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The cut-off values of anthropometric variables for predicting mild cognitive impairment in Malaysian older adults: a large population based cross-sectional study

Authors Won H, Abdul Manaf Z, Mat Ludin AF, Omar MA, Razali R, Shahar S

Received 4 August 2016

Accepted for publication 1 November 2016

Published 7 February 2017 Volume 2017:12 Pages 275—282

DOI https://doi.org/10.2147/CIA.S118942

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 2

Editor who approved publication: Dr Richard Walker


Huiloo Won,1 Zahara Abdul Manaf,2 Arimi Fitri Mat Ludin,3 Mohd Azahadi Omar,4 Rosdinom Razali,5 Suzana Shahar2

1Nutrition Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 2Dietetics Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 3Biomedical Science Program, School of Diagnostic and Applied Health Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 4Centre for Burden of Disease Research, Institute for Public Health, Ministry of Health Malaysia, 5Department of Psychiatry, Faculty of Medicine, Hospital Canselor Tuanku Muhriz, University Kebangsaan Malaysia, Kuala Lumpur, Malaysia

Purpose: Older adults are at risk of mild cognitive impairment (MCI), and simple anthropometric measurements can be used to screen for this condition. Thus, the aim of this study was to explore the cut-off values of body mass index (BMI) and waist circumference (WC) for predicting the risk of MCI in older Malaysian adults.
Methods: A total of 2,240 Malaysian older adults aged ≥60 years were recruited using multistage random sampling in a population based cross-sectional study. Receiver operating characteristic (ROC) curve was used to determine the cut-off values of BMI and WC with optimum sensitivity and specificity for the detection of MCI. Age, gender, years of education, smoking habit, alcohol consumption, depression, and medical conditions were used as confounding factors in this analysis.
Results: A BMI cut-off value of 26 kg/m2 (area under the receiver operating characteristic curve [AUC] 0.725; sensitivity 90.5%; specificity 38.8%) was appropriate in identifying the risk of getting MCI in both men and women. The optimum WC cut-offs for likelihood of MCI were 90 cm (AUC 0.745; sensitivity 78.0%; specificity 59.8%) for men and 82 cm (AUC 0.714; sensitivity 84.3%; specificity 49.7%) for women. The optimum calf circumference (CC) cut-off values for identifying MCI were 29 cm (AUC 0.731; sensitivity 72.6%; specificity 61.1%) for men and 26 cm (AUC 0.598; sensitivity 79.1%; specificity 45.3%) for women.
Conclusion: The cut-off values could be advocated and used as part of the screening of MCI among older Malaysian adults. There is a need to further determine the predictive values of these cut-off points on outcomes through longitudinal study design.

Keywords: body mass index, BMI, cut-off values, MCI, older adults, waist circumference, WC

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