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

Savva, Savvas C.; Lamnisos, Demetris; Kafatos, Anthony

doi:10.2147/dmso.s34220

Cited by 210 publications

(205 citation statements)

References 56 publications

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“…The overweight category width is larger in the Chinese study, and the fact that the overweight threshold is lower than the estimated presently (see Figure 8) is explainable by racial differences. [24] Yet, the narrower overweight range, than might be anticipated, may be due to the presumed fixed value for the obesity threshold, whereas the current result suggests it may vary with age. One problem shared by the Australian, Chinese and as well as the American study is though that the "overweight" segment includes also all obese, and the "obese" segment all stages thereof.…”

Section: Overweight and Obese Wchrcontrasting

confidence: 59%

Correspondence between waist-to-height ratio and body mass index in juniors

Yatsko

2017

JBEI

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Despite the increase in body mass through childhood and adolescence is countered by the increase in height in the Body Mass Index (BMI), this measure is inadequate for judging the degree of excess weight among the young. Unlike using clearly defined cut points, same for any stage of adulthood, it is required to consult BMI-for-age charts, which can be a demanding exercise when data analysis is involved. The waist circumference to height ratio (WCHR) was hypothesised to be invariant to age change, and this is generally supported by the epidemiological evidence. This paper analyses a sample of NHANES data to find a connection between BMI, WCHR and Age. A strong linearity between the anthropometric measures is demonstrated, thus enabling estimation of WCHR for a given BMI and Age. The pattern of change of this parameter at BMI levels that indicate the transition to overweight state or obesity thus becomes unravelled. The results strongly support the feasibility of a universal WCHR threshold for the overweight state past early childhood and through adolescence, and the estimated one is similar to the WCHR levels found elsewhere in the literature.

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Section: Overweight and Obese Wchrcontrasting

confidence: 59%

Correspondence between waist-to-height ratio and body mass index in juniors

Yatsko

2017

JBEI

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“…One of the suggested advantages in choosing WHt ratio instead of BMI is the ability to use one single cut-off point (0.5), irrespectively of age, sex, or ethnicity [28], resulting in an immediate and simple message, namely to "keep the waist circumference to less than half the height". A recent meta-analysis of epidemiological studies found that the WHt ratio represents a superior diagnostic tool in detecting subjects with high cardiometabolic risk, including diabetes; however, this has proved more useful in Asian populations [29]. The latter may explain why the two measurements (BMI and WHt) were found to be equal in predicting diabetes risk.…”

Section: Discussionmentioning

confidence: 99%

10-year Incidence of Diabetes and Associated Risk Factors in Greece: the ATTICA study (2002-2012)

Koloverou¹,

Panagiotakos²,

Pitsavos³

et al. 2014

Rev Diabet Stud

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■ Abstract BACKGROUND:The incidence of diabetes in the general population is increasing world-wide. The increase is attributed to the consumption of saturated fatty acids, obesity, lack of physical activity, genetic predisposition, and other factors, but knowledge about the reasons, biological mechanisms, and late complications is insufficient. It is therefore important to clarify the reasons more exactly through longterm clinical trials to stop the rise of diabetes and its complications. AIM: To evaluate the 10-year incidence of type 2 diabetes in apparently healthy Greek adults. METHODS: In 2001-2002, a random sample of 1514 men (18-87 years old) and 1528 women (18-89 years old) was selected to participate in the ATTICA study. During 2011-2012, the 10-year follow-up was performed. Patients diagnosed with diabetes at baseline (n = 210) and those lost at the 10-year follow-up (n = 1347) were excluded, yielding a final sample of 1485 participants. RESULTS: During the period of investigation, diabetes was diagnosed in 191 cases corresponding to a 12.9% incidence (95%CI: 10.4-15.4), with 13.4% (95%CI: 10.8-16) in men and 12.4% (95%CI: 10.1-14.7) in women. A relative increase was observed in the second half of the 10-year followup when age became significant. Multiple logistic regression analysis revealed that age (OR = 1.14, 95%CI: 1.09-1.19), abnormal waist-to-height ratio (OR = 3.27, 95%CI: 1.07-10.0), fasting blood glucose (OR per 1 mg/dl = 0.05, 95%CI: 1.02-1.08), energy intake (OR per 500 kcal = 1.02, 95%CI: 1.01-1.35), and family history of diabetes (OR = 2.8, 95%CI: 1.30-6.03) were the most significant baseline predictors for diabetes, after adjusting for potential confounders. Waist-to-height ratio showed the best explanatory power of all anthropometric variables. Physical activity exerts an effect on risk factors. Being active was found to eliminate the aggravating effect of diabetes family history and fasting blood glucose. CON-CLUSIONS: The findings confirm the escalating increase of type 2 diabetes incidence in Greece, which is in line with global trends. A lifestyle change in individuals at risk of developing diabetes towards healthier eating and increased physical activity would be an effective and inexpensive means of reducing diabetes.

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“…El ICT no es reportado en el INTERHEART, donde muestra una asociación global en varones menor que la propia cintura abdominal (OR: 1,18 vs. 1,19) (11). Sin embargo, el ICT es un buen indicador ROC en estudios predictivos o de riesgo cardiovascular en poblaciones españolas y mundiales (12,13,27,29,30). En nuestro estudio también presenta un alto grado de asociación, aunque la medida específica de CU y su quintil superior justifican con diferencias significativas el mayor rigor y poder del índice a nivel umbilical (ICUT).…”

Section: Discussionunclassified

“…Las estrategias en prevención cardiovascular deben fijar los objetivos de control antropométrico con aquellos indicadores que se muestren más fieles y útiles en traducir el riesgo cardiometabólico real. El índice de masa corporal (IMC) y su capacidad para expresar dicho riesgo o predecir eventos cardiovasculares es debatido, y se recomiendan otros indicadores como la circunferencia de cintura (CC) (6-10), el índice cintura-cadera (ICCad) (10,11) o el índice cintura-talla (ICT) (12,13). Sin embargo, cada indicador y cada medición antropométrica mantienen relaciones dispares con la distribución volumétrica del riesgo cardiometabólico y con la discriminación de los verdaderos componentes corporales de riesgo.…”

Section: Introductionunclassified

Obesidad y riesgo de infarto de miocardio en una muestra de varones europeos. El índice cintura-cadera sesga el riesgo real de la obesidad abdominal

et al. 2017

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Martín-Castellanos A, Cabañas Armesilla MD, Barca Durán FJ, Martín Castellanos P, Gómez Barrado JJ. Obesidad y riesgo de infarto de miocardio en una muestra de varones europeos. El índice cintura-cadera sesga el riesgo real de la obesidad abdominal. AbstractBackground: Obesity is a coronary risk factor associated to myocardial infarction although waist to-hip-ratio has shown higher predictive power. Objective: The aim of this study was a Receiver Operating Characteristic anthropometric analysis in infarcted males to identify the strength of association for simple measurements, obesity and indicators such as, waist to-hip-ratios, waist to-height-ratios and conicity index. Methods: Case-control study of myocardial infarction in European males. One hundred and twelve cases and 112 controls aged 30-74 years were enrolled. We measured weight, height, waist circumference, umbilical waist circumference and hip circumference. We calculated various anthropometric indicators. We obtained the areas under the ROC curves, the odds ratio and correlations for measurements and anthropometric indicators. . The correlations for waist to-height-ratios and conicity index were strong (all r ≥ 0.85; p < 0.001). Conclusions: Waist and height are measurements of associated independent risk. Hip circumference does no show discriminatory power. Obesity and waist-ratios are associated to myocardial infarction with different strength. Between other indicators, general obesity is more weakly associated. Waist to-hip-ratios present the best ROC curves but it occur information bias of their predictive power of risk. Umbilical waist to-height-ratio and conicity index present high discriminatory power and the best anthropometric risk correlations that support its use for the identifi cation of obesity as risk factor associated to myocardial infarction and in all strategies for coronary health promotion.

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

Cited by 210 publications

References 56 publications

Correspondence between waist-to-height ratio and body mass index in juniors

Correspondence between waist-to-height ratio and body mass index in juniors

10-year Incidence of Diabetes and Associated Risk Factors in Greece: the ATTICA study (2002-2012)

Obesidad y riesgo de infarto de miocardio en una muestra de varones europeos. El índice cintura-cadera sesga el riesgo real de la obesidad abdominal

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