Waist circumference and abdominal obesity measurement -
Some cross-sectional results regarding the waist circumference in the Tromsø 6 survey — have been published [ 26 ], but not in any detail.
The prevalence of abdominal obesity in Tromsø 6 — was somewhat lower than for non-Hispanic white subjects in the US [ 32 ]. The US data were based on the NHANES, and the waist circumference was measured just above the iliac crest.
In men, the prevalence of abdominal obesity was somewhat higher than in another Norwegian population study, the HUNT study [ 14 ], which used very similar screening methods and was conducted at the same time as Tromsø 4 and Tromsø 6 HUNT 2 in — and HUNT 3 in — In this Tromsø population, the prevalence of obesity as assessed by general obesity BMI [ 22 ] and abdominal obesity waist circumference the present study differs considerably, the latter being higher.
This is in accordance with previous studies [ 10 , 14 , 33 ] and may indicate that the WHO criteria for general and abdominal obesity need to be harmonized.
In the analyses, we chose to concentrate on waist circumference rather than e. The primary reason was that both these measures of anthropometry are strongly correlated to waist circumference.
We also note that there is a strong tracking for abdominal obesity, as we have previously demonstrated for general obesity [ 35 ] and that the increase in waist circumference during — was for both men and women significantly larger than can be expected from the increases in body mass index and age.
This is in accordance with findings from some previous studies [ 8 , 9 ]. It is also a significant strength that all the data concerning waist circumference were based on measurements using standardized procedures. However, waist circumference is prone to measurement error [ 29 ], and to avoid the effect of any possible systematic differences in how the circumference were measured at the surveys, z-scores were computed.
When comparing the longitudinal results based on the actual measured waist circumference and the z-score analyses, the conclusions regarding the longitudinal changes were unchanged. This further strengthens the results from the longitudinal analyses of the waist circumference.
There are also limitations, however. It is well known that attenders to a health survey tend to differ from non-attenders as the latter group generally has more health problems, higher mortality and were of lower socioeconomic status.
This has been found both in the Tromsø Study [ 25 , 36 ] and in similar studies in Norway [ 37 , 38 ]. Furthermore, subjects who attended both the Tromsø 4 and Tromsø 6 survey had in Tromsø 4 1. These were subjects who were not invited to the survey, chose not attend, had moved out of Tromsø or had died.
This relatively minor difference in waist circumference, although statistically significant, is of particular importance for longitudinal analyses presented in this study. We consider that it is unlikely that any major bias has been introduced, but we cannot exclude that selective attrition has had an impact on our findings, particularly in the older age groups.
If men and women with high waist circumference in Tromsø 4 died or chose not to attend 13 years later, a relatively low increase in the waist circumference from Tromsø 4 to Tromsø 6 will be the result in the subjects available for the presented analyses.
However, even if subjects aged 65—69 in Tromsø 4, i. The waist circumference may be measured in different ways like at the level of belly button, the top of the iliac crest, or the minimal waist circumference [ 5 ]. Assessment of waist circumference is, as noted above, more difficult to standardize than e.
This has without doubt resulted in misclassification and it hampers the comparison with other studies. A further limitation in our study is the low number of subjects in some age groups, particularly in Tromsø 4. High waist circumference has been linked to a number of chronic diseases, and the relationships has been considered both strong and convincing by the World Health Organization [ 5 ], and an increase in waist circumference has detrimental metabolic consequences [ 39 ].
The relationships between waist circumference and mortality may be attenuated in older subjects, though [ 3 , 40 ]. Our findings from both cross-sectional and longitudinal analyses of an increased mean waist circumference, and particularly that the increase is inversely associated with age, are therefore of concern.
There is a need for further longitudinal studies of the changes in waist circumference and the predictors for it. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk.
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Scand J Public Health. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. It also offers information based on your personal results. Your BMI is a guide to tell you if you are the correct weight for your height.
Your BMI can give an indication of your chance of developing weight-related disease such as diabetes. NEED TO LOSE WEIGHT? BMI is not always accurate for assessing healthy weight in some people. People carry fat in different parts of their bodies. Some people carry extra body fat around their middle.
This is more of a health risk than carrying weight on your hips and thighs. This is the dangerous internal fat that coats your organs. Measuring visceral fat can give a more accurate predictor of some health conditions. These include:. These waist circumference measurements only apply to adults.
Overweight and obesity are health conditions of excess weight. Being overweight, especially being obese, can increase your risk of developing serious health problems, including:. Many of these diseases can be prevented by having a healthy weight and a healthy lifestyle.
This includes eating a well-balanced diet and doing regular physical activity. These benefits can be a lower your risk of getting heart disease or type 2 diabetes. ARE YOU AT RISK?
Use the Risk Checker to find out. Probably the most successful way for weight loss is to make a change to your lifestyle. Try to eat food that is healthier and do more physical activity like exercise.
It will still result in important health improvements. Some people may need a more intensive approach. This can mean having a very low energy diet or taking weight loss medicine. Some people may need bariatric surgery. This is especially likely in those who are obese or have other risk factors.
Waist circumference and BMI are important indicators of risk. However, many other factors also contribute to disease. Remember, increased physical activity and improved diet will help reduce your risk of disease. You may also have health benefits that are not directly related to weight loss.
Learn more here about the development and quality assurance of healthdirect content. Read more on Heart Foundation website. BMI was defined as body weight kilograms divided by the square of body height meters.
WC-IC was measured in the horizontal plane at the superior border of the right iliac crest. WC-mid was measured in the horizontal plane midway between lowest rib and the iliac crest. Both WC-IC and WC-mid were measured to the nearest 0.
Before recording the measurement, the nurse would ensure that the tape was snug but did not compress the skin and was parallel to the floor.
The reproducibility was assessed. WC-IC and WC-mid were measured repeatedly in 10 men and 10 women by 3 trained nurses on 3 consecutive days. The coefficients of variation for WC-IC were 0. The coefficients of variation for WC-mid were 0.
Blood pressure was recorded to the nearest 2 mmHg by a mercury sphygmomanometer with the arm supported at heart level after sitting quietly for 10 min. Well-trained nurses took three separate readings at 1-min intervals. The average of the last two readings was used for analysis.
FPG was measured after fasting for at least 8 h. A standard oral g glucose tolerance test was performed to measure 2-h postprandial plasma glucose 2hPG.
Plasma glucose and fasting serum total cholesterol, triglycerides TG , HDL cholesterol HDL-C , LDL cholesterol LDL-C , and high-sensitivity C-reactive protein hsCRP concentrations were measured with an automatic analyzer Toshiba TBA FR; Toshiba Medical Systems Co.
HbA 1c was measured by automatic analyzers HLC G7 HPLC systems; Tosoh Corporation, Tokyo, Japan. The HbA 1c assay was certified by the National Glycohemoglobin Standardization Program 23 and standardized to the Diabetes Control and Complications Trial reference assay.
Imaging of each subject in a supine position was performed on a MDCT scanner LightSpeed 16; GE Healthcare, Milwaukee, WI kVp, mAs, slice thickness 5 mm.
Image analysis software ImageJ, version 1. MS was defined in accordance with the updated NCEP ATP III guideline 7. Data are presented as means and SDs for continuous variables and as a percentage for categorical variables. Pearson correlation coefficients and partial correlation coefficients were used to assess the relationship among WC, abdominal fat areas, and metabolic variables.
The association of the different diagnostic criteria for central obesity with high VFA and with metabolic disease was analyzed by receiver operating characteristic ROC curve analysis. ROC statistics were calculated by using percentile values of disease case measures relative to the corresponding marker distribution among controls 25 , Age was adjusted with a linear regression approach.
CIs were calculated by bootstrap methods. Kaplan-Meier failure curves were used to estimate the cumulative incidence of hypertension, diabetes, and MS in individuals with and without central obesity defined by WC-IC or WC-mid cutoff values.
The results were tested by Cox proportional hazard model adjusted for age. WC-IC and WC-mid were less correlated in women.
The partial correlation coefficients adjusted for age in men and women were 0. There were participants, including males and females, who underwent abdominal CT for assessment of abdominal fat areas.
Comparing participants with and without CT measurements, those who had CT evaluations showed slightly higher HDL-C 52 ± 12 vs. Women with CT measurement had higher WC-IC than women without CT measurement 85 ± 9 vs.
As shown in Table 2 , both WC-IC and WC-mid correlated significantly with BMI, total abdominal fat area, VFA, and SFA. The data presented in Supplementary Table 1 show that both WC-IC and WC-mid correlated significantly with systolic and diastolic blood pressure, FPG, 2hPG, HbA 1c , TG, HDL-C, and hsCRP in both sexes, and WC-mid was better correlated than WC-IC with these metabolic variables in both sexes.
Similar findings were noted after adjusting for age data not shown. Results in Table 3 show that the identification of individuals with hypertension, diabetes, and MS by WC-IC and WC-mid was fair AUC 0. The optimal cutoffs for WC-IC and WC-mid varied, depending on which disease to identify.
Generally, WC-IC was more sensitive, whereas WC-mid was more specific. WC-mid had a higher age-adjusted AUC than WC-IC for diabetes in men, hypertension in women, and MS in both sexes Supplementary Table 2.
The data in Supplementary Table 3 show that WC-mid at its optimal cutoffs had the highest AUC for hypertension in females and diabetes and MS in both sexes. The differences in AUC for hypertension, diabetes, and MS among four criteria were larger in women 0.
There were 1, subjects who stayed in the study for at least 12 months. The median follow-up period was 31 months. The data in Table 3 indicate that the performance of WC-IC and WC-mid to predict incident hypertension, diabetes, and MS was fair AUC 0.
The optimal cutoff values for WC-IC and WC-mid to predict different diseases varied, and WC-IC was more sensitive, whereas WC-mid was more specific. As demonstrated by the data in Supplementary Table 2 , there was no significant difference between WC-IC and WC-mid to predict hypertension, diabetes, or MS.
However, WC-mid had slightly higher AUCs than WC-IC for diabetes and for hypertension in women both age-adjusted P values 0.
Data in Supplementary Table 3 show that the best criteria for highest AUC depended on the disease to be predicted and the sex to be considered. There were subjects, including men and women, who did not have hypertension at baseline.
During the follow-up period median As shown in Fig. There were subjects, including men and women, who did not have diabetes at baseline. During follow-up median There were subjects, including men and women, who had less than two components of MS at baseline.
Different definitions of central obesity to predict metabolic diseases. Kaplan-Meier curves for the cumulative incidence of developing hypertension A and B , diabetes C and D , or MS E and F by WC-IC A , C , and E or WC-mid B , D , and F to define central obesity.
Age-adjusted P values are shown. F, female; M, male. To the best of our knowledge, this is the first comprehensive study to compare different measurements of WC to define central obesity. We showed that WC-mid predicts high VFA better than WC-IC in women.
Correlation, as compared by AUC, with hypertension, diabetes, and MS was better by WC-mid criteria than WC-IC criteria. However, the performance of WC-IC and WC-mid to predict hypertension, diabetes, and MS was similar, although only central obesity by WC-mid criteria, and not WC-IC criteria, predicted future diabetes incidence.
Overall, our findings suggest that WC-mid is a better measurement of central obesity than WC-IC. It is practical to keep the current cutoffs for central obesity i.
Using these cutoffs, in the current study, we found that the sensitivity of WC-IC measurement values for identifying or predicting hypertension, diabetes, and MS was greater than that of WC-mid measurements. Since central obesity is a screening tool for metabolic diseases, higher sensitivity of WC-IC values may be a desirable attribute.
Furthermore, WC-IC can be more precisely located than WC-mid, which may make it more consistent during follow-up. In contrast, WC-mid correlated better to VFA and metabolic variables and worked better to identify and predict metabolic diseases in the current study.
These findings suggest that WC-mid is a better measurement for central obesity. Indeed, when optimal cutoffs were used, WC-mid showed better performance than WC-IC did, with more balanced sensitivity and specificity.
Furthermore, although measurement of WC-mid is a slightly more complex procedure, findings from the current study and from Mason and Katzmarzyk 27 have shown that the reproducibility of WC-mid measurement is also high. Thus, if modification of the cutoffs for central obesity is to be considered, WC-mid is a better location of measurement than WC-IC.
The impact of the location of WC measurement varies by sex. In the current study, the difference between WC-IC and WC-mid was larger in women 5. This may explain why the differences between the correlation coefficients of VFA to WC-IC and WC-mid were larger in women than in men in present study Table 2.
Also, the differences in AUC among the four WC criteria used to identify these diseases were larger in women than in men Supplementary Table 3 , and similar findings were also reported in the previous study in Caucasians In that study, the differences between WC-IC and WC-mid were 0.
All of these findings suggest that the location of WC measurement has greater impact in women than in men. The optimal cutoffs depend on the diseases to be identified or predicted.
In the current study, the optimal cutoffs for both WC-IC and WC-mid were all different Table 3. Supporting our findings, the optimal cutoffs for WC were also different for different metabolic diseases in another large cross-sectional study in Taiwan that included 55, people In that study, optimal cutoffs were determined based on the performance for identifying at least one disease, including hypertension, diabetes, and dyslipidemia.
Moreover, there have been two Chinese studies investigating the optimal cutoffs based on the relationship of WC to VFA 18 , Bao et al.
Body fat can be abxominal in several ways, with each circumfference fat assessment method having pros and cons. Circumferencce is a brief Refillable toiletries of Boosting energy with healthy foods of the abdominall popular Boosting energy with healthy foods for measuring body fat-from basic body measurements to high-tech body scans-along with their strengths and limitations. Adapted from 1. Like the waist circumference, the waist-to-hip ratio WHR is also used to measure abdominal obesity. Equations are used to predict body fat percentage based on these measurements. BIA equipment sends a small, imperceptible, safe electric current through the body, measuring the resistance. Mayo Clinic does Boosting energy with healthy foods endorse companies or products. Advertising revenue Waisst our not-for-profit mission. Check out these icrcumference and special offers abdminal books and newsletters from Mayo Clinic Press. This content does not have an English version. This content does not have an Arabic version. Mayo Clinic Press Check out these best-sellers and special offers on books and newsletters from Mayo Clinic Press.
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