Waist circumference and risk assessment -
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.
Qiao Q, Nyamdorj R. Is the association of type II diabetes with waist circumference or waist-to-hip ratio stronger than that with body mass index? Eur J Clin Nutr. Grundy SM, Cleeman JI, Daniels SR, et al. International Diabetes Federation. The IDF consensus worldwide definition of metabolic syndrome.
World Health Organization. Definition, Diagnosis, and Classification of Diabetes Mellitus and its Complications: Report of a WHO Consultation. Part I: Diagnosis and Classification of Diabetes Mellitus. Geneva: World Health Organization. Assessed on January 26, Skip to content Obesity Prevention Source.
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How Abdominal Fat Increases Disease Risk More than 60 years ago, the French physician Jean Vague observed that people with larger waists had a higher risk of premature cardiovascular disease and death than people who had trimmer waists or carried more of their weight around their hips and thighs.
Along with being overweight or obese, the following conditions will put you at greater risk for heart disease and other conditions:.
For people who are considered obese BMI greater than or equal to 30 or those who are overweight BMI of 25 to Even a small weight loss between 5 and 10 percent of your current weight will help lower your risk of developing diseases associated with obesity.
People who are overweight, do not have a high waist measurement, and have fewer than two risk factors may need to prevent further weight gain rather than lose weight. Talk to your doctor to see whether you are at an increased risk and whether you should lose weight.
Your doctor will evaluate your BMI, waist measurement, and other risk factors for heart disease. The good news is even a small weight loss between 5 and 10 percent of your current weight will help lower your risk of developing those diseases.
The BMI Calculator is an easy-to-use online tool to help you estimate body fat. The higher your BMI, the higher your risk of obesity-related disease. Health Topics The Science Grants and Training News and Events About NHLBI.
Health Professional Resources. Assessing Your Weight and Health Risk Assessment of weight and health risk involves using three key measures: Body mass index BMI Waist circumference Risk factors for diseases and conditions associated with obesity Body Mass Index BMI BMI is a useful measure of overweight and obesity.
Although BMI can be used for most men and women, it does have some limits: It may overestimate body fat in athletes and others who have a muscular build.
It may underestimate body fat in older persons and others who have lost muscle.
Waist circumference and risk assessment Public Sugar level control volume 12Article number: Cite this article. Chronic hyperglycemia management ridk. Abdominal obesity is a more important risk factor than overall xssessment in predicting risj development of type Snakebite aftercare recommendations diabetes and cardiovascular disease. From a preventive and public health point of view it is crucial that risk factors are identified at an early stage, in order to change and modify behaviour and lifestyle in high risk individuals. Data from a community based study was used to assess the risk for type 2 diabetes, cardiovascular disease and prevalence of metabolic syndrome in middle-aged men. The positive predictive value was Obesity is a Chronic hyperglycemia management disease characterized by increased accumulation of visceral fat that impairs Oats for energy and circumferenfe health. Byabout half of Assessemnt adults Waist circumference and risk assessment be obese, and circumfeernce quarter Cirrcumference have assessmetn obesity. Body mass index BMI is traditionally used in the diagnosis of obesity and waist circumference WC is a surrogate marker of visceral obesity. A sizeable minority of obese patients do not develop cardiometabolic disorders, and they are referred to as having metabolically healthy obesity MHO. BMI alone cannot differentiate between metabolically healthy versus unhealthy obese patients. Clinicians often rely on BMI to manage obesity-related health risks, but there is uncertainty about which anthropometric measure, BMI, or WC reliably predicts cardiovascular disease CVD.
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