Prevalence of low and high BMI during the first 3 years of life: using New Zealand national electronic health data.

Pediatr Obes

Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.

Published: May 2023

Background: Data on body mass index (BMI) in infants and toddlers worldwide are lacking, relative to older age groups.

Objectives: To describe the growth (weight, length/height, head circumference, and BMI z-score) of New Zealand children under the age of 3 years, and examine differences by sociodemographic characteristics (sex, ethnicity, and deprivation).

Methods: Electronic health data were collected by Whānau Āwhina Plunket, who provide free 'Well Child' services for approximately 85% of newborn babies in New Zealand. Data from children under the age of 3, who had their weight and length/height measured between 2017 and 2019, were included. The prevalence of BMI (WHO child growth standards) ≤2nd, ≥85th, and ≥95th percentiles were determined.

Results: Between 12 weeks and 27 months of age, the percentage of infants ≥85th BMI percentile increased from 10.8% (95% CI, 10.4%-11.2%) to 35.0% (34.2%-35.9%). The percentage of infants with high BMI (≥95th percentile) also increased, particularly between 6 months (6.4%; 95% CI, 6.0%-6.7%) and 27 months (16.4%; 15.8%-17.1%). By contrast, the percentage of infants with low BMI (≤2nd percentile) appeared steady between 6 weeks and 6 months, and declined at older ages. The prevalence of infants with a high BMI appears to increase substantially from 6 months across sociodemographic characteristics, with a widening prevalence gap by ethnicity occurring from 6 months, mirroring that of infants with a low BMI.

Conclusions: The number of children with high BMI increases rapidly between 6 months and 27 months of age, suggesting this is an important timeframe for monitoring and preventive action. Future work should investigate the longitudinal growth trajectories of these children to determine if any particular patterns predict later obesity and what strategies could effectively change them.

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http://dx.doi.org/10.1111/ijpo.13013DOI Listing

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