A New Index to Replace Body Mass Index (BMI) as an Indicator of Fat Mass
Objective: Body Mass Index (BMI) has long served as the standard metric for classifying obesity, estimating fat mass, and assessing related health risks. However, BMI's limitations in accurately reflecting fat distribution and predicting individual health outcomes have become increasingly apparent, especially regarding gender differences, cultural variations, and athletic body types. This research aims to develop a novel index that addresses some of BMI’s limitations by incorporating body shape alongside overall body size. The main objective of this thesis was to investigate the contribution of anthropometric measures to estimating fat mass. A secondary objective was to evaluate the effectiveness of a novel index for estimating fat mass across different subgroups defined by sex and ethnicity. Methodology: A cross-sectional observational design was used, sampling adults from New Zealand across the four primary ethnic categories: Māori, European, Asian, and Pacific Islander. A total of 99 participants (49 males and 50 females) aged between 18 and 83 years were included. The measurements collected from participants included weight, height, waist/hip circumference, and eight skinfold sites. Body fat percentage (%BF) was estimated using validated bio-impedance equipment (Tanita BC420MA). Pearson’s correlation coefficients (r) were calculated to quantify the relationships between %BF and BMI, and %BF and the new Bodyfat Distribution Index (BDI), in order to compare their predictive accuracy of %BF. Linear regression analysis was performed to assess the relationship between %BF and both BMI and BDI, with comparisons across gender and ethnicity to assess their predictive ability to distinguish between the groups. Results: BDI accounted for 60% of the variability in %BF, compared to BMI, which accounted for 45%. Utilizing BDI Females still have greater scores than males for the same %BF, but the sex differences are markedly less than for BMI. Conclusion: The BDI, a simple novel index, provided a more comprehensive estimate of %BF than BMI, successfully addressing some of BMI’s key limitations, offering improved differentiation between genders, and partially accounting for ethnic variations. Future Direction: This study underscores the potential benefits of a simple new index to improve health assessments, interventions, and outcomes, particularly in New Zealand’s urban and remote rural populations, where access to advanced medical facilities may be limited. By leveraging mobile technology, such as smartwatches and smartphones, a simple novel index focusing on fat mass distribution could offer a more accurate measure of body composition. If digitized into an app, this novel index could improve accessibility and enable more effective, personalized health strategies and outcomes. This approach to estimating %BF may help reduce the stigma associated with BMI classifications, fostering a more nuanced understanding of health.
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