Introduction
Anthropometric measurements are a series of quantitative measurements of the muscle, bone, and adipose tissue used to assess the composition of the body. Anthropometric values are closely related to nutrition, genetic makeup, environmental characteristics, social and cultural conditions, lifestyle, functionsl status, and health.
Some questions regarding Anthropometry are given below.
- How is the age calculated in anthro software?
Age is calculated in anthro software by entering the date of birth and date of visit in the given assigned area. When the user opens a new record for data-entry, date of visit (DoV) is displayed as the current date. Then the user is asked to enter the child’s exact date of birth (DoB). There are 2 ways of entering the date; either by typing it in or selecting a date through the calendar window.
The software then uses DoB and DoV to derive age in completed months as well as age in days and displays this information for the user to double check. For the calculation of age in months at the time of leap year, 365.25 is divided by 12. So one month is equal to 30.44 days.
The age of the child is very much important to calculate the indicators like height for age and weight for age if age is not collected at the time of data collection these indicators are hard to derive.
- For which age group is anthro and anthro plus software used? Where is the child categories oedema?
Anthro software is used to calculate the age of children from 0 to 5 years of age and anthro plus software is used to calculate the age of children from 5 to 19.
- What are the indicators used in the software to assess nutritional status?
The indicators used in the software to assess nutritional status are
- Weight for length
- Weight for height
- BMI for age
- Length/height for age
- Weight for age
- Give the color codes and the numeric range for the standard classification of malnutrition?
The color codes and the numeric range for the standard classification of malnutrition are given below:
| Color | z-scores | Degree of malnutrition |
| Green | ≥ -1 and ≤+1 SD
Median |
Normal |
| Gold | ≥ -2 and <-1 SD;
or >+1 and ≤+2 SD |
Mild undernutrition
Or mild overnutrition |
| Red | ≥-3 and <-2 SD;
or >+2 and ≤+3 SD |
Moderate under or
Moderate overnutrition |
| Black | < -3
or
> +3 SD
|
Severely undernutrition
or severely overnutrition
|
- Green code is for the normal nutrition status that is the z score must be in between the S.D range of ≥ -2 and <-1 SD.
- Yellow/gold color code for mild malnutrition, if the standard deviation is between ≥ -2 and <-1 SD it can be interpreted as mild undernutrition and if it is between >+1 and ≤+2 SD it can be interpreted as mild over nutrition.
- The red color code indicates a moderate malnutrition status. When the standard deviation is between the range of ≥-3 and <-2 SD the nutritional condition can be interpreted as moderate undernutrition and if the standard deviation range is between >+2 and ≤+3 SD then it is moderate over nutrition.
- The black color code indicates severe malnutrition status. When the standard deviation is >-3SD the nutritional condition can be interpreted as severe undernutrition and if the standard deviation is >+3SD then it is severe over nutrition.
- Give the categories to access the severity of population prevalence of undernutrition.
The categories to access the severity of population prevalence of undernutrition is:
- Weight-for-age, length/height-for-age and Weight-for-length/height must be <-3 SD.
- Describe MGRS
MGRS is Multicenter Growth Reference Study which was designed to generate new growth curves for assessing the growth and development of infants and young children around the world, it provides data that describe “how children should grow” by including in the study’s selection criteria specific health behaviors that are consistent with current health promotion recommendations.
Another key characteristic of the new standard is that it makes breastfeeding the biological nom and establishes the breastfed infant as the normative growth model.
Reference
- Sánchez-García, S., García-Peña, C., Duque-López, M. X., Juárez-Cedillo, T., Cortés-Núñez, A. R., & Reyes-Beaman, S. (2007). Anthropometric measures and nutritional status in a healthy elderly population. BMC public health, 7, 2. doi:10.1186/1471-2458-7-2
- https://www.who.int/childgrowth/mgrs/en/
- Casadei K, Kiel J. Anthropometric Measurement. [Updated 2019 Mar 24]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2019 Jan-
- https://www.who.int/growthref/tools/who_anthroplus_manual.pdf