Inequalities in paediatric obesity trends: challenges and opportunities
Authors: William Johnson
Journal: The Lancet Public Health (2021)

Changes in childhood body-mass index (BMI) trends and obesity rates over time have been well documented in many populations.1Abarca-Gómez L Abdeen ZA Hamid ZA et al.Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults.Lancet. 2017; 390: 2627-2642Summary Full Text Full Text PDF PubMed Scopus (2781) Google Scholar But less is known about inequality in secular trends. Using more than 1·3 million measurements from 675 991 children in Victoria (Australia), Melanie Nichols and colleagues2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar investigated how trends in 2003–17 differed according to socioeconomic status and remoteness. Mean BMI for all six age–sex groups (children aged 1, 2, and 3·5 years) decreased over time overall and in major cities, whereas in regional and remote areas (2·4% of the sample population), BMI showed an increasing secular trend across all socioeconomic strata. The study clearly shows how results for an entire population, such as Victoria, might mask important inequalities in paediatric obesity trends. In addition to finding differences in metropolitan versus regional and remote areas, inequalities according to socioeconomic status were also observed. The pattern of a higher BMI in more disadvantaged than advantaged groups, remained fairly consistent during the study period in all areas. Therefore, policy efforts to reduce inequalities in paediatric obesity rates have been unsuccessful according to these data. Even the secular declines in childhood BMI, overall and in major cities, are attributed by Nichols and colleagues2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar potentially to increases in migration as opposed to any specific government or non-government initiatives. Obesity has its roots in early life, and one of the novelties of this study is the focus on very young children. However, the use of BMI at the studied ages, for reasons that have been discussed extensively elsewhere,3Prentice AM Jebb SA Beyond body mass index.Obes Rev. 2001; 2: 141-147Crossref PubMed Scopus (801) Google Scholar should be questioned. Any investigation of secular trends in BMI should ideally also consider height separately, particularly if the participants are children. If height has remained stable over time, a stronger argument can be made that the reported trends in BMI reflect changes in weight (and potentially fat mass) more than height (and potentially fat-free mass). In regional and remote areas, Nichols and colleagues2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar found evidence that BMI had increased over time, largely because of a secular decline in height. It is a shame that these data are not shown because they might affect the interpretation of the findings. After birth, BMI increases to a peak at age 6–12 months, before declining to a nadir known as the adiposity rebound at age 5–7 years. This fact makes studying secular trends in BMI at age 1, 2, and 3·5 years difficult because the timing of the peak and rebound might have shifted over time.4Johnson W Choh AC Lee M Towne B Czerwinski SA Demerath EW Characterization of the infant BMI peak: sex differences, birth year cohort effects, association with concurrent adiposity, and heritability.Am J Hum Biol. 2013; 25: 378-388Crossref PubMed Scopus (27) Google Scholar, 5Johnson W Soloway LE Erickson D et al.A changing pattern of childhood BMI growth during the 20th century: 70 y of data from the Fels Longitudinal Study.Am J Clin Nutr. 2012; 95: 1136-1143Crossref PubMed Scopus (51) Google Scholar Similar to the way greater pre-pubertal height can reflect earlier puberty and not necessarily result in taller adults,6Prentice A Dibba B Sawo Y Cole TJ The effect of prepubertal calcium carbonate supplementation on the age of peak height velocity in Gambian adolescents.Am J Clin Nutr. 2012; 96: 1042-1050Crossref PubMed Scopus (40) Google Scholar trends in early childhood BMI can reflect changes in the timing of the peak and rebound, and can change (magnitude and even direction) at later ages.5Johnson W Soloway LE Erickson D et al.A changing pattern of childhood BMI growth during the 20th century: 70 y of data from the Fels Longitudinal Study.Am J Clin Nutr. 2012; 95: 1136-1143Crossref PubMed Scopus (51) Google Scholar This reason is why longitudinal data are so important in secular childhood BMI research. Although treated as being cross-sectional in their analysis, the data in Nichols and colleagues' study2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar were in fact longitudinal. Future research with this dataset could address some of these limitations by investigating weight gain and height growth separately. Such analyses could provide novel evidence on trends and inequalities in rapid infant weight gain, a key risk factor for obesity,7Zheng M Lamb KE Grimes C et al.Rapid weight gain during infancy and subsequent adiposity: a systematic review and meta-analysis of evidence.Obes Rev. 2018; 19: 321-332Crossref PubMed Scopus (119) Google Scholar particularly if it were possible to add in birthweight to the dataset via linkage to routine birth records. The fact that the paediatric obesity epidemic reflects a right-skewing of the BMI distribution is well accepted.8Johnson W Li L Kuh D Hardy R How has the age-related process of overweight or obesity development changed over time? Co-ordinated analyses of individual participant data from five United Kingdom birth cohorts.PLoS Med. 2015; 12e1001828Crossref PubMed Scopus (101) Google Scholar Therefore, the trends and inequalities in mean BMI reported by Nichols and colleagues2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar are likely to be smaller than those occurring at higher ends of the distribution (eg, 75th percentile), which has been shown in the UK.8Johnson W Li L Kuh D Hardy R How has the age-related process of overweight or obesity development changed over time? Co-ordinated analyses of individual participant data from five United Kingdom birth cohorts.PLoS Med. 2015; 12e1001828Crossref PubMed Scopus (101) Google Scholar, 9Bann D Johnson W Li L Kuh D Hardy R Socioeconomic inequalities in childhood and adolescent body-mass index, weight, and height from 1953 to 2015: an analysis of four longitudinal, observational, British birth cohort studies.Lancet Public Health. 2018; 3: e194-e203Summary Full Text Full Text PDF PubMed Scopus (83) Google Scholar The authors did investigate trends in the proportion of children with high BMI (eg, Z scores of >+2), and found a pattern of results similar to that for mean BMI. However, thinness (ie, low BMI) was not considered. This group is often neglected in secular trend and inequality research, despite arguably being just as important as the high BMI groups. The prevalence of childhood thinness is Australia is much lower than that of obesity,1Abarca-Gómez L Abdeen ZA Hamid ZA et al.Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults.Lancet. 2017; 390: 2627-2642Summary Full Text Full Text PDF PubMed Scopus (2781) Google Scholar but thinness should not be ignored for this reason. Indeed, large scale data, such as those in the study by Nichols and colleagues,2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar are needed to provide robust estimates of inequalities in childhood thinness trends. Data from the Non-Communicable Disease Risk Factor Collaboration have shown a higher prevalence of adulthood obesity in rural versus urban areas, and a greater increase in mean BMI between 1985 and 2017 in rural areas in some countries, including Australia.10NCD Risk Factor Collaboration (NCD-RisC)Rising rural body-mass index is the main driver of the global obesity epidemic in adults.Nature. 2019; 569: 260-264Crossref PubMed Scopus (226) Google Scholar Results from Nichols and colleagues' study2Nichols M Allender S Swinburn B Orellana L Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year cross-sectional study.Lancet Public Health. 2021; 6: e462-e471Google Scholar are in general agreement, but provide a more detailed picture focusing on early childhood and incorporating socioeconomic inequalities. Similar research for other countries using national or global data would be highly valuable. I declare no competing interests. WJ is supported by a UK Medical Research Council New Investigator Research Grant (MR/P023347/1) and acknowledges support from the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, a partnership between University Hospitals of Leicester NHS Trust, Loughborough University, and the University of Leicester. Inequalities in early childhood body-mass index Z scores in Victoria, Australia: a 15-year observational studyThis study showed that at a state level, mean BMIz and prevalence of high BMIz decreased in children aged 1, 2, and 3·5 years in Victoria between 2003 and 2017. We found metropolitan–regional differences to be key source of inequality in early childhood BMIz trends, alongside area-level socioeconomic status. These findings highlight the risk that analysis of overall trends in childhood BMIz might obscure important inequalities according to, for example, remoteness, socioeconomic status, and ethnicity. Full-Text PDF Open Access