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01.12.2015 | Research article | Ausgabe 1/2016 Open Access

BMC Public Health 1/2016

Comparison of body mass index (BMI) with the CUN-BAE body adiposity estimator in the prediction of hypertension and type 2 diabetes

Zeitschrift:
BMC Public Health > Ausgabe 1/2016
Autoren:
Vicente Martín, Verónica Dávila-Batista, Jesús Castilla, Pere Godoy, Miguel Delgado-Rodríguez, Nuria Soldevila, Antonio J. Molina, Tania Fernandez-Villa, Jenaro Astray, Ady Castro, Fernando González-Candelas, José María Mayoral, José María Quintana, Angela Domínguez, CIBERESP Cases and Controls in Pandemic Influenza Working Group, Spain
Wichtige Hinweise

Competing interest

The authors declare that they have no competing interests

Authors’ contributions

VM directed the study; VM and VDB analysed the data and wrote the manuscript, AD JC PG NS MDR AJM TFV JA AC FGC JMM JMQ and the CIBERESP Working Group conceived, performed and designed the study; and AD JC PG NS MDR AJM TFV JA AC FGC JMM JMQ contributed to the supervision of the study and critical analysis of the article. All authors read and approved the final manuscript.

Abstract

Background

Obesity is a world-wide epidemic whose prevalence is underestimated by BMI measurements, but CUN-BAE (Clínica Universidad de Navarra - Body Adiposity Estimator) estimates the percentage of body fat (BF) while incorporating information on sex and age, thus giving a better match. Our aim is to compare the BMI and CUN-BAE in determining the population attributable fraction (AFp) for obesity as a cause of chronic diseases.

Methods

We calculated the Pearson correlation coefficient between BMI and CUN-BAE, the Kappa index and the internal validity of the BMI. The risks of arterial hypertension (AHT) and diabetes mellitus (DM) and the AFp for obesity were assessed using both the BMI and CUN-BAE.

Results

3888 white subjects were investigated. The overall correlation between BMI and CUN-BAE was R2 = 0.48, which improved when sex and age were taken into account (R2 > 0.90). The Kappa coefficient for diagnosis of obesity was low (28.7 %). The AFp was 50 % higher for DM and double for AHT when CUN-BAE was used.

Conclusions

The overall correlation between BMI and CUN-BAE was not good. The AFp of obesity for AHT and DM may be underestimated if assessed using the BMI, as may the prevalence of obesity when estimated from the percentage of BF.
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