Waist circumference and cardiovascular fitness -
The sensitivity and specificity of the predictive WC cut-off points for CVD events and all-cause mortality were presented in Supplementary Tables 1 and 2 , respectively. Although, the C-index was slightly higher in women than in men, the difference was statistically significant only in the overweight group Table 4.
The same results were obtained after sensitivity analysis and exclusion of the incidents happening in the first two years of the follow-up. Kaplan-Meier survival curves examining waist circumference thresholds based on incident cardiovascular disease a all-cause mortality b among BMI categories.
This large prospective cohort study intended to determine BMI-specific WC thresholds for predicting CVD events and all-cause mortality. Although the correlation of BMI and WC with CVD risk factors had been well established in many previous studies [ 32 , 33 , 34 ] it is not yet well understood how BMI and WC are related to outcomes such as CVD events, all-cause mortality, and CVD-related mortality.
Studies have demonstrated that in certain groups of people, such as patients with chronic diseases and those with established coronary artery diseases, a U-shaped correlation exists between BMI and mortality meaning that overweight and mildly obese individuals have lower mortality while patients with either low BMI or too high BMI are more likely to experience CVD events and mortality [ 35 , 36 , 37 , 38 ] a phenomenon called the obesity paradox [ 39 ].
In a study by Adegbija et al. In contrast, before adjustment for BMI, WC was not associated with mortality while after the adjustment, the mortality rate was observed to be higher in the upper WC quartile than in the lower quartile. As observed in previous studies, WC seems to be a better predictor of CVD events or mortality than BMI.
In our study, the incidence of CVD events increased from normal weight to overweight, and from overweight to obesity group, in both men CVD incidence rate of 0. As well, all-cause mortality in obese men was higher than in overweight peers 0.
Among women, the highest all-cause mortality was seen in obese people 0. The combination use of BMI and WC can provide a more accurate predictor of mortality, as seen in previous studies [ 40 , 41 ].
In a study on more than 23 million Korean people, a linear association was noticed between WC and all-cause mortality in all BMI categories [ 40 ].
It is well-established that WC varies considerably within any BMI category and shows a notable correlation with health-related risk factors. In a pooled analysis of 11 studies on , subjects, mortality positively correlated with WC in each BMI category [ 11 ].
However, when adjusted for WC, mortality was lower in subjects with higher BMI [ 42 ]. The association of WC with CVD events and CVD-related mortality has also been established in other studies [ 43 , 44 , 45 ].
In another prospective cohort study, a higher WC predicted higher nonfatal and fatal CVD incidents [ 45 ]. Also, in a cohort study on more than 58, elderly subjects, a greater WC was associated with a higher relative risk of CVD mortality in any BMI category [ 44 ].
In recent years many studies suggested different WC cut-off points to predict the incidence of CVD events and incidence of metabolic syndrome as well as cardio metabolic alterations [ 19 , 20 , 21 ]. These cut-off values range from 85 to 95 cm in men and 80 to 90 cm in women of different ethnicities.
Few studies have evaluated the role of WC thresholds predicting CVD outcomes [ 22 , 23 ]. In a study by Talaei et al. Another study by Hadaegh et al. The above-mentioned cut-offs were similar to those presented in the current study and higher compared to the thresholds suggested for metabolic syndrome or cardiovascular risk factors.
The cut-off values reported in the present study i. On the other hand, there is a trade-off between sensitivity and specificity, meaning that in order to reach a higher sensitivity, specificity should be sacrificed and vice versa.
The optimal cut-off points in our study were defined based on the maximum level of the Youden index. Generally, when WC is used as a screening tool, sensitivity is of greater importance.
In the study of Lee et al. The suggested thresholds were 80 and 89 cm for normal weight and overweight men and 78 and 94 cm for women, respectively, which except in overweight women, are lower values than our suggested thresholds. In our study, the sensitivity ranged from The lowest sensitivity values for CVD-related mortality According to the results of our study, the WC thresholds obtained for CVD events and all-cause mortality were 82 and 88 cm normal weight , 95 overweight and cm obese in men and 82 and 83 cm normal weight , 89 and 90 cm overweight and 99 and cm obese in women, respectively.
Few studies have evaluated the predictive value of BMI-specific WC cut-off points [ 24 , 47 ]. In a study by Staiano et al. These values are almost the same as those observed in ours study, however, the values obtained for women in the recent study were lower compared to ours.
In another study, the WC thresholds predicting a high risk of coronary events in the normal-weight, overweight, obesity I, and obesity II groups were obtained as 82—89, 95—99, —, and — cm in men ; and 79—81, 90—93, —, and — cm in women, respectively [ 24 ].
Also, these values were close to those observed in our study. This study has several strengths and limitations. The main strengths of our study include the long median follow-up time, its prospective cohort design, using CVD events and mortality as endpoints, and collection of subjective instead of self-report data.
Regarding the limitations of the present study, the data were related to the middle-east Caucasian residents of a metropolitan city in Iran, who cannot be representative of national population. Different methods of WC measurement have been established.
In the present study, WC was measured at the umbilical level. Since there are different methods for measuring WC, although it is unlikely for the method of WC measurement to affects the results [ 13 ], this point should be considered when comparing the results of different studies.
In conclusion, the results of this study suggested BMI-specific WC thresholds for predicting CVD events, CVD-related and mortality, and all-cause mortality, which can used as a clue for future studies to define more accurate WC cut-off values as a screening tool in different populations. This approach can help better identify individuals who are at a high risk of developing CVD and take effective measures to modify their risk factors.
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Collaborators GO. Health effects of overweight and obesity in countries over 25 years.
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Association of waist circumference and body mass index with all-cause mortality in CKD: the REGARDS reasons for Geographic and racial differences in stroke study. However, measurement of WC has not been widely adopted in clinical practice, and the anatomical, metabolic, and clinical implications of WC data can be confusing.
Therefore, Shaping America's Health: Association for Weight Management and Obesity Prevention; NAASO: The Obesity Society; and the American Diabetes Association convened a panel, comprised of members with expertise in obesity management, obesity-related epidemiology, adipose tissue metabolic pathophysiology, statistics, and nutrition science to review the published scientific literature and hear presentations from other experts in these fields.
The Consensus Panel met from December 17 to 20, , in Washington, DC, and was charged to provide answers to the following four questions:. What are the biological mechanisms responsible for the association between waist circumference and cardiometabolic risk?
What is the power of waist circumference to predict adverse cardiometabolic outcomes? How does the predictive power of waist circumference compare with that of BMI? Does measuring waist circumference in addition to BMI improve predictability? Waist circumference is actually a perimeter, which provides an estimate of body girth at the level of the abdomen.
Different anatomical landmarks have been used to determine the exact location for measuring WC in different clinical studies, including: 1 midpoint between the lowest rib and the iliac crest; 2 the umbilicus; 3 narrowest minimum or widest maximum waist circumference; 4 just below the lowest rib; and 5 just above the iliac crest.
The specific site used to measure WC influences the absolute WC value that is obtained 9. Although sites that use an easily identifiable and reproducible landmark e.
Waist circumference measurements should be made around a patient's bare midriff, after the patient exhales while standing without shoes, both feet touching, and arms hanging freely. The measuring tape should be made of a material that is not easily stretched, such as fiberglass.
The tape should be placed perpendicular to the long axis of the body and horizontal to the floor and applied with sufficient tension to conform to the measurement surface.
In a research setting, WC measurements are typically taken three times and recorded to the nearest 0. Although specific techniques have been recommended for measuring WC in the clinical setting 2 , 10 , there is no uniformly accepted approach.
Training technicians and even patients to use an appropriate technique for measuring WC is essential to obtain reliable data; special tape measures, instructional manuals, and videotapes are available for this purpose The reproducibility of WC measurements at all sites is high for both men and women e.
However, self-reported measurements are prone to a systematic bias, and there is a nontrivial underestimate of self-measured WC at all anatomic sites Adipose tissue consists of adipocytes, inflammatory cells, and vascular, connective, and neural tissues.
Magnetic resonance imaging MRI and computed tomography CT are considered the gold-standard methods for determining the quantity of subcutaneous abdominal adipose tissue SAAT and intra-abdominal adipose tissue IAAT Most MRI and CT methods involve acquisition of cross-sectional abdominal images, which are then analyzed for fat content.
A single slice is often acquired at the L 4 -L 5 intervertebral level to estimate SAAT and IAAT volume, expressed as cm 3. However, L 4 -L 5 imaging does not provide the best estimate of total IAAT mass, which is more reliably estimated several centimeters cephalad of the L 4 -L 5 intervertebral space 17 , In addition, measurement site influences the relationship between IAAT volume and cardiometabolic risk; the association between IAAT volume and presence of the metabolic syndrome is greater when IAAT volume is determined at the L 1 -L 2 than at the L 4 -L 5 level Currently, there is no universally accepted site for measuring IAAT and SAAT.
The relationship between WC, weight, and BMI can be conceptualized by using simple geometric relationships that consider the body as a cylinder; WC is the cylinder's circumference, height is its length, and weight is a measure of mass. Therefore, BMI provides information about body volume and mass, and WC provides information about body shape.
In general, BMI and WC are highly correlated, typically with r values in the range of 0. The relationships among WC, BMI, and adipose tissue compartments in primarily Caucasian and African-American men and women are shown in Table 2 These data demonstrate that both BMI and WC are strongly correlated with total body adipose tissue mass but that WC is a better predictor of IAAT than is BMI.
Assessment of WC provides a measure of fat distribution that cannot be obtained by measuring BMI. However, there is no standardized approach for measuring WC and different anatomical landmarks have been used to measure WC in different studies. Moreover, the measurement site that provides the best correlation with disease risk and best reflects changes in abdominal adipose tissue mass has not been established.
Nonetheless, the precision of WC measurement is high at any given landmark. Even self-measurement can be highly reproducible when performed by properly trained subjects, although self-measurement results in an underestimation of true WC.
Measurement of WC cannot determine the individual contributions of SAAT and IAAT to abdominal girth, which require imaging by MRI or CT. The value of these scanning techniques in clinical practice has not been determined. It is not known whether the storage of an absolute or relative excess amount of triglycerides in abdominal fat depots is directly responsible for increased disease risk or whether such deposition is simply associated with other processes that cause risk, or both.
In addition, WC values provide a measure of both SAAT and IAAT masses. Therefore, the relationship between WC and cardiometabolic risk cannot determine whether risk is associated with SAAT, IAAT, or both. The mechanism s responsible for the relationship between excess abdominal fat distribution and cardiometabolic disease is not known, but several hypotheses have been proposed.
One of the earliest hypotheses that implicated IAAT as a metabolic risk factor suggested that activation of the central nervous system—adrenal axis by environmental stressors caused both the preferential deposition of adipose tissue in the trunk and the cardiovascular and metabolic disorders associated with that deposition Excessive ectopic fat accumulation then causes metabolic dysfunction in those organs.
In fact, increased intrahepatic fat is associated with dyslipidemia and hepatic insulin resistance 23 , and increased intramyocellular fat is associated with skeletal muscle insulin resistance In this paradigm, IAAT is primarily a marker of the magnitude of overflow of fatty acids from subcutaneous depots.
Therefore, increased WC could be a discernible marker of a system-wide impairment in energy storage regulation, in which an increase in IAAT reflects a reduced capacity for energy storage in other adipose tissues. A third hypothesis proposes a direct effect of omental and mesenteric adipose tissue depots on insulin resistance, lipoprotein metabolism, and blood pressure.
Metabolic products of omental and mesenteric adipose tissue depots are released into the portal vein, which provides direct delivery to the liver. Lipolysis of omental and mesenteric adipose tissue triglycerides release free fatty acids that can induce hepatic insulin resistance and provide substrate for lipoprotein synthesis and neutral lipid storage in hepatocytes.
In addition, specific proteins and hormones produced by omental and mesenteric adipose tissue, such as inflammatory adipokines, angiotensinogen, and cortisol generated by local activity of 11 β-hydroxysteroid dehydrogenase , can also contribute to cardiometabolic disease.
A fourth hypothesis is that genes that predispose to preferential deposition of fat in abdominal depots independently cause cardiometabolic disease.
These hypotheses are not mutually exclusive, and it is possible that all, and other unknown mechanisms, are involved in the association between abdominal fat mass and adverse metabolic consequences. The importance of WC in predicting cardiometabolic risk factors e.
Specific relative risks between WC and these outcomes vary, depending on the population sampled and the outcome measured. The relationship between WC and clinical outcome is consistently strong for diabetes risk, and WC is a stronger predictor of diabetes than is BMI.
The relative risk of developing diabetes between subjects in the highest and lowest categories of reported WC often exceeds 10 and remains statistically significant after adjusting for BMI.
These data demonstrate that WC can identify persons who are at greater cardiometabolic risk than those identified by BMI alone. Values for WC are also consistently related to the risk of developing CHD, and the relative risk of developing CHD between subjects in the highest and lowest categories of WC ranges from 1.
Values for WC are usually strongly associated with all-cause and selected cause-specific mortality rates. Data from several studies support the notion that WC is an important predictor of diabetes, CHD, and mortality rate, independent of traditional clinical tests, such as blood pressure, blood glucose, and lipoproteins 7 , However, there is not yet a compelling body of evidence demonstrating that WC provides clinically meaningful information that is independent of well-known cardiometabolic risk factors.
WC is an important predictor of health outcomes in men and women; Caucasians, African Americans, Asians, and Hispanics; and adults of all age-groups. In fact, the relationship between WC and health outcome changes much less with increasing age than does the relationship between BMI and health outcome The shape of the relationship between WC and health outcomes e.
Data from most studies suggest that the shape of the relationship between WC and health outcome lends itself to identifying clinically meaningful cut point values because risk often accelerates monotonically above, and can be relatively flat below, a specific WC value.
Optimum WC cut points will likely vary according to the population studied, the health outcome of interest, and demographic factors.
Data from most clinical weight loss and exercise training trials have shown that reductions in WC occur concomitantly with reductions in obesity-related cardiometabolic risk factors and disease.
However, these results do not prove that the reduction in WC was responsible for the beneficial effect on health outcome. Additional studies are needed to evaluate the effect of decreasing WC on cardiometabolic outcomes. The panel concluded that determining whether waist circumference should be measured in clinical practice depends on the responses to the following four key questions:.
Health care personnel and even patients themselves, who are given appropriate training in technique, can provide highly reproducible measurements of WC in men and women. However, it is not know whether measurement of one anatomical site is a better indicator of cardiometabolic risk than measurement at other sites.
Does waist circumference provide: a good prediction of diabetes, CHD, and mortality rate? Answer: Yes ; b incremental value in predicting diabetes, CHD, and mortality rate above and beyond that provided by BMI?
Answer: Yes ; c sufficient incremental value in these predictions above and beyond that offered by BMI and commonly evaluated cardiometabolic risk factors, such as blood glucose concentration, lipid profile and blood pressure?
Answer: Uncertain. Data from many large population studies have found waist circumference to be a strong correlate of clinical outcome, particularly diabetes, and to be independent of BMI.
In addition, data from a limited number of studies demonstrates that WC remains a predictor of diabetes, CHD, and mortality rate, even after adjusting for BMI and several other cardiometabolic risk factors.
Additional studies are needed to confirm that WC remains an independent predictor of risk. Answer: Yes. It is not known what portion of subjects who had a large WC would have been identified as having increased cardiometabolic risk based on findings from a standard medical evaluation.
Answer: Probably not. Measurement of WC in clinical practice is not trivial, because providing this assessment competes for the limited time available in a busy office practice and requires specific training to ensure that reliable data are obtained. Therefore, waist circumference should only be measured if it can provide additional information that influences patient management.
Based on NHANES III data, However, it is likely that different WC cut point values could provide more useful clinical information. For example, an analysis of data obtained from the NHANES III and the Canadian Heart Health Surveys found that BMI-specific WC cut points provided a better indicator of cardiometabolic risk than the recommended WC thresholds For normal-weight BMI Waist circumference provides a unique indicator of body fat distribution, which can identify patients who are at increased risk for obesity-related cardiometabolic disease, above and beyond the measurement of BMI.
Therefore, the clinical usefulness of measuring WC, when risk is based on the currently accepted guidelines, is limited.
However, WC measurement can sometimes provide additional information to help the clinician determine which patients should be evaluated for the presence of cardiometabolic risk factors, such as dyslipidemia, and hyperglycemia.
In addition, measuring WC can be useful in monitoring a patient's response to diet and exercise treatment because regular aerobic exercise can cause a reduction in both WC and cardiometabolic risk, without a change in BMI Further studies are needed to establish WC cut points that can assess cardiometabolic risk, not adequately captured by BMI and routine clinical assessments.
Nonetheless, it should be possible to determine more useful WC cut points than are currently recommended, by carefully reviewing published data and reevaluating datasets available from existing population studies.
These additional analyses will define the future role of WC measurement in clinical practice. Adapted from reference Data are correlation coefficients. has received research grants from Frito-Lay and OMP; has served as a consultant to Kraft Foods, Pfizer, Bristol-Myers Squibb, and Bio Era; and has received financial support from Lilly, Pfizer, Merck Pharmaceutical Company, Unilever, Coca-Cola, General Mills, International Life Sciences Institute, GlaxoSmithKline, OMP, Jansen Pharmaceuticals, and Frito-Lay.
has received research grants from Sanofi-Aventis, Merck, and Takeda for clinical trials; has served as a consultant to Sanofi-Aventis, Amylin Pharmaceuticals, EnteroMedics, Dannon-Yakult, and Merck Pharmaceutical Company. is an employee of Merck Pharmaceutical Company. A table elsewhere in this issue shows conventional and Système International SI units and conversion factors for many substances.
The costs of publication of this article were defrayed in part by the payment of page charges. C Section solely to indicate this fact.
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Volume 30, Issue 6. Previous Article Next Article. QUESTION 1: What does waist circumference measure? QUESTION 2: What are the biological mechanisms responsible for the association between waist circumference and metabolic and cardiometabolic risk? QUESTION 3: What is the power of waist circumference to predict adverse cardiometabolic outcomes?
Does waist circumference measurement in addition to BMI improve predictability? QUESTION 4: Should waist circumference be measured in clinical practice?
Organic eco-friendly toys with bigger waists relative to their hips face a higher risk of heart fitnesw than Waizt with a similar body shape, according to a new Innovative weight control. The study, published Wednesday in ajd Journal of the Carviovascular Heart Organic eco-friendly toyscircumferencce Waist circumference and cardiovascular fitness a waist-to-hip cardiovascuoar measurement may be cardiovasfular better indicator of fitjess attack risk than body mass cirfumference for Waist circumference and cardiovascular fitness men and women. Previous studies have shown it's not just general obesity, but also where fat is stored on the body, that contributes to an increased risk of heart disease. However, past research was unclear on what role gender played in the equation, despite clear differences between men and women in body fat distribution. For this study, researchers looked for sex-specific links between excess weight, fat distribution, and heart disease risk in nearly half a million men and women ages 40 to 69 in the United Kingdom who had no previous history of heart disease. During seven years of follow-up, 5, heart attacks were recorded among participants, with women experiencing a 15 percent higher risk of heart attacks than men with a similar waist-to-hip fat distribution.:max_bytes(150000):strip_icc()/waist-circumference-and-diabetes-1087703-v2-73f91b4e84f44bd5a06bcb83f8fa6fb1.png "Waist circumference and cardiovascular fitness")
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