Introduction to Anthropometry & Body Composition

Anthropometry literally means human measurements. It derives from the Greek words “anthropos” meaning “human”, and “metron” meaning “measure”. Anthropometric measurements are used to assess the size, proportions and composition of the human body.

Examples of anthropometric measurements

  1. Weight (or mass)
  2. Height
  3. Recumbent length
  4. Circumferences (head, waist, hip, mid-upper arm, mid-thigh, calf, chest, neck)
  5. Limb lengths (knee height, arm-span, demi-span, half-span)
  6. Abdominal sagittal diameter
  7. Skinfold thicknesses

Anthropometric measurements can be combined with each other or with other information to calculate anthropometric indices. These indices can be used to make inferences about body composition, growth and development.

Examples include body mass index (BMI), which adjusts weight for height to infer "fatness" or "thinness". Waist-to-hip ratio and waist-to-height ratio are used as to infer central distribution of body fat.

Examples of anthropometric indices

  1. BMI (weight/height2) (kg/m2)
  2. Waist-to-hip ratio
  3. Waist-to-height ratio
  4. Ponderal index (weight/height2) (kg/m2)
  5. Fat mass index (fat mass/height2) (kg/m2)
  6. Fat free mass index (lean mass/height2) (kg/m2)

Growth indices

Anthropometric measurements can be adjusted for non-anthropometric parameters (e.g. age and sex) to infer childhood growth and states of under or over-nutrition. These adjustments can be performed internally, using means and standard deviations from the study population at hand, or externally, by comparison against published growth reference data. The resulting values are expressed as percentiles or Z-scores (or standard deviation scores), which quantify the extent to which an individual deviates from the population average.

  1. BMI-for-age
  2. Height-for-age
  3. Length-for-age
  4. Weight-for-age
  5. Head circumference-for-age
  6. Arm circumference-for-age
  7. Subscapular skinfold-for-age
  8. Triceps skinfold-for-age
  9. Weight-for-height
  10. Weight-for-length

In epidemiological studies, anthropometry is often used to evaluate disease risk as well as assessing body composition changes. 

Anthropometric measurements can provide valuable information about health and development status, either as standalone or as combined measurements. For instance, waist circumference is often used as an indicator of central obesity, whereas changes in height or head circumference over time reflect rates of somatic growth.

Anthropometry can also be used to evaluate the nutritional status of an individual or a population, such as obesity resulting from over-nutrition or emaciation caused by malnutrition. Simple anthropometric measures are often implemented as proxy measures of overall and central fat in epidemiological studies.

Threshold values commonly used to indicate nutritional status

  1. Adult obesity (BMI ≥ 30.0 kg/m2)
  2. Adult overweight (BMI ≥ 25.0 kg/m2)
  3. Adult underweight (BMI < 18.5 kg/m2)

Note: in children, nutritional status is typically inferred by percentile thresholds

Specific characteristics of anthropometric methods will be discussed on specific pages, but they are generally:

  1. Easy-to-administer
  2. Require little or no expensive equipment
  3. Can be portable
  4. Non-invasive
  5. Applicable to the general population
  6. Suitable in resource constrained settings
  7. Simple
  8. Relatively low cost

These methods generally demonstrate good feasibility, but they do require:

  1. Training and standardisation to maximise accuracy and precision and minimise inter- and intra- observer measurement errors.
  2. Standardisation of measurement protocols within and between study sites is an essential component that ensures the data are comparable across observers and sites and over the course of a study.
  3. Quality control and quality assurance processes ensure that observers/field workers develop, refine, and maintain their techniques so that they yield repeatable and reproducible data. These processes involve review of study protocols, monitoring operators’ technical skills as well as assessing inter and intra - observer errors.

The estimation of body composition is an important component of health and fitness assessments in individuals and populations. In particular, the amount and distribution of fat and lean mass are important for health throughout the lifespan.

Levels of human body composition

Body composition can be studied at different levels of complexity (as shown in Figure A.1.1 and Table A.1.1):

  1. Atomic
  2. Molecular
  3. Cellular
  4. Functional/Tissue-Organ
  5. Whole body

Figure A.1.1 The five body composition levels.
Abbreviations: Extracellular solids (ECS) and extracellular fluid (ECF).
1Nitrogen and other elements
2Minerals, carbohydrates and other molecules
3Other tissues
Source: adapted from [11].

Table A.1.1 Examples of methods for measuring body composition by level.

Level Information obtained Examples of methods
Atomic Elemental: O, C, Ca, P, S, Cl, Na Whole body counting of total body potassium Neutron Activation analysis Isotope dilution
Molecular Water, protein, lipid, minerals and glycogen Isotope dilution, Magnetic Resonance Spectroscopy (MRS), multi-component models, Dual-Energy X-ray Absorptiometry (DEXA)
Cellular Fat, cell mass, extracellular fluids, extracellular solids Isotope dilution, Bioelectrical Impedance Analysis (BIA)
Functional /Tissue-organ Adipose, bone, muscle, organ Computer Tomography (CT), Magnetic Resonance Imaging (MRI), ultrasound, near Infrared Interactance, DEXA
Whole body Circumferences, linear dimensions, lengths, skinfolds, body volumes and body surface area Anthropometry, densitometry, Bioelectrical Impedance Analysis (BIA), 3D photonic scan

There is no single method that allows for the measurement of all tissues and organs, and no method is free from error. The ultimate method for assessment of body composition is chemical analysis of the human cadaver, which is clearly infeasible in most settings and there are no in vivo techniques that meet such high accuracy. Multi-component models (also known as multi-compartment models) are considered to be the reference method for the assessment of body composition (discriminating fat mass from fat free mass), and other methods are generally validated against these techniques.

When selecting a method, the following factors should be considered:

Research question and clinical application:

  1. Which body composition variables are to be quantified
  2. Clinical significance of these body composition compartments
  3. Desired level of accuracy and precision
  4. Validity of the method in the specific study population
  5. Availability of reference data for comparison

Feasibility and Resources:

  1. Number of participants and amount of time available
  2. Number and frequency of repeated measurements
  3. Level of participant burden and (dis)comfort
  4. Cost and availability of the equipment
  5. Staff skills, training and supervision

Assessment of body composition can use either direct methods, which provide output in the desired units (e.g. fat free mass in g), or indirect methods, which provide anthropometric parameters as proxy measures of body composition. As is the case for other anthropometric outcomes, body composition data can be combined with other data to derive indices (e.g. lean mass index).

The following methods can be used to directly, or indirectly, assess body composition. They are categorised according to their likely study location.

Field-based methods:

  1. Indirect anthropometric measurements and indices (e.g. circumferences,  skinfold thickness and BMI)
  2. Bioelectric impedance analysis

Laboratory (or clinic) based methods:

  1. Multicomponent models
  2. Hydrostatic underwater weighing
  3. Plethysmography (whole-body air-displacement)
  4. Hydrometry (isotope dilution) (can also be used in the field)
  5. Dual-energy X-ray absorptiometry (DEXA)
  6. Near infrared interactance (can also be used in the field)
  7. Whole body counting of total body potassium (TBK)
  8. 3D photonic scan
  9. Magnetic resonance imaging (MRI) / Magnetic resonance spectroscopy (MRS)
  10. Total body electrical conductivity (TOBEC)
  11. Computed tomography (CT)
  12. Ultrasonography (can also be used in the field)
  1. Cheikh Ismail L, Knight HE, Ohuma EO, Hoch L, Chumlea WC, International Fetal and Newborn Growth Consortium for the 21st Century International Fetal and Newborn Growth Consortium for the 21st Century, Anthropometric standardisation and quality control protocols for the construction of new, international, fetal and newborn growth standards: the INTERGROWTH-21st Project. BJOG : an international journal of obstetrics and gynaecology.2012;120 Suppl 2:48-55, v
  2. Després JP, Body fat distribution and risk of cardiovascular disease: an update. Circulation.2012;126:1301-13
  3. Duggan C, Watkins JB, Walker WA. Nutrition in Pediatrics. 4 ed. Shelton, CT: People's Medical Publishing House - USA; 2008.v
  4. Duren DL, Sherwood RJ, Czerwinski SA, Lee M, Choh AC, Siervogel RM, Cameron Chumlea W, Body composition methods: comparisons and interpretation. Journal of diabetes science and technology.2009;2:1139-46
  5. Ellis KJ, Human body composition: in vivo methods. Physiological reviews.2000;80:649-80
  6. Heymsfield SB, Ebbeling CB, Zheng J, Pietrobelli A, Strauss BJ, Silva AM, et al. Multi-component molecular-level body composition reference methods: evolving concepts and future directions. Obes Rev. 2015;16(4):282-94.
  7. Heymsfield SB, Lohman TG, Wang Z, Going SB. Human Body Composition. 2 ed. Champaign, IL: Human Kinetics; 2005.
  8. Johnson W, Wright J, Cameron N. The risk of obesity by assessing infant growth against the UK-WHO charts compared to the UK90 reference: findings from the Born in Bradford birth cohort study. BMC Pediatr. 2012;12:104.
  9. Lee J-W, Lim N-K, Baek T-H, Park S-H, Park H-Y. Anthropometric indices as predictors of hypertension among men and women aged 40–69 years in the Korean population: the Korean Genome and Epidemiology Study. BMC Public Health. 2015;15(1):140.
  10. Lin WY, Lee LT, Chen CY, Lo H, Hsia HH, Liu IL, et al. Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. Int J Obes Relat Metab Disord. 2002;26(9):1232-8.
  11. Lefkowitz RJ, Identification of adenylate cyclase-coupled beta-adrenergic receptors with radiolabeled beta-adrenergic antagonists. Biochemical pharmacology.1975;24:1651-8
  12. Wells JC, Fewtrell MS. Measuring body composition. Arch Dis Child. 2006;91(7):612-7.
  13. WHO Expert Committee. Physical status: The use and interpretation of anthropometry Geneva, Switzerland: World Health Organization; 1995 [5th December 2016]. Available from:
  14. Woodruff BA, Bornemisza O, Checchi F, Sondorp E. The use of epidemiological tools in conflict-affected populations: open-access educational resources for policy-makers: London School of Hygiene and Tropical Medicine; 2009 [5th December 2016]. Available from:
  15. Woodruff BA, Duffield A. Assessment of Nutritional Status in Emergency-Affected Populations - Adolescents Switzerland: United Nations; 2000 [5th December 2016]. Available from:
  16. World Health Organization. The WHO Child Growth Standards - Weight-for-age: World Health Organization,; 2016 [cited 2016 5th December]. Available from:
  17. World Health Organization. Global Database on Child Growth and Malnutrition: World Health Organization,; 2016 [5th December 2016]. Available from: