An Integrative Review of Anthropometric

Measurements in Primary Care

May Fakhiriyazdi, BSN, RN, MSN-FNP Student, Christina DeJesus, MSN-FNP, Alicia Akamine, MSN-FNP

University of Southern California

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Objectives:

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• Describe limitations with the use of BMI in regards to gender disparity.
• Discuss limitations in the use of BMI in relation to ethnicity and race disparities.
• Present accurate and feasible alternative anthropometric equations for clinical practice in the classification of fat-defined obesity and prediction of obesity related health risks.

ID#S-296

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Purpose

The purpose of this integrative review is to examine and compare the effectiveness of body mass index (BMI) to alternative anthropometric equations in accurately predicting fat-defined obesity and obesity related health risks among ethnically diverse adult women.

Methods

Systematic searches were conducted using the databases: PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Key terms used included: overweight, obesity, moderate obesity, abdominal obesity, relative fat index, RFI, RFM, relative fat mass, body fat estimator, relative fat calculation, relative body fat, adipose tissue distribution, body fat percentage, height waist ratio, anthropometric measurement, BMI, body mass index, and body mass composition.

Search was limited to articles published after 2014 and those including subjects over the age of 18, in the english language.

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Results and Implications

BMI lends to the misclassification of obesity in women.

BMI Incongruencies in turn impact the patient’s self-perception as well as scue targeted dietary and obesity interventions (Gaba, et. al. 2016)

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In women, BMI has a specificity of 99 percent and a sensitivity of 52 percent in the detection of body fat percentage.

The use of relative fat mass (RFM) demonstrated significantly higher overall accuracy and precision and had a more linear relationship with body fat percentage when compared to body mass index (BMI) in both men and women (Woolcott & Bergman, 2018).

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Sensitivity and specificity of BMI fluctuates based on the covariates of gender, age, and ethnicity.

References

Chang, C., Chen, C., Guo, F., Hung, S., & Jan, C. (2016). Combine body mass index and body fat percentage measures to improve the accuracy of obesity screening in young adults. Obesity Research & Clinical Practice, 11 : 11-18. doi: 10.1016/j.orcp.2016.02.005.

Chui, K., Deuster, P. A., McKeown, N. M., Must, A., & Shams-White, M. M. (2020). Comparison of anthropometric measures in US military personnel in the classification of overweight and obesity. Obesity, 28 (2): 362-370. doi: 10.1002/oby.22675

Keenan, C. (2018, April 18). Assessing and addressing bias in systematic reviews - Meta-Evidence. Retrieved March 21, 2020, from

Lawal, Y., Bello, F., Anumah, F., & Bakari, A. (2019). Waist-height ratio: How well does it predict glucose intolerance and systemic hypertension? Diabetes Research and Clinical Practice, 158, 107925. DOI: 10.1016/j.diabres.2019.107925

Liu, X., Shi, Z., Wang, Y., Wei, J., & Xue, H. (2019). Comparisons of visceral adiposity index, body shape index, body mass index and waist circumference and their associations with diabetes mellitus in adults. Nutrients, 11 (7): 1580. doi: 10.3390/nu11071580

Liu, L., Wang, Y., Zhang, W., Chang, W., Jin, Y., & Yao, Y. (2019). Waist height ratio predicts chronic kidney disease: a systematic review and meta-analysis, 1998–2019. Archives of Public Health, 77(1). DOI: 10.1186/s13690-019-0379-4 http://meta-evidence.co.uk/assessing-and-addressing-bias-in-systematic-reviews/

Nevill, A M., Stewart, A, D., Olds, T., & Duncan, M, J., (2020) A new waist-to-height ratio predicts abdominal adiposity in adults, Research in Sports Medicine, 28:1, 15-26, DOI: 10.1080/15438627.2018.1502183

Nickerson, B., McLester, C.N., McLester, J.R., Kliszczewicz, B.M. (2019) Relative accuracy of 14 anthropometric-based body fat equations in males and females with varying BMI classifications. Clinical nutrition ESPEN, 35: 136 - 140.

Paek, J.K., Kim, J., Kim, K., Lee, S.Y. (2019) Usefulness of relative fat mass in estimating body adiposity in Korean adult population. Endocrine Journal, 66(8) : 723- 729. DOI: 10.1507/endocrj.EJ19-0064

Woolcott, O. & Bergman, R.N. Relative fat mass (RFM) as a new estimator of whole-body fat percentage - A cross sectional study in American adult individuals. (2018). ScientificReports, 8 . DOI:10.1038/s41598-018-29362-1

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