Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Sep;140(3):e20171072.
doi: 10.1542/peds.2017-1072. Epub 2017 Aug 22.

Tracking of BMI z Scores for Severe Obesity

Affiliations

Tracking of BMI z Scores for Severe Obesity

David S Freedman et al. Pediatrics. 2017 Sep.

Abstract

Background: Although the Centers for Disease Control (CDC) growth charts are widely used in studies of childhood obesity, BMI z scores are known to be inaccurate at values greater than the 97th percentile.

Methods: We used longitudinal data from 6994 children in the Bogalusa Heart Study who were examined multiple times to compare tracking of 3 BMI metrics: BMI-for-sex/age z score (BMIz), BMI expressed as a percentage of the 95th percentile (%BMIp95), and levels of BMI z score that adjust for the compression of very high z scores (adjusted z score [BMIaz]). The later 2 metrics, unlike BMIz, do not have an upper limit. The mean interval between examinations was 2.8 years. We were particularly interested in these metrics among children with obesity or severe obesity (%BMIp95 ≥120%).

Results: Although there was little difference in the tracking of the 3 metrics in the overall sample, among 247 children with severe obesity, the correlation of BMIz levels between examinations (r = 0.46) was substantially weaker than those for BMIaz and %BMIp95 (r = 0.65 and 0.61). Age-stratified analyses indicated that the weak tracking of BMIz was particularly evident before the age of 10 years (r = 0.36 vs 0.57 and 0.60). Several children with severe obesity showed BMIz decreases between examinations despite having BMI increases of over 5.

Conclusions: Among children with severe obesity, the tracking of BMIz is weak. This is because of the constraints in converting very high BMIs into z scores based on the CDC growth charts. Rather than using BMIz, it would be preferable to express very high BMIs relative to the CDC 95th percentile or to use BMIaz.

PubMed Disclaimer

Conflict of interest statement

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

Figures

FIGURE 1
FIGURE 1
Maximum values of the BMI metrics among children in the Bogalusa Heart Study by sex and 2-year age groups.
FIGURE 2
FIGURE 2
Initial and subsequent levels of BMI, BMIz, BMIaz, and %BMIp95 among children who had severe obesity at the initial examination. The points labeled 1 through 4 represent the children who showed a BMIz decrease of more than 0.33 SDs between examinations but an increase in %BMIp95 of more than 10 U.

References

    1. Kuczmarski RJ, Ogden CL, Guo SS, et al. . 2000 CDC growth charts for the United States: methods and development. Vital Health Stat 11. 2002;11(246):1–190 - PubMed
    1. Ogden CL, Kuczmarski RJ, Flegal KM, et al. . Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics. 2002;109(1):45–60 - PubMed
    1. Flegal KM, Cole TJ. Construction of LMS parameters for the Centers for Disease Control and Prevention 2000 growth charts. Natl Health Stat Rep. 2013;9(63):1–3 - PubMed
    1. Cole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr. 1990;44(1):45–60 - PubMed
    1. Cole TJ, Green PJ. Smoothing reference centile curves: the LMS method and penalized likelihood. Stat Med. 1992;11(10):1305–1319 - PubMed