Obesity and related cardiovascular diseases (CVD) present a pressing public health challenge, influenced by factors like hypertension, diabetes mellitus, and metabolic syndrome. Internationally, obesity is defined as abnormal or excessive fat accumulation that poses a health risk. Traditionally, Body Mass Index (BMI) has been used to gauge obesity in epidemiological settings. However, BMI’s reliability is questioned as it cannot distinguish between different types of mass like muscle or fat, leading to its limited use in accurately assessing CVD risk. This limitation has steered research toward more precise measures, such as the percentage of body fat, which better correlates with cardiovascular risk.
This Research Topic aims to refine and evaluate anthropometric measures to better predict cardiometabolic risks across various populations. Notwithstanding the broad use of BMI, its effectiveness varies significantly across ethnic groups due to genetic differences, particularly in sub-Saharan Africa where BMI fails to adequately represent cardiovascular risk. New approaches such as the "abdominometer," measuring abdominal height, have been posited to improve risk assessment in these populations. By focusing on measures that consider the location and type of fat, like waist circumference and waist-to-height ratio, this research seeks more accurate predictors of cardiometabolic diseases than BMI alone.
To gather further insights in the efficacy and applicability of anthropometric indices globally, we welcome articles addressing, but not limited to, the following themes:
-Comparison of BMI with other anthropometric indices in diverse ethnic groups
-Development and validation of the abdominometer for use in sub-Saharan populations
-The role of fat distribution in cardiometabolic disease risks
-Ethnic and phenotypic variations in cardiovascular anthropometry
-Establishing appropriate cut-off points for anthropometric measures in different populations
This Research Topic welcomes the submission of review articles, original research papers, brief communications, and meta-analyses to explore these critical aspects.
Obesity and related cardiovascular diseases (CVD) present a pressing public health challenge, influenced by factors like hypertension, diabetes mellitus, and metabolic syndrome. Internationally, obesity is defined as abnormal or excessive fat accumulation that poses a health risk. Traditionally, Body Mass Index (BMI) has been used to gauge obesity in epidemiological settings. However, BMI’s reliability is questioned as it cannot distinguish between different types of mass like muscle or fat, leading to its limited use in accurately assessing CVD risk. This limitation has steered research toward more precise measures, such as the percentage of body fat, which better correlates with cardiovascular risk.
This Research Topic aims to refine and evaluate anthropometric measures to better predict cardiometabolic risks across various populations. Notwithstanding the broad use of BMI, its effectiveness varies significantly across ethnic groups due to genetic differences, particularly in sub-Saharan Africa where BMI fails to adequately represent cardiovascular risk. New approaches such as the "abdominometer," measuring abdominal height, have been posited to improve risk assessment in these populations. By focusing on measures that consider the location and type of fat, like waist circumference and waist-to-height ratio, this research seeks more accurate predictors of cardiometabolic diseases than BMI alone.
To gather further insights in the efficacy and applicability of anthropometric indices globally, we welcome articles addressing, but not limited to, the following themes:
-Comparison of BMI with other anthropometric indices in diverse ethnic groups
-Development and validation of the abdominometer for use in sub-Saharan populations
-The role of fat distribution in cardiometabolic disease risks
-Ethnic and phenotypic variations in cardiovascular anthropometry
-Establishing appropriate cut-off points for anthropometric measures in different populations
This Research Topic welcomes the submission of review articles, original research papers, brief communications, and meta-analyses to explore these critical aspects.