International Journal of Cardiovascular Sciences. 11/jun/2025;38:e20240163.
Unconventional Anthropometric Indicators: Foundations, Applicability, and Validity as Predictors of Health Conditions
Haroldo da Silva Ferreira
, Antonio Fernando Silva Xavier Júnior
, Élison Ruan da Silva Almeida
, Tainá Cardoso Caminha-Uchôa
, Andressa Bruna Batista de Verçoza
, Hitalo de Moraes Vieira
Abstract
Several anthropometric parameters have been proposed as indicators of health conditions. Some have achieved wide acceptance and applicability. Others, although grounded in solid theoretical frameworks and demonstrating good diagnostic validity, have not gained the same level of recognition. These are referred to here as “unconventional anthropometric indicators”. This article aims to provide a descriptive and conceptual synthesis of these measures, addressing their nuances and applicability. It is a narrative review that discusses the following indicators: Head-to-height index (HHI), Waist-to-Height Ratio (WHtR), Conicity Index (C-Index), Waist-to-Hip Ratio (WHR), A Body Shape Index (ABSI), Neck Circumference (NC), and Adductor Pollicis Muscle Thickness (APMT). WHtR, C-Index, WHR, and ABSI are based on the identification of abdominal fat accumulation and its association with cardiometabolic risks. However, for this purpose, waist circumference stands out due to its methodological simplicity and predictive effectiveness. NC is an indicator of subcutaneous fat, whose excess increases disease risk and is not influenced by factors that alter abdominal volume. APMT identifies muscle depletion and is comparable to other anthropometric predictors of malnutrition risk. HHI was proposed to identify individuals who experienced undernutrition early in life. Grounded in a robust theoretical foundation, it is a promising tool for advancing research on the Developmental Origins of Health and Disease (DOHaD). The indicators analyzed are valuable for monitoring cardiometabolic risk factors, each with its unique characteristics. Understanding these particularities is essential for selecting the most appropriate indicators for different contexts, thus enabling more effective interventions.
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