Use of anthropometry in school-aged children and adolescents
This is a summary of a Field Exchange research summary that was included in issue 66. The original article was authored by Natasha Lelijveld
Natasha Lelijveld is a Senior Nutritionist at ENN.
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This article summarises the use of anthropometry to assess nutritional status in school-aged children and adolescents
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Being under- or over-nourished during childhood and adolescence is associated with adverse consequences. Across all age groups, anthropometry is used to assess nutritional status and subsequent health risks. However, there is a lack of evidence, clarity and standardisation on assessing and classifying malnutrition in school-aged children and adolescents.
In recent years, the importance of nutrition in school-aged children and adolescents has been recognised. Indicators for anaemia in adolescent girls are included in the Sustainable Development Goals and large global datasets have been utilised to summarise the prevalence of malnutrition in adolescents. Table 1 summarises the papers in which anthropometric data has been most comprehensively reported. These papers have included data for different age ranges and have defined thinness and overweight using different reference data with different cut-off values. This limits our understanding of global and national prevalence rates as well as our ability to compare between settings and understand trends.
Table 1: Summary of references and cut-offs used for school-aged children and adolescents
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WHO 2007 growth reference |
IOTF growth reference |
CDC growth reference |
WHO adult cut-off |
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Applicable age bracket |
5-19 years |
2-18 years |
2-18 years |
>18 years |
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Weight categories |
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Thin or underweight |
BAZ <-2 |
Equivalent to BMI <18.5 at 18 years |
BAZ <5th percentile |
BMI <18.5 |
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Normal weight |
BAZ -2 to +1 |
Equivalent to BMI 18.5 to <25 at 18 years |
BAZ ≥5th percentile to <85th percentile |
BMI 18.5 to <25 |
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Overweight |
BAZ >+1 |
Equivalent to BMI ≥25 at 18 years |
BAZ ≥85th percentile |
BMI ≥25
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Obesity |
BAZ >+2 |
Equivalent to BMI ≥30 at 18 years |
BAZ ≥95th percentile |
BMI ≥30 |
Abbreviations: BMI, body mass index (kg/m2); BAZ, BMI-for-age z-score; CDC, Centers for Disease Control; IOTF, International Obesity Task Force; WHO, World Health Organization.
The Benedict et al paper (2018) was the first demographic and health survey (DHS) report to use adolescent-specific definitions of thinness and overweight (based on the World Health Organization (WHO) 2007 reference). Usually, DHS uses adult thresholds to define thinness (body mass index (BMI) <18.5 kg/m2) and overweight (BMI >25 kg/m2) in adolescents 15-19 years of age. This tends to overestimate the prevalence of thinness and underestimate the prevalence of overweight. The WHO recommends defining thinness as BMI-for-age z-score <-2 and overweight as BMI-for-age z-score >+1, based on the WHO 2007 reference. This reference uses primary data from adolescents in the United States of America in the 1970s but is statistically adapted to reflect more international norms. The International Obesity Task Force (IOTF) reference uses data on children from six countries to align the thresholds for thinness and overweight to adult BMI cut-offs. Using the IOTF reference results in a greater prevalence of thinness and a lower prevalence of overweight than the WHO reference. Often IOTF thinness data is presented as “Grade 1 thinness” which is similar to a BMI z-score <-1.
The interchangeable use of the terms thinness and underweight in the literature often makes it unclear whether BMI or weight-for-age are being presented. As discussed in previous research, the different timing of the adolescent growth spurt and the impact of muscle development on the accuracy of references also adds to the complexity of using anthropometry in school-aged children and adolescents.
Overall, the papers highlighted in Table 2 show that for school-aged children and adolescents in low- and middle-income countries (LMICs):
- The prevalence of overweight was higher in girls than in boys
- Overweight prevalence was highest in the Middle East, ranging from 15% to 34%
- Less data was available for thinness, with almost no data for boys
- The highest prevalence of thinness was found for girls in South Asia (23%)
- The prevalence of obesity increased globally from 0.7% to 5.6% in girls and from 0.9% to 7.8% in boys between 1975 and 2016
- The prevalence of thinness decreased from 9.2% to 8.4% in girls and from 14.8% to 12.4% in boys over the same period
Table 2: Summary of recent papers presenting prevalence rates of global adolescent anthropometric status
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Author, date |
Data used |
Population and date of data |
Thinness definition |
Overweight definition |
Reference used |
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Akseer et al, 2017 |
Global Burden of Disease (GBD) 2013 and WHO Data Repository, Global School-based Student Health Survey (GSHS) |
10-24 years 186 countries 2009 to 2015 |
BMI-for-age Z <-2 |
BMI-for-age Z >+1 |
Not specified |
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Azzopardi et al, 2019 |
GBD – compiled secondary data |
10-24 years 195 countries 2016 |
Not reported
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BMI-for-age equivalent to BMI >25 at age 18 years (10-18 years) BMI ≥ 25 kg/m2 (19-24 years) |
IOTF |
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Benedict et al, 2018 |
Demographic and health surveys |
15-19 years 87 LMICs 2000 to 2017 |
BMI-for-age Z <-2 |
BMI-for-age Z >+1 |
WHO 2007 |
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Caleyachetty et al, 2018 |
GSHS and Health Behaviour in School-aged Children surveys |
12-15 years 57 LMICs 2003 to 2013 |
BMI-for-age z<-2 |
BMI-for-age z>+1 |
WHO 2007 |
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Spinelli et al, 2021 |
Childhood Obesity Surveillance Initiative |
6-10 years 36 European countries 2015 to 2017 |
BMI-for-age z<-2 |
BMI-for-age z>+1 |
WHO 2007 |
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Ng et al, 2014 |
GBD, 2013 - compiled secondary data |
5-19 years 188 countries 1980 to 2013 |
Not reported |
BMI-for-age equivalent to BMI>25 at age 18 years (some self-reported anthropometry included) |
IOTF |
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NCD Risk Factor Collaboration, 2017 |
Non-communicable Disease Risk Factor Collaboration database and WHO STEPS surveys |
5-19 years 200 countries 2016 |
BMI-for-age z<-2 |
BMI-for-age z>+1 |
WHO 2007 |
The increasing number of studies presenting prevalence data for malnutrition in school-aged children and adolescents is promising. However, differences in the age categories, reference data and the indicators used limit our understanding of their nutritional status. More data and greater standardisation of anthropometric indicators are needed to monitor trends, design solutions and set national and global targets.
For more information, please contact Natasha Lelijveld at natasha@ennonline.net.