Dataset Information

BMI, waist to height ratio and waist circumference as a screening tool for hypertension in hospital outpatients: a cross-sectional, non-inferiority study.

ABSTRACT:

Objective

This non-inferiority study aimed to determine the burden of obesity in a hospital outpatient setting of a developing country, using three commonly employed metrics as predictors of hypertension (HTN).

Design

A cross-sectional study design was adopted.

Setting

This study was conducted in Health Promotion and Risk Factor Screening Services of a tertiary hospital for eye and ear, nose, throat in a semiurban area of Nepal.

Participants

2256 randomly selected outpatients between 40 and 69 years old.

Outcome measures

The three obesity metrics and HTN were analysed for association using correlation, the area under the receiver operating characteristic (ROC) curve and ORs.

Results

The prevalence of obesity or overweight by body mass index (BMI) was 58.29%; by waist-to-height ratio (WHtR) was 85.95%, high waist circumference (WC) was observed among 66.76% of participants. Female participants had a greater prevalence of high WC (77.46%) than males (53.73%) (p<0.001). Prevalence of HTN and pre-HTN were 40.67% and 36.77%, respectively. The areas under the ROC curve were significantly higher than 0.5 for BMI (0.593), WHtR (0.602) and WC (0.610).

Conclusion

This study showed that WHtR and WC measured were not inferior to BMI as a metric for obesity detection and HTN prediction. Because of its low cost, simplicity of measurement and better ability to predict HTN, it may become a more usable metric in health facilities of low-income and middle-income countries.

SUBMITTER: Shrestha R

PROVIDER: S-EPMC8628118 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWaist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) are all independent predictors of cardio-metabolic risk and therefore important in HIV/AIDS patients on antiretroviral therapy at risk of increased visceral adiposity. This study aimed to assess the extent of agreement between these parameters and the body mass index (BMI), as anthropometric parameters and in classifying cardio-metabolic risk in HIV/AIDS patients.MethodsA secondary analysis of data from a cross-sectional study involving 200 HIV/AIDS patients was done. Anthropometric parameters were measured from participants using standard guidelines and central obesity defined according to recommended criteria. Increased cardio-metabolic risk was defined according to the standard cut-off values for all four parameters. Data were analyzed using STATA version 14.1.ResultsThe prevalence of WC-defined central obesity, WHR-defined central obesity and WHtR > 0.50 were 33.5%, 44.5% and 36.5%, respectively. The prevalence of BMI-defined overweight and obesity was 40.5%. After adjusting for gender and HAART status, there was a significant linear association and correlation between WC and BMI (regression equation: WC (cm) = 37.184 + 1.756 BMI (Kg/m2) + 0.825 Male + 1.002 HAART, (p < 0.001, r = 0.65)), and between WHtR and BMI (regression equation: WHtR = 0.223 + 0.011 BMI (Kg/m2)- 0.0153 Male + 0.003 HAART, (p < 0.001, r = 0.65)), but not between WHR and BMI (p = 0.097, r = 0.13). There was no agreement between the WC, WHtR and BMI, and minimal agreement between the WHR and BMI, in identifying patients with an increased cardio-metabolic risk.ConclusionDespite the observed linear association and correlation between these anthropometric parameters, the routine use of WC, WHR and WHtR as better predictors of cardio-metabolic risk should be encouraged in these patients, due to their minimal agreement with BMI in identifying HIV/AIDS patients with increased cardio-metabolic risk. HAART status does not appear to significantly affect the association between these anthropometric parameters.

Project description:ObjectiveObesity is the prominent modifiable risk factor known to influence the occurrence and progression of diabetes other than age, and the objective of this study was to evaluate and compare the predictive value of three simple baseline anthropometric indicators of obesity, body mass index (BMI), waist circumference (WC), and waist-height ratio (WHtR), for the occurrence of diabetes at different time points in the future.MethodsThe study subjects were 12,823 individuals with normoglycemic at baseline who underwent health screening and had measurements of BMI, WC, and WHtR. The outcome of interest was new-onset diabetes during follow-up. Time-dependent receiver operator characteristics (ROC) curves of baseline BMI, WC, and WHtR for predicting the risk of diabetes in the next 2 to 12 years were constructed and their area under the ROC curves (AUCs) and corresponding optimal threshold values were calculated for each time point, which were used to compare the accuracy and stability of the above three indicators for predicting the occurrence of diabetes in different future periods.ResultsDuring a median follow-up period of 7.02 years, with a maximum follow-up of 13 years, 320 new-onset diabetes were recorded. After adjusting for confounders and comparing standardized hazard ratios (HRs), WC was shown to be the best simple anthropometric indicator of obesity reflecting diabetes risk in all models, followed by WHtR. Time-dependent ROC analysis showed that WC had the highest AUC in predicting the occurrence of diabetes in the short term (2-5 years), and WHtR had the highest AUC in predicting the occurrence of diabetes in the medium to long term (6-12 years), while in any time point, both WC and WHtR had higher AUC than BMI in predicting future diabetes. In addition, we found relatively larger fluctuations in the thresholds of BMI and WC for predicting diabetes over time, while the thresholds of WHtR consistently remained between 0.47-0.50; comparatively speaking, WHtR may have greater application value in predicting future diabetes.ConclusionsOur analysis sustained that central obesity is a more important predictor of diabetes, and in clinical practice, we proposed measuring WHtR as a useful tool for predicting future diabetes.