Performance of Anthropometric Indicators in the Prediction of Metabolic Syndrome in the Elderly

Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study

Objective

To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors.

Methods

The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis.

Results

A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability.

Conclusions

Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.

Cut Points of the Conicity Index and Associated Factors in Brazilian Rural Workers

(1) Background: Metabolic syndrome is associated with cardiovascular complications. Therefore, this study aims to establish cut points for the conicity index based on the components of metabolic syndrome and to associate it with characteristic sociodemographic, food consumption and occupational factors in Brazilian rural workers; (2) Methods: A cross-sectional study carried out with farmers. The receiver operating characteristic curve was calculated and the cut-off points for the conicity index were identified by the area under the curve, sensitivity and specificity. The variables included in the binary logistic regression analysis were selected by considering p < 0.20 in the bivariate test; (3) Results: The cut points were similar in females according to both criteria, resulting in a single cut-off of 1.269. In males, the cut points showed differences, resulting in 1.272 according to the NCEP-ATP III and 1.252 according to the IDF. We have shown that younger people, those who work more than 40 h a week and the lowest contribution of culinary ingredients are associated with increased odds of abdominal obesity, while the consumption of the products they sell or produce decreases these chances; (4) Conclusions: The conicity index showed high discriminatory power for the identification of abdominal obesity in rural workers. Therefore, there is a need to improve eating habits and promote healthier eating environments for individuals, respecting traditional food culture, mainly to contain the advance of MS in rural areas.

Exploring the relationships between anthropometric indices of adiposity and physical performance in middle-aged and older Brazilian women: a canonical correlation analysis

OBJECTIVES

This study analyzed the influence of anthropometric indices of adiposity on the physical performance of middle-aged and older women.

METHODS

A cross-sectional study was conducted among 368 women from 50 years to 80 years old. Anthropometric and biochemical characteristics were analyzed, and physical performance was evaluated. The statistical analysis used measures of central tendency and dispersion for descriptive data, Pearson correlations to demonstrate the initial associations between the variables, and canonical correlation (CC) to evaluate the relationship between the set of anthropometric adiposity indices and performance-related variables.

RESULTS

The participants had a mean age of 58.57±8.21 years, a visceral adiposity index of 7.09±4.23, a body mass index of 29.20±4.94 kg/m2, and a conicity index of 1.33±0.07. The average handgrip strength was 25.06±4.89 kgf, gait speed was 1.07±0.23 m/s, and the mean Short Physical Performance Battery (SPPB) score was 10.83±1.36. The first canonical function presented the highest shared variance, CC, and redundancy index (cumulative percentage of variance, 82.52; Wilks' lambda, 0.66; CC, 0.532; p<0.001). From the analysis of this canonical function, the conicity index (-0.59) displayed inverse correlations with handgrip strength (0.84) and the SPPB (0.68), as well as a direct correlation with gait speed (-0.43).

CONCLUSIONS

In middle-aged and older women, there was an inverse relationship between the conicity index and muscle strength and power, while a direct relationship was found between the same index and gait speed.

Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.

A comparison of the different anthropometric indices for assessing malnutrition among older people in Turkey: a large population-based screening

OBJECTIVE

Due to an increase in aging worldwide, assessment of the nutritional status of older people becomes an important matter. Malnutrition in older people increases the risk of infections, disease period and hospitalization rates. This study aimed to compare the different anthropometric indices for detecting malnutrition among older people and comparing these indices among males and females to explain the possible differences.

METHODS

In this cross-sectional study, 2721 aged 65 years and older in Turkey were enrolled. Anthropometric measurements weight, height, hip circumference (HC), and waist circumference (WC), abdominal circumference (AC), mid-upper arm circumference (MUAC), triceps skinfold thickness (TST), calf circumference (CC)) were measured. Body mass index (BMI), abdominal volume index (AVI), body roundness index (BRI) and body adiposity index (BAI), and waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) indices were calculated using standardized formulas. The receiver operator characteristic curves (ROCs) were conducted in detecting the best anthropometric parameters. Adjusted odds ratios (OR) (stratified by sex) calculated for each anthropometric index.

RESULTS

Participants with both BMI < 18.5 (1.1%) and BMI > 25 (80%) defined as the malnourished group and BMI of 18.5-24.99 (18.9%) defined as the normal group. In both sexes, the area under the curve (AUC) was > 0.7 for all anthropometric indices except WHR in females (AUC 0.66). BRI, WHR, WHtR, and AVI indices strongly predict the risk of malnutrition among both sexes. In males, the ORs were for BRI (6.83, 95% CI 5.39-8.66), WHR (6.43, 95% CI 5.9-6.9), AVI (2.02, 95% CI 1.86-2.12). In females, the ORs were for BRI (3.72, 95% CI 3.09-4.48), WtHR (2.63, 95% CI 1.3-3.5), and WHR (2.45, 95% CI 1.9-3.06).

DISCUSSION

The presence of a large AUC in almost all anthropometric indices suggests that they can be used to assess the risk of malnutrition among older persons in both sexes.

Noninvasive and Convenient Screening of Metabolic Syndrome Using the Controlled Attenuation Parameter Technology: An Evaluation Based on Self-Paid Health Examination Participants

Background: There is a medical need for an easy, fast, and non-invasive method for metabolic syndrome (MetS) screening. This study aimed to assess the ability of FibroScan to detect MetS, in participants who underwent a self-paid health examination. Methods: A retrospective cohort study was conducted on all adults who underwent a self-paid health examination comprising of an abdominal transient elastography inspection using FibroScan 502 Touch from March 2015 to February 2019. FibroScan can assess the level of liver fibrosis by using a liver stiffness score, and the level of liver steatosis by using the controlled attenuation parameter (CAP) score. The logistic regression analysis and receiver operating characteristic curve were applied to select significant predictors and assess their predictability. A final model that included all significant predictors that are found by univariate analysis, and a convenient model that excluded all invasive parameters were created. Results: Of 1983 participants, 13.6% had a physical status that fulfilled MetS criteria. The results showed that the CAP score solely could achieve an area under the curve (AUC) of 0.79 (0.76–0.82) in predicting MetS, and the AUC can be improved to 0.88 (0.85–0.90) in the final model. An AUC of 0.85 (0.83–0.88) in predicting MetS was obtained in the convenient model, which includes only 4 parameters (CAP score, gender, age, and BMI). A panel of predictability indices (the ranges of sensitivity, specificity, positive and negative likelihood ratio: 0.78–0.89, 0.66–0.82, 2.64–4.47, and 0.17–0.26) concerning gender- and BMI-specific CAP cut-off values (range: 191.65–564.95) were presented for practical reference. Conclusions: Two prediction systems were proposed for identifying individuals with a physical status that fulfilled the MetS criteria, and a panel of predictability indices was presented for practical reference. Both systems had moderate predictive performance. The findings suggested that FibroScan evaluation is appropriate as a first-line MetS screening; however, the variation in prediction performance of such systems among groups with varying metabolic derangements warrants further studies in the future.