Predicting cardiometabolic risk: waist-to-height ratio or BMI. A meta-analysis

Savvas C Savva,1 Demetris Lamnisos,2 Anthony Kafatos3 1Research and Education Institute of Child Health, Strovolos, Cyprus; 2Department of Nursing, School of Health Sciences, Cyprus University of Technology, Limassol, Cyprus; 3Preventive Medicine and Nutrition Unit, School of Medicine, University of...

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Autores principales: Savva SC, Lamnisos D, Kafatos AG
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2013
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Acceso en línea:https://doaj.org/article/f265d80342074bb1a799c6fde4494666
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Sumario:Savvas C Savva,1 Demetris Lamnisos,2 Anthony Kafatos3 1Research and Education Institute of Child Health, Strovolos, Cyprus; 2Department of Nursing, School of Health Sciences, Cyprus University of Technology, Limassol, Cyprus; 3Preventive Medicine and Nutrition Unit, School of Medicine, University of Crete, Heraklion, Crete, Greece Background and objectives: The identification of increased cardiometabolic risk among asymptomatic individuals remains a huge challenge. The aim of this meta-analysis was to compare the association of body mass index (BMI), which is an index of general obesity, and waist-to-height ratio (WHtR), an index of abdominal obesity, with cardiometabolic risk in cross-sectional and prospective studies. Methods: PubMed and Embase databases were searched for cross-sectional or prospective studies that evaluated the association of both BMI and WHtR with several cardiometabolic outcomes. The strength of relative risk (RR) with 95% confidence interval (CI) was calculated using the optimal cutoffs of BMI and WHtR in cross-sectional studies, while any available cutoff was used in prospective studies. The pooled estimate of the ratio of RRs (rRR [=RRBMI/RRWHtR]) with 95% CIs was used to compare the association of WHtR and BMI with cardiometabolic risk. Meta-regression was used to identify possible sources of heterogeneity between the studies. Results: Twenty-four cross-sectional studies and ten prospective studies with a total number of 512,809 participants were identified as suitable for the purpose of this meta-analysis. WHtR was found to have a stronger association than BMI with diabetes mellitus (rRR: 0.71, 95% CI: 0.59–0.84) and metabolic syndrome (rRR: 0.92, 95% CI: 0.89–0.96) in cross-sectional studies. Also in prospective studies, WHtR appears to be superior to BMI in detecting several outcomes, including incident cardiovascular disease, cardiovascular disease mortality, and all-cause mortality. The usefulness of WHtR appears to be better in Asian than in non-Asian populations. BMI was not superior to WHtR in any of the outcomes that were evaluated. However, the results of the utilized approach should be interpreted cautiously because of a substantial heterogeneity between the results of the studies. Meta-regression analysis was performed to explain this heterogeneity, but none of the evaluated factors, ie, sex, origin (Asians, non-Asians), and optimal BMI or WHtR cutoffs were significantly related with rRR. Conclusion: The results of this meta-analysis support the use of WHtR in identifying adults at increased cardiometabolic risk. However, further evidence is warranted because of a substantial heterogeneity between the studies. Keywords: body mass index, waist-to-height ratio, meta-analysis, cardiometabolic