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. 2024 May 10;19(5):e0300221.
doi: 10.1371/journal.pone.0300221. eCollection 2024.

Children and young people's body mass index measures derived from routine data sources: A national data linkage study in Wales

Lucy J Griffiths  1 , James Rafferty  1 , Richard Fry  1 , Helen Daniels  1 , Carol Dezateux  2 , Nicola Firman  2 , Theodora Pouliou  1 , Gareth Stratton  3 , Amy Mizen  1 , Ronan A Lyons  1 , Alan Watkins  1 , Jo Davies  1 , Rowena Bailey  1
Affiliations

Children and young people's body mass index measures derived from routine data sources: A national data linkage study in Wales

Lucy J Griffiths et al. PLoS One. .

Abstract

Background: Routine monitoring of Body Mass Index (BMI) in general practice, and via national surveillance programmes, is essential for the identification, prevention, and management of unhealthy childhood weight. We examined and compared the presence and representativeness of children and young people's (CYPs) BMI recorded in two routinely collected administrative datasets: general practice electronic health records (GP-BMI) and the Child Measurement Programme for Wales (CMP-BMI), which measures height and weight in 4-5-year-old school children. We also assessed the feasibility of combining GP-BMI and CMP-BMI data for longitudinal analyses.

Methods: We accessed de-identified population-level GP-BMI data for calendar years 2011 to 2019 for 246,817 CYP, and CMP-BMI measures for 222,772 CYP, held within the Secure Anonymised Information Linkage Databank. We examined the proportion of CYP in Wales with at least one GP-BMI record, its distribution by child socio-demographic characteristics, and trends over time. We compared GP-BMI and CMP-BMI distributions. We quantified the proportion of children with a CMP-BMI measure and a follow-up GP-BMI recorded at an older age and explored the representativeness of these measures.

Results: We identified a GP-BMI record in 246,817 (41%) CYP, present in a higher proportion of females (54.2%), infants (20.7%) and adolescents. There was no difference in the deprivation profile of those with a GP-BMI measurement. 31,521 CYP with a CMP-BMI had at least one follow-up GP-BMI; those with a CMP-BMI considered underweight or very overweight were 87% and 70% more likely to have at least one follow-up GP-BMI record respectively compared to those with a healthy weight, as were males and CYP living in the most deprived areas of Wales.

Conclusions: Records of childhood weight status extracted from general practice are not representative of the population and are biased with respect to weight status. Linkage of information from the national programme to GP records has the potential to enhance discussions around healthy weight at the point of care but does not provide a representative estimate of population level weight trajectories, essential to provide insights into factors determining a healthy weight gain across the early life course. A second CMP measurement is required in Wales.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
GP-BMI data cohort (a) and CMP and GP-BMI data cohort (b).
Fig 2
Fig 2. QQ plot comparing distribution of z-scores in the CMP (x-axis) and in primary care (y-axis).
Fig 3
Fig 3. BMI measurements and primary care follow-up.
Fig 4
Fig 4. The number of follow-ups in primary care by deprivation and age.
Each colour represents a different deprivation quintile, with quintile 1 being the most deprived and quintile 5 being the least deprived.
See this image and copyright information in PMC

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