Figures & data
Table 1 Characteristics of included studies
Table 2 Summary of optimal exposure cutoffs from cross-sectional studies
Figure 2 Forest plot for discrimination of diabetes mellitus in cross-sectional studies with optimal BMI and WHtR cutoffs.
![Figure 2 Forest plot for discrimination of diabetes mellitus in cross-sectional studies with optimal BMI and WHtR cutoffs.](/cms/asset/68b660bd-4743-4eff-ac59-fe07594fa5c1/dmso_a_34220_f0002_b.jpg)
Figure 3 Forest plot for discrimination of dyslipidemia in cross-sectional studies with optimal BMI and WHtR cutoffs.
![Figure 3 Forest plot for discrimination of dyslipidemia in cross-sectional studies with optimal BMI and WHtR cutoffs.](/cms/asset/ea840820-8251-4ad5-b746-493db8172dc3/dmso_a_34220_f0003_b.jpg)
Figure 4 Forest plot for discrimination of elevated blood pressure in cross-sectional studies with optimal BMI and WHtR cutoffs.
![Figure 4 Forest plot for discrimination of elevated blood pressure in cross-sectional studies with optimal BMI and WHtR cutoffs.](/cms/asset/e0a541f1-5e99-4a0d-936d-e1c844d9ec18/dmso_a_34220_f0004_b.jpg)
Figure 5 Forest plot for discrimination of metabolic syndrome in cross-sectional studies with optimal BMI and WHtR cutoffs.
![Figure 5 Forest plot for discrimination of metabolic syndrome in cross-sectional studies with optimal BMI and WHtR cutoffs.](/cms/asset/b2596d48-82b3-444c-b35c-9f9936c815e0/dmso_a_34220_f0005_b.jpg)
Figure 6 Forest plot for discrimination of incident diabetes mellitus, incident CVD, CVD mortality, and all-cause mortality in prospective studies with BMI and WHtR.
![Figure 6 Forest plot for discrimination of incident diabetes mellitus, incident CVD, CVD mortality, and all-cause mortality in prospective studies with BMI and WHtR.](/cms/asset/3b776d06-3485-42c8-ae2e-8fb20431eb1a/dmso_a_34220_f0006_b.jpg)
Table 3 Study heterogeneity and publication biases
Table S1 Quality assessment of prospective studies based on the Newcastle-Ottawa scale
Table S2 Quality assessment of cross-sectional studies
Table S3 Random effects meta-regression analysis for cross-sectional studies using predefined study covariates