Literature DB >> 32159675

Accuracy of BMI and waist circumference cut-off points to predict obesity in older adults.

Erika Aparecida Silveira1, Valéria Pagotto2, Larissa Silva Barbosa1, César de Oliveira3, Georgia das Graças Pena4, Gustavo Velasquez-Melendez5.   

Abstract

The main objectives were to analyse the validity and accuracy of Body Mass Index (BMI) and Waist Circumference (WC) to evaluate obesity by excess of body fat in older adults and to identify more adequate cut-off points for this age group. The recommended cut-off points for BMI (25, 27 or 30 kg/m2) and WC (≥ 102 cm for men and ≥ 88 cm for women or ≥ 90cm for men and ≥ 80 cm for women) were compared to the total body densitometry. BF was defined by a value higher than the 90th percentile. Out of the 132 participants, 61% were women and aged between 60 and 91 years. The recommended cut-off points of BMI ≥ 25kg/m2 and BMI ≥ 27 kg/m2 showed similar performances. BMI ≥ 30 kg/m2 showed high specificity but low sensitivity to identify BF in men and better performance in women. Conventional WC cut-off points showed low sensitivity and specificity. Based on our analyses, new cut-off points for BMI (25 kg/m2 for men and 26.6 kg/m2 for women) and WC (98.8 cm for men and 77.8cm for women) were proposed. The new cut-off points showed sensitivity and specificity values > 74% and accuracy > 76%. The areas under the curve (ROC) were > 0.86. The new BMI and WC cut-off points proposed in the present study for the diagnosis of obesity in older adults showed the best levels of sensitivity and specificity for this age group.

Entities:  

Year:  2018        PMID: 32159675     DOI: 10.1590/1413-81232020253.13762018

Source DB:  PubMed          Journal:  Cien Saude Colet        ISSN: 1413-8123


  4 in total

1.  Sarcopenia and mortality risk in community-dwelling Brazilian older adults.

Authors:  Cristina Camargo Pereira; Valéria Pagotto; Cesar de Oliveira; Erika Aparecida Silveira
Journal:  Sci Rep       Date:  2022-10-20       Impact factor: 4.996

2.  Body fat percentage assessment by skinfold equation, bioimpedance and densitometry in older adults.

Authors:  Erika Aparecida Silveira; Larissa Silva Barbosa; Ana Paula Santos Rodrigues; Matias Noll; Cesar De Oliveira
Journal:  Arch Public Health       Date:  2020-07-18

3.  Machine Learning Methods for Hypercholesterolemia Long-Term Risk Prediction.

Authors:  Elias Dritsas; Maria Trigka
Journal:  Sensors (Basel)       Date:  2022-07-18       Impact factor: 3.847

Review 4.  Differences in Classification Standards For the Prevalence of Overweight and Obesity in Children. A Systematic Review and Meta-Analysis.

Authors:  Francisco Llorca-Colomer; María Teresa Murillo-Llorente; María Ester Legidos-García; Alma Palau-Ferré; Marcelino Pérez-Bermejo
Journal:  Clin Epidemiol       Date:  2022-09-01       Impact factor: 5.814

  4 in total

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