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Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering?

ABSTRACT: The present study evaluated the ability of five obesity-related parameters, including a body shape index (ABSI), conicity index (CI), body roundness index (BRI), body mass index (BMI), and waist-to-height ratio (WtHR) for predicting increased cardiometabolic risk in a population of elderly Colombians. A cross-sectional study was conducted on 1502 participants (60.3% women, mean age 70 ± 7.6 years) and subjects' weight, height, waist circumference, serum lipid indices, blood pressure, and fasting plasma glucose were measured. A cardiometabolic risk index (CMRI) was calculated using the participants' systolic and diastolic blood pressure, triglycerides, high-density lipoprotein and fasting glucose levels, and waist circumference. Following the International Diabetes Federation definition, metabolic syndrome was defined as having three or more metabolic abnormalities. All surrogate anthropometric indices correlated significantly with CMRI (p < 0.01). Receiver operating characteristic curve analysis of how well the anthropometric indices identified high cardiometabolic risk showed that WtHR and BRI were the most accurate indices. The best WtHR and BRI cut-off points in men were 0.56 (area under curve, AUC 0.77) and 4.71 (AUC 0.77), respectively. For women, the WtHR and BRI cut-off points were 0.63 (AUC 0.77) and 6.20 (AUC 0.77), respectively. In conclusion, BRI and WtHR have a moderate discriminating power for detecting high cardiometabolic risk in older Colombian adults, supporting the idea that both anthropometric indices are useful screening tools for use in the elderly.

SUBMITTER: Ramirez-Velez R

PROVIDER: S-EPMC6723899 | biostudies-other | 2019 Jul

REPOSITORIES: biostudies-other

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Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering?

Ramírez-Vélez Robinson R Pérez-Sousa Miguel Ángel MÁ Izquierdo Mikel M Cano-Gutierrez Carlos A CA González-Jiménez Emilio E Schmidt-RioValle Jacqueline J González-Ruíz Katherine K Correa-Rodríguez María M

Nutrients 20190724 8

The present study evaluated the ability of five obesity-related parameters, including a body shape index (ABSI), conicity index (CI), body roundness index (BRI), body mass index (BMI), and waist-to-height ratio (WtHR) for predicting increased cardiometabolic risk in a population of elderly Colombians. A cross-sectional study was conducted on 1502 participants (60.3% women, mean age 70 ± 7.6 years) and subjects' weight, height, waist circumference, serum lipid indices, blood pressure, and fasting ...[more]

PMID: 31344803

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Project description:BackgroundPeople with the metabolically obese normal weight (MONW) phenotype have been confirmed to significantly increase the risk of unfavorable health consequences. This study aimed to investigate the relationships between traditional and novel anthropometric indices with the MONW phenotype and compare the predictive ability of different anthropometric indices in identifying individuals with the MONW phenotype.MethodsThis cross-sectional study involved a total of 26,332 participants aged 18 years or older with a normal weight from Nanjing, China. Sociodemographic information, biochemical measurements, and anthropometric indices were collected. The novel body fat anthropometric indices included body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), weight-adjusted-waist index (WWI), body adiposity index (BAI), conicity index (CI), waist-hip-height ratio (WHHR), as well as traditional indices such as waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR).The prevalence ratio (PR) from modified poisson regression and area under the receiver-operating characteristic curve (AUC) were conducted to compare the association and predictive capacity of different obesity indicators for the MONW phenotype. All analyses were stratified by sex.ResultsModified poisson regression analyses revealed that weight, WC, HC, BMI, WHR, WHtR, ABSI, BRI, AVI, WWI, BAI, CI, and WHHR were independently associated with higher risk of the MONW phenotype, regardless of whether they were treated as a continuous or categorical variable (P < 0.05). Notably, BRI demonstrated the strongest association in both men (highest quartile VS lowest quartile; PR = 3.14, 95%CI, 2.49, 3.96; P < 0.001) and women (PR = 4.63, 95%CI, 3.81, 5.62; P < 0.001). Receiver operating characteristic analysis indicated that AUC for the different anthropometric indices ranged from 0.50 to 0.80. BRI and WHtR had the largest AUC in both males (both AUC = 0.733; 95% CI, 0.717, 0.750) and females (both AUC = 0.773; 95% CI, 0.761, 0.786). The optimal cut-off points for BRI, determined by maximizing the Youden's index, were 3.102 (sensitivity: 63.2%, specificity: 36.2%) in males and 3.136 (sensitivity: 68.9%, specificity: 44.2%) in females. Moreover, BRI and WHtR exhibited the highest diagnostic accuracy in younger age groups, specifically those aged 18-34 in both sexes.ConclusionsBRI emerged as the optimal predictor and independent determinant of the MONW phenotype, regardless of gender. This association was particularly pronounced in young individuals.

Project description:OBJECTIVES:Whether the association between obesity-related anthropometric indices and multimorbidity differs by age among Chinese older adults (aged 65+) is unclear. We aimed to investigate the association between body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) with multimorbidity among the young-old (aged 65-79) and old-old (aged 80+) adults. DESIGN:Cross-sectional population-based study. SETTING:Shandong province on the eastern coast of China. PARTICIPANTS:5493 subjects aged 65 years or above. MEASUREMENTS:Details on sociodemographics, lifestyle characteristics and chronic conditions were collected using a structured questionnaire. The respondents were assessed with anthropometric measurements including height, weight, WC, hip circumference. RESULTS:The overall prevalence of multimorbidity in older adults (aged 65+) was 35.2%. The BMI-obesity, WC-obesity and WHR-obesity rates were 7.4%, 57.5% and 80.4%, respectively. In the young-old adults (aged 65-79), the likelihood of multimorbidity was more than two times higher among the BMI-obese than the BMI-normal population (OR 2.08, 95%?CI 1.66 to 2.60). Similar but less strong associations were found for the WC-obese and WHR-obese young-old population (OR 1.60, 95%?CI 1.42 to 1.81; OR 1.31, 95%?CI 1.10 to 1.56, respectively). For the old-old group (aged 80+), the BMI-obese, WC-obese and WHR-obese had a higher likelihood of having multimorbidity compared with the normal weight category (OR 2.10, 95%?CI 0.96 to 4.57; OR 1.75, 95%?CI 1.21 to 2.54; OR 2.15, 95%?CI 1.18 to 3.93, respectively). CONCLUSION:BMI-obesity, WC-obesity and WHR-obesity were associated with a greater risk of multimorbidity, and the associations were different between the young-old and the old-old adults. These age differences need to be considered in assessing healthy body weight in old age. These findings may be vital for public health surveillance, prevention and management strategies for multimorbidity in older adults.

Project description:BackgroundPrevious studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study.MethodsData collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity.ResultsA total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m2 and WC≥90 (men)/80 (women) group and BMI≥24 kg/m2 and WC≥90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC≥90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18).ConclusionsCentral obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.

Project description:The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA.We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices.In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst.Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power.

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Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering?

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Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering?

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