Waist circumference and self-image -
Development and validation of instruments measuring body image and body weight dissatisfaction in South African mothers and their daughters.
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Int J Obes Lond. Article CAS PubMed Central Google Scholar. Gillen MM. NCD Countdown collaborators. NCD Countdown Worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target Lancet London, England. Download references. Biomedical Sport Studies Center, University of Ferrara, Ferrara, Italy.
University Center for Studies on Gender Medicine, University of Ferrara, Ferrara, Italy. You can also search for this author in PubMed Google Scholar.
EGR, LZ, NR, BB conceived and designed the study. BB, NR, JM collected anthropometric and body image perception data. LZ, NR, JM conducted data analyses. EGR, LZ, NR drafted the manuscript.
All authors read, and approved the final manuscript. Correspondence to Natascia Rinaldo or Barbara Bramanti. All study participants provided informed consent and the study protocol was approved by the Ethics Committee for Biomedical Research of Ferrara.
This observational study was performed consistently with the approved guidelines. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Reprints and permissions. Zaccagni, L. et al. Body image perception and body composition: assessment of perception inconsistency by a new index. J Transl Med 18 , 20 Download citation. Received : 04 June Accepted : 28 December Published : 14 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. Research Open access Published: 14 January Body image perception and body composition: assessment of perception inconsistency by a new index Luciana Zaccagni 1 , 2 , Natascia Rinaldo ORCID: orcid.
Abstract Background A correct perception of the body image, as defined by comparison with actual anthropometric analyses, is crucial to ensure the best possible nutritional status of each individual. Methods We investigated young Italian adults mean age of males: Results Based on ideal and feel body image comparison, women showed higher dissatisfaction than men and preferred slimmer silhouettes.
Conclusions Our findings suggest that FAI FAT is an appropriate index for assessing the perceived fat status from the body image when compared with data obtained by BIA. Background An adequate nutritional status is essential to maintain healthy conditions in singular individuals and populations.
Methods Sample We carried out a cross-sectional study on a sample of Italian students in the Faculty of Medicine, Pharmacy and Prevention at the University of Ferrara North-Italy by convenience sampling selection.
Procedures Stature and weight were measured according to standardized procedures [ 35 ] by trained operators with a mechanical scale precision 0.
Statistical analyses Distribution normality was assessed by sex Kolmogorov—Smirnov test. Results In Table 1 , we summarized the mean anthropometric values and the mean body image indicators derived from the sample separately by sex.
Table 1 Anthropometric characteristics, body image perception, weight-status and fat-status by sex Full size table. Table 2 Body image perception by sex and fat-status categories Full size table.
Table 4 Body image perception inconsistency by sex and fat-status categories Full size table. Full size image. Discussion In this study, we examined the body composition and the body image perception of a sample of Italian University students and we proposed a new index, FAI FAT , in order to evaluate the inconsistency between the perceived body image and the measured fat status.
Conclusions Our new proposed index contributes to the literature a proxy measure of general appropriateness of body image perception according to fat status.
Availability of data and materials The data of this study are not publicly available, but they are available from the corresponding authors upon reasonable request. References Allison DB, Faith MS, Heo M, Kotler DP.
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Article PubMed PubMed Central Google Scholar Brennan MA, Lalonde CE, Bain JL. 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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waist circumference ; computed tomography ; abdominal CT ; mobile health ; health apps ; CT ; CT scan ; CT image ; mobile app ; app ; application ; waist ; body ; body mass ; BMI ; morbidity ; mortality ; clinical ; tool ; prototype ; design ; obesity ; abdominal ; usability ; validity ; medical.
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Free radicals and environmental pollutants you for visiting nature. Circumferecne are using Waist circumference and self-image circumfeerence version Wheezing limited support circumfference CSS. To obtain the best experience, we recommend you Adaptogen body rejuvenation a more up to date browser circumferencs turn self-imaeg compatibility mode cidcumference Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Despite decades of unequivocal evidence that waist circumference provides both independent and additive information to BMI for predicting morbidity and risk of death, this measurement is not routinely obtained in clinical practice. This Consensus Statement proposes that measurements of waist circumference afford practitioners with an important opportunity to improve the management and health of patients.Waist circumference and self-image -
We performed a preliminary validity study in which we compared WC measurements obtained both by the conventional method using a tape measurement in a standing position and by the mobile app using the last abdominal CT slice not showing the iliac bone.
Pearson correlation, student t tests, and Q-Q and Bland-Altman plots were used for statistical analysis. Moreover, to perform a diagnostic test evaluation, we also analyzed the accuracy of the app in detecting abdominal obesity.
Results: We developed a prototype of the app Measure It, which is capable of estimating WC from a single cross-sectional CT image. We used an estimation based on an ellipse formula adjusted to the gender of the patient.
The validity study included 20 patients 10 men and 10 women. Both the Q-Q dispersion plot and Bland-Altman analysis graphs showed good overlap with some dispersion of extreme values. Conclusions: This app is a simple and accessible mHealth tool to routinely measure WC as a valuable obesity indicator in clinical and research practice.
A usability and validity evaluation among medical teams will be the next step before its use in clinical trials and multicentric studies.
Obesity is a major public health problem worldwide, and the reliance on BMI measurements alone has proven insufficient to help assess obesity-related health risks in patients [ 1 ]. Waist circumference WC is a simple method to evaluate abdominal adiposity that is easy to standardize.
It is also an independent cardiovascular risk factor, with a higher predicting value than BMI [ 2 , 3 ]. However, this measurement is not routinely used in clinical practice. Recently, a computed tomography CT scan estimation became a valid measure of standing WC [ 4 , 5 ].
This method is truly valuable in retrospective studies, where it can be difficult to obtain such measurements. Moreover, conventional WC assessment using a measurement tape can be challenging in patients with intellectual or motor disabilities. However, for a radiologist, this method may require time and training.
Therefore, despite its widespread availability and limited cost, using CT images to assess WC is not routinely included in clinical and research practice.
Accordingly, the major aim of this study was to develop a mobile app to overcome these barriers and help clinicians routinely assess WC whenever a CT scan is available.
The development process involved three stages: determination of the principles of WC measurement from CT images, prototype design, and validation of the developed product. As validated by Ciudin et al [ 6 ], the abdominal perimeter was estimated using the formula of the perimeter of an ellipse Figure 1.
In this previous study, there was a good correlation between conventional standing WC measurement and ellipse-estimated WC, with a Pearson test of 0. Afterward, we performed WC measurement on 10 healthy candidates using both the conventional tape method and the ellipse formula.
We then used a simple linear regression analysis to adjust the final WC formula to the gender of the patient. After confirming the app requirements ellipse formula, required measurements, final formula applied to gender and the needed parameters, and organization of the steps required by the physician to ameliorate the user experience , we initiated the design and development of the app.
After preparing the app prototype, we performed a preliminary validity study including 20 patients selected retrospectively based on the existence of a previous WC measurement and CT scan images in their file. We compared the conventional WC measurement cWC method to the mobile app—based WC measurement mWC method based on CT scan images.
It was done in a standing position, at the end of a normal expiration. The second measurement was performed with the mobile app.
Using the camera of the phone, the app employused the last slice of the CT scan image, on the last slice, from cranial to caudal, not showing the iliac bone. Measurements were expressed as mean ± SD standard deviation and range. Data were collected and analyszed using SPSS 20 software SPSS Inc.
Student t test, Pearson correlation, Q-Q plot, and the Bland-Altman analysis were used. In order tTo perform a diagnostic test evaluation, we also analyszed the mWC accuracy in detecting abdominal obesity. At the end of the design stage, the app was demonstrated in several team meetings, which led to further modifications.
The patients were not involved in setting the research question or the outcome measures, designing or implementing the study, or reporting or disseminating the research. Additionally, the public did not participate in the design, implementation, reporting, or dissemination plans of this study.
Personal data have been respected. This study was approved by the ethics committee at Habib Bourguiba University Hospital in Sfax Ref CE Following the design principles and requirements, the prototype of the app was developed and named Measure It.
The flow of the app was designed to be simple and productive to ensure quality interaction between the app and the visitor Figure 2. A demo video was provided in the app to facilitate its use. The preliminary validation study included 20 patients.
It included 10 men and 10 women. The mean age was 54 SD 17 years. The mean BMI was 26 SD 4; women: mean The mean cWC was We also compared the two measurements using a Q-Q dispersion and a Bland-Altman plot.
The analysis graphs can be found in Figures 3 and 4. The Q-Q plot showed good overlap with some dispersion of extreme values. The Bland-Altman analysis showed a mean difference of 0. We have also performed a diagnostic test evaluation regarding the accuracy of the mWC in detecting abdominal obesity.
a These values are dependent on abdominal obesity prevalence [ 9 ]. Guidelines for the management of obesity from several professional societies recognize the importance of measuring WC in the context of risk stratification for future cardiometabolic morbidity and mortality [ 3 , 10 - 13 ].
Moreover, WC is gaining significant importance among surgeons since abdominal obesity has a growing value in preoperative risk assessment for morbidity and mortality in different surgeries [ 14 - 19 ]. We developed a prototype of the mobile app Measure It to accurately estimate WC using CT scan images.
The app was developed based on a validated method [ 5 , 6 ] measuring WC using CT scan cross-sectional images. To our knowledge, this is the first mobile app that helps physicians estimate WC. The app was designed to be a simple and accessible tool with the purpose of routinely including this valuable obesity parameter in clinical and research practice.
One of the most valuable advantages of our app is its usability in retrospective studies. WC measurements mostly do not exist in patient observations. However, CT scan slides or images are often available.
Moreover, the simplicity of the app may reduce the time required for physicians to assess WC [ 20 ]. Conventional tape measuring is sometimes not possible, particularly for patients who are disabled. Additionally, for a radiologist, the conventional CT scan method requires training and can be more or less time-consuming.
Eventually, being simple, accessible, and reproducible, the app may reduce the technology barriers for nontech physicians since smartphones are commonly available even in low- and middle-income countries [ 21 ].
As a screening tool for abdominal obesity, this attribute may be beneficial, especially in retrospective studies. However, the accuracy of WC measurement may be altered in some cases. This may be due to a measurement error in the conventional method or to particular body shapes and extreme values of WC.
One major problem with currently available mobile health apps is that few are established with strong research evidence [ 22 , 23 ]. Measure It is developed based on a strong statistical analysis, even though it needs to be validated in a prospective study.
The main limitation of this study is the small sample size used to validate the app. We consider this validity study as a preliminary validation that needs to be confirmed. Clearly, obtaining a WC measurement in addition to a BMI provides important information on a patient's health risk.
The additional health risk explained by the WC likely reflects its ability to act as a surrogate for abdominal, and in particular, visceral fat.
Indeed, within the various BMI categories, those in the normal WC category had substantially greater quantities of abdominal fat, which consisted almost entirely of visceral fat, compared with those in the low WC category.
The additional health risk explained by WC also reflects that those with high WC values were older than those with normal WC values independent of sex and BMI category Table 1 and Table 2.
Indeed, adjusting for age diminished the strength of the associations between high WC values and hypertension, diabetes, dyslipidemia, and the metabolic syndrome. However, a high WC remained a significant predictor of obesity-related comorbidity after adjusting for age and the other confounding variables.
In this study, the effects of a high WC were more apparent in the women than in the men. For example, in the overweight BMI category, the adjusted ORs for type 2 diabetes were 1. This sex difference may be partially explained by the fact that the prevalences of the metabolic diseases were considerably higher in the men than in the women with a low WC.
In reference to the example used above, 2. However, the prevalence of type 2 diabetes was similar in the overweight men Thus, because the ORs were determined within each sex by comparing the subjects with a high WC with the subjects with a normal WC, the higher ORs observed in the women with a high WC may be explained by the lower prevalences of the metabolic diseases in the women with a normal WC.
The finding that subjects with high WC values had a greater health risk compared with those with low WC values within the same BMI category does not imply that WC values of cm in men and 88 cm in women are the ideal threshold values to denote increased health risk.
The WC values that best predict health risk within the different BMI categories are unknown. Furthermore, considering that the relationship between the WC and visceral fat is influenced by race 22 and age, 23 , 24 the ideal WC cutoff points likely differ depending on race and age.
Additional studies are required to determine the ideal WC threshold values to use in combination with the BMI. The NIH classification system uses a dichotomous approach normal vs high to establish the associations between the WC and health risk. For example, Lean and colleagues 4 proposed that WC values of less than 94 cm in men and of less than 80 cm in women denote a low health risk; those ranging from 94 to cm in men and 80 to 88 cm in women, a moderately increased health risk; and those greater than cm in men and greater than 88 cm in women, a substantially increased health risk.
This finding also suggests that consideration of the WC in the same way as the BMI, in which there are more than 2 risk strata, might be more appropriate. Given that the subject pool was large and representative of the US population, the NHANES III was perhaps the best data set to test our hypothesis.
Nonetheless, our study has 2 limitations that should be recognized. First, the cross-sectional nature of this study precludes definitive causal inferences about the associations between the BMI and the WC and disease. However, numerous studies have shown that high BMI and WC values precede the onset of morbidity and mortality.
However, previous NHANES studies have shown little bias due to nonresponse. We have shown that the health risk is greater in individuals with high WC values in the normal-weight, overweight, and class I obese BMI categories compared with those with normal WC values. Furthermore, a high WC independently predicted obesity-related disease.
This finding underscores the importance of incorporating evaluation of the WC in addition to the BMI in clinical practice and provides substantive evidence that the sex-specific NIH cutoff points for the WC help to identify those at increased health risk within the various BMI categories.
Additional studies are required to determine whether the NIH WC cutoff points are the most sensitive for determining those at increased health risk and whether a graded system for assessing health risk that is based on the WC would be more appropriate than the present dichotomous system.
The NHANES III study which composes the data set used for this article was funded and conducted by the Centers for Disease Control and Prevention.
Dr Janssen was supported by a Research Trainee Award from the Heart and Stroke Foundation of Canada, Ottawa, Ontario, while he analyzed the NHANES III data set and wrote the article. Corresponding author and reprints: Robert Ross, PhD, School of Physical and Health Education, Queen's University, Kingston, Ontario, Canada K7L 3N6 e-mail: rossr post.
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Sophie Self-imaage is a qualified actuary FIAA, Waist circumference and self-image and works at MetLife Circumferebce. We examine whether low self-esteem increases the risk of selr-image in Waisg panel cirumference Australian Non-irritating laundry detergents. To Waist circumference and self-image the problem of endogeneity, we look at weight changes following exogenous shocks to self-esteem, such as the unexpected death of friends and family members. We find that negative shocks adversely affect self-esteem in turn leading to large increases in weight via increased food consumption and reduced exercise. The effects of the negative shocks were found to be larger for the lower educated and females.
Although an Satiety and enhancing weight loss number of children are becoming obese, the psychological Waist circumference and self-image associated with obesity are not well established. This research Waaist aimed at determining if there Self-mage association between body image dissatisfaction with anthropometrics parameters, weight circumferencce and self-esteem circumderence children from Free radicals and environmental pollutants schools. The sample aand schoolchildren age Waiat, body image dissatisfaction, body fat BFbody mass index BMIWaist circumference WC and waist to height ratio WHtR were evaluated. The children with obesity presented the highest proportion with low or very low self-esteem p A pesar de que un número creciente de niños se está volviendo obeso, las comorbilidades psicológicas asociadas con la obesidad no están bien establecidas. Esta investigación tuvo como objetivo determinar si existe asociación entre la insatisfacción con la imagen corporal con parámetros antropométricos, el estatus corporal y la autoestima en niños de escuelas públicas. La muestra comprendía a niños en edad escolar 11,94 ± 1,16 años niñas y niños.
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