8: Introduction to Anthropometry (Chapter 9)
- Page ID
- 116866
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Anthropometric measurements are used to assess body size and body composition. The measurements are simple, safe, and non-invasive and provide information on past exposure, but cannot detect short-term disturbances or deficiency of a specific nutrient. There are three major sources of error in anthropometry: (i) measurement errors, (ii) alterations in the composition and physical properties of certain tissues, and, (iii) use of invalid assumptions in the derivation of body composition from the measurements.
Anthropometric indices are derived from two or more raw measurements and are essential to interpret and group the anthropometric data. Selection of indices must take into account their sensitivity, specificity, predictive value, and any potential modifying factors.Examples of indices include weight-for-height, body mass index (weight kg) / (height m)2, and waist-hip circumference ratio. Anthropometric indices are often evaluated by comparison with predetermined reference limits or cutoff points. Calculation of the number and proportion of individuals (as %) with anthropometric indices below or above a designated reference limit or cutoff, generates “anthropometric indicators” that can be used in clinical and public health settings to classify individuals at risk of malnutrition. Examples of indicators used in this way include mid‑upper‑arm circumference (MUAC) with a cutoff < 115mm to identify severe acute malnutrition (SAM) in children 6–60mos, and WHZ < −2, BMIZ > +2, and HAZ < −2, used by WHO and UNICEF to define wasting, overweight, and stunting respectively in children < 5y and to define prevalence thresholds and identify priority countries. Cutoffs, unlike statistically derived reference limits, are based on functional impairment or clinical signs of malnutrition, and occasionally mortality.
The reference growth data recommended by WHO for international use are the prescriptive WHO Child Growth Standards for 0–5y, and the WHO growth reference data for older 5–19y. Updated childhood growth charts are also available for U.S. infants age 0–36mos and children 2–20y. Local reference data are preferred for body composition, although few are available. Instead, WHO recommends using reference data for MUAC, triceps, and subscapular skinfolds collected for the WHO Child Growth Standards.
The term “nutritional anthropometry” first appeared in “Body Measurements and Human Nutrition” (Brožek, 1956) and was later defined by Jelliffe (1966) as:
“measurements of the variations of the physical dimensions and the gross composition of the human body at different age levels and degrees of nutrition”
Subsequently, a number of publications made recommendations on specific body measurements for characterizing nutritional status, standardized measurement techniques, and suitable reference data (Jelliffe, 1966; WHO, 1968; Weiner and Lourie, 1969). Today, anthropometric measurements are widely used for the assessment of nutritional status and health, at both the individual and population levels. One of their main advantages is that anthropometric measurements may be related to past exposures, to present processes, or to future events (WHO, 1995).
For individuals in low-income countries, anthropometry is particularly useful when there is a chronic imbalance between intakes of energy, protein, and certain micronutrients. Such disturbances modify the patterns of physical growth and the relative proportions of body tissues such as fat, muscle, and total body water. For individuals in clinical settings, anthropometry can be used to diagnose failure to thrive in infants and young children, and monitor overweight and obesity in children and adults.
At the population level, anthropometry has an important role in targeting interventions through screening, in assessing the response to interventions, in identifying the determinants and consequences of malnutrition, and in conducting nutritional surveillance. Increasingly, anthropometry is also being used to characterize and compare the health and nutritional status of populations across countries (WHO/UNICEF, 2019).
- 8.1: Measurements, indices, and indicators
- This page discusses anthropometric measurements, including height, weight, and waist circumference, to assess body size, composition, and visceral fat. It emphasizes the distinction between fat mass and fat-free mass, incorporating muscle assessments. Indices like BMI are used to evaluate nutritional status and inform public health practices. The validity and suitability of these indicators, such as Z-scores, are essential for accurately identifying malnutrition risks in diverse populations.
- 8.2: Advantages and limitations of anthropometry
- This page discusses the significance of anthropometric measurements in nutritional assessment, highlighting their simplicity and cost-effectiveness in monitoring growth and body composition. While they may not effectively detect short-term nutritional issues or specific deficiencies, proper experimental design can mitigate the impact of non-nutritional factors on measurement accuracy.
- 8.3: Errors in anthropometry
- This page discusses the challenges in nutritional anthropometry, highlighting errors that impact measurement precision and validity, stemming from examiner training, equipment issues, and assumptions. It emphasizes the importance of training, standardization, and reliable measurement personnel. The text addresses method discrepancies, like the technical error of measurement (TEM) and the need for accurate data in surveillance studies.
- 8.4: Interpretation and evaluation of anthropometric data
- This page covers the significance of anthropometric indices for assessing nutritional status, malnutrition, and guiding interventions, considering factors like age, sex, and maternal characteristics. It details the development of growth standards influenced by WHO and CDC, the importance of including diverse populations, and the use of percentiles and Z-scores for classification.