Include measurement of waist circumference in GP contract.
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ABSTRACT:
SUBMITTER: Haslam D
PROVIDER: S-EPMC1188151 | biostudies-literature | 2005 Aug
REPOSITORIES: biostudies-literature
Publications
Include measurement of waist circumference in GP contract.
BMJ (Clinical research ed.) 20050801 7514
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Project description: Not available
| S-EPMC1352079 | biostudies-literature
Project description:BMI and waist circumference (WC) are used to identify individuals with elevated obesity-related health risks. The current thresholds were derived largely in populations of European origin. This study determined optimal BMI and WC thresholds for the identification of cardiometabolic risk among white and African-American (AA) adults. The sample included 2096 white women, 1789 AA women, 1948 white men, and 643 AA men aged 18-64 years. Elevated cardiometabolic risk was defined as ≥2 risk factors (blood pressure ≥ 130/85 mm Hg; glucose ≥100 mg/dl; triglycerides ≥150 mg/dl; high-density lipoprotein-cholesterol <40 mg/dl (men) or <50 mg/dl (women)). Receiver Operating Characteristic (ROC) curves were used to identify optimal BMI and WC thresholds in each sex-by-ethnicity group. The optimal BMI thresholds were 30 kg/m2 in white women, 32.9 kg/m2 in AA women, 29.1 kg/m2 white men, and 30.4 kg/m2 in AA men, whereas optimal WC thresholds were 91.9 cm in white women, 96.8 cm in AA women, 99.4 in white men, and 99.1 cm in AA men. The sensitivities at the optimal thresholds ranged from 63.5 to 68.5% for BMI and 68.4 to 71.0% for WC and the specificities ranged from 64.2 to 68.8% for BMI and from 68.5 to 71.0% for WC, respectively. In general, the optimal BMI and WC thresholds approximated currently used thresholds in men and in white women. There are no apparent ethnic differences in men; however, in AA women the optimal BMI and WC values are ~3 kg/m2 and 5 cm higher than in white women.
| S-EPMC3933952 | biostudies-literature
Project description:BackgroundWaist circumference (WC), calf circumference (CC), and body mass index (BMI) have been independently linked to mortality. However, it's not yet clear how the waist-calf circumference ratio (WCR) relates to mortality. This study aims to investigate the relationship between WCR, WC, CC, and BMI with all-cause and cause-specific mortality in older adults.MethodsIn the 2014 Chinese Longitudinal Healthy Longevity Survey, 4627 participants aged 65 years and older were included, and they were subsequently followed up in 2018. Cox proportional hazards models were utilized to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality, based on WCR, WC, CC, and BMI.ResultsDuring a median follow-up of 3.4 years, 1671 deaths (36.1%) occurred. Compared to the second quartile of WCR, the highest quartile had a higher risk of mortality from all causes (HR 1.42, 95%CI 1.24-1.64), cardiovascular disease (CVD) (HR 1.88, 95%CI 1.38-2.56), and other causes (HR 1.37, 95%CI 1.15-1.63). The first and fourth quartiles of WC had HRs of 2.19 (1.00-4.79) and 2.69 (1.23-5.89), respectively, for cancer mortality. The highest quartile of CC was associated with a lower risk of all-cause and other-cause mortality, whereas the lowest quartile was associated with a higher risk of all-cause, CVD, and other-cause mortality compared to the second CC quartile. Additionally, the lowest quartile of BMI was associated with a higher risk of all-cause and respiratory disease mortality. Interaction analyses showed that the effects of CC on all-cause and CVD mortality were more pronounced in adults aged ≥ 80 years (P-interaction < .05).ConclusionsHigher WCR and lower CC increased the risk of all-cause, CVD, and other-cause mortality. Lower BMI was associated with higher all-cause and respiratory disease mortality risk, while WC only predicted cancer mortality.
| S-EPMC10498546 | biostudies-literature
Project description:We examined whether established metabolic risk genetic variants in the population confer a risk for increased waist circumference in patients with schizophrenia spectrum disorders and also an association with schizophrenia spectrum disorders irrespective of waist circumference.We analyzed the association in (i) a case-case model in which patients with schizophrenia spectrum disorder with increased waist circumference (?80?cm for women and ?94?cm for men) (n=534) were compared with patients with normal waist circumference (<80?cm for women; <94?cm for men) (n=124), and in (ii) a case-control model in which schizophrenia spectrum disorder patients with increased waist circumference or irrespective of waist circumference were compared with population-derived controls (n=494) adjusted for age, sex, fasting glucose, smoking, and family history of diabetes.Genetic variants in five genes (MIA3, MRAS, P2RX7, CAMKK2, and SMAD3) were associated with increased waist circumference in patients with schizophrenia spectrum disorder (P<0.046). Genetic variants in three other genes (PPARD, MNTR1B, and NOTCH2) were associated with increased waist circumference in patients when compared with control individuals (P<0.037). Genetic variants in the PPARD, MNTR1B, NOTCH2, and HNF1B were nominally associated with schizophrenia spectrum disorder irrespective of waist circumference (P<0.027). No differences in waist circumference between specific psychosis diagnoses were detected.Increased waist circumference in patients with schizophrenia spectrum disorder may be explained, in part, by increased metabolic risk gene burden, and it indicates a shared genetic susceptibility to metabolic disorder and psychosis per se. Along these lines, common metabolic risk genetic variants confer a risk for increased waist circumference in patients with schizophrenia spectrum disorders.
| S-EPMC5662154 | biostudies-literature
Project description:Background:To lower the risk of diabetes and heart disease in Africa, identification of African-centred thresholds for inexpensive biomarkers of insulin resistance (IR) is essential. The waist circumference (WC) thresholds that predicts IR in African men and women have not been established, but investigations recently conducted in Africa using indirect measures of IR suggest IR is predicted by WC of 80-95 cm in men and 90-99 cm in women. These WC cannot be used for guidelines until validated by direct measurements of IR and visceral adipose tissue (VAT). Therefore, we determined in a group of African-born black people living in America (A) the WC, which predicts IR and (B) the influence of abdominal fat distribution on IR. Methods:The 375 participants (age 38±10 ?years (mean±SD), 67% men) had IR determined by HOMA-IR and Matsuda index. VAT and subcutaneous adipose tissue (SAT) were measured by abdominal CT scans. Optimal WC for the prediction of IR was determined in sex-specific analyses by area under the receiver operating characteristic (AUC-ROC) and Youden index. Results:Women had more SAT (203±114 vs 128±74 ?cm2) and less VAT than men (63±48 vs 117±72 ?cm2, p<0.001). Optimal WC for prediction of IR in men and women were: 91?cm (AUC-ROC: 0.80±0.03 (mean±SE)) and 96?cm (AUC-ROC: 0.81±0.08), respectively. Regression analyses revealed a significant sex-VAT interaction (p<0.001). Therefore, for every unit increase in VAT, women had a 0.94 higher unit increase in SAT and 0.07 higher unit increase in WC than men. Conclusion:Working with a group of African-born black people living in America, we accessed technology, which validated observations made in Africa. Higher SAT at every level of VAT explained why the WC that predicted IR was higher in women (96?cm) than men (91?cm). For Africans to benefit from WC measurements, convening a panel of experts to develop evidence-based African-centred WC guidelines may be the way forward.
| S-EPMC6195140 | biostudies-literature
Project description:BackgroundAbdominal obesity, which is a strong indicator of cardiometabolic risk, is widely evaluated using waist circumference (WC) and waist-height ratio (WHtR). In Korea, the reference values for WC for children and adolescents were published in 2007 and need to be revised. Moreover, there is no reference for WHtR. The aim of this study was to establish new reference values for WC and WHtR in Korean children and adolescents.MethodsData of 20,033 subjects from the Korea National Health and Nutrition Examination Survey (2007-2019) were used. Tables for reference values and the graphs of smoothed percentile curves of WC and WHtR for children and adolescents aged 2-18 years by sex were generated using the LMS method and locally estimated scatterplot smoothing regression analysis after removing extreme values.ResultsSex-specific reference tables and percentile curves for WC and WHtR were developed. In the new WC curves, the 10th, 50th, and 90th percentile lines were lower than the corresponding lines of the 2007 reference for both sexes. The WHtR curves showed sex-specific differences, although they demonstrated a relative plateau among those aged ≥10 years in both sexes. In the logistic regression analysis, the WC and WHtR z-scores showed higher odds ratios for predicting cardiometabolic risk factors than the body mass index z-score.ConclusionNew WC and WHtR reference values for Korean children and adolescents aged 2-18 years were developed using the latest statistical methods. These references will help monitor and track WC and WHtR for evaluating abdominal obesity among at-risk children and adolescents in Korea.
| S-EPMC9579477 | biostudies-literature
Project description: Not available
| S-EPMC11688229 | biostudies-literature
Project description:Background Obesity, especially abdominal obesity, is an independent indicator of increased cardiovascular risk. Observational studies have shown an observational association between obesity and venous thromboembolism (VTE). As a type of VTE, pulmonary embolism (PE) is also associated with obesity. However, it is unclear whether the observed associations are causal or caused by confounding bias or reverse causality.Methods We performed a two-sample test by obtaining the exposure dataset of waist circumference (WC) and hip circumference (HC) from the Neale Laboratory Consortium's genome-wide association study summary data and the summary-level outcome data of VTE and PE from FinnGen Biobank of European ancestry to determine the causal effect of WC and HC on VTE and PE.Results All three Mendelian randomization methods displayed a positive association between WC/HC and VTE/PE. WC and HC were positively associated with VTE (odds ratio [OR] = 1.803 per 1 standard deviation [SD] increase in WC, 95% confidence interval [CI] = 1.393-2.333; p < 0.001; OR = 1.479 per 1 SD increase in HC, 95% CI = 1.219-1.796; p < 0.001, respectively). Furthermore, we found a causal association between genetically predicted WC/HC and a higher risk of PE (OR = 1.929 per 1 SD increase in WC, 95% CI = 1.339-2.778, p < 0.001; OR = 1.431 per 1 SD increase in HC, 95% CI =1.095-1.869; p = 0.009, respectively).Conclusion There is a significant causal relationship between WC/HC and VTE/PE, which is consistent with observational studies. Taking measures to reduce WC/HC of obesity may help reduce the incidence of VTE/PE.
| S-EPMC9981277 | biostudies-literature
Project description:BackgroundAssociations of waist circumferences (WC) and body mass index (BMI) measured once or over time, with cancer incidence were studied. WC is associated with some cancers independent of BMI. Analyses of cumulative central adiposity and cancer are lacking. We investigated associations between waist circumference-years, incorporating exposure time to WC ≥ 102 cm in men or ≥88 cm in women, and cancer, and compared this with single WC or BMI.MethodsSerial WC measurements taken over 9 years in the prospective Atherosclerosis Risk in Communities Study (ARIC) predicted yearly WC. Cox proportional hazards regression estimated hazard ratios (HRs) of cancer incidence for waist circumference-years, WC or BMI, measured in Visit 4. Harrell's C-statistic quantified metric predictive performances.Results10,172 participants were followed up from Visit 4 for cancer over a median 13.7 for men and 15.8 years for women. For obesity-related cancers, HRs per standard deviation waist circumference-years were 1.14 (95%CI:1.04,1.25) and 1.19 (95%CI:1.12,1.27), respectively. Differences in metric predictive performances were marginal.DiscussionThis is the first study to identify positive associations between waist circumference-years and cancer. Waist circumference-years did not provide additional information on cancer risk beyond that of WC and BMI. BMI is routinely measured in clinic so it may be preferred over WC.
| S-EPMC11554801 | biostudies-literature
Project description:BackgroundWaist circumference is becoming recognized as a useful predictor of health risks in clinical research. However, clinical datasets tend to lack this measurement and self-reported values tend to be inaccurate. Predicting waist circumference from standard physical features could be a viable method for generating this information when it is missing or mitigating the impact of inaccurate self-reports. This study determined the degree to which the XGBoost advanced machine learning algorithm could build models that predict waist circumference from height, weight, calculated Body Mass Index, age, race/ethnicity and sex, whether they perform better than current models based on linear regression, and the relative importance of each feature in this prediction.MethodsWe trained tree-based models (via XGBoost gradient boosting) and linear models (via regression) to predict waist circumference from height, weight, Body Mass Index, age, race/ethnicity and sex (n = 60,740 participants). We created 10 iterations of each model, each using 90% of the dataset for training and the remaining 10% for testing performance (this group was different for each iteration). We calculated model performance and feature importance as an average across 10 iterations. We then externally validated the ensembled version of the top model.ResultsThe XGBoost model predicted waist circumference with a mean bias ± standard deviation of 0.0 ± 0.04 cm and a root mean squared error of 4.7 ± 0.05 cm, with performance varying slightly by sex and race/ethnicity. The XGBoost model showed varying degrees of improvement over linear regression models. The top 3 predictors were Body Mass Index, weight and race (Asian). External validation found that on average this model overestimated waist circumference by 4.65 cm in the United Kingdom population (mainly due to overprediction in females) and underestimated waist circumference by 1.7 cm in the Chinese population. The respective root mean squared errors were 7.7 cm and 7.1 cm.ConclusionsXGBoost-based models accurately predict waist circumference from standard physical features. Waist circumference prediction using this approach would be valuable for epidemiological research and beyond.
| S-EPMC7944598 | biostudies-literature