Literature DB >> 26862707

BMI and BMI SDS in childhood: annual increments and conditional change.

Bente Brannsether1,2, Geir Egil Eide3,4, Mathieu Roelants5, Robert Bjerknes1, Pétur Benedikt Júlíusson1,6.   

Abstract

Background Early detection of abnormal weight gain in childhood may be important for preventive purposes. It is still debated which annual changes in BMI should warrant attention. Aim To analyse 1-year increments of Body Mass Index (BMI) and standardised BMI (BMI SDS) in childhood and explore conditional change in BMI SDS as an alternative method to evaluate 1-year changes in BMI. Subjects and methods The distributions of 1-year increments of BMI (kg/m2) and BMI SDS are summarised by percentiles. Differences according to sex, age, height, weight, initial BMI and weight status on the BMI and BMI SDS increments were assessed with multiple linear regression. Conditional change in BMI SDS was based on the correlation between annual BMI measurements converted to SDS. Results BMI increments depended significantly on sex, height, weight and initial BMI. Changes in BMI SDS depended significantly only on the initial BMI SDS. The distribution of conditional change in BMI SDS using a two-correlation model was close to normal (mean = 0.11, SD = 1.02, n = 1167), with 3.2% (2.3-4.4%) of the observations below -2 SD and 2.8% (2.0-4.0%) above +2 SD. Conclusion Conditional change in BMI SDS can be used to detect unexpected large changes in BMI SDS. Although this method requires the use of a computer, it may be clinically useful to detect aberrant weight development.

Entities:  

Keywords:  BMI increments; Overweight; childhood; early detection of risk

Mesh:

Year:  2016        PMID: 26862707     DOI: 10.3109/03014460.2016.1151933

Source DB:  PubMed          Journal:  Ann Hum Biol        ISSN: 0301-4460            Impact factor:   1.533


  5 in total

1.  Developmental Trajectories of Body Mass Index, Waist Circumference, and Aerobic Fitness in Youth: Implications for Physical Activity Guideline Recommendations (CHAMPS Study-DK).

Authors:  Jeffrey J Hébert; Martin Sénéchal; Timothy Fairchild; Niels Christian Møller; Heidi Klakk; Niels Wedderkopp
Journal:  Sports Med       Date:  2020-12       Impact factor: 11.136

2.  Tracking of BMI z Scores for Severe Obesity.

Authors:  David S Freedman; Gerald S Berenson
Journal:  Pediatrics       Date:  2017-08-22       Impact factor: 7.124

3.  What Change in Body Mass Index Is Required to Improve Cardiovascular Outcomes in Childhood and Adolescent Obesity through Lifestyle Interventions: A Meta-Regression.

Authors:  Ahmed Y M El-Medany; Laura Birch; Linda P Hunt; Rhys I B Matson; Amanda H W Chong; Rhona Beynon; Julian Hamilton-Shield; Rachel Perry
Journal:  Child Obes       Date:  2020-08-11       Impact factor: 2.992

4.  Tracking and Variability in Childhood Levels of BMI: The Bogalusa Heart Study.

Authors:  David S Freedman; Hannah G Lawman; Deborah A Galuska; Alyson B Goodman; Gerald S Berenson
Journal:  Obesity (Silver Spring)       Date:  2018-06-11       Impact factor: 5.002

5.  Does a Gluten-Free Diet Affect BMI and Glycosylated Hemoglobin in Children and Adolescents with Type 1 Diabetes and Asymptomatic Celiac Disease? A Meta-Analysis and Systematic Review.

Authors:  Salma Burayzat; Nour Elsahoryi; Ali Freitekh; Osama Alzoubi; Rahaf Al-Najjar; Reema Tayyem
Journal:  Children (Basel)       Date:  2022-08-18
  5 in total

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