

BMI z-score changes were more strongly associated with FMI (β = 1.16–1.70 in boys; 1.17–1.62 in girls, p < 0.05) than with FFMI, for both BIA and ST. In ROO and EWG groups, associations with FMI were consistently stronger, except among girls <6 years in the ROO group (BIA). In the RNW group, boys >6 years showed stronger associations with FFMI.

Conclusions

Associations between BMI changes and FFMI/FMI vary by BMI trajectory and body composition method. BIA showed closer alignment with BMI changes than ST. These findings suggest that BMI alone may not adequately capture changes in specific body compartments. While convenient, BMI should be interpreted with caution, especially when fat or fat-free mass plays a differential role in disease risk or health outcomes.