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Waist circumference and fitness

Waist circumference and fitness

Height and fitneds must be measured to Performance optimization consultancy BMI. Occup Med. Waist circumference and fitness Google Scholar Cricumference references. Waist circumference cutoff points and action levels for Asian Indians for identification of abdominal obesity. Comparison of Body Mass Index BMIBody Adiposity Index BAIWaist Circumference WCWaist-To-Hip Ratio WHR and Waist-To-Height Ratio WHtR as predictors of cardiovascular disease risk factors in an adult population in Singapore.

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Similarly, Sandra Albrecht and colleagues examined the secular changes in waist circumference in the USA — , England — , China — and Mexico — 36 and reported statistically significantly increased waist circumference values relative to BMI in all countries studied and in most subpopulations.

These observations are consistent with those of Tommy Visscher and colleagues, who performed an extensive review and concluded that the majority of the evidence suggests a trend in which the relative increases in waist circumference were larger than the relative increases in BMI This observation is seemingly independent of age, sex and ethnicity, as few groups failed to demonstrate the general trend of secular waist circumference increasing beyond that expected by BMI Fig.

The failure of BMI to detect such an increase in abdominal obesity confirms the limitations of BMI alone to identify the phenotype of obesity that conveys the greatest health risk.

Changes in the prevalence of abdominal obesity measured using waist circumference and general obesity measured using BMI measured in different studies during the time period indicated on the x axis. However, Xi et al.

In addition, Barzin et al. Years given for example, — indicate the years in which data were collected. F, female; M, male. Data are from refs 37 , , , , , , , , , Although the prevalence of obesity measured by BMI might have plateaued in some countries, the prevalence of abdominal obesity as measured by waist circumference is generally increasing.

The lack of inclusion of waist circumference in global obesity surveillance might inadequately characterize the health risk associated with the global obesity prevalence, as it seems that the prevalence of abdominal obesity is increasing.

Current obesity prevalence trends based on BMI alone should be interpreted with caution. We recommend that serious consideration should be given to the inclusion of waist circumference in obesity surveillance studies. It is not surprising that waist circumference and BMI alone are positively associated with morbidity 15 and mortality 13 independent of age, sex and ethnicity, given the strong association between these anthropometric variables across cohorts.

However, it is also well established that, for any given BMI, the variation in waist circumference is considerable, and, in any given BMI category, adults with higher waist circumference values are at increased adverse health risk compared with those with a lower waist circumference 38 , 39 , This observation is well illustrated by James Cerhan and colleagues, who pooled data from 11 prospective cohort studies with , white adults from the USA, Australia and Sweden aged 20—83 years This finding is consistent with that of Ellen de Hollander and colleagues, who performed a meta-analysis involving over 58, predominantly white older adults from around the world and reported that the age-adjusted and smoking-adjusted mortality was substantially greater for those with an elevated waist circumference within normal weight, overweight and obese categories as defined by BMI The ability of waist circumference to add to the adverse health risk observed within a given BMI category provides the basis for the current classification system used to characterize obesity-related health risk 8 , Despite the observation that the association between waist circumference and adverse health risk varies across BMI categories 11 , current obesity-risk classification systems recommend using the same waist circumference threshold values for all BMI categories We propose that important information about BMI and waist circumference is lost when they are converted from continuous to broad categorical variables and that this loss of information affects the manner in which BMI and waist circumference predict morbidity and mortality.

Specifically, when BMI and waist circumference are considered as categorical variables in the same risk prediction model, they are both positively related to morbidity and mortality However, when BMI and waist circumference are considered as continuous variables in the same risk prediction model, risk prediction by waist circumference improves, whereas the association between BMI and adverse health risk is weakened 10 , Evidence in support of adjusting waist circumference for BMI comes from Janne Bigaard and colleagues who report that a strong association exists between waist circumference and all-cause mortality after adjustment for BMI Consistent with observations based on asymptomatic adults, Thais Coutinho and colleagues report similar observations for a cohort of 14, adults with CVD who were followed up for 2.

The cohort was divided into tertiles for both waist circumference and BMI. In comparison with the lowest waist circumference tertile, a significant association with risk of death was observed for the highest tertile for waist circumference after adjustment for age, sex, smoking, diabetes mellitus, hypertension and BMI HR 1.

By contrast, after adjustment for age, sex, smoking, diabetes mellitus, hypertension and waist circumference, increasing tertiles of BMI were inversely associated with risk of death HR 0. The findings from this systematic review 44 are partially confirmed by Diewertje Sluik and colleagues, who examined the relationships between waist circumference, BMI and survival in 5, individuals with T2DM over 4.

In this prospective cohort study, the cohort was divided into quintiles for both BMI and waist circumference. After adjustment for T2DM duration, insulin treatment, prevalent myocardial infarction, stroke, cancer, smoking status, smoking duration, educational level, physical activity, alcohol consumption and BMI, the HR for risk of death associated with the highest tertile was 2.

By contrast, in comparison with the lowest quintile for BMI adjusted for the same variables, with waist circumference replacing BMI , the HR for risk of death for the highest BMI quintile was 0.

In summary, when associations between waist circumference and BMI with morbidity and mortality are considered in continuous models, for a given waist circumference, the higher the BMI the lower the adverse health risk.

Why the association between waist circumference and adverse health risk is increased following adjustment for BMI is not established.

It is possible that the health protective effect of a larger BMI for a given waist circumference is explained by an increased accumulation of subcutaneous adipose tissue in the lower body This observation was confirmed by Sophie Eastwood and colleagues, who reported that in South Asian adults the protective effects of total subcutaneous adipose tissue for T2DM and HbA 1c levels emerge only after accounting for visceral adipose tissue VAT accumulation A causal mechanism has not been established that explains the attenuation in morbidity and mortality associated with increased lower body adiposity for a given level of abdominal obesity.

We suggest that the increased capacity to store excess energy consumption in the gluteal—femoral subcutaneous adipocytes might protect against excess lipid deposition in VAT and ectopic depots such as the liver, the heart and the skeletal muscle Fig.

Thus, for a given waist circumference, a larger BMI might represent a phenotype with elevations in lower body subcutaneous adipose tissue. Alternatively, adults with elevations in BMI for a given waist circumference could have decreased amounts of VAT.

Excess lipid accumulation in VAT and ectopic depots is associated with increased cardiometabolic risk 47 , 48 , Moreover, VAT is an established marker of morbidity 50 , 51 and mortality 24 , These findings provide a plausible mechanism by which lower values for BMI or hip circumference for a given waist circumference would increase adverse health risk.

When this process becomes saturated or in situations where adipose tissue has a limited ability to expand, there is a spillover of the excess energy, which must be stored in visceral adipose tissue as well as in normally lean organs such as the skeletal muscle, the liver, the pancreas and the heart, a process described as ectopic fat deposition.

Visceral adiposity is associated with a hyperlipolytic state resistant to the effect of insulin along with an altered secretion of adipokines including inflammatory cytokines whereas a set of metabolic dysfunctions are specifically associated with increased skeletal muscle, liver, pancreas, and epicardial, pericardial and intra-myocardial fat.

FFA, free fatty acid. This notion is reinforced by Jennifer Kuk and colleagues who reported that BMI is an independent and positive correlate of VAT in adults before adjustment for waist circumference; however, BMI is negatively associated with VAT mass after adjustment for waist circumference This study also reported that, after adjustment for waist circumference, BMI was positively associated with lower body subcutaneous adipose tissue mass and skeletal muscle mass.

These observations support the putative mechanism described above and, consequently, that the negative association commonly observed between BMI and morbidity and mortality after adjustment for waist circumference might be explained by a decreased deposition of lower body subcutaneous adipose tissue and muscle mass, an increased accumulation of visceral adiposity, or both.

In summary, the combination of BMI and waist circumference can identify the highest-risk phenotype of obesity far better than either measure alone. Although guidelines for the management of obesity from several professional societies recognize the importance of measuring waist circumference, in the context of risk stratification for future cardiometabolic morbidity and mortality, these guidelines limit the recommendation to measure waist circumference to adults defined by BMI to have overweight or obesity.

On the basis of the observations described in this section, waist circumference could be just as important, if not more informative, in persons with lower BMI, where an elevated waist circumference is more likely to signify visceral adiposity and increased cardiometabolic risk.

This observation is particularly true for older adults In categorical analyses, waist circumference is associated with health outcomes within all BMI categories independent of sex and age.

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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The search strategy combined Key Medical Subject Heading and indexed search descriptors to refine the data, following the recommendation from the Cochrane Handbook for Systematic Review of Intervention Higgins and Altman, , as shown in Table 1.

To be included in the present systematic review with meta-analysis, studies must meet the following inclusion criteria: 1 RCT studies with exercise intervention with intervention group and control group , with any prescription in terms of intensities and duration, according to ACSM guidelines American College of Sports Medicine, ; 2 All participants mut have an IDD diagnosis, whatever the degrees, including other subgroups with IDD diagnosis by Wechsler Adult Intelligence Scale—Fourth Edition Wechsler, or The Wechsler Intelligence Scale for Children—Fifth Edition Integrated Raiford, ; 3 Participants with IDD of any age, gender, race or ethnicity, regarding ACSM American College of Sports Medicine, ; 4 Studies focusing on aerobic, neuromuscular, flexibility or combined capacity training that combines more than one physical capacity, e.

In turn, all studies with the following characteristics were excluded: 1 Studies published in a language other than English; 2 Studies that do no describe the intervention protocol; 3 Studies with participants with another type of disability or other associated pathologies; 4 Studies in which the intervention is multidimensional studies involving exercise and nutrition, exercise and health education sessions ; 5 Studies that do not show anthropometric data BMI and WC ; 6 Studies that the intervention protocol is through virtual reality institution where we want to replicate the protocol does not have access to this material, as well as other institutions where most of this population usually spends their day ; sports programs.

All studies that did not meet the initial selection criteria and did not report results adequately mean, standard deviation and sample size or if the respective authors did not reply to our inquiries sent by email, were excluded. Finally, articles presented in abstracts, letters to the editor, systematic reviews, study protocols, and book chapters were excluded.

Studies were imported into EndNote X7 software, and duplicates were removed. The study selection procedure was carried out in phases. In the first phase, the search for potentially relevant studies was carried out with the participation of two independent reviewers, based on the titles and the abstract.

These studies would proceed to the next evaluation phase in case of doubt following. In the second phase, the studies from the previous stage were reviewed by the same independent reviewers based on the application of the previously defined eligibility criteria. In this phase, discrepancies about the extracted data were resolved by consensus among reviewers.

The PEDro Scale from the Physiotherapy Evidence Database, was used Maher et al. The scale consists of 11 items, which analyse the different characteristics of each study, one of which is not counted item 1 and the two others are not applicable in the field of sports science items 5 and 6.

The results obtained by both were compared and discussed so that there was a consensus. When there was no consensus, a third researcher was invited to collaborate.

Meta-analysis was performed using Comprehensive Meta-analysis Version 3. Favours A corresponds to, EG and Favour B correspond to CG.

The Q statistic was used to test the null hypothesis, according to which all studies under analysis share a typical magnitude of effects. If all studies share the same effect-size, the expected values of Q would be equal to the number of degrees of freedom N T 2 is the variance of the true effect dimensions in log units between studies Higgins et al.

The homogeneity was verified by visualizing the asymmetry of the funnel-shaped scatter plot Egger et al. Since the funnel-shaped scatter plot interpretation is sometimes subjective, the Egger test was used to check for publication bias Rosenblad, Four meta-analyses were carried out, two to investigate the impact of exercise on the BMI and WC and another two to find out which type of training is most effective in provoking such adaptations.

With the search carried out in different databases PubMed, Web of Science, and Scopus studies were identified. Subsequently, after eliminating the duplicate studies and reading the titles and abstracts, 47 studies with potential relevance to the study were identified.

Considering the eligibility criteria previously defined for this systematic review with meta-analysis, from the complete reading of the articles, a sample of nine studies was constituted for their full analysis Figure 2. FIGURE 2. Difference of means of effect size comparing pre versus post intervention BMI.

Details of the 9 studies included in the systematic review and assessed for quantitative analysis are presented in Table 2. Rosety-Rodriguez and collaborators Rosety-Rodriguez et al. The total number of participants included in the different studies was , in experimental groups and in CG.

The studies included different types of IDD, whether it is DS, autism, or others. In Boer et al. study Boer et al. In Boer and Moss study Boer and Moss, , participants were recruited from three care centres for persons with IDD.

Participants in the Diaz and collaborators study Diaz et al. Also, González-Agüero and collaborators González-Agüero et al. Ortiz-Ortiz Boer et al.

Shields and Taylor Shields and Taylor, recruited participants by contacting family members who were interested and Yu and collaborators Ortiz-Ortiz et al. The exercise intervention programs ranged from 8 to 36 weeks, however is more prevalent a prescription of 10—12 weeks Ordonez et al.

The two combined exercise programs included in this systematic review lasted for 21—36 weeks González-Agüero et al. The frequency varied between 2 and 5 times per week, with most studies implementing 3 times per week Ordonez et al.

The two combined exercise programs included in this systematic review with meta-analysis have a frequency of 2 times per week González-Agüero et al. Regarding neuromuscular capacity, one of the exercise programs have a frequency of 5 times per week Ortiz-Ortiz et al.

Finally, the 5 aerobic exercise programs have a frequency of 2 and 3 times per week, with the majority implemented 3 times per week Boer et al.

Regarding the duration of the exercise intervention session, sessions varied between 25 and 65 min including a brief warm-up and a return to calm period. The duration of the training session in the two combined exercise programs varied from 25 to 60 min González-Agüero et al.

One of the studies did not mention the duration of the training session, but mentions the weekly volume, namely, min per week Shields and Taylor, Interval training programs demonstrate a reduced volume compared to continuo training and used periods of 10 s of maximum speed, followed by 90 s of rest Boer and Moss, or 15 s of full speed followed by 45 s of rest Boer et al.

All the exercise programs focused on neuromuscular capacity used a training circuit with different materials. The study by Diaz and collaborators Diaz et al. On the other hand, this range does not include the difference of zero, which means that the true difference in means is different from zero.

The obtained value of Q is 3. We cannot reject the null hypothesis that the true magnitude of effects is the same across studies, and we can say that the true extent of effects does not varies from study to study.

On the other hand, T 2 corresponds to the variance of the true magnitude of the impact true effect sizes between studies that, in the present study, have a value of 0, as well as the value of T , concerning the deviation pattern of the true magnitude of the effects.

In addition, the Egger test was carried out, which proposes to test the null hypothesis according to which the intercept is equal to zero in the population.

There is no statistical evidence for the existence of publication bias. We can accept the null hypothesis that the actual effect size is the same in all studies. However, the study that shows the greatest effectiveness is combined training, which has a higher magnitude of effect, although the difference between the effects of different studies is not significant.

The obtained value of Q is We cannot reject the null hypothesis that the true magnitude of effects is the same across studies, and we cannot say that the true extent of effects varies from study to study. In the present meta-analysis, the I 2 value obtained is On the other hand, T 2 corresponds to the variance of the true magnitude of the impact true effect sizes between studies that, in the present study, have a value of 0.

The recommended value of p 2-tailed is 0. There is statistical evidence of the existence of publication bias. However, the study that shows the greatest effectiveness is continuous aerobic training, which has a higher magnitude of effect, although the difference between the effects of different studies is not significant.

This systematic review with meta-analysis aimed to assess the magnitude of the effects of different types of exercise programs on BMI and WC, variables related to metabolic and cardiovascular health of individuals with IDD.

The fact that the present systematic review encompassed people with IDD of varying degrees and diagnoses DS, autism, or others may have influenced our results, because subgroups may have different responses to exercise ACSM American College of Sports Medicine, However, these different responses to exercise still need further study to determine the optimal exercise intensities and modes for the population.

However, taking into account the purposes of this systematic review with meta-analysis, we found that all studies that assess the BMI Boer et al. In the González-Agüero and collaborators González-Agüero et al. On the other hand, this increase was beneficial due to the relatively low mean BMI values of the sample, according to the cut-off values, in contrast to most of the literature.

In the Diaz and collaborators Diaz et al. All studies used the same paradigm, whereby individuals with IDD were randomly placed in the experimental group with exercise or the CG. There is a shortage of exercise programs with randomized controlled methodology that assesses the impact on BMI and WC, along with only the population with IDD.

The results were reported regarding the improvement of the BMI or WC. The most used training methodology is the continuous aerobic type Boer et al.

Therefore, which presupposes that the results of this study should be taken with caution. Considering the present systematic review with meta-analysis, exercise had superior effects in most studies.

However, the differences were not significant in some studies. Thus, we can reject the null hypothesis that exercise does not affect the BMI or WC of individuals with IDD, on the other hand, exercise seems decreases BMI and WC values.

This is the strength of the study, since previous research shows that exercise interventions did not promote BMI and WC of individuals with IDD Harris et al. Currently, more researchers interested in promoting the QoL of these individuals may be at the origin of the results of the present study Schalock et al.

This increased interest increases knowledge of effective strategy and methodologies for QoL improvement. Since individuals with disabilities usually have high levels of overweight and obesity, the results of this study highlight the importance of regular exercise practice by individuals with IDD, to prevent the increase in values such as BMI and WC and, consequently, prevent the onset of metabolic and cardiovascular diseases.

On the other hand, a follow-up by the technical of exercise, in order to assess and prescribe exercise in a correct and adapted way should be considered American College of Sports Medicine, According to this systematic review with meta-analysis, combined training appears to be the most efficient method for the promotion of BMI and aerobic training for WC and, in turn, the metabolic health of individuals with IDD.

The literature is not clear about the training methodology that best promotes the variables under study. For Skrypnik and collaborators Skrypnik et al. Aerobic training reduces fat mass but has little effect on maintaining fat free mass Garrow and Summerbell, , and some authors point out that it is effectively the best method to reduce body mass Willis et al.

However, strength training, which produces fat-free mass gain, also increases resting energy expenditure Hunter et al. Exercise combined resistance and aerobic training showed to be a good alternative for increasing fat-free mass and reducing fat mass Willis et al. This article investigates which type of intervention best promotes BMI and WC in individuals with IDD.

However, the small number of articles included and heterogeneity of population and diagnosis in the meta-analysis and a higher prevalence of studies with continuous aerobic methodology may have limited the results.

It is recommended to continue implementing exercise programs with different methods, focusing on physical abilities in isolation or combination, so that further studies can measure these results way more precisely and robustly. On the other hand, waist circumference, may be considered a limitation of the present study, despite its usefulness, low cost and wide availability in any clinical setting, due to measurement errors because of its lack of reproducibility Bouchard, Several studies are recommending the use of imaging techniques as they are more accurate and reproducible, however, they are also more expensive and complex El Ghoch et al.

At the same time, we recommend that future studies investigate the impact of a multidisciplinary intervention on these variables. Seeing if it can have more impact than exercise alone. We also recommend that future interventions are aimed at reducing energy intake and not just energy expenditure through the exercise.

Based on the results of the systematic review with meta-analysis, we can affirm that exercise programs prevent BMI and WC increments of individuals with IDD. Although without significant results, combined training looks to be more effective in promoting BMI and continuous aerobic training for WC since it had a greater effect size.

The interest of various stakeholders in studying the QoL of individuals with IDD has increased, and the results of this systematic review with meta-analysis should be considered when planning interventions with the focus populations, in the sense that exercise programs promote BMI and WC, which, in turn, is associated with metabolic and cardiovascular health.

The practice of exercise, in addition to promoting physical capacity, reduces the risk of diseases, being an essential aspect for a better QoL in individuals with IDD. MJ, MC, JF, and RM contributed to the conception and design of the study.

MJ organized the database. MJ, DM, and RA performed the statistical analysis. MJ wrote the first draft of the manuscript. DM, RA, MC, JF, and RM wrote sections of the manuscript.

All authors contributed to the article and approved the submitted version. This work was supported by CIDAF research unit funded by the Portuguese Foundation for Science and Technology FCT , I. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Foley, J. Body mass index and waist circumference of Latin American adult athletes with intellectual disability. Salud Publica Mex. Garrow, J. Meta-analysis: Effect of exercise, with or without dieting, on the body composition of overweight subjects.

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The effects of physical activity interventions on preventing weight gain and the effects on body composition in young adults with intellectual disabilities: Systematic review and meta-analysis of randomized controlled trials. The effects of multi-component weight management interventions on weight loss in adults with intellectual disabilities and obesity: A systematic review and meta-analysis of randomised controlled trials.

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BMC Public Health 12 1 ,

Results: Considering the eligibility Supplements for improved cellular energy production, a ad sample of nine circumferebce was circumferdnce. Discussion: Physical exercise prevents circumferrence Waist circumference and fitness BMI Waist circumference and fitness WC in individuals with IDD. Aerobic training seems to be more effective in promoting WC and combined training in BMI. Obesity is a major public health problem due to its growing prevalence, as it increases the risk of developing various diseases such as cardiovascular or metabolic diseases de Winter et al. Excessive adiposity results from an imbalance between energy intake and expenditure. Waist circumference and fitness Examining the hidden Waist circumference and fitness fotness abdominal obesity. Waist circumference is a metric fitnees acknowledge but often curcumference when assessing our health Cognitive function optimization strategies well-being. abdomen vs. lower body. Scientists have discovered Waist circumference and fitness a large waist circumference correlates closely to excess fat around the organs, which can significantly increase health risks such as cardiovascular disease and diabetes. For this reason, losing inches can be a great benefit, even without losing weight! A large-scale study out of Europe found that people of the same body weight with a smaller waist have a significantly lower risk of death 1.

Author: Dajora

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