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Updated: Oct 14, 2025

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Does adjusting for biological maturity when calculating child weight status improve the accuracy of predicting future
Fiona B Gillison1, Elisabeth B Grey2, Sean P Cumming2
1Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK. f.b.gillison@bath.ac.uk.
Background:
The aim of this study was to assess whether adjusting the weight categorisation of children for their biological maturity status could improve the accuracy of predicting weight status and cardiometabolic risk at age 17.
Methods:
Data from 1525 participants (787 female) from the ALSPAC study were analysed. Participants' weight status at age 11 was estimated using first standard chronological age and sex adjusted BMI cut-offs, and again using maturity adjusted BMI cut-offs. Each BMI category at age 11 was regressed against cardiometabolic risk score and BMI category at age 17, controlling for sex, ethnicity and socio-economic status.
Results:
At age 11 years, 22% of boys and 46% of girls who were categorised as overweight or having obesity based on chronological age were re-categorised into a lower BMI category after adjusting for biological maturity. Biologically adjusted BMI categories better predicted BMI category at age 17 compared with non-adjusted BMI categories (∆BIC = - 21.69); the odds of having obesity at age 17 were 18.28 times greater with each increase in BMI category at age 11. Adjusted and non-adjusted BMI status at 11 years showed equivalent accuracy in predicting cardiometabolic risk at age 17; the odds ratio of high cardiometabolic risk was 1.85, with heightened risk in boys, particularly early maturers.
Conclusion:
The traditional method of categorising adolescents into a BMI category may over-predict overweight and obesity, particularly in girls. Adjusting for biological maturity when estimating weight status through calculating adolescents' BMI classification was equivalent to standard approaches in predicting other cardiovascular risk at age 17.
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