Anil Sirisena, B. Okeahialam, E. Ike, D. Pam, J. Barki
{"title":"Abdominometer: A novel instrument to determine the level of risk for cardiometabolic diseases","authors":"Anil Sirisena, B. Okeahialam, E. Ike, D. Pam, J. Barki","doi":"10.4103/njc.njc_20_17","DOIUrl":null,"url":null,"abstract":"Background: The standard measure for classifying obesity, the body mass index (BMI) has been found to be deficient in some populations, Sub-Saharan Africans inclusive. Until recently, waist-to-height ratio (WHtR) was considered an improvement in this regard. Abdominal height (AH) measured with a novel appliance was recently found to be a superior cardiac anthropometric measure in our population; hence, there is a need to correlate it mathematically with the older indices. Objective: To determine a mathematical formula that permits computation of AH from BMI and WHtR. Methodology: A total of 200 randomly selected consenting young adult Nigerians (100 males and 100 females) between the ages 16 and 44 years who were undergoing preadmission medical examinations in a higher educational institution participated in this study. Height and weight were measured to determine BMI; waist and hip circumferences were measured and waist-to-hip ratio and WHtR computed. Results: Correlations between two anthropometric indices, BMI, and WHtR with AH were determined, and linear relationships were established using regression analysis to compute the AH using BMI and WHtR (P < 0.01). Reference levels of AH for low risk, increased risk, substantially increased risk, and severe risk were established. From this study, AH for severe risk level was found to be >32 cm and 30 cm by BMI and WHtR classifications, respectively. Conclusion: Where there is no abdominometer to measure AH, it is possible from BMI and WHtR to determine AH; which has been shown to predict cardiometabolic diseases better in our population.","PeriodicalId":228906,"journal":{"name":"Nigerian Journal of Cardiology","volume":"379 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nigerian Journal of Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/njc.njc_20_17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Background: The standard measure for classifying obesity, the body mass index (BMI) has been found to be deficient in some populations, Sub-Saharan Africans inclusive. Until recently, waist-to-height ratio (WHtR) was considered an improvement in this regard. Abdominal height (AH) measured with a novel appliance was recently found to be a superior cardiac anthropometric measure in our population; hence, there is a need to correlate it mathematically with the older indices. Objective: To determine a mathematical formula that permits computation of AH from BMI and WHtR. Methodology: A total of 200 randomly selected consenting young adult Nigerians (100 males and 100 females) between the ages 16 and 44 years who were undergoing preadmission medical examinations in a higher educational institution participated in this study. Height and weight were measured to determine BMI; waist and hip circumferences were measured and waist-to-hip ratio and WHtR computed. Results: Correlations between two anthropometric indices, BMI, and WHtR with AH were determined, and linear relationships were established using regression analysis to compute the AH using BMI and WHtR (P < 0.01). Reference levels of AH for low risk, increased risk, substantially increased risk, and severe risk were established. From this study, AH for severe risk level was found to be >32 cm and 30 cm by BMI and WHtR classifications, respectively. Conclusion: Where there is no abdominometer to measure AH, it is possible from BMI and WHtR to determine AH; which has been shown to predict cardiometabolic diseases better in our population.