Usefulness of waist-to-height ratio in screening incident metabolic syndrome among Japanese community-dwelling elderly individuals

Diagnostic Accuracy of Waist-to-Height Ratio, Waist Circumference, and Body Mass Index in Identifying Metabolic Syndrome and Its Components in Older Adults: A Systematic Review and Meta-Analysis

Background

Although numerous studies have indicated the utility of waist-to-height ratio (WHtR) in early screening for individuals with adverse cardiometabolic health, there is controversy on using WHtR as a one-size-fits-all approach, including in older adults.

Objectives

Our study aims to identify the pooled diagnostic accuracy of WHtR in screening for metabolic syndrome (MetS) and its components among older adults.

Methods

A systematic review of observational studies was performed using 4 databases. A diagnostic meta-analysis with a random effects model was conducted, and the pooled area under the summary receiver operating characteristic curve, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (dOR) of each outcome compared with WHtR, body mass index (BMI), and waist circumference (WC) were calculated, with sex-stratified analysis.

Results

A total of 17 studies with 74,520 participants were included. As reflected by the dOR, WHtR (7.65; 95% CI: 6.00, 9.75) performed better than BMI (5.17; 95% CI: 4.75, 5.62) and WC (5.77; 95% CI: 4.60, 7.25) in screening for MetS among older adults and was potentially better among males. For hyperglycemia, hypertension, and dyslipidemia, the performances of WHtR, BMI, and WC were comparable.

Conclusion

More studies focusing on older adults are still needed to determine the cutoff values of WHtR to screen for MetS.The search strategy was registered in PROSPERO as CRD42022350379.

Thigh-hip ratio is significantly associated with all-cause mortality among Japanese community-dwelling men

Anthropometric evaluation is a simple yet essential indicator of muscle and fat mass when studying life prognosis in aging. This study aimed to investigate the contributions of anthropometric measurements, independent of body mass index, to measures of all-cause mortality. We examined data for 1,704 participants from the 2014 Nomura Cohort Study who attended follow-ups for the subsequent eight years (follow-up rate: 93.0%). Of these, 765 were male (aged 69 ± 11 years) and 939 were female (aged 69 ± 9 years). The Japanese Basic Resident Registry provided data on adjusted relative hazards for all-cause mortality. The data were subjected to a Cox regression analysis, wherein the time variable was age and the risk factors were gender, age, anthropometric index, smoking habits, drinking habits, exercise habits, cardiovascular history, hypertension, lipid levels, diabetes, renal function, and serum uric acid. Of the total number of participants, 158 (9.3%) were confirmed to have died, and of these, 92 were male (12.0% of all male participants) and 66 were female (7.0% of all female participants). The multivariable Cox regression analysis revealed that a smaller thigh-hip ratio predicted eight-year all-cause mortality in male participants, but only baseline body mass index was associated with all-cause mortality in female participants. Thigh-hip ratio is a useful predictor of death in Japanese community-dwelling men.

Relationship Between Neck Circumference and Risk Factors of Metabolic Syndrome in a Bushehr Elderly Health Study

Metabolic syndrome includes a set of metabolic disorders such as obesity, high blood pressure, hypertriglyceridemia, lipid disorders, and glucose intolerance. In this cross-sectional (descriptive-analytical) study, 2,426 people were selected from the 60 years old and above population of Bushehr for a second-phase investigation of the relationship between neck circumference (NC) and cardiometabolic risk factors in the elderly people. The data (mean and standard deviation) were analyzed using STATA MP Version 15 software. The results of the study showed that the average age of all elderly participants in the study was 69.34 ± 6.39 years. The mean and standard deviation of the NC index in men, women, and all participants were 39.31 ± 2.89, 34.86 ± 2.84, and 37.00 ± 3.62, respectively. The mean and standard deviation of most laboratory indicators (triglyceride [TG], total cholesterol [TC], low-density lipoprotein [LDL], high-density lipoprotein [HDL]) were significantly higher in women, and there was no significant difference in fasting blood glucose (FBG) between men and women. NC index in the total population was significantly associated with all risk factors of metabolic syndrome (body mass index, systolic blood pressure, diastolic blood pressure) and laboratory indicators (FBG, TG, TC, LDLC, and HDL). The present study shows that the NC index can be a good predictor for the diagnosis of metabolic syndrome and visceral adipose tissue in the elderly.

Metabolic Syndrome and Body Composition Among People Aged 50 Years and Over: Results from The Neyshabur Longitudinal Study on Ageing (NeLSA)

There are few studies regarding body composition and metabolic syndrome (MetS) association in older adults. To evaluate the association between MetS and body composition indices in a large-scale population of subjects with an age of 50 and up. This study was based on the data from Neyshabur Longitudinal Study on Ageing (NeLSA) in a total of 7462 people of Neyshabur city in IRAN. The best cut-off scores and AUC value of body composition variables for having association with likelihood of MetS were determined by using a receiver operating curve analysis. Each unit increase in the Waist/Hip ratio, the odds of having MetS increase 3-6 times (OR: 4.937, 95%CI: 3.930, 6.203 in men; OR: 3.322, 95%CI: 2.259, 4.884 in women). In addition, in the case of BMI (OR: 1.256, 95% Cl: 1.226, 1.286 in men; OR: 1.104, 95% Cl: 1.086, 1.121 in women) and BFM (OR: 1.119, 95% Cl: 1.105, 1.133 in men; OR: 1.050, 95% Cl: 1.041, 1.060 in women), the chance of having MetS increases with increasing these variables. Totally, BMI and BFM showed the best AUC values. The optimal cut-off values for BMI in men was 26.45 and in women was 27.35 and for BFM in men was 23.35 and in women was 26.85. These results suggest that adiposity measures such as BMI and BFM are associated with likelihood of having MetS in subjects with an age of 50 and up, and that avoiding high adiposity is important to prevent MetS incidence.

Adiposity measures in screening for metabolic syndrome among Chinese children and adolescents

BACKGROUND

Existing various and complicated metabolic syndrome (MetS) definitions have contributed to the difficulty in assessing MetS in children and adolescents, and therefore it is urgently needed to develop a convenient and effective screening tool for pediatric MetS. This study aimed to identify the optimal adiposity measure to screen for pediatric MetS.

METHODS

The cross-sectional data was collected from 8,150 children and adolescents aged 7-17 y living in southern China. Anthropometric indices, blood lipids, and serum glucose were determined. Results of two commonly used MetS definitions were compared: International Diabetes Federation (IDF) and National Cholesterol Education Program Adult Treatment Panel Ⅲ (NCEP-ATP) modified by Cook. Receiver operating characteristic curve analyses were performed and areas under the curve (AUCs) were calculated to determine the optimal index for MetS screening.

RESULTS

MetS prevalence assessed by NCEP-ATP was significantly higher than that by IDF (6.2% vs. 1.5%, p<0.001). Waist-to-height ratio (WHtR) showed the highest screening power for MetS defined by both IDF and NCEP-ATP (AUC 0.932 and 0.900, respectively), and its optimal cut-off point was 0.48 by both IDF and NCEP-ATP definition (sensitivity 0.944 and 0.847, specificity 0.800 and 0.830, respectively), regardless of age or sex. When taking sex diversity into account, the optimal WHtR cut-off point was 0.49 (IDF) or 0.50 (NCEP-ATP) in boys, and 0.46 (both definitions) in girls.

CONCLUSIONS

Among children and adolescents aged 7-17 y in southern China, a WHtR greater than 0.48 can be a simple but effective screening tool for MetS.

Using noninvasive anthropometric indices to develop and validate a predictive model for metabolic syndrome in Chinese adults: a nationwide study

PURPOSE

Metabolic syndrome (Mets) is a pathological condition that includes many abnormal metabolic components and requires a simple detection method for rapid use in a large population. The aim of the study was to develop a diagnostic model for Mets in a Chinese population with noninvasive anthropometric and demographic predictors.

PATIENTS AND METHODS

Least absolute shrinkage and selection operator (LASSO) regression was used to screen predictors. A large sample from the China National Diabetes and Metabolic Disorders Survey (CNDMDS) was used to develop the model with logistic regression, and internal, internal-external and external validation were conducted to evaluate the model performance. A score calculator was developed to display the final model.

RESULTS

We evaluated the discrimination and calibration of the model by receiver operator characteristic (ROC) curves and calibration curve analysis. The area under the ROC curves (AUCs) and the Brier score of the original model were 0.88 and 0.122, respectively. The mean AUCs and the mean Brier score of 10-fold cross validation were 0.879 and 0.122, respectively. The mean AUCs and the mean Brier score of internal-external validation were 0.878 and 0.121, respectively. The AUCs and Brier score of external validation were 0.862 and 0.133, respectively.

CONCLUSIONS

The model developed in this study has good discrimination and calibration performance. Its stability was proved by internal validation, external validation and internal-external validation. Then, this model has been displayed by a calculator which can exhibit the specific predictive probability for easy use in Chinese population.

Curcuma Longa, the "Golden Spice" to Counteract Neuroinflammaging and Cognitive Decline-What Have We Learned and What Needs to Be Done

Due to the global increase in lifespan, the proportion of people showing cognitive impairment is expected to grow exponentially. As target-specific drugs capable of tackling dementia are lagging behind, the focus of preclinical and clinical research has recently shifted towards natural products. Curcumin, one of the best investigated botanical constituents in the biomedical literature, has been receiving increased interest due to its unique molecular structure, which targets inflammatory and antioxidant pathways. These pathways have been shown to be critical for neurodegenerative disorders such as Alzheimer’s disease and more in general for cognitive decline. Despite the substantial preclinical literature on the potential biomedical effects of curcumin, its relatively low bioavailability, poor water solubility and rapid metabolism/excretion have hampered clinical trials, resulting in mixed and inconclusive findings. In this review, we highlight current knowledge on the potential effects of this natural compound on cognition. Furthermore, we focus on new strategies to overcome current limitations in its use and improve its efficacy, with attention also on gender-driven differences.

Comparison of Various Obesity-Related Indices for Identification of Metabolic Syndrome: A Population-Based Study from Taiwan Biobank

This study aimed to evaluate the performance of 11 obesity-related indices, including body mass index (BMI), waist circumference, waist-to-height ratio, waist–hip ratio, a body shape index, abdominal volume index, body adiposity index, body roundness index, conicity index, visceral adiposity index (VAI), and triglyceride glucose (TyG) index, in identifying metabolic syndrome (MetS) in adults. The information of 5000 participants was obtained from the Taiwan Biobank. Logistic regression analyses were performed to determine the associations between MetS and obesity-related indices with odds ratio (ORs). The predictive performance of the indices to identify MetS was compared using receiver operating characteristic (ROC) curves and areas under curves (AUCs). Multivariate-adjusted logistic regression showed that the ORs for MetS increased across the quartiles of each index. ROC curves analysis demonstrated that TyG index had the greatest AUC in men (AUC = 0.850) and women (AUC = 0.890). Furthermore, VAI had the greatest AUC in men (AUC = 0.867) and women (AUC = 0.925) aged 30−50 years, while TyG index had the greatest AUC in men (AUC = 0.849) and women (AUC = 0.854) aged 51−70 years. Among the studied obesity-related indices, TyG index and VAI exhibited the best performance for identifying MetS in adults. TyG index and VAI may be the relevant indices to assess MetS in clinical practice.

Prevalence of the Metabolic Syndrome and its components in the Brazilian adult population

We estimated the prevalence of the Metabolic Syndrome (MetS) and its components in the Brazilian population according to sociodemographic factors. This is a cross-sectional population-based study that used laboratory data from the National Health Survey. We estimated the prevalence of MetS and its components with 95% confidence intervals and the unadjusted and adjusted prevalence ratio (PR) with the Poisson regression. MetS prevalence ratio was 38.4%. High waist circumference (WC) (65.5%) and low HDL cholesterol (49.4%) were the most prevalent components, including in the youngest people. MetS and its components were more frequent among women (41.8%), individuals with low schooling (47.5%), and older adults (66.1%). In the adjusted analysis, females (PR = 1.16; 95% CI 1.08-1.24), older adults (PR = 3.69; 95% CI 3.26-4.17), and low schooling (PR = 1.32; 95% CI 1.17-1.49) were associated with MetS. MetS was prevalent in the Brazilian population, especially among women, individuals with low schooling, and older adults. High WC and low HDL cholesterol were the most prevalent components, with the aggravating high prevalence factor in young adults. These findings reveal the need to consider laboratory data for a more accurate analysis of this condition, which can be challenging at the national level.

New Simplified Diagnostic Decision Trees for the Detention of Metabolic Syndrome in the Elderly

BACKGROUND

A new simplified method for the detention of metabolic syndrome (MetS) is proposed using two variables (anthropometric and minimally invasive).

METHODS

A study of MetS prevalence was made on a sample of 361 older people. The anthropometric variables analyzed were: blood pressure, body mass index, waist circumference (WC), waist-height ratio, body fat percentage, and waist-hip ratio. A crude and adjusted binary logistic regression was performed, and receiver operating characteristic curves were obtained for determining the predictive capacity of those variables. For the new detection method, decision trees were employed using automatic detection by interaction through Chi-square.

RESULTS

The prevalence of the MetS was of 43.7%. The final decision trees uses WC and basal glucose (BG), whose cutoff values were: for men, WC ≥ 102.5 cm and BG > 98 mg/dL (sensitivity = 67.1%, specificity = 90.3%, positive predictive value = 85%, validity index = 79.9%); and for women, WC ≥ 92.5 cm and BG ≥ 97 mg/dL (sensitivity = 65.9%, specificity = 92.7%, positive predictive value = 87.1%, validity index = 81.3%). In older women the best predictive value of MetS was a WC of 92.5 cm.

CONCLUSIONS

It is possible to make a simplified diagnosis of MetS in older people using the WC and basal capillary glucose, with a high diagnostic accuracy and whose use could be recommended in the resource-poor health areas. A new cutting point in older women for the WC should be valued.

External validation of the relative fat mass (RFM) index in adults from north-west Mexico using different reference methods

Background

Analysis of body composition is becoming increasingly important for the assessment, understanding and monitoring of multiple health issues. The body mass index (BMI) has been questioned as a tool to estimate whole-body fat percentage (FM%). Recently, a simple equation described as relative fat mass (RFM) was proposed by Woolcott & Bergman. This equation estimates FM% using two anthropometric measurements: height and waist circumference (WC). The authors state that due to its simplicity and better performance than BMI, RFM could be used in daily clinical practice as a tool for the evaluation of body composition. The aim of this study was to externally validate the equation of Woolcott & Bergman to estimate FM% among adults from north-west Mexico compared with Dual-energy X-ray absorptiometry (DXA) as an alternative to BMI and secondly, to make the same comparison using air displacement plethysmography (ADP), Bioelectrical Impedance Analysis (BIA) and a 4-compartment model (4C model).

Methods

Weight, height and WC were measured following standard procedures. The RFM index was calculated for each of the 61 participating subjects (29 females and 32 males, ages 20–37 years). The RFM was then regressed against each of the four body composition methods for estimating FM%.

Results

Compared with BMI, RFM was a better predictor of FM% determined by each of the body composition methods. In terms of precision the best equation was RFM regressed against DXA (y = 1.12 + 0.99 x; R² = 0.84 p<0.001). Accuracy (represented by the closeness to the zero-intercept) was 1.12 (95% CI: -2.44, to 4.68) and thus, not significantly different from zero. For the rest of the methods, precision in the prediction of FM% was improved compared to BMI, with significant increases in the R² and reduction of the root mean squared error (RMSE). However, the intercepts of each regression did not show accuracy since they were different from zero, for ADP: -9.95 (95%CI: -15.7 to -4.14), for BIA: -12.6 (95%CI: -17.5 to -7.74) and for the 4C model: -13.6 (95%CI: -18.6 to -8.60). Irrespectively, FM% measured by each of the body composition methods was higher for DXA than the other three methods (p<0.001).

Conclusions

This external validation proved that the performance of the RFM equation used in this study to estimate FM% was more consistent than BMI in this Mexican population, showing a stronger correlation with DXA than with the other body composition methods.

A simple cut-off for waist-to-height ratio (0·5) can act as an indicator for cardiometabolic risk: recent data from adults in the Health Survey for England

The National Institute for Health and Care Excellence (NICE) has acknowledged the value of waist-to-height ratio (WHtR) as an indicator for ‘early health risk’. We used recent UK data to explore whether classification based on WHtR identifies more adults at cardiometabolic risk than the ‘matrix’ based on BMI and waist circumference, currently used for screening. Data from the Health Survey for England (4112 adults aged 18+ years) were used to identify cardiometabolic risk, indicated by raised glycated Hb, dyslipidaemia and hypertension. HbA1c, total/HDL-cholesterol and systolic blood pressure (BP) were more strongly associated with WHtR than the ‘matrix’. In logistic regression models for HbA1c ≥ 48 mmol/mol, total/HDL-cholesterol > 4 and hypertension (BP > 140/90 mmHg or on medication), WHtR had a higher predictive value than the ‘matrix’. AUC was significantly greater for WHtR than the ‘matrix’ for raised HbA1c and hypertension. Of adults with raised HbA1c, 15 % would be judged as ‘no increased risk’ using the ‘matrix’ in contrast to 3 % using WHtR < 0·5. For hypertension, comparative values were 23 and 9 %, and for total/HDL-cholesterol > 4, 26 and 13 %. Nearly one-third of the ‘no increased risk’ group in the ‘matrix’ had WHtR ≥ 0·5 and hence could be underdiagnosed for cardiometabolic risk. WHtR has the potential to be a better indicator of cardiometabolic risks associated with central obesity than the current NICE ‘matrix’. The cut-off WHtR 0·5 in early screening translates to a simple message, ‘your waist should be less than half your height’, that allows individuals to be aware of their health risks.