Optimal cut-offs of five anthropometric indices and their predictive ability of type 2 diabetes in a nationally representative Kenyan study

Anthony Muchai Manyara; Anthony Muchai Manyara

doi:10.3934/publichealth.2021041

AIMS Public Health

2021, Volume 8, Issue 3: 507-518. doi: 10.3934/publichealth.2021041

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Research article

Optimal cut-offs of five anthropometric indices and their predictive ability of type 2 diabetes in a nationally representative Kenyan study

Anthony Muchai Manyara ^,

Social and Political Sciences, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK

Received: 06 May 2021 Accepted: 06 July 2021 Published: 09 July 2021

Background
Type 2 diabetes (T2D) is one of the top non-communicable diseases in Kenya and prevention strategies are urgently needed. Intervening to reduce obesity is the most common prevention strategy. However, black populations develop T2D at lower obesity levels and it is unclear which anthropometric cut-offs could provide the best predictive ability for T2D risk. This study, therefore, aimed to determine the optimal anthropometric cut-offs and their predictive ability of T2D in Kenya.

Methods
The study included 2159 participants (59% women) aged 35–70 years from the Kenya STEPwise survey conducted in 2014. Five anthropometric indices were used—body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR) and waist divided by height^0.5(WHt.5R). Diabetes was defined as a fasting blood glucose of ≥7.0 mmol/l or a previous diagnosis by a health worker. Optimal anthropometric cut-offs and their receiver operating characteristics, such as the area under the curve (AUC), were computed.

Results
Overall, the optimal cut-off for BMI, WC, WHR, WHtR and WHt.5R were 24.8 kg.m⁻², 90 cm, 0.88, 0.54 and 6.9. On disaggregation by sex, the optimal cut-off for BMI, WC, WHR WHtR and WHt.5R was 27.1 kg.m⁻², 87 cm, 0.85, 0.55 and 6.9 in women, and 24.8 kg.m⁻², 91 cm, 0.88, 0.54 and 6.9 in men. Overall, WC (AUC 0.71 (95% confidence interval 0.65, 0.76)) WHtR (AUC 0.71 (0.66, 0.76)) and WHt.5R (AUC 0.70 (0.65,0.75)) had a better predictive ability for T2D than BMI (AUC 0.68 (0.62, 0.73)).

Conclusions
WC, WHtR and WHt.5R were better predictors of T2D than BMI and should be used for risk stratification in Kenya. A WC cut-off of 87cm in women and 91cm in men, a WHtR cut-off of 0.54 or a WHt.5R of 6.9 in both men and women should be used to identify individuals at an elevated risk of T2D.
- diabetes,
- prediction,
- anthropometric cut-offs,
- Kenya,
- Africa,
- waist circumference,
- waist-to-height ratio
Citation: Anthony Muchai Manyara. Optimal cut-offs of five anthropometric indices and their predictive ability of type 2 diabetes in a nationally representative Kenyan study[J]. AIMS Public Health, 2021, 8(3): 507-518. doi: 10.3934/publichealth.2021041

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Abstract

Background

Type 2 diabetes (T2D) is one of the top non-communicable diseases in Kenya and prevention strategies are urgently needed. Intervening to reduce obesity is the most common prevention strategy. However, black populations develop T2D at lower obesity levels and it is unclear which anthropometric cut-offs could provide the best predictive ability for T2D risk. This study, therefore, aimed to determine the optimal anthropometric cut-offs and their predictive ability of T2D in Kenya.

Methods

The study included 2159 participants (59% women) aged 35–70 years from the Kenya STEPwise survey conducted in 2014. Five anthropometric indices were used—body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR) and waist divided by height^0.5(WHt.5R). Diabetes was defined as a fasting blood glucose of ≥7.0 mmol/l or a previous diagnosis by a health worker. Optimal anthropometric cut-offs and their receiver operating characteristics, such as the area under the curve (AUC), were computed.

Results

Overall, the optimal cut-off for BMI, WC, WHR, WHtR and WHt.5R were 24.8 kg.m⁻², 90 cm, 0.88, 0.54 and 6.9. On disaggregation by sex, the optimal cut-off for BMI, WC, WHR WHtR and WHt.5R was 27.1 kg.m⁻², 87 cm, 0.85, 0.55 and 6.9 in women, and 24.8 kg.m⁻², 91 cm, 0.88, 0.54 and 6.9 in men. Overall, WC (AUC 0.71 (95% confidence interval 0.65, 0.76)) WHtR (AUC 0.71 (0.66, 0.76)) and WHt.5R (AUC 0.70 (0.65,0.75)) had a better predictive ability for T2D than BMI (AUC 0.68 (0.62, 0.73)).

Conclusions

WC, WHtR and WHt.5R were better predictors of T2D than BMI and should be used for risk stratification in Kenya. A WC cut-off of 87cm in women and 91cm in men, a WHtR cut-off of 0.54 or a WHt.5R of 6.9 in both men and women should be used to identify individuals at an elevated risk of T2D.

Abbreviations

BMI

Body Mass Index

Waist Circumference

WHrR

Waist-to-Height Ratio

WHR

Waist-to-Hip Ratio

WHt.5R

waist divided by height^0.5

ROC

Receiver Operating Curve

T2D

Type 2 Diabetes

AUC

Area Under the Curve

SSA

Sub-Saharan Africa

Confidence Intervals

Standard Deviation

WHO

World Health Organisation

Acknowledgments

The authors would like to thank the three anonymous reviewers whose input improved the quality of this article. The views expressed are those of the authors and not necessarily those of the University of Glasgow.

Availability of data and materials

The Kenya STEPwise survey 2014 data can be assessed from the Kenya National Bureau of Statistics using this link: http://statistics.knbs.or.ke/nada/index.php/catalog/90.

Conflict of interest

The authors declare that they have no competing interests.

Authors' contributions

AMM conceptualised the study, analysed and interpreted the data, and drafted the manuscript.

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