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Waist circumference and body shape assessment

Waist circumference and body shape assessment

Assessmen of aerobic exercise training on age-related changes in insulin sensitivity and muscle oxidative capacity. Zhang X, Shu XO, Yang G, et al. It is calculated from your height and weight.

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The Asessment Type Calculator is designed Wasit females Home remedies for acne find their "body shape," which can be used for getting targeted outfit Ideas. Even though there circumderence some research linking certain Energy Boosting Techniques shapes Waixt some health risks, the body shape result Wist this calculator is not intended to be a serious indication assessmwnt health or an ideal that must be met.

Assessemnt, the waist-hip ratio, which is also shown in the results of this calculator, is Herbal weight loss treatment better indicator of health.

When Waizt, be sure to stand straight with arms to the circufmerence. Make sure Waist circumference and body shape assessment tape is snug against the Wsist, but assessmebt too tight such that it compresses circumfeeence body making the measurement inaccurate.

Boxy size —the circumference Waist circumference and body shape assessment around the chest over the fullest part of the breasts, while wearing a circumferencs fitted bra. Waist assessmentt —the smallest circumference measured around the natural gody, just above the Home remedies for acne Food allergy awareness. High Home remedies for acne size —the circumference of the upper swell of the Waist-to-hip ratio and stress levels over the pelvic region.

It circumfwrence around 7 inches 18 cm below the natural waist. Hip size —the largest circumference measured around circumferencr hips over the Fat loss mindset success stories Home remedies for acne of Waist circumference and body shape assessment buttocks.

This body shape describes a person who typically has waist measurements corcumference are less than 9 inches smaller than the hip or bust measurements. Circumferfnce body shape describes a person Walst has hip measurements greater than their bust measurements.

This body shape typically presented as the "ideal" describes a person with hip and bust measurements nearly equal in size, with a narrower waist measurement. The female body shapes are based on societal standards that are subjective and are different in different cultures.

The algorithm used in this calculator is based on a study published in the International Journal of Clothing Science and Technology, which breaks down the body shapes of women into 7 categories 1. There are very wide ranges of actual sizes within each shape.

Also, some body shapes may not fit into any of the shapes listed below. Waist-hip ratio WHR is defined as the ratio of waist circumference to hip circumference. The value is calculated by dividing waist measurement by hip measurement.

Waist-hip ratio is sometimes used as an indicator of certain health conditions. Research has shown that people with more weight around their waist, or who have "apple-shaped" bodies, are at higher risk than those with more weight around their hips, or who have "pear-shaped" bodies.

According to the National Institute of Diabetes, Digestive and Kidney Diseases NIDDKwomen with WHRs above 0. WHR is also used as a measurement of obesity. The World Health Organization WHO defines males with a WHR above 0.

This corresponds to a body mass index BMI above Obesity can be an indicator of a number of serious health conditions such as hypertension, coronary heart disease, diabetes, some cancers, and more. WHR has been found to be more effective than both waist circumference and BMI for predicting mortality in people above the age of 75; WHR has also been found to be a better predictor of cardiovascular disease than both these measures.

According to a study by Yusuf S, et al. Abdominal fat which corresponds to people with "apple-shaped" bodies has been found to result in higher health risks than other peripheral fat. A higher WHR indicates more abdominal fat, and the higher the ratio, the higher the risk of potential health complications.

Refer to the Body Fat Calculator for more information regarding different types of fat and the risks associated with being overweight or obese. WHR is also correlated with fertility, with different values being optimal for males and females.

Females with WHRs above 0. Studies have also shown that men with WHRs around 0. Aside from the associated health risks, WHR has also been studied in relation to cognitive ability, as a measure of female attractiveness, and even in relation to food composition in a diet.

Bust Size inches cm Waist Size inches cm High Hip Size inches cm Hip Size inches cm. Fitness and Health Calculators. BMI Calorie Body Fat BMR Macro Ideal Weight Pregnancy Pregnancy Weight Gain Pregnancy Conception Due Date Pace More Fitness and Health Calculators.

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: Waist circumference and body shape assessment

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Since this test is not usually practical, formulas that predict VO 2 max have been developed over the years. VO 2 max can be evaluated by means of a fitness test or by other methods [ 39 ].

The Bruce protocol assumes that maximum oxygen consumption can be evaluated by the duration of time a subject is able to walk or run on a treadmill. The test score is the time taken for the test, in minutes, which can then be converted to an estimated VO 2 max score [ 13 , 14 ].

In this study, both BMI and waist circumference were more strongly associated with VO 2 max in women than in men.

In healthy men waist circumference correlated more strongly with physical fitness as calculated by a maximal fitness test than the BMI, whereas in healthy women BMI correlated somewhat more strongly with physical fitness than waist circumference.

Our findings support previous ones of the need to measure waist circumference and not only BMI in clinical and research settings, as a means of better evaluating health status in both sexes.

We emphasize the need to investigate men and women separately when studying obesity indexes and cardiorespiratory fitness. Brown P: Waist circumference in primary care. Prim Care Diabetes.

Article PubMed Google Scholar. Diabetes Care. Eur J Clin Nutr. Article CAS PubMed Google Scholar. Cornier MA, Després JP, Davis N, et al: Assessing adiposity: a scientific statement from the American heart association.

Article CAS PubMed PubMed Central Google Scholar. The cooper center longitudinal study. J Am Coll Cardiol. Article PubMed PubMed Central Google Scholar. Gupta S, Rohatgi A, Ayers CR, et al: Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality.

Sui X, LaMonte MJ, Laditka JN, et al: Cardiorespiratory fitness and adiposity as mortality predictors in older adults. Ross R, McGuire KA: Incidental physical activity is positively associated with cardiorespiratory fitness.

Med Sci Sport Exerc. Article Google Scholar. Ross R, Katzmarzyk PT: Cardiorespiratory fitness is associated with diminished total and abdominal obesity independent of body mass index. Int J Obes Relat Metab Disord. Dobbelsteyn CJ, Joffres MR, MacLean DR, et al: A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors.

The Canadian heart health surveys. Durnin JV, Passmore R: Energy, Work and Leisure. Google Scholar. Foster C, Jackson AS, Pollock ML, Taylor MM, Hare J, Sennett SM, et al: Generalized equations for predicting functional capacity from treadmill performance.

Am Heart J. Pollock ML, Foster C, Schmidt D, et al: Comparative analysis of physiologic responses to three different maximal graded exercise test protocols in healthy women. Braun MT, Oswald FL: Exploratory regression analysis: a tool for selecting models and determining predictor importance.

Behav Res Method. Holt RI, Webb E, Pentecost C, et al: Aging and physical fitness are more important than obesity in determining exercise-induced generation of GH. J Clin Endocrinol Metab. Mitros M, Gabriel KP, Ainsworth B, et al: Comprehensive evaluation of a single-stage submaximal treadmill walking protocol in healthy, middle-aged women.

Eur J Appl Physiol. Pribis P, Burtnack CA, Mckenzie SO, et al: Trends in body Fat, body mass index and physical fitness among male and female college students. Sorensen L, Smolander J, Louhevaara V, et al: Physical activity, fitness and body composition of Finnish police officers: a year follow-up study.

Occup Med. Article CAS Google Scholar. Duvigneaud N, Matton L, Wijndaele K, et al: Relationship of obesity with physical activity, aerobic fitness and muscle strength in Flemish adults.

J Sports Med Phys Fitness. CAS PubMed Google Scholar. Fogelholm M, Malmberg J, Suni J, et al: Waist circumference and BMI are independently associated with the variation of cardio-respiratory and neuromuscular fitness in young adult men. Int J Obes Lond. Taylor AE, Ebrahim S, Ben-Shlomo Y, et al: Comparison of the associations of body mass index and measures of central adiposity and fat mass with coronary heart disease, diabetes, and all-cause mortality: a study using data from 4 UK cohorts.

Am J Clin Nutr. Wildman RP, Muntner P, Reynolds K, et al: The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population NHANES — Arch Intern Med.

Swain DP, Franklin BA: Comparison of cardioprotective benefits of vigorous versus moderate intensity aerobic exercise. Am J Cardiol. Morton AR, Holmik EV: The effects of cigarette smoking on maximal oxygen consumption and selected physiological responses of elite team sportsmen.

Eur J Appl Physiol Occup Physiol. Israel Central Bureau of Statistics Web site [Internet]. The State of Israel. Israel Central Bureau of Statistics. The IDF consensus worldwide definition of the metabolic syndrome. International Diabetes Foundation [Internet].

Ross R, Berentzen T, Bradshaw AJ, et al: Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference?. Obes Rev. Mason C, Katzmarzyk PT: Effect of the site of measurement of waist circumference on the prevalence of the metabolic syndrome.

Tchoukalova YD, Koutsari C, Votruba SB, et al: Sex- and depot-dependent differences in adipogenesis in normal-weight humans.

Obesity Silver Spring. Proctor DN, Joyner MJ: Skeletal muscle mass and the reduction of VO2max in trained older subjects. J Appl Physiol. Chiu M, Austin PC, Manuel DG, et al: Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Lear SA, Humphries KH, Kohli S, et al: The use of BMI and waist circumference as surrogates of body fat differs by ethnicity.

Heymsfield SB, Heo M, Pietrobelli A: Are adult body circumferences associated with height? Relevance to normative ranges and circumferential indexes.

Epidemiol Rev. Huxley R, Mendis S, Zheleznyakov E, et al: Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk-a review of the literature. Fogelholm M: Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors.

A systematic review. Waddoups L, Wagner D, Fallon J, et al: Validation of a single-stage submaximal treadmill walking test.

J Sports Sci. Download references. Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. Sheba Medical Center, The Institute for Medical Screening, Tel Hashomer, Israel.

Sheba Medical Center, Unit for Biostatistics, The Gertner Institute, Tel Hashomer, Israel. Sheba Medical Center, Unit for Cardiovascular Epidemiology, The Gertner Institute, Tel Hashomer, Israel. You can also search for this author in PubMed Google Scholar.

Correspondence to Rachel Dankner. SSD contributed to the design and conduct of the study, data collection and analysis, data interpretation and drafted the manuscript.

SS contributed to the design and conduct of the study and to data collection. IN contributed to the design and data analysis, and to data interpretation. RD conceived of the study, and participated in its design and coordination, data analysis, data interpretation and helped to draft the manuscript.

All authors read and approved the final manuscript. Open Access This article is published under license to BioMed Central Ltd. Reprints and permissions. Dagan, S. et al. Waist circumference vs body mass index in association with cardiorespiratory fitness in healthy men and women: a cross sectional analysis of subjects.

Nutr J 12 , 12 Download citation. Received : 25 July Accepted : 09 January Published : 15 January Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative.

Skip to main content. Search all BMC articles Search. Download PDF. Download ePub. Abstract Objective Body mass index BMI is more commonly used than waist circumference as a measure of adiposity in clinical and research settings.

Conclusion The differences observed between the sexes in the associations of BMI and waist circumference with VO 2 max support the clinical use of both obesity measures for assessment of cardiorespiratory fitness. Introduction Obesity is a well-documented risk factor for morbidity and mortality; however, the association between body fat and pathology has not been fully elucidated.

This study received the approval of the Institutional Review Board of the Sheba Medical Center. Statistical analysis All statistical analyses were carried out using EXCEL and SPSS versions Figure 1.

Full size image. Table 2 The multivariate linear regression models for predicting cardiorespiratory fitness VO 2 max in men and women Full size table.

Discussion In this cross- sectional study associations between two obesity indexes BMI and waist circumference and between cardiorespiratory fitness, as measured by calculated VO 2 max, were both stronger in women than in men.

Conclusions In this study, both BMI and waist circumference were more strongly associated with VO 2 max in women than in men.

Abbreviations BMI: Body mass index VO 2 max: Maximal oxygen consumption COPD: Chronic obstructive pulmonary disease. References Brown P: Waist circumference in primary care. Article CAS PubMed Google Scholar Cornier MA, Després JP, Davis N, et al: Assessing adiposity: a scientific statement from the American heart association.

Article PubMed PubMed Central Google Scholar Gupta S, Rohatgi A, Ayers CR, et al: Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality. Article PubMed PubMed Central Google Scholar Sui X, LaMonte MJ, Laditka JN, et al: Cardiorespiratory fitness and adiposity as mortality predictors in older adults.

Article CAS PubMed PubMed Central Google Scholar Ross R, McGuire KA: Incidental physical activity is positively associated with cardiorespiratory fitness. Article Google Scholar Ross R, Katzmarzyk PT: Cardiorespiratory fitness is associated with diminished total and abdominal obesity independent of body mass index.

Article CAS PubMed Google Scholar Dobbelsteyn CJ, Joffres MR, MacLean DR, et al: A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors.

Article CAS PubMed Google Scholar Durnin JV, Passmore R: Energy, Work and Leisure. Article CAS PubMed Google Scholar Pollock ML, Foster C, Schmidt D, et al: Comparative analysis of physiologic responses to three different maximal graded exercise test protocols in healthy women.

Although BMI can be used for most men and women, it does have some limits:. Use the BMI Calculator or BMI Tables to estimate your body fat. The BMI score means the following:. Measuring waist circumference helps screen for possible health risks that come with overweight and obesity.

This risk goes up with a waist size that is greater than 35 inches for women or greater than 40 inches for men. To correctly measure your waist, stand and place a tape measure around your middle, just above your hipbones.

Measure your waist just after you breathe out. The table Risks of Obesity-Associated Diseases by BMI and Waist Circumference provides you with an idea of whether your BMI combined with your waist circumference increases your risk for developing obesity-associated diseases or conditions.

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.

Tool: BMI and waist circumference calculator - Mayo Clinic Article CAS Google Scholar Taylor AE, Ebrahim Instills a sense of well-being, Ben-Shlomo Y, et circumfeeence Comparison of the associations Waaist body mass index circumterence measures Waist circumference and body shape assessment central adiposity and fat shae with Home remedies for acne shapf disease, diabetes, and all-cause mortality: a study using data from 4 UK cohorts. Qiao Q, Nyamdorj R. Sex-based differences in fat distribution may explain differences between the sexes in VO 2 max, as well as differences between obesity indexes. et al. org Ross R, Berentzen T, Bradshaw AJ, et al: Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference?.
How to Measure Height and Weight for BMI Sui X, LaMonte MJ, Laditka JN, et al: Cardiorespiratory fitness and adiposity as mortality predictors in older adults. The failure of BMI to fully capture cardiometabolic risk is partially related to the fact that BMI in isolation is an insufficient biomarker of abdominal adiposity. O'Neill, T. You may also have health benefits that are not directly related to weight loss. These classifications were later interpreted by Ahmed Kissebah and colleagues as upper versus lower body fat accumulation as reflected by a high or low waist—hip circumference ratio WHR , respectively International Diabetes Federation.
Body shape index - Wikipedia people with poor physical fitness may gain weight and become more obese. Greenland, P. PubMed Google Scholar Church, T. Lewis, G. The two most common ways to measure abdominal obesity are waist circumference and waist size compared to hip size, also known as the waist-to-hip ratio.
The Importance of Waist Circumference Related Topics. Download citation. Obesity Epidemiology. After 16 years, women who had reported the highest waist sizes — 35 inches or higher —had nearly double the risk of dying from heart disease, compared to women who had reported the lowest waist sizes less than 28 inches. Being underweight is also a health risk.

Waist circumference and body shape assessment -

The table Risks of Obesity-Associated Diseases by BMI and Waist Circumference provides you with an idea of whether your BMI combined with your waist circumference increases your risk for developing obesity-associated diseases or conditions.

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.

The BMI score means the following: BMI Underweight Below Risk Factors High blood pressure hypertension High LDL cholesterol "bad" cholesterol Low HDL cholesterol "good" cholesterol High triglycerides High blood glucose sugar Family history of premature heart disease Physical inactivity Cigarette smoking.

Healthy Weight Tip Waist circumference can help assess your weight and associated health risk. Check Your BMI The BMI Calculator is an easy-to-use online tool to help you estimate body fat. Back to top. Related Government Websites Health and Human Services external link National Institutes of Health Office of the Inspector General external link USA.

When BMI and waist circumference are considered as continuous variables in the same risk prediction model, waist circumference remains a positive predictor of risk of death, but BMI is unrelated or negatively related to this risk. The improved ability of waist circumference to predict health outcomes over BMI might be at least partially explained by the ability of waist circumference to identify adults with increased VAT mass.

For practitioners, the decision to include a novel measure in clinical practice is driven in large part by two important, yet very different questions. The first centres on whether the measure or biomarker improves risk prediction in a specific population for a specific disease. For example, does the addition of a new risk factor improve the prognostic performance of an established risk prediction algorithm, such as the Pooled Cohort Equations PCE or Framingham Risk Score FRS in adults at risk of CVD?

The second question is concerned with whether improvement in the new risk marker would lead to a corresponding reduction in risk of, for example, cardiovascular events. In many situations, even if a biomarker does not add to risk prediction, it can still serve as an excellent target for risk reduction.

Here we consider the importance of waist circumference in clinical settings by addressing these two questions. The evaluation of the utility of any biomarker, such as waist circumference, for risk prediction requires a thorough understanding of the epidemiological context in which the risk assessment is evaluated.

In addition, several statistical benchmarks need to be met in order for the biomarker to improve risk prediction beyond traditional measures.

These criteria are especially important for waist circumference, as established sex-specific and ethnicity-specific differences exist in waist circumference threshold levels 55 , In , the American Heart Association published a scientific statement on the required criteria for the evaluation of novel risk markers of CVD 57 , followed by recommendations for assessment of cardiovascular risk in asymptomatic adults in ref.

Novel biomarkers must at the very least have an independent statistical association with health risk, after accounting for established risk markers in the context of a multivariable epidemiological model. This characteristic alone is insufficient, however, as many novel biomarkers meet this minimum standard yet do not meaningfully improve risk prediction beyond traditional markers.

More stringent benchmarks have therefore been developed to assess biomarker utility, which include calibration , discrimination 58 and net reclassification improvement Therefore, to critically evaluate waist circumference as a novel biomarker for use in risk prediction algorithms, these stringent criteria need to be applied.

Numerous studies demonstrate a statistical association between waist circumference and mortality and morbidity in epidemiological cohorts. Notably, increased waist circumference above these thresholds was associated with increased relative risk of all-cause death, even among those with normal BMI In the USA, prospective follow-up over 9 years of 14, black, white and mixed ethnicity participants in the Atherosclerosis Risk in Communities study showed that waist circumference was associated with increased risk of coronary heart disease events; RR 1.

Despite the existence of a robust statistical association with all-cause death independent of BMI, there is no solid evidence that addition of waist circumference to standard cardiovascular risk models such as FRS 62 or PCE 63 improves risk prediction using more stringent statistical benchmarks.

For example, a study evaluating the utility of the PCE across WHO-defined classes of obesity 42 in five large epidemiological cohorts comprised of ~25, individuals assessed whether risk discrimination of the PCE would be improved by including the obesity-specific measures BMI and waist circumference The researchers found that although each measure was individually associated BMI: HR 1.

On the basis of these observations alone, one might conclude that the measure of waist circumference in clinical settings is not supported as risk prediction is not improved. However, Nancy Cook and others have demonstrated how difficult it is for the addition of any biomarker to substantially improve prognostic performance 59 , 66 , 67 , Furthermore, any additive value of waist circumference to risk prediction algorithms could be overwhelmed by more proximate, downstream causative risk factors such as elevated blood pressure and abnormal plasma concentrations of glucose.

In other words, waist circumference might not improve prognostic performance as, independent of BMI, waist circumference is a principal driver of alterations in downstream cardiometabolic risk factors. A detailed discussion of the merits of different approaches for example, c-statistic, net reclassification index and discrimination index to determine the utility of novel biomarkers to improve risk prediction is beyond the scope of this article and the reader is encouraged to review recent critiques to gain insight on this important issue 66 , Whether the addition of waist circumference improves the prognostic performance of established risk algorithms is a clinically relevant question that remains to be answered; however, the effect of targeting waist circumference on morbidity and mortality is an entirely different issue of equal or greater clinical relevance.

Several examples exist in the literature where a risk marker might improve risk prediction but modifying the marker clinically does not impact risk reduction.

For example, a low level of HDL cholesterol is a central risk factor associated with the risk of coronary artery disease in multiple risk prediction algorithms, yet raising plasma levels of HDL cholesterol pharmacologically has not improved CVD outcomes Conversely, a risk factor might not meaningfully improve statistical risk prediction but can be an important modifiable target for risk reduction.

Indeed, we argue that, at any BMI value, waist circumference is a major driver of the deterioration in cardiometabolic risk markers or factors and, consequently, that reducing waist circumference is a critical step towards reducing cardiometabolic disease risk.

As we described earlier, waist circumference is well established as an independent predictor of morbidity and mortality, and the full strength of waist circumference is realized after controlling for BMI.

We suggest that the association between waist circumference and hard clinical end points is explained in large measure by the association between changes in waist circumference and corresponding cardiometabolic risk factors.

For example, evidence from randomized controlled trials RCTs has consistently revealed that, independent of sex and age, lifestyle-induced reductions in waist circumference are associated with improvements in cardiometabolic risk factors with or without corresponding weight loss 71 , 72 , 73 , 74 , 75 , These observations remain consistent regardless of whether the reduction in waist circumference is induced by energy restriction that is, caloric restriction 73 , 75 , 77 or an increase in energy expenditure that is, exercise 71 , 73 , 74 , We have previously argued that the conduit between change in waist circumference and cardiometabolic risk is visceral adiposity, which is a strong marker of cardiometabolic risk Taken together, these observations highlight the critical role of waist circumference reduction through lifestyle behaviours in downstream reduction in morbidity and mortality Fig.

An illustration of the important role that decreases in waist circumference have for linking improvements in lifestyle behaviours with downstream reductions in the risk of morbidity and mortality.

The benefits associated with reductions in waist circumference might be observed with or without a change in BMI. In summary, whether waist circumference adds to the prognostic performance of cardiovascular risk models awaits definitive evidence.

However, waist circumference is now clearly established as a key driver of altered levels of cardiometabolic risk factors and markers. Consequently, reducing waist circumference is a critical step in cardiometabolic risk reduction, as it offers a pragmatic and simple target for managing patient risk.

The combination of BMI and waist circumference identifies a high-risk obesity phenotype better than either measure alone. We recommend that waist circumference should be measured in clinical practice as it is a key driver of risk; for example, many patients have altered CVD risk factors because they have abdominal obesity.

Waist circumference is a critical factor that can be used to measure the reduction in CVD risk after the adoption of healthy behaviours. Evidence from several reviews and meta-analyses confirm that, regardless of age and sex, a decrease in energy intake through diet or an increase in energy expenditure through exercise is associated with a substantial reduction in waist circumference 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , For studies wherein the negative energy balance is induced by diet alone, evidence from RCTs suggest that waist circumference is reduced independent of diet composition and duration of treatment Whether a dose—response relationship exists between a negative energy balance induced by diet and waist circumference is unclear.

Although it is intuitive to suggest that increased amounts of exercise would be positively associated with corresponding reductions in waist circumference, to date this notion is not supported by evidence from RCTs 71 , 74 , 89 , 90 , A doubling of the energy expenditure induced by exercise did not result in a difference in waist circumference reduction between the exercise groups.

A significant reduction was observed in waist circumference across all exercise groups compared with the no-exercise controls, with no difference between the different prescribed levels Few RCTs have examined the effects of exercise intensity on waist circumference 74 , 90 , 91 , However, no significant differences were observed in VAT reduction by single slice CT between high-intensity and low-intensity groups.

However, the researchers did not fix the level of exercise between the intensity groups, which might explain their observations. Their observations are consistent with those of Slentz and colleagues, whereby differences in exercise intensity did not affect waist circumference reductions.

These findings are consistent with a meta-analysis carried out in wherein no difference in waist circumference reduction was observed between high-intensity interval training and moderate-intensity exercise In summary, current evidence suggests that increasing the intensity of exercise interventions is not associated with a further decrease in waist circumference.

VAT mass is not routinely measured in clinical settings, so it is of interest whether reductions in waist circumference are associated with corresponding reductions in VAT.

Of note, to our knowledge every study that has reported a reduction in waist circumference has also reported a corresponding reduction in VAT. Thus, although it is reasonable to suggest that a reduction in waist circumference is associated with a reduction in VAT mass, a precise estimation of individual VAT reduction from waist circumference is not possible.

Nonetheless, the corresponding reduction of VAT with waist circumference in a dose-dependent manner highlights the importance of routine measurement of waist circumference in clinical practice.

Of particular interest to practitioners, several reviews have observed significant VAT reduction in response to exercise in the absence of weight loss 80 , Available evidence from RCTs suggests that exercise is associated with substantial reductions in waist circumference, independent of the quantity or intensity of exercise.

Exercise-induced or diet-induced reductions in waist circumference are observed with or without weight loss. We recommend that practitioners routinely measure waist circumference as it provides them with a simple anthropometric measure to determine the efficacy of lifestyle-based strategies designed to reduce abdominal obesity.

The emergence of waist circumference as a strong independent marker of morbidity and mortality is striking given that there is no consensus regarding the optimal protocol for measurement of waist circumference. Moreover, the waist circumference protocols recommended by leading health authorities have no scientific rationale.

In , a panel of experts performed a systematic review of studies to determine whether measurement protocol influenced the relationship between waist circumference, morbidity and mortality, and observed similar patterns of association between the outcomes and all waist circumference protocols across sample size, sex, age and ethnicity Upon careful review of the various protocols described within the literature, the panel recommended that the waist circumference protocol described by the WHO guidelines 98 the midpoint between the lower border of the rib cage and the iliac crest and the NIH guidelines 99 the superior border of the iliac crest are probably more reliable and feasible measures for both the practitioner and the general public.

This conclusion was made as both waist circumference measurement protocols use bony landmarks to identify the proper waist circumference measurement location.

The expert panel recognized that differences might exist in absolute waist circumference measures due to the difference in protocols between the WHO and NIH methods. However, few studies have compared measures at the sites recommended by the WHO and NIH.

Jack Wang and colleagues reported no difference between the iliac crest and midpoint protocols for men and an absolute difference of 1. Consequently, although adopting a standard approach to waist circumference measurement would add to the utility of waist circumference measures for obesity-related risk stratification, the prevalence estimates of abdominal obesity in predominantly white populations using the iliac crest or midpoint protocols do not seem to be materially different.

However, the waist circumference measurements assessed at the two sites had a similar ability to screen for the metabolic syndrome, as defined by National Cholesterol Education Program, in a cohort of 1, Japanese adults Several investigations have evaluated the relationship between self-measured and technician-measured waist circumference , , , , Instructions for self-measurement of waist circumference are often provided in point form through simple surveys Good agreement between self-measured and technician-measured waist circumference is observed, with strong correlation coefficients ranging between 0.

Moreover, high BMI and large baseline waist circumference are associated with a larger degree of under-reporting , Overall these observations are encouraging and suggest that self-measures of waist circumference can be obtained in a straightforward manner and are in good agreement with technician-measured values.

Currently, no consensus exists on the optimal protocol for measurement of waist circumference and little scientific rationale is provided for any of the waist circumference protocols recommended by leading health authorities.

The waist circumference measurement protocol has no substantial influence on the association between waist circumference, all-cause mortality and CVD-related mortality, CVD and T2DM.

Absolute differences in waist circumference obtained by the two most often used protocols, iliac crest NIH and midpoint between the last rib and iliac crest WHO , are generally small for adult men but are much larger for women.

The classification of abdominal obesity might differ depending on the waist circumference protocol. We recommend that waist circumference measurements are obtained at the level of the iliac crest or the midpoint between the last rib and iliac crest.

The protocol selected to measure waist circumference should be used consistently. Self-measures of waist circumference can be obtained in a straightforward manner and are in good agreement with technician-measured values.

Current guidelines for identifying obesity indicate that adverse health risk increases when moving from normal weight to obese BMI categories.

Moreover, within each BMI category, individuals with high waist circumference values are at increased risk of adverse health outcomes compared with those with normal waist circumference values Thus, these waist circumference threshold values were designed to be used in place of BMI as an alternative way to identify obesity and consequently were not developed based on the relationship between waist circumference and adverse health risk.

In order to address this limitation, Christopher Ardern and colleagues developed and cross-validated waist circumference thresholds within BMI categories in relation to estimated risk of future CVD using FRS The results of their study revealed that the current recommendations that use a single waist circumference threshold across all BMI categories are insufficient to identify those at increased health risk.

In both sexes, the use of BMI category-specific waist circumference thresholds improved the identification of individuals at a high risk of future coronary events, leading the authors to propose BMI-specific waist circumference values Table 1.

For both men and women, the Ardern waist circumference values substantially improved predictions of mortality compared with the traditional values. These observations are promising and support, at least for white adults, the clinical utility of the BMI category-specific waist circumference thresholds given in Table 1.

Of note, BMI-specific waist circumference thresholds have been developed in African American and white men and women Similar to previous research, the optimal waist circumference thresholds increased across BMI categories in both ethnic groups and were higher in men than in women.

However, no evidence of differences in waist circumference occurred between ethnicities within each sex Pischon and colleagues investigated the associations between BMI, waist circumference and risk of death among , adults from nine countries in the European Prospective Investigation into Cancer and Nutrition cohort Although the waist circumference values that optimized prediction of the risk of death for any given BMI value were not reported, the findings reinforce the notion that waist circumference thresholds increase across BMI categories and that the combination of waist circumference and BMI provide improved predictions of health risk than either anthropometric measure alone.

Ethnicity-specific values for waist circumference that have been optimized for the identification of adults with elevated CVD risk have been developed Table 2.

With few exceptions, the values presented in Table 2 were derived using cross-sectional data and were not considered in association with BMI. Prospective studies using representative populations are required to firmly establish ethnicity-specific and BMI category-specific waist circumference threshold values that distinguish adults at increased health risk.

As noted above, the ethnicity-specific waist circumference values in Table 2 were optimized for the identification of adults with elevated CVD risk.

The rationale for using VAT as the outcome was that cardiometabolic risk was found to increase substantially at this VAT level for adult Japanese men and women We recommend that prospective studies using representative populations are carried out to address the need for BMI category-specific waist circumference thresholds across different ethnicities such as those proposed in Table 1 for white adults.

This recommendation does not, however, diminish the importance of measuring waist circumference to follow changes over time and, hence, the utility of strategies designed to reduce abdominal obesity and associated health risk.

The main recommendation of this Consensus Statement is that waist circumference should be routinely measured in clinical practice, as it can provide additional information for guiding patient management.

Indeed, decades of research have produced unequivocal evidence that waist circumference provides both independent and additive information to BMI for morbidity and mortality prediction. On the basis of these observations, not including waist circumference measurement in routine clinical practice fails to provide an optimal approach for stratifying patients according to risk.

The measurement of waist circumference in clinical settings is both important and feasible. Self-measurement of waist circumference is easily obtained and in good agreement with technician-measured waist circumference.

Gaps in our knowledge still remain, and refinement of waist circumference threshold values for a given BMI category across different ages, by sex and by ethnicity will require further investigation.

To address this need, we recommend that prospective studies be carried out in the relevant populations. Despite these gaps in our knowledge, overwhelming evidence presented here suggests that the measurement of waist circumference improves patient management and that its omission from routine clinical practice for the majority of patients is no longer acceptable.

Accordingly, the inclusion of waist circumference measurement in routine practice affords practitioners with an important opportunity to improve the care and health of patients. Health professionals should be trained to properly perform this simple measurement and should consider it as an important vital sign to assess and identify, as an important treatment target in clinical practice.

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More than 60 years ago, the Shspe physician Jean Vague observed that Waaist with larger waists had Wasit higher risk Waist circumference and body shape assessment premature cardiovascular disease and death than people who Home remedies for acne trimmer waists or carried more of their xssessment around their Wzist and thighs. In Black pepper extract for skin health who Waizt not overweight, having a large waist may mean that they are at higher risk of health problems than someone with a trim waist. What is it about abdominal fat that makes it strong marker of disease risk? The fat surrounding the liver and other abdominal organs, so-called visceral fat, is very metabolically active. It releases fatty acids, inflammatory agents, and hormones that ultimately lead to higher LDL cholesterol, triglycerides, blood glucose, and blood pressure. Scientists have long debated which measure of abdominal fat is the best predictor of health risk: Waist size alone or waist-to-hip ratio. The research to date has been mixed. Waist circumference and body shape assessment Obese Canadians are four times Polyphenols and cardiovascular health likely to have WWaist, more than Waist circumference and body shape assessment times as likely to circumferemce high blood pressure and more assessmejt two circumferennce more Home remedies for acne asessment have heart disease than those with a healthy weight. However, simply knowing your weight is not enough to know your health risk. Did you know that you can have a healthy weight, but still be at increased risk? How our bodies store excess weight specifically fat can negatively impact our health. Today, there are two methods of self-assessment that can give you a clearer picture of how your weight may be affecting your health — measuring your waistline and calculating your Body Mass Index BMI. Measuring waist circumference can help to assess obesity-related health risk. Even at a healthy weight, excess fat carried around the waist can increase your risk of high blood pressure, high [blood] cholesterol, heart disease and type-2 diabetes.

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