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
. 2009;2(5):302-10.
doi: 10.1159/000235561. Epub 2009 Sep 10.

Longitudinal modelling of body mass index from birth to 14 years

Affiliations

Longitudinal modelling of body mass index from birth to 14 years

Paola Chivers et al. Obes Facts. 2009.

Abstract

Background: To examine the tracking of BMI from birth to age 14 years.

Participants and methods: Linear mixed model (LMM) analysis was used to model the trajectories of BMI (n = 1,403). Adiposity rebound was investigated for a subset of individuals (n = 173).

Results: Adolescents who were overweight or obese at 14 years followed a different BMI trajectory from birth compared to those of normal weight. There was a difference between weight status groups for the timing of adiposity rebound (p < 0.001) and BMI at nadir (p < 0.001). The LMM depicted a significant difference in rate of change of BMI over time for males and females (p < 0.001), with female BMI increasing at a faster rate, and for weight status groups (p < 0.005), with the obese cohort having the faster increase in BMI over time. BMI at birth was significantly lower for the normal weight cohort compared to the overweight (p = 0.029) and obese (p = 0.019) cohorts.

Conclusion: This study introduces a powerful analytic tool, LMM, to model BMI and shows that weight status at 14 years is the result of a distinct path in earlier years. Compared to their normal weight peers, overweight and obese adolescents experience an earlier adiposity rebound, with a higher BMI at rebound.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Predicted BMI trajectories from birth to 14 years, separated by weight categories normal weight, overweight, and obese (determined at 14 years using IOTF cut-offs), and gender. Mean age-adjusted BMI calculated for each survey wave is overlaid for each weight category and gender to demonstrate goodness of fit to the predicted BMI trajectory model.
Fig. 2
Fig. 2
Mean BMI over time based on BMI IOTF weight category as determined at survey year 14 (n = 1,403). Adiposity rebound in this study was determined as the minimum BMI value.

Similar articles

Cited by

References

    1. Australian Institute of Health and Welfare: Australia's health 2006 AIHW Cat. No. AUS 73. Canberra, Australian Institute of Health and Welfare. 2006
    1. Haslam DW, James WPT. Obesity. Lancet. 2005;366:1197–1209. - PubMed
    1. World Health Organisation: Obesity and overweight Fact Sheet No. 311. 2006 www.who.int/mediacentre/factsheets/fs311/en/print.html.
    1. Blair NJ, Thompson JM, Black PN, Becroft DM, Clark PM, Han DY, Robinson E, Waldie KE, Wild CJ, Mitchell EA. Risk factors for obesity in 7-year-old European children the Auckland Birthweight Collaborative Study. Arch Dis Child. 2007;92:866–871. - PMC - PubMed
    1. National Health and Medical Research Council: Clinical practice guidelines for the management of overweight and obesity in children and adolescents Canberra, Commonwealth of Australia. 2003 www.health.gov.au/internet/main/publishing.nsf/Content/893169B10DD846FCC....

Publication types