The predictive value of different measures of obesity for incident cardiovascular events and mortality.
BACKGROUND
To date, it is unclear which measure of obesity is the most appropriate for risk stratification.


OBJECTIVE
The aim of the study was to compare the associations of various measures of obesity with incident cardiovascular events and mortality.


METHODS
We analyzed two German cohort studies, the DETECT study and SHIP, including primary care and general population.


METHODS
A total of 6355 (mean follow-up, 3.3 yr) and 4297 (mean follow-up, 8.5 yr) individuals participated in DETECT and SHIP, respectively.


METHODS
We measured body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) and assessed cardiovascular and all-cause mortality and the composite endpoint of incident stroke, myocardial infarction, or cardiovascular death.


RESULTS
In both studies, we found a positive association of the composite endpoint with WHtR but not with BMI. There was no heterogeneity among studies. The relative risks in the highest versus the lowest sex- and age-specific quartile of WHtR, WC, WHR, and BMI after adjustment for multiple confounders were as follows in the pooled data: cardiovascular mortality, 2.75 (95% confidence interval, 1.31-5.77), 1.74 (0.84-3.6), 1.71 (0.91-3.22), and 0.74 (0.35-1.57), respectively; all-cause mortality, 1.86 (1.25-2.76), 1.62 (1.22-2.38), 1.36 (0.93-1.69), and 0.77 (0.53-1.13), respectively; and composite endpoint, 2.16 (1.39-3.35), 1.59 (1.04-2.44), 1.49 (1.07-2.07), and 0.57 (0.37-0.89), respectively. Separate analyses of sex and age groups yielded comparable results. Receiver operating characteristics analysis yielded the highest areas under the curve for WHtR for predicting these endpoints.


CONCLUSIONS
WHtR represents the best predictor of cardiovascular risk and mortality, followed by WC and WHR. Our results discourage the use of the BMI.
Medizinische Klinik-Innenstadt, Ludwig-Maximilians University, Ziemssenstrasse 1, 80336 Munich, Germany. harald.schneider@med.uni-muenchen.de
Harald J
HJ
Schneider
Nele
N
Friedrich
Jens
J
Klotsche
Lars
L
Pieper
Matthias
M
Nauck
Ulrich
U
John
Marcus
M
Dörr
Stephan
S
Felix
Hendrik
H
Lehnert
David
D
Pittrow
Sigmund
S
Silber
Henry
H
Völzke
Günter K
GK
Stalla
Henri
H
Wallaschofski
Hans-Ulrich
HU
Wittchen
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000886:Anthropometry; D002318:Cardiovascular Diseases / Q000209:etiology* / Q000401:mortality*; D015331:Cohort Studies; D004493:Education; D023381:Endpoint Determination; D005260:Female; D005858:Germany / Q000453:epidemiology; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000150:complications / Q000175:diagnosis* / Q000401:mortality*; D011153:Population; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012044:Regression Analysis; D012737:Sex Factors; D012907:Smoking / Q000453:epidemiology; D012959:Socioeconomic Factors; D055815:Young Adult