Evaluation of Eight Anthropometric Indices for Identification of Metabolic Syndrome in Adults with Diabetes

Association between two novel anthropometric measures and type 2 diabetes in a Chinese population

AIMS

To investigate the associations of conicity index (C-index) and relative fat mass (RFM) with incident type 2 diabetes mellitus (T2DM) among adults in China.

MATERIALS AND METHODS

A total of 10 813 participants aged over 18 years in Shenzhen Longhua district were enrolled in a follow-up study conducted from 2018 to 2022. The participants were categorized based on quartiles (Q) of C-index and RFM. The Cox proportional hazards model was performed to examine the relationships between C-index, RFM and the risk of T2DM.

RESULTS

After adjusting for potential confounding factors, including age, sex, occupation, marital status, education level, smoking status, alcohol consumption, physical exercise, hypertension status, fasting blood glucose (FBG) and total cholesterol (TC), both C-index and RFM showed positive and independent associations with risk of T2DM. The multivariable-adjusted hazard ratios (95% confidence intervals) for T2DM risk in participants in C-index Q3 and Q4 compared with those in C-index Q1 were 1.50 (1.12, 2.02) and 1.73 (1.29, 2.30), and 1.94 (1.44, 2.63), 3.18 (1.79, 5.64), 4.91 (2.68, 9.00) for participants in RFM Q2, Q3 and Q4 compared with RFM Q1. These differences were statistically significant (all p < 0.05).

CONCLUSION

C-index and RFM are strongly associated with new-onset T2DM and could be used to identify the risk of diabetes in large-scale epidemiological studies.

Association of the CUN-BAE body adiposity estimator and other obesity indicators with cardiometabolic multimorbidity: a cross-sectional study

Cardiometabolic multimorbidity (CM), defined as the coexistence of two or three cardiometabolic disorders, is one of the most common and deleterious multimorbidities. This study aimed to investigate the association of Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) with the prevalence of CM. The data were obtained from the 2021 health checkup database for residents of the Electronic Health Management Center in Xinzheng, Henan Province, China. 81,532 participants aged ≥ 60 years were included in this study. Logistic regression models were used to estimate the odd ratios (ORs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in CM. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for CM. The multivariable-adjusted ORs (95% CIs) (per 1 SD increase) of CM were 1.799 (1.710-1.893) for CUN-BAE, 1.329 (1.295-1.364) for BMI, 1.343 (1.308-1.378) for WC, and 1.314 (1.280-1.349) for WHtR, respectively. Compared with BMI, WC and WHtR, CUN-BAE had the highest AUC in both males and females (AUC: 0.642; 95% CI 0.630-0.653 for males, AUC: 0.614; 95% CI 0.630-0.653 for females). CUN-BAE may be a better measure of the adverse effect of adiposity on the prevalence of CM than BMI, WC, and WHtR.

Evaluating the performance of a novel anthropometric index: weight adjusted for waist-to-height ratio (W-WHR) - for predicting cardiometabolic risk among adults in Addis Ababa

OBJECTIVE

Various anthropometric indices had been proposed to predict cardiometabolic risk, yet few were validated in the African population. We evaluated the diagnostic accuracy of a novel anthropometric index-weight adjusted for waist-to-height ratio (W-WHR)-as a predictor of cardiometabolic risk among adults 18-64 years in Addis Ababa, Ethiopia; and compared its performance with other indices commonly used in the literature.

DESIGN

Cross-sectional study.

SETTING

Community-based study in Addis Ababa, Ethiopia.

PARTICIPANTS

Randomly selected adults (n=600) completed serum lipid, blood pressure, blood glucose and anthropometric measurements.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcomes of interest were dyslipidaemia, hypertension and hyperglycaemia. Having at least one of the three outcomes was considered as a secondary outcome. Receiver-operating characteristic curve (ROC) used to measure the diagnostic accuracy of W-WHR and another 13 indices for predicting the primary and secondary outcomes. Optimal thresholds were determined using Youden's index.

RESULTS

W-WHR demonstrated an acceptable diagnostic accuracy (area under the curve (AUC), 95% CI) for correctly classifying dyslipidaemia (0.80, 0.76 to 0.84), hypertension (0.74, 0.70 to 0.78), hyperglycaemia (0.76, 0.70 to 0.82) and the secondary outcome of interest (0.79, 0.75 to 0.83). Depending on the outcomes, thresholds between 32.6 and 36.7 concurrently maximised sensitivity and specificity of the index. ROC analysis indicated, W-WHR (AUC=0.80), abdominal volume index (AVI) (AUC=0.78) and waist circumference (WC) (AUC=0.78) for dyslipidaemia; W-WHR (AUC=0.74) and WC (AUC=0.74) for hypertension; and waist-to-height ratio (AUC=0.80) and body roundness index (AUC=0.80) for hyperglycaemia, had the highest diagnostic accuracy. Likewise, W-WHR (AUC=0.79), AVI (AUC=0.78) and WC (AUC=0.78) had better performance for the secondary outcome. Most indices have better utility among younger than older adults, and per cent body fat had the highest diagnostic accuracy among women (AUC 0.74-0.83).

CONCLUSION

W-WHR is a useful index for predicting cardiometabolic risk, especially among young adults.

Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio is a more powerful marker than TyG index for predicting metabolic syndrome in patients with type 2 diabetes mellitus

Purpose

The prevalence of metabolic syndrome (MetS) is increasing globally and has become a global and national public health problem that cannot be ignored as an independent predictor of cardiovascular events, cancer and all-cause mortality. γ-glutamyl transferase (GGT) and high-density lipoprotein cholesterol (HDL-C) are associated with insulin resistance, dyslipidemia and oxidative stress. This study was designed to explore the relationship and predictive performance between γ-glutamyl transferase high-density lipoprotein cholesterol ratio (GGT/HDL-C) and MetS.

Methods

This was a cross-sectional study. MetS was diagnosed from biochemical and anthropometric data in subjects with T2DM. Multivariate logistic regression was used to analyses the relationship between GGT/HDL-C ratio, TyG index and HOMA-IR and MetS in subjects with T2DM. Receiver operating characteristic (ROC) curve was drawn and the areas under the curve (AUC) were used to assess the ability of these indexes in screening MetS in subjects with T2DM. Statistical differences between the AUC values of these indexes were compared. In addition, we performed subgroup analyses and interactions.

Results

769 (70.55%) patients with T2DM were defined as having MetS. patients with MetS had higher anthropometric values and biochemical indicators compared to those without MetS. Multivariate logistic regression analysis of GGT/HDL-C ratio was an independent risk factor for MetS (Per 1 SD increase, OR = 2.49, 95% CI: 1.51, 4.10). According to ROC curve analysis, the value of GGT/HDL-C ratio in predicting MetS in subjects with T2DM was superior to that of TyG index and HOMA-IR. The best cut-off value for GGT/HDL-C prediction was 19.94.

Conclusions

GGT/HDL-C ratio may be an important predictor of MetS in subjects with T2DM, and its predictive power is stronger than that of TyG index and HOMA-IR. The risk of MetS in subjects with T2DM is increased in the presence of a higher GGT/HDL-C ratio.

Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study

Objectives: Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is considered to be a more accurate indicator of body fat estimation. We aimed to investigate the association of CUN-BAE with the risk of type 2 diabetes mellitus (T2DM) and to compare the strength of the association between CUN-BAE, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and T2DM. Methods: The data were obtained from the annual health checkup database of residents in Xinzheng, China. From January 2011 to December 2021, 80,555 subjects aged ≥45 years met the inclusion criteria. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in T2DM. Results: During a mean follow-up of 6.26 years, T2DM occurred in 12,967 subjects. The multivariable-adjusted HRs (95% CIs) of T2DM (highest vs. reference group) were 1.994 (1.811-2.196) for CUN-BAE, 1.751 (1.665-1.842) for WC, 1.715 (1.631-1.804) for WHtR, and 1.510 (1.436-1.588) for BMI, respectively. In addition, the risk of T2DM increased with baseline CUN-BAE (HR: 1.374; 95% CI: 1.328, 1.421), WC (HR: 1.236; 95% CI: 1.215, 1.256), WHtR (HR: 1.228; 95% CI: 1.208, 1.248), and BMI (HR: 1.175; 95% CI: 1.156, 1.195). Conclusion: Compared to BMI, WC or WHtR, CUN-BAE may more adequately reflect the adverse effects of adiposity on the risk of T2DM.

Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study

Objective

Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults.

Method

A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS.

Results

A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women.

Conclusion

Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.

The relationship between the CUN-BAE body fatness index and incident diabetes: a longitudinal retrospective study

BACKGROUND

The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index has been recommended as an ideal indicator of body fat and exhibited significant correlation with cardiometabolic risk factors. However, whether the CUN-BAE index correlates with incident diabetes in Asian populations is unknown. Therefore, this longitudinal study was designed to evaluate the association between baseline CUN-BAE index and type 2 diabetes mellitus (T2DM).

METHODS

This retrospective longitudinal study involved 15,464 participants of 18-79 years of age in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study over the period of 2004-2015. Cox proportional hazards regression was performed to test the relationship between the baseline CUN-BAE index and diabetes incidence. Further stratification analysis was conducted to ensure that the results were robust. The diagnostic utility of the CUN-BAE index was tested by the receiver operating characteristic (ROC) curve.

RESULTS

Over the course of an average follow-up of 5.4 years, 373 (2.41%) participants developed diabetes. A higher diabetes incidence was associated with higher CUN-BAE quartiles (P for trend< 0.001). Each 1 unit increase in CUN-BAE index was associated with a 1.08-fold and 1.14-fold increased risk of diabetes after adjustment for confounders in males and females, respectively (both P < 0.001). Stratification analysis demonstrated a consistent positive correlation between baseline CUN-BAE and diabetes incidence. Moreover, based on ROC analysis, CUN-BAE exhibited a better capacity for diabetes prediction than both body mass index (BMI) and waist circumference (WC) in both sexes.

CONCLUSIONS

The baseline CUN-BAE level was independently related to the incidence of diabetes. Increased adiposity determined by CUN-BAE could be used as a strong nonlaboratory predictor of incident diabetes in clinical practice.

Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up

BACKGROUND

Abdominal obesity (AO) has been regarded as the most dangerous type of obesity. The Conicity-index (C-index) had a high ability to discriminate underlying AO. The purpose of this study was to determine the ability of C-index to predict all-cause mortality among non-cancer Chinese older people.

METHODS

The participants were residents of the Wanshou Road community in Beijing, China. Receiver operating curve (ROC) curves were used to determine the sensitivity and specificity of the best cut-off values for different anthropometric measures for predicting all-cause mortality. The area under the curve (AUC) of the ROC curves were calculated to compare the relative ability of various anthropometric measures to correctly identify older people in the community where all-cause mortality occurs. Included subjects were grouped according to C-index tertiles. The association between C-index and all-cause mortality was verified using Kaplan-Meier survival analysis and different Cox regression models.

RESULTS

During a mean follow-up period of 9.87 years, 1821 subjects completed follow-up. The average age was 71.21 years, of which 59.4% were female. The ROC curve results showed that the AUC of the C-index in predicting all-cause mortality was 0.633. Kaplan-Meier survival curves showed a clear dose-response relationship between C-index and all-cause mortality. With the increase of C-index, the survival rate of the study population showed a significant downward trend (P < 0.05). Adjusted for age, gender, hip circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPG), glycosylated hemoglobin, high-density lipids protein (LDL), triglyceride, serum creatinine, serum uric acid, urine albumin-creatinine ratio (UACR), Mini-Mental State Examination (MMSE), smoking history, and drinking history, COX regression analysis showed that in the model adjusted for all covariates, the risk of all-cause mortality in tertile 3 was 1.505 times that in tertile 1, and the difference was statistically significant.

CONCLUSIONS

The C-index is an independent risk factor for all-cause mortality in the non-cancer Chinese older people.

Assessing metabolic syndrome prediction quality using seven anthropometric indices among Jordanian adults: a cross-sectional study

Metabolic syndrome (MSyn) is a considerable health concern in developing and developed countries, and it is a critical predictor of all-cause mortality. Obesity, specifically central obesity, is highly associated with MSyn incidence and development. In this study, seven anthropometric indices (Body Mass Index (BMI), Waist circumference (WC), Waist-to-Height Ratio (WHtR), A Body Shape Index (ABSI), Body Roundness Index (BRI), conicity index (CI), and the Visceral Adiposity Index (VAI)) were used to identify individuals with MSyn among the Jordanian population. These indices were assessed to identify their superiority in predicting the risk of MSyn. A total of 756 subjects (410 were male and 346 were female) were met between May 2018 and September 2019 and enrolled in this study. Height, weight, and waist circumferences were measured and BMI, WHtR, ABSI, BRI, CI, and VAI were calculated. Fasting plasma glucose level, lipid profile, and blood pressure were measured. Receiver-operating characteristic (ROC) curve was used to determine the discriminatory power of the anthropometric indices as classifiers for MSyn presence using the Third Adult Treatment Panel III (ATP III) definition. MSyn prevalence was 42.5%, and obese women and men have a significantly higher prevalence. BRI and WHtR showed the highest ability to predict MSyn (AUC = 0.83 for both indices). The optimal cutoff point for an early diagnosis of MSyn was > 28.4 kg/m² for BMI, > 98.5 cm for WC, > 5.13 for BRI, > 0.09 m^11/6 kg^-2/3 for ABSI, > 5.55 cm² for AVI, > 1.33 m^3/2 kg^-1/2 for CI, and > 0.59 for WHtR with males having higher cutoff points for MSyn early detection than females. In conclusion, we found that WHtR and BRI may be the best-suggested indices for MSyn prediction among Jordanian adults. These indices are affordable and might result in better early detection for MSyn and thereby may be helpful in the prevention of MSyn and its complications.

Waist-to-height ratio is a simple and practical alternative to waist circumference to diagnose metabolic syndrome in type 2 diabetes

BACKGROUND

As an indicator of abdominal obesity, waist circumference (WC) varied with race and gender in diagnosing metabolic syndrome (MetS). Therefore, it is clinically important to find an alternative indicator of abdominal obesity independent of these factors to diagnose MetS. Our aims were to evaluate the association between waist-to-height ratio (WHtR) and MetS and further determine whether WHtR could be used as a simple and practical alternative to WC to diagnose MetS in patients with type 2 diabetes mellitus (T2DM).

METHODS

This cross-sectional, real-world study recruited 8488 hospitalized T2DM patients including 3719 women (43.8%) aged from 18 to 94 years and 4769 men (56.2%) aged from 18 to 91 years. A WHtR cut-off of 0.52 was used to diagnose MetS in both men and women T2DM patients based on our previous study. The association of WHtR with MetS in T2DM patients was analyzed by binary logistic regression. The consistency of two diagnostic criteria for MetS according to WC and WHtR was determined by Kappa test.

RESULTS

The prevalence of MetS according to WHtR was 79.4% in women and 68.6% in men T2DM patients, which was very close to the prevalence of MetS according to WC in both women (82.6%) and men (68.3%). The prevalence of MetS diagnosed by WC in both men and women with WHtR ≥ 0.52 was significantly higher than in those with WHtR < 0.52 after adjustment for age and duration of diabetes (89.2 vs. 38.7% for men; 92.8 vs. 57.4% for women; respectively, all p < 0.001). Binary logistic regression analysis displayed that after adjusting for confounding factors, WHtR was significantly associated with the presence of MetS in both men and women (men: OR = 4.821, 95% CI: 3.949-5.885; women: OR = 3.096, 95% CI: 2.484-3.860; respectively, all p < 0.001). Kappa test revealed that there was an excellent consistency between the diagnosis of MetS based on WC and on WHtR in T2DM patients (men: kappa value = 0.929, 95% CI: 0.918-0.940; women: kappa value = 0.874, 95% CI: 0.854-0.894; total: kappa value = 0.911, 95% CI: 0.901-0.921; respectively, all p < 0.001).

CONCLUSION

WHtR is independently associated with the presence of MetS and can be used as a simple and practical alternative to WC to diagnose MetS regardless of gender in T2DM patients.

What is the best anthropometry index to evaluate the risk of metabolic abnormalities in Chinese adults?

AIMS

Obesity, defined by body mass index (BMI), is a heterogeneous condition with varying metabolic manifestations, and the best index for predicting metabolic abnormalities remains unclear. This study aimed to explore the most suitable anthropometry index for predicting metabolic abnormalities in Chinese adults.

METHODS

A cross-sectional study was conducted using the data obtained from 9517 Chinese adults who underwent physical examination, bioelectrical impedance analysis, and laboratory examinations between March 2018 and March 2022. Participants were further divided into eight subgroups according to age, BMI, and sex. Descriptive statistics were calculated, and the area under the receiver operating characteristic curve and Youden index values were calculated to identify the best predictor of metabolic abnormalities in Chinese adults.

RESULTS

The waist-to-height ratio (WHtR) had the largest area under the curve for predicting metabolic abnormalities in men of any age and women aged 18-49 years. However, BMI showed the highest accuracy in predicting metabolic abnormalities in women aged 50 years and older. Based on the highest Youden index, the optimal WHtR threshold was 0.51 in women and 0.53 in men.

CONCLUSIONS

The WHtR was the most effective index for predicting metabolic abnormalities in most Chinese adults, whereas BMI showed a higher accuracy only in elderly women. This observation supports WHtR as a novel adiposity marker for screening metabolic abnormalities and shows value for public health practice.

Relationship of body fat and left ventricular hypertrophy with the risk of all-cause death in patients with coronary artery disease

BACKGROUND

Left ventricular hypertrophy (LVH) is prevalent in obese individuals. Besides, both of LVH and obesity is associated with subclinical LV dysfunction. The study aims to investigate the interplay between body fat and LVH in relation to all-cause death in patients with coronary artery disease (CAD).

METHODS

In this retrospective cohort study, a total of 2243 patients with angiographically proven CAD were included. Body fat and LV mass were calculated using established formulas. Patients were grouped according to body fat percentage and presence or absence of LVH. Cox-proportional hazard models were used to observe the interaction effect of body fat and LVH on all-cause death.

RESULTS

Of 2243 patients enrolled, 560 (25%) had a higher body fat percentage, and 1045 (46.6%) had LVH. After a median follow-up of 2.2 years, the cumulative mortality rate was 8.2% in the group with higher body fat and LVH, 2.5% in those with lower body fat and no LVH, 5.4% in those with higher body fat and no LVH, and 7.8% in those with lower body fat and LVH (log-rank P < 0.001). There was a statistically significant interaction between body fat percentage and LVH ( P interaction was 0.003). After correcting for confounding factors, patients with higher body fat and LVH had the highest risk of all-cause death (HR = 3.49, 95% CI: 1.40-8.69, P = 0.007) compared with those with lower body fat and no LVH; in contrast, patients with higher body fat and no LVH had no statistically significant difference in risk of death compared with those with lower body fat and no LVH (HR = 2.03, 95% CI: 0.70-5.92, P = 0.195).

CONCLUSION

A higher body fat percentage was associated with a different risk of all-cause death in patients with CAD, stratified by coexistence of LVH or not. Higher body fat was significantly associated with a greater risk of mortality among patients with LVH but not among those without LVH.

Metabolically healthy obesity is associated with increased risk of lower urinary tract symptoms secondary to benign prostatic hyperplasia: A cohort study of Chinese elderly males

OBJECTIVES

Obesity and metabolic status are both modifiable risk factors of lower urinary tract symptoms secondary to benign prostatic hyperplasia (LUTS/BPH). However, the association between metabolically healthy obesity (MHO) and LUTS/BPH is largely unexplored. This study aimed to investigate the risk of LUTS/BPH among different metabolic syndrome-body mass index (MetS-BMI) phenotypes in a cohort of Chinese males.

METHODS

A total of 3321 males from the China Health and Retirement Longitudinal Study (CHARLS) without history of LUTS/BPH at baseline were included into the analyses. Participants were categorized into six mutually exclusive groups according to presence or absence of MetS combined with BMI status: metabolically healthy normal weight/overweight/obesity (MHN/MHOW/MHO) and metabolically unhealthy normal weight/overweight/obesity (MUN/MUOW/MUO). Adjusted odds ratios (OR) and 95% CI of LUTS/BPH across MetS-BMI categories were estimated with multivariable logistic regression models.

RESULTS

A total of 394 (11.86%) participants developed LUTS/BPH during the follow-up. After adjusting for age, educational level, smoking status, drinking status, and BMI change, the multivariable-adjusted OR (95% CI) for incident LUTS/BPH comparing MUO, MHO, MUOW, MHOW, and MUN with MHN were 1.99 (1.23-3.22), 2.04 (1.14-3.66), 1.61 (1.11-2.34), 1.45 (1.02-2.05), and 0.91 (0.54-1.56), respectively.

CONCLUSIONS

MHO and MHOW were risk populations of LUTS/BPH, suggesting that overweight and obesity can independently contribute to LUTS/BPH, even among metabolically healthy individuals. These findings emphasize metabolically healthy individuals may still benefit from maintaining normal body weight to prevent LUTS/BPH. Our findings also support that those recommendations for LUTS/BPH should highlight the importance of maintaining metabolic health across all BMI groups among Chinese males.

Associations between Metabolic Syndrome and Obesity-Related Indices and Bone Mineral Density T-Score in Hemodialysis Patients

Previous studies have reported inconsistent results regarding the associations between metabolic syndrome (MetS) and obesity-related indices and bone mineral density (BMD). However, no previous studies have reported these associations among hemodialysis (HD) patients. The aims of this study were to investigate associations between MetS and its components and BMD T-score in HD patients and also between obesity-related indices and BMD T-score in HD patients with and without MetS. MetS was defined according to the Adult Treatment Panel III for Asians, and BMD T-score was calculated using dual-energy X-ray absorptiometry. Eight obesity-related indices were evaluated, including lipid accumulation product (LAP), visceral adiposity index (VAI), body adiposity index, conicity index (CI), body roundness index (BRI), abdominal volume index (AVI), waist-to-height ratio (WHtR), waist–hip ratio, and body mass index (BMI). One hundred and sixty-four patients undergoing HD were enrolled, and the prevalence of MetS was 61.6%. MetS was significantly associated with high lumbar spine and total hip T-scores. Regarding the MetS components, abdominal obesity and low HDL-C were significantly associated with high lumbar spine, femoral neck, and total hip T-scores; hypertriglyceridemia was significantly associated with high lumbar spine and total hip T-scores; hyperglycemia was significantly associated with a high lumbar spine T-score, whereas high blood pressure was not associated with T-score at any site. In the patients with MetS, BMI, WHtR, AVI, and BRI were significantly associated with T-score at all sites, and high CI, VAI, and LAP were also related to a high lumbar T-score. However, these indices were not associated with T-score at any site in patients without MetS. This study demonstrated positive associations between MetS and its five components and BMD T-score among HD patients. MetS, abdominal obesity, hypertriglyceridemia, and low HDL-cholesterol were associated with low risk of osteoporosis among the HD patients. Furthermore, we found that some obesity-related indices were associated with BMD T-score among HD patients with MetS but not in those without MetS. Our study highlights the importance of BMI, WHtR, AVI, and BRI in predicting the risk of osteoporosis among HD patients with MetS. In clinical practice, they can be easily calculated through simple anthropometric measurements and routine laboratory examinations and be used to quickly and conveniently assess the risk of osteoporosis among HD patients.