Abstract
Introduction: Prediabetes is a significant public health concern due to its high risk of progressing to diabetes. Anthropometric measures of obesity, including body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) have been demonstrated as key risk factors in the development of prediabetes. However, there is a lack of clarity on the diagnostic accuracy and cut-off points of these measures. Objective: To determine the diagnostic accuracy of these anthropometric measures for their most effective use in identifying prediabetes. Methodology: A systematic review (SR) with metanalysis of observational studies was carried out. The search was conducted in four databases: Pubmed/Medline, SCOPUS, Web of Science, and EMBASE. For the meta-analysis, sensitivity and specificity, together with their 95% confidence intervals (CI 95%) were calculated. Results: Among all the manuscripts chosen for review, we had four cross-sectional studies, and three were classified as cohort studies. The forest plots showed the combined sensitivity and specificity for both cross-sectional and cohort studies. For cross-sectional studies, the values were as follows: BMI had a sensitivity of 0.63 and specificity of 0.56, WC had a sensitivity of 0.59 and specificity of 0.58, and WHtR had a sensitivity of 0.63 and specificity of 0.73. In the cohort studies, the combined sensitivity and specificity were: BMI at 0.70 and 0.45, WC at 0.68 and 0.56, and WHtR at 0.68 and 0.56, respectively. All values are provided with 95% confidence intervals. Conclusions: This systematic review and meta-analysis evaluated the diagnostic accuracy of BMI, WC, and WHtR in identifying prediabetes. The results showed variations in sensitivity and specificity, with WHtR having the highest specificity in cross-sectional studies and BMI having improved sensitivity in cohort studies.
| Original language | American English |
|---|---|
| Pages (from-to) | 115-125 |
| Number of pages | 11 |
| Journal | International Journal of Statistics in Medical Research |
| Volume | 12 |
| DOIs | |
| State | Indexed - 2023 |
Bibliographical note
Publisher Copyright:© (2023). All Rights Reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Prediabetic state
- body mass index
- body weights and measures
- sensitivity and specificity (source: MeSH NLM)
- waist circumference
- waist-height ratio
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