Cebu City- The most important anthropometric factors to consider when determining the nutritional status of a population are weight, sex, and age. It is important to ascertain if the collected and recorded information can deliver accurate information. For policymakers, program administrators, academics, and campaigners, the accuracy of anthropometric data is crucial and should be a well-supported source of evidence. 

When evaluating the efficacy of health and nutrition programs and as a reference for future plans and interventions, the quality of anthropometric data is also crucial. High-quality data can yield better knowledge, a strong basis for decision-making, and the right info on the health of the population under scrutiny. The validity of anthropometric data can be impacted positively or negatively by a number of variables including age estimation and the child’s date of birth which often are the two common sources of data errors.

Improper techniques or procedures in conducting anthropometric measurement is also one of the human errors that could result in poor data quality While using uncalibrated, unstandardized, and unvalidated equipment is also one of the big factors in the poor results.

These human-made errors related to equipment can be easily corrected. See a series of Things to remember in taking anthropometric measurements the tips and guidelines to follow in order to ensure good quality data. Furthermore, it is also presented in the OPT plus flowchart of activities that preparing and establishing  an OPT plus team is one of the keys that could guarantee good quality data. // DMOII Christine Lopez, RND