Using different anthropometric indices to assess prediction ability of type 2 diabetes in elderly population: a 5 year prospective study

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort

BACKGROUND

Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk.

METHODS

We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes.

RESULTS

Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI.

CONCLUSION

Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Novel anthropometric indices for predicting type 2 diabetes mellitus

BACKGROUND

This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community.

METHODS

In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC).

RESULTS

The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes.

CONCLUSION

The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.

Gender-specific link between sleep quality and body composition components: a cross-sectional study on the elderly

Sleep duration has been associated with overweight/obesity. Since sleep quality and body composition alter during aging, we conducted this study to determine if sleep quality is linked to body composition components in elderly people. This is a cross-sectional study conducted on 305 Iranian community-dwelling elderly aged ≥ 65 years. Sleep quality and body composition components were evaluated using Pittsburgh sleep quality index and bioelectric impedance analysis, respectively. The association of sleep quality and body composition components was examined using linear regression analysis. The prevalence of poor sleep quality and overweight/obesity was 48.9% and 54.4% in men and 77.0% and 79.3% in women, respectively. Women had significantly higher scores in most PSQI items than men, indicating their worse sleep quality compared to men. Women also had significantly higher body mass index (BMI), body fat percentage, and visceral adipose tissue and lower skeletal muscle and fat-free mass percentages than men. In the adjusted regression model, men showed positive associations between the third tertile of poor sleep quality and BMI (B = 1.35; 95% CI 0.08-2.61) and waist circumference (B = 4.14; 95% CI 0.39-7.89), but they did not demonstrate an association between sleep quality and body composition components. In the adjusted regression model for women, there were positive associations for BMI (B = 1.21; 95% CI 0.34-2.07), waist circumference (B = 2.95; 95% CI 0.99-4.91), body fat percentage (B = 2.75; 95% CI 1.06-4.45), and visceral adipose tissue (B = 7.80; 95% CI 1.73-13.87); also there were negative associations for skeletal muscle (B =  - 1.40; 95% CI - 2.39 - - 0.41) and fat-free mass (B =  - 2.76; 95% CI - 4.46 - -1.07) percentages. Except for waist circumference, other variables differed between men and women (P < 0.001). Weight management, prevention of muscle wasting, and improvement of sleep quality should be considered in a consortium when designing healthcare strategies for the elderly.

The role of adiponectin in the association between abdominal obesity and type 2 diabetes: a mediation analysis among 232,438 Chinese participants

Background

Adiposity and adipokines are closely associated with obesity-related metabolic abnormalities, but little is known regarding whether abdominal obesity is linked to type 2 diabetes mellitus (T2DM) through circulating adiponectin levels. Thus, this large-population-based study was designed to investigate the mediating effect of adiponectin in the relationship between abdominal obesity and T2DM.

Methods

A total of 232,438 adults who lived in Dongguan, Guangdong Province, China, were enrolled in the present study. The circulating adiponectin concentrations were measured using latex-enhanced immunoturbidimetric assay. The association between circulating adiponectin and other clinical parameters was detected by Spearman's correlation analysis. Restricted cubic spline (RCS) regression was also used to address the non-linearity of the relationship between waist circumference and diabetes. Mediation analyses of circulating adiponectin were conducted using linear and logistic regression.

Results

Subjects with abdominal obesity had lower levels of circulating adiponectin (P < 0.001). The circulating adiponectin value was inversely related to BMI (r = -0.370, P < 0.001), waist circumference (r = -0.361, P < 0.001), and fasting plasma glucose (r = -0.221, P < 0.001). The RCS plot showed a non-linear relation linking waist circumference with T2DM (P for non-linearity < 0.001). Patients with abdominal obesity presented 2.062 times higher odds of T2DM in comparison with those with non-abdominal obesity (odds ratio, 2.062; 95% confidence interval, 1.969-2.161) after adjusting for confounders. In the mediation analyses, the circulating adiponectin mediated the association between abdominal obesity and T2DM, with a mediation effect of 41.02% after adjustments. The above results were consistent in both men and women.

Conclusion

The relationship between abdominal obesity and T2DM is mediated through circulating adiponectin level in adults, suggesting that circulating adiponectin might be a potential predictor for controlling the adverse progression from adiposity to T2DM.

Association of changes in waist circumference, waist-to-height ratio and weight-adjusted-waist index with multimorbidity among older Chinese adults: results from the Chinese longitudinal healthy longevity survey (CLHLS)

BACKGROUND

The association of changes in waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted-waist index (WWI) with subsequent risk of multimorbidity remains unclear among older Chinese adults. Therefore, we aimed to assess this association by utilizing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

METHODS

Our study was based on the 2011/2012 wave of the CLHLS whose follow-up surveys were conducted in 2014 and 2017/2018. A total of 2900 participants aged 65 and above at baseline were enrolled. WC, WHtR, and WWI were calculated from measured height, weight, and waist circumference. Multimorbidity refers to the coexistence of two or more of 18 chronic diseases. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95%CIs) to evaluate the effect of three-year changes in WC, WHtR, and WWI on the risk of multimorbidity.

RESULTS

During a mean follow-up time of 4.2 (2.0) years, 906 multimorbidity cases were identified. Compared to participants in the persistently low WC group, those in the WC gain group and the persistently high WC group had a higher multimorbidity risk with adjusted HRs (95%CI) of 1.23 (1.01-1.50) and 1.34(1.14-1.58), respectively. Participants in the WHtR gain group and the persistently high WHtR group also had higher risks of multimorbidity with HRs (95%CI) of 1.35 (1.08-1.67) and 1.27 (1.05-1.53), respectively, relative to the persistently low WHtR group. Compared to the persistently low WWI group, those in the WWI loss group had a lower risk of multimorbidity with HRs (95%CI) of 0.80 (0.66-0.98). For every standard deviation increase in WC, WHtR, and WWI over three years, the risk of multimorbidity was higher by 12% (95%CI: 1.05-1.19), 13% (95%CI: 1.06-1.20), and 12% (95%CI: 1.05-1.20), respectively.

CONCLUSIONS

Associations of changes in WC, WHtR and WWI with multimorbidity are significant among older Chinese adults. The findings highlight the importance of evaluating changes in WC, WHtR, and WWI in screening and prevention of multimorbidity in older adults.

Severity of adipose tissue dysfunction is associated with progression of pre-diabetes to type 2 diabetes: the Tehran Lipid and Glucose Study

BACKGROUND

The association of prediabetes (Pre-DM) regression and progression with visceral adiposity index (VAI) and adipose tissue dysfunction (ATD) remains to be investigated.

METHODS

The present cohort study was conducted within the framework of the Tehran Lipid and Glucose Study (TLGS) on 1458 Pre-DM cases (aged ≥ 21 years) who were followed for nine years. VAI was estimated based on waist circumference, body mass index, triglycerides, and high-density lipoprotein cholesterol. ATD status (i.e., absent, mild-moderate, and severe) was defined based on the age-stratified cutoff values of VAI. Multinomial logistic regression models with adjustment of potential confounders were used to estimate the chance of Pre-DM regression to normoglycemia or progression to T2D across ATD status.

RESULTS

During the study follow-up, 39.0% of the participants developed T2D, and 37.7% returned to normoglycemia. Compared to mild-moderate ATD, Pre-DM subjects with severe ATD had a higher risk of developing T2D by 45% (OR = 1.45, 95% CI = 11.08-1.93). Severe ATD was also associated with a decreased chance of returning to normoglycemia by 26% (OR = 0.74, 95% CI = 0.55-0.99). Participants with severe ATD had significantly higher fasting (overall mean = 111, 95% CI = 109-112 vs. 106, 95% CI = 105-108 mg/dL) and 2h-serum glucose (overall mean = 165, 95% CI = 161-168 vs. 153, 95% CI = 149-156 mg/dL) concentrations over time.

CONCLUSION

Severe ATD was associated with an elevated risk of developing T2D and longitudinal poor-glycemic controls in Pre-DM subjects. ATD may be a simple and useful index for detecting subjects at a higher risk of Pre-DM progression to T2D, allowing for timely intervention strategies.

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.

Abnormal adiposity indices are associated with an increased risk of diabetes in a non-obese Asian population

OBJECTIVES

The aim of this study was to evaluate the association between adiposity indices and the risk of incident diabetes and to compare their predictive ability in non-obese healthy individuals.

STUDY DESIGN

Population-based cohort study.

METHODS

Data were taken from the NAGALA research study, which enrolled Japanese adults aged 18-79 years. Cox regression was used to evaluate the association between adiposity indices (including waist circumference [WC], waist-to-height ratio [WHtR], lipid accumulation product index [LAP], body roundness index [BRI], visceral adiposity index [VAI] and Chinese visceral adiposity index [CVAI]) and diabetes risk. The performance of the indices for predicting diabetes was explored using area under the receiver operating characteristic curve (AUC). A Chinese community-based population was used for validation.

RESULTS

A total of 12,940 healthy Japanese individuals with normal body mass index and glycaemic levels were included and were followed up for a median of 6 years. Multivariable Cox models revealed a positive and significant association between all indices and incident diabetes, with the hazard ratios for the highest quartile of the indices ranging from 1.89 to 2.90 (all P-values < 0.01). A non-linear association between WC, BRI and VAI and a linear association between WHtR, LAP and CVAI and diabetes risk were observed. CVAI, VAI and LAP had comparable ability in predicting diabetes, with the highest AUC being 0.733 for CVAI. Data from 10,830 Chinese individuals confirmed these results.

CONCLUSIONS

Adiposity indices are associated with incident diabetes in healthy non-obese individuals. Participants in the highest quartile of WC, WHtR, LAP, BRI, VAI and CVAI had an increased risk of developing diabetes.

Excessive weight gain onset-age and risk of developing diabetes mellitus: a large, prospective Chinese cohort study

Background

Excessive weight gain and obesity are widely accepted as risk factors for diabetes mellitus, and the age at which obesity onsets may be related to the development of cardiovascular diseases and certain cancers. Here, we aimed to investigate associations between the onset-age of overweight/obesity and risk of developing diabetes mellitus in China.

Methods

42,144 people with the normal weight range and without diabetes at baseline, were enrolled from the Kailuan cohort which began on the 1st June 2006. All participants were followed-up, biennially, until 31st December 2017. During follow-up, 11,220 participants had become overweight/obese. For each case, one normal-weight control was matched according to age ( ± 1 year) and sex. Our final analysis included 10,858 case-control pairs. An age-scaled Cox model was implemented to estimate hazard ratios (HR) with corresponding 95% confidence intervals (CI) for diabetes mellitus incidence across age-groups.

Results

At a median follow-up of 5.46 years, 1,403 cases of diabetes mellitus were identified. After multivariate adjustments, age-scaled Cox modelling suggested that risk gradually attenuated with every 10 year increase in age of onset of overweight/obesity. Diabetes mellitus adjusted HRs (aHRs) for new-onset overweight/obesity at <45years, 45-54 years, and 55-64 years were 1.47 (95%CI, 1.12-1.93), 1.38 (95%CI, 1.13-1.68), 1.32 (95%CI, 1.09-1.59), respectively. However, new-onset of overweight/obesity at ≥65 years did not relate to diabetes mellitus (aHR, 1.20; 95%CI, 0.92-1.57). This trend was not observed in women or the new-onset obesity subgroup but was evident in men and the new overweight onset subgroup.

Conclusion

Participants with early onset of excessive weight gain issues are at considerably higher risk of developing diabetes mellitus compared to those who maintain a normal weight.

Diagnostic Performance of the Measurement of Skinfold Thickness for Abdominal and Overall Obesity in the Peruvian Population: A 5-Year Cohort Analysis

The escalating prevalence of overall and abdominal obesity, particularly affecting Latin America, underscores the urgent need for accessible and cost-effective predictive methods to address the growing disease burden. This study assessed skinfold thicknesses' predictive capacity for overall and abdominal obesity in Peruvian adults aged 30 or older over 5 years. Data from the PERU MIGRANT 5-year cohort study were analyzed, defining obesity using BMI and waist circumference. Receiver operating characteristic curves and area under the curve (AUC) with 95% confidence intervals (CI) were calculated. Adults aged ≥ 30 (n = 988) completed the study at baseline, with 47% male. A total of 682 participants were included for overall and abdominal obesity analysis. The 5-year prevalence values for overall and abdominal obesity were 26.7% and 26.6%, respectively. Subscapular skinfold (SS) best predicted overall obesity in men (AUC = 0.81, 95% CI: 0.75-0.88) and women (AUC = 0.77, 95% CI: 0.67-0.88). Regarding abdominal obesity, SS exhibited the highest AUC in men (AUC = 0.83, 95% CI: 0.77-0.89), while SS and the sum of trunk skinfolds showed the highest AUC in women. In secondary analysis excluding participants with type-2 diabetes mellitus (DM2) at baseline, SS significantly predicted DM2 development in men (AUC = 0.70, 95% CI: 0.58-0.83) and bicipital skinfold (BS) did in women (AUC = 0.73, 95% CI: 0.62-0.84). The findings highlight SS significance as an indicator of overall and abdominal obesity in both sexes among Peruvian adults. Additionally, SS, and BS offer robust predictive indicators for DM2.

Comparison of bioelectrical body and visceral fat indices and anthropometric measures in relation to type 2 diabetes by sex among Chinese adults, a cross-sectional study

Objectives

We aim to compare the efficacies of the bioelectrical indices (percentage of body fat, PBF; visceral fat area, VFA) with the conventional anthropometric measures (body mass index, BMI; waist-hip ratio, WHR) for predicting type 2 diabetes (T2D) risk by sex and to determine the sex-specific optimal adiposity indices to predict the T2D risk.

Design

Cross-sectional design.

Setting

Tianjin First Central Hospital and Tianjin Union Medical Center, Tianjin, China.

Participants

A total of 9,332 adults (41.35% men) undergoing physical examination.

Primary and secondary outcome measures

T2D was defined using the WHO's criteria: fasting blood glucose (FBG) ≥7.0 mmol/L and/or previous diagnosis of T2D. Height, weight, waist, hip, PBF, VFA, and fasting plasma glucose were measured.

Results

All studied adiposity indices were associated with T2D among both males and females, and the observed associations differed by sex. The standardized aORs of BMI, WHR, PBF and VFA for T2D were 1.60 (95% CI 1.42-1.81), 1.43 (95% CI 1.25-1.64), 1.42 (95% CI 1.23-1.62) and 1.53 (95% CI 1.35-1.75) for females, and 1.47 (95% CI 1.31-1.66), 1.40 (95% CI 1.25-1.58), 1.54 (95% CI 1.36-1.74) and 1.47 (95% CI 1.31-1.65) for males, respectively. The AUCs of VFA, WHR and BMI were 0.743, 0.742 and 0.717 in women, respectively, whereas none of the indices had AUC larger than 0.70 in men. The AUCs were not significantly different between VFA and WHR, while both demonstrate larger AUCs than BMI and PBF in females (all p < 0.05). The optimal cutoff values of VFA, WHR, and BMI for T2D in women were 103.55 cm2, 0.905, and 24.15 kg/m2, respectively.

Conclusion

Although BMI, WHR, and PBF and VFA as measured by bioelectrical impedance analysis (BIA) were all positively associated with T2D, their efficacy for predicting the risk of T2D differed by sex. VFA, WHR and BMI could be used as biomarkers to predict T2D risk in women, however none of the study indicators demonstrated favorable efficacy of predicting T2D risk in men.

Normal-weight central obesity: implications for diabetes mellitus

Background

Current guidelines for obesity prevention and control focus on body mass index (BMI) and rarely address central obesity. Few studies have been conducted on the association between normal-weight central obesity and the risk of diabetes mellitus (DM).

Methods

26,825 participants from the National Health and Nutrition Examination Survey (NHANES) were included in our study. A weighted multivariate logistic regression model was used to analyze the relationship between different obesity patterns and the risk of DM.

Results

Our results suggest that normal-weight central obesity is associated with an increased risk of DM (OR: 2.37, 95% CI: 1.75-3.23) compared with normal-weight participants without central obesity. When stratified by sex, men with normal-weight central obesity, obesity and central obesity were found to have a similar risk of DM (OR: 3.83, 95% CI: 2.10-5.97; OR: 4.20, 95% CI: 3.48-5.08, respectively) and a higher risk than all other types of obesity, including men who were overweight with no central obesity (OR: 1.21, 95% CI: 0.96-1.51) and obese with no central obesity (OR: 0.53, 95% CI: 0.30-0.91).

Conclusion

Our results highlight the need for more attention in people with central obesity, even if they have a normal BMI.

Is Metabolic Score for Visceral Fat (METS-VF) a Better Index Than Other Adiposity Indices for the Prediction of Visceral Adiposity

Background

Visceral adiposity is an important risk factor for cardiometabolic diseases.

Objective

To determine whether the Metabolic Score for Visceral Fat (METS-VF) is more effective than other adiposity indices in predicting visceral fat area (VFA).

Methods

In this single-center and cross-sectional study, we included patients aged 20-50 years, without diabetes and coronary artery disease, who underwent computed tomography (CT) including the third lumbar vertebra. Age, blood pressure, waist circumference (WC), hip circumference, fasting lipids, and glucose were assessed. VFA was measured by cross-sectional examination of CT. The correlation of WC, body mass index (BMI), waist-hip ratio (WHR), lipid accumulation product (LAP), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), and METS-VF with VFA was analyzed by correlation analysis. The cut-off values and area under the curve (AUC) for identifying increased VFA (>130 cm2) were determined.

Results

We included 185 individuals with mean age 38.2 ± 8 and female predominance (58.4%). There was a significant positive correlation between all indices and VFA (p<0.001). ROC analysis revealed that METS-VF and WC demonstrated the highest predictive value for identifying increased VFA. In both men (p=0.001) and women (p<0.001), METS-VF (AUC 0.922 and 0.939, respectively) showed a significant superiority over ABSI (AUC 0.702 and 0.658, respectively), and VAI (AUC 0.731 and 0.725, respectively). Additionally, in women, its superiority over WHR (AUC 0.807) was also statistically significant (p=0.003). We identified a METS-VF cut-off point >6.4 in males >6.5 in females and WC cut-off point >88 cm in males (AUC 0.922), >90.5 cm in females (AUC 0.938).

Conclusion

METS-VF is strongly associated with visceral adiposity and better to predict increased VFA. However, its superiority over WC, BMI, BRI, and LAP was not significant. The results emphasize that WC is more appealing as screening indicator for visceral adiposity considering its easy use.

Clinical Trial Registry Name

Clinicaltrials.gov (http://www.clinicaltrials.gov).

Clinical Trial Registry Url

https://clinicaltrials.gov/ct2/show/NCT05648409.

Clinical Trial Registry Number

NCT05648409.

The role of residential greenness levels, green land cover types and diversity in overweight/obesity among older adults: A cohort study

BACKGROUND

Few studies have investigated the effects of greenness exposure, green land cover types and diversity and their interaction with particulate matter (PM) to adiposity.

METHOD

Cohort data were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Baseline data on greenness levels, green land cover types and diversity were assessed by the Normalized Difference Vegetation Index (NDVI), three greenery types (trees, shrublands and grassland) and Shannon's diversity index, respectively. Body mass index (BMI) and waist circumference (WC) were separately used as dependent variables and represented for peripheral overweight/obesity and central obesity, respectively. The mixed Cox model with random intercept was used to estimate the effects of greenness levels, types and diversity on overweight/obesity using single and multiple exposure models. We also examined the interaction of PM and the aforementioned indicators on overweight/obesity on both additive and multiplicative scales.

RESULTS

Single exposure models showed that higher levels of residential greenness, tree coverage and ratio of trees to shrublands/grassland were inversely associated with peripheral overweight/obesity and central obesity. An increase in shrublands, grassland and diversity of green was related to lower odds of peripheral overweight/obesity. Multiple exposure models confirmed the association between greenness levels and peripheral overweight/obesity. Males, educated participants and elderly who lived in southern regions and areas with cleaner air environments acquired more benefits from greenspace exposure. Single and multiple exposure models indicated that an antagonistic effect of increasing PM and decreasing greenness levels on peripheral overweight/obesity and central obesity. Single exposure models showed the potential interaction of tree coverage, ratio of trees to grassland and PM_2.5 exposures on the risk of peripheral overweight/obesity.

CONCLUSION

Increasing residential greenness and diversity of green were associated with healthy weight status. The relationship between greenery and overweight/obesity varied, and the effects of greenspace exposure on overweight/obesity were associated with air pollution.

Independent and Joint Associations of BMI and Waist Circumference With the Onset of Type 2 Diabetes Mellitus in Chinese Adults: Prospective Data Linkage Study

BACKGROUND

General obesity and abdominal obesity, typically measured by BMI and waist circumference (WC), respectively, are associated with an increased risk of type 2 diabetes mellitus (T2DM). However, the magnitude of the association of these two obesity indicators and their joint association with the onset of T2DM remain controversial.

OBJECTIVE

The aim of this study was to investigate the associations between these two obesity indicators and T2DM among the Chinese population to contribute scientific evidence for appropriate T2DM interventions.

METHODS

A cohort of 3001 eligible participants was selected from the Ningbo Adult Chronic Disease Surveillance Project running since 2015. Based on BMI, individuals were categorized into groups of underweight or normal, overweight, and obesity. Based on WC, individuals were categorized in groups of normal, precentral obesity, and central obesity. Follow-up was performed by linking data of the baseline data set with the diabetes registry data set and the vital registry data set (both from the Ningbo Municipal Integrated Noncommunicable Disease Collaborative Management System), mainly using the participants' identity numbers. Follow-up was completed when a participant was diagnosed with T2DM. The associations were estimated with multivariate Cox proportional hazard regression.

RESULTS

In the cohort, 90 of 3001 participants developed T2DM (incidence density: 6.483/1000 person-years) with a median 4.72 years of follow-up. After controlling for age, sex, hypertension, dyslipidemia, smoking status, and family history of diabetes, the multivariate adjusted hazard ratios (HRs) across underweight/normal, overweight, and obesity BMI categories were 1.000, 1.653 (95% CI 1.030-2.654), and 2.375 (95% CI 1.261-4.473), respectively. The multivariate adjusted HRs across the normal, precentral obesity, and central obesity WC categories were 1.000, 1.215 (95% CI 0.689-2.142), and 1.663 (95% CI 1.016-2.723), respectively. Compared with the reference group (normal WC with an underweight/normal BMI), the multivariate adjusted HR for participants with both central obesity according to WC and obesity according to BMI was 2.489 (95% CI 1.284-4.825).

CONCLUSIONS

Both elevated BMI and WC at baseline increased the risk of T2DM. Compared with WC, BMI as an obesity indicator was more strongly associated with the onset of T2DM.

Individual and combined associations of body mass index and waist circumference with components of metabolic syndrome among multiethnic middle-aged and older adults: A cross-sectional study

OBJECTIVES

Body mass index (BMI) and waist circumference (WC) are closely associated with metabolic syndrome and its components. Hence, a combination of these two obesity markers may be more predictive. In this study, we aimed to investigate the individual and combined associations of BMI and WC with selected components of metabolic syndrome and explored whether age, sex and ethnicity affected the aforementioned associations.

METHODS

A total of 6,298 middle-aged and older adults were included. Based on BMI and WC, the participants were divided into 4 groups: comorbid obesity (BMI ≥ 28 kg/m² and WC< 85/90 cm for women/men), abdominal obesity alone (BMI< 28 kg/m² and WC≥ 85/90 cm for women/men), general obesity alone (BMI ≥ 28 kg/m² and WC< 85/90 cm for women/men) and nonobesity subgroups (BMI< 28 kg/m² and WC< 85/90 cm for women/men). Selected components of metabolic syndrome were evaluated using the criteria recommended by the Chinese Diabetes Society. Poisson regression models with robust variance were used to evaluate the associations of obesity groups with selected components of metabolic syndrome. An interaction test was conducted to explore whether age, sex and ethnicity affect the aforementioned associations.

RESULTS

Compared with participants in the reference group (comorbid obesity), participants in the other 3 groups showed a decreased prevalence of fasting hyperglycemia (PR=0.83, 95% CI=0.73-0.94 for abdominal obesity alone, PR=0.60, 95% CI=0.38-0.96 for general obesity alone and PR=0.46, 95% CI=0.40-0.53 for nonobesity), hypertension (PR=0.86, 95% CI=0.82-0.90 for abdominal obesity alone, PR=0.80, 95% CI=0.65-0.97 for general obesity alone and PR=0.69, 95% CI = 0.66-0.73 for nonobesity) and hypertriglyceridemia (PR=0.88, 95% CI=0.82-0.95 for abdominal obesity alone, PR=0.62, 95% CI=0.47-0.81 for general obesity alone and PR=0.53, 95% CI=0.49-0.57 for nonobesity). However, participants in the abdominal obesity alone and nonobesity groups showed a decreased prevalence of low HDL-C levels while participants in the general obesity alone group did not (PR=0.65, 95% CI=0.41-1.03, p>0.05). In addition, the aforementioned associations were not affected by age, sex or ethnicity (all p for interactions>0.05).

CONCLUSIONS

Comorbid obesity is superior to general and abdominal obesity in identifying individuals at high risk of developing metabolic syndrome in middle-aged and older adults. Great importance should be attached to the combined effect of BMI and WC on the prevention and management of metabolic syndrome.

Evaluation of novel obesity- and lipid-related indices as predictors of abnormal glucose tolerance in Chinese women with polycystic ovary syndrome

PURPOSE

We aimed to evaluate the performance of Chinese visceral adiposity index (CVAI), visceral adiposity index (VAI), lipid accumulation product (LAP), triglyceride glucose (TyG) as indices in screening abnormal glucose tolerance (AGT) in Chinese women with polycystic ovary syndrome (PCOS), using the oral glucose tolerance test (OGTT) as a reference test. In addition, we essentially compared the abilities of these indices with body mass index (BMI), waist circumference (WC), fasting plasma glucose (FPG).

MATERIALS AND METHODS

All 1113 PCOS patients evaluated in this study underwent OGTTs. The 2-h post-oral glucose load (2 h-PG) level was used to categorize subjects into two groups: those having AGT or normal glucose tolerance (NGT) levels.

RESULTS

A statistically significant positive correlation between levels of 2 h-PG and FPG, BMI, WC, LAP, VAI, CVAI, TyG, (P < 0.05), was observed. The strongest correlation was found between the levels of 2 h-PG and CVAI (r = 0.47). The CVAI provided the highest area under the receiver-operating characteristic curve (AUC) for AGT, followed by LAP, BMI, TyG, VAI, WC, and FPG. The CVAI of 32.61 (with AUC: 0.76, sensitivity: 73%, specificity: 70%, positive preductive value (PPV): 0.41, negative predictive value (NPV): 0.90) was found to be the cut-off point for AGT in Chinese women with PCOS.

CONCLUSIONS

CVAI may not reliably detect AGT in Chinese women with PCOS. However, it is suitable as a first screening indicator to guide physicians to ordering OGTT.

Cost-effectiveness of community diabetes screening: Application of Akaike information criterion in rural communities of Nigeria

Background

The prevalence of diabetes mellitus (DM) is increasing globally, and this requires several approaches to screening. There are reports of alternative indices for prediction of DM, besides fasting blood glucose (FBG) level. This study, investigated the ability of combination of biochemical and anthropometric parameters and orodental disease indicators (ODIs) to generate models for DM prediction, using Akaike information criterion (AIC) to substantiate health economics of diabetes screening.

Methods

Four hundred and thirty-three subjects were enrolled in the study in Ndokwa communities, Delta State, Nigeria, and their glycaemic status was determined, using the CardioChek analyser^® and previous data from the Prediabetes and Cardiovascular Complications Study were also used. The cost of screening for diabetes (NGN 300 = $0.72) in a not-for-profit organization/hospital was used as basis to calculate the health economics of number of individuals with DM in 1,000 participants. Data on the subjects' anthropometric, biochemical and ODI parameters were used to generate different models, using R statistical software (version 4.0.0). The different models were evaluated for their AIC values. Lowest AIC was considered as best model. Microsoft Excel software (version 2020) was used in preliminary analysis.

Result

The cost of identifying <2 new subjects with hyperglycemia, in 1,000 people was ≥NGN 300,000 ($ 716). A total of 4,125 models were generated. AIC modeling indicates FBG test as the best model (AIC = 4), and the least being combination of random blood sugar + waist circumference + hip circumference (AIC ≈ 34). Models containing ODI parameters had AIC values >34, hence considered as not recommendable.

Conclusion

The cost of general screening for diabetes in rural communities may appear high and burdensome in terms of health economics. However, the use of prediction models involving AIC is of value in terms of cost-benefit and cost-effectiveness to the healthcare consumers, which favors health economics.

High prevalence of diabetes in elderly of Iran: an urgent public health issue

Purpose

To determine the distribution of blood glucose and prevalence of diabetes in people above 60 years living in Tehran and their relationship with some variables.

Methods

In this cross-sectional population-based study, multistage cluster sampling was performed in the over 60-year-old population of Tehran. Blood samples were collected from all participants and the data of the history of diabetes and the use of blood glucose lowering agents or other drugs were collected using interviews.

Results

Of 3791 selected subjects, 3310 participated in the study (response rate = 87.3%). The mean blood Sugar (BS) and hemoglobin A1c (HbA1c) of the patients was 118.11(95% CI: 115.34 -120.88) and 6.12(95% CI: 6.05-6.2) respectively. The prevalence of diabetes was 29.03%(95% CI: 27.12-30.94) in all subjects, 26.83%(95% CI: 24.58-29.07) in men, and 31.2%(95% CI: 28.24-34.16) in women. Odds of diabetes was significantly worse in women. systolic blood pressure, diasstolic blood pressure, height, weight, waist circumference, wrist circumference, hip circumference, neck circumference and body mass Index were significantly higher in diabetic after adjusting for the effect of sex and age. The odds of blindness was 2.69 (95% CI: 1.10-6.59) times higher in diabetic than in non-diabetics.

Conclusions

On average, one in every three persons above 60 years of age was diabetic. Therefore, attention should be paid to this age group, especially women, due the higher prevalence of diabetes. All anthropometric measurements except height had a strong correlation with diabetes. Blindness was significantly more in diabetics.

Comparison of obesity indices and triglyceride glucose-related parameters to predict type 2 diabetes mellitus among normal-weight elderly in China

PURPOSE

Although a significant proportion of type 2 diabetes mellitus (T2DM) cases arose from normal-weight individuals, studies on indicators of T2DM in normal-weight people are limited. Accordingly, this study aims to investigate the predictive value of obesity indices and triglyceride glucose-related parameters (TyG-related parameters) in T2DM among normal-weight Chinese elderly.

METHODS

A total of 24,215 normal-weight Chinese elderly (age ≥ 60 years) [body mass index-BMI (18.5-23.9 kg/m²)] were included. Obesity indices and triglyceride glucose-related parameters (TyG-related parameters) included waist circumference (WC), waist-to-height ratio (WHtR), visceral adiposity index (VAI), lipid accumulation product (LAP), and TyG-related parameters (TyG, TyG-BMI, TyG-WC, and TyG-WHtR). Multivariate logistic regression analysis was performed to examine the associations between obesity- and TyG-related indices and T2DM. The areas under the curve (AUC) of the receiver-operating characteristic (ROC) curve analyses were used to evaluate and compare the predictive value of the different indices.

RESULTS

The prevalence of T2DM was 14.2% in normal-weight individuals. Among the indices, TyG was significantly associated with T2DM among men and women, respectively, (adjusted odds ratio-aOR per SD 3.46; 95% CI 3.23-3.71) and (aOR per SD 3.64; 95% CI 3.43-3.86). Compared with other indices, TyG had the highest AUC value for T2DM in men (AUC: 0.818, 95% CI 0.810-0.825) and women (AUC: 0.824, 95% CI 0.814-0.833).

CONCLUSIONS

TyG is an effective marker and outperforms other indices when predicting T2DM in the normal-weight Chinese elderly population.

LEVEL OF EVIDENCE

Level V: Opinions of authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.

Evaluation of anthropometric indices as a predictor of diabetes in Dong and Miao ethnicities in China: A cross-sectional analysis of China Multi-Ethnic Cohort Study

Background

Although it is known that obesity is inseparable from diabetes, many anthropometric indices are used for determining obesity. At the same time, research on the predictive indices of diabetes in Chinese minority populations is lacking. Therefore, this study determines the relationship between different anthropometric indices and diabetes, and identifies the best index and best cut-off values for predicting diabetes.

Method

In total, 11,035 Dong and Miao ethnic participants (age: 30–79 years) from the China Multi-Ethnic Cohort study were included. The logistic regression model was used to examine the relationship between the different anthropometric indices and diabetes risk. The receiver operating characteristic curve and the area under the curve (AUC) were used to identify the best predictor of diabetes.

Results

In multivariate adjusted logistic regression models, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and visceral adiposity index (VAI) were positively correlated with diabetes risk. Among Chinese Dong men and women and Miao men, WHR had the largest AUC (0.654/0.719/0.651). Among Miao women, VAI had the largest AUC(0.701). The best cut-off values of WHR for Dong men and women and Miao men were 0.94, 0.92, and 0.91, respectively. The best cut-off value of VAI for Miao women was 2.20.

Conclusion

Obesity indicators better predict diabetes in women than men. WHR may be the best predictor of diabetes risk in both sex of Dong ethnicity and Miao men, and VAI may be the best predictor of diabetes risk in Miao women.

Comparison of the Ability of Anthropometric Indices to Predict the Risk of Diabetes Mellitus in South African Males: SANHANES-1

This study aimed to assess the sensitivity of body mass index (BMI) to predict the risk of diabetes mellitus (DM) and whether waist circumference (WC), waist-to-hip (WHR) and waist-to-height (WHtR) ratios are better predictors of the risk of DM than BMI in South African men aged 20 years and older. Data from the first South African National Health and Nutrition Examination Survey (SANHANES-1) were used. Overall, 1405 men who had valid HbA1c outcomes were included. The sensitivity, specificity, and optimal cut-off points for predicting DM were determined using the receiver operating characteristic (ROC) curve analysis. A total of 34.6% percent of the study participants were overweight/obese, while 10.5%, 10.4%, 36.6% and 61.0% had HbA1c, WC, WHR and WHtR above the normal reference ranges, respectively. Based on age-adjusted logistic regression analysis, the highest likelihood of DM was observed for those participants who had increased WC and WHtR (odds ratios [OR] were 6.285 (95% CI: 4.136−9.550; p < 0.001) and 8.108 (95% CI: 3.721−17.667; p < 0.001)). The ROC curve analyses for WC, WHR, and WHtR displayed excellent ability to predict the risk of DM, with their areas under the curve (AUC) being 80.4%, 80.2% and 80.8%, respectively. The overall cut-off points to predict the risk of DM for WC, WHR, and WHtR were ≥88.95 cm, ≥0.92, and >0.54, respectively. The ROC analysis for BMI, on the other hand, showed acceptable ability to predict the risk of DM (AUC = 75.6%), with its cut-off point being ≥24.64 kg/m2. Even after stratifying the data by two age groups, WHtR remained a superior index to predict DM, especially in the younger age group. To conclude, no significant differences were observed between the AUC for BMI the AUCs for other indices. However, the AUCs for these indices showed significant excellent ability as opposed to the significant acceptable ability of BMI to predict DM in adult South African men.

Non-linear relationship between the body roundness index and incident type 2 diabetes in Japan: a secondary retrospective analysis

Background

Body roundness index (BRI) is one of the obesity-related anthropometric indices. However, studies on the relationship between BRI and diabetes risk is limited. The purpose of this study was to explore the relationship between baseline BRI and incident type 2 diabetes mellitus (T2DM) in the Japanese population.

Methods

A retrospective longitudinal study of 15,310 participants in a physical examination program at Murakami Memorial Hospital in Japan from 2004 to 2015. The association between BRI levels and incident T2DM was analyzed by Cox proportional-hazards regression, smooth curve fitting, subgroup analyses, and a set of sensitivity analyses. Receiver operating characteristic curve analysis was used to assess the ability of BRI to predict diabetes.

Result

Baseline BRI levels were elevated in participants who developed T2DM. Baseline BRI levels were positively associated with incident T2DM after adjusting confounding variables (HR = 1.570, 95% CI 1.360–1.811). Additionally, we did a set of sensitivity analyses to ensure the robustness of the results. There was also a non-linear relationship between BRI and incident diabetes in both genders, and the inflection point of BRI was 4.137 in females and 3.146 in males. We found a strong positive correlation between BRI and the incidence of diabetes on the right of the inflection point (Male: HR = 1.827, 95% CI 1.449–2.303; Female: HR = 4.189, 95% CI 1.862–9.421). What’s more, among the anthropometric indices, BRI showed the optimal capability to predict T2DM (Male: AUC = 0.706, 95% CI 0.674–0.738; Female: AUC = 0.735, 95% CI 0.676–0.795).

Conclusion

An elevated BRI level in baseline was independently associated with incident T2DM. Baseline BRI improves the identification of patients at risk of T2DM and may enable early and optimized therapy to improve their outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03321-x.

Association of visceral adiposity index with new-onset type 2 diabetes and impaired fasting glucose in hypertensive Chinese adults

PURPOSE

Visceral adiposity index (VAI) is a reliable indicator for the distribution and function of adipose tissue in the body. The relation of VAI with new-onset type 2 diabetes and new-onset impaired fasting glucose (IFG) remains uncertain. We aimed to investigate the prospective relation of VAI with new-onset type 2 diabetes and new-onset IFG in Chinese hypertensive adults.

METHODS

A total of 14,838 hypertensive adults free of type 2 diabetes at baseline were included from the China Stroke Primary Prevention Trial. The primary outcome was new-onset type 2 diabetes, defined as physician-diagnosed diabetes or use of glucose-lowering drugs during follow-up, or fasting glucose ≥ 7.0 mmol/L at the exit visit. The secondary outcome was new-onset IFG, defined as fasting glucose < 6.1 mmol/L at baseline, while fasting glucose ≥ 6.1 mmol/L and < 7.0 mmol/L at the exit visit.

RESULTS

Over a median of 4.5 years' follow-up, 1612 (10.9%) participants developed type 2 diabetes. When VAI was categorized into quartiles, compared with participants in quartile 1-3 (< 2.80), significantly higher risk of new-onset type 2 diabetes (OR 1.30; 95% CI 1.08-1.56) and new-onset IFG (OR 1.28; 95% CI 1.08-1.52) was found in those in quartile 4 (≥ 2.80). Moreover, the positive associations were consistent in participants with or without single abnormal VAI components, including general obesity, abdominal obesity, elevated triglycerides and low high-density lipoprotein cholesterol (HDL-C) levels; or with different numbers of abnormal VAI components (all P interactions > 0.05).

CONCLUSION

Our study suggested a positive relation of VAI with the risk of new-onset type 2 diabetes and new-onset IFG in Chinese hypertensive patients, independent of its components.

LEVEL OF EVIDENCE

Level III, a well-designed cohort.

Comparison of different obesity indices associated with type 2 diabetes mellitus among different sex and age groups in Nantong, China: a cross-section study

Background

Obesity is associated with type 2 diabetes mellitus (T2DM). However, the obesity index that is most closely related to type 2 diabetes remains controversial. Therefore, the aim of this study was to compare the associations of five anthropometric indices (body mass index [BMI], body adiposity index, waist circumference [WC], waist-to-hip ratio, and waist-to-height ratio [WHtR]) with T2DM among Chinese adults divided into four groups according to sex and age.

Methods

A total of 4007 adult participants (1669 men and 2338 women) were included in the study. Odds ratios (ORs) and 95% confidence intervals were used with binary logistic regression models to estimate the risk of T2DM for each obesity index. Furthermore, we compared the area under the receiver operating characteristic curve (AUC) of each obesity index for the criterion of T2DM under the influence of risk factors.

Results

WC had the highest OR (3.211 and 1.452) and AUC (0.783 and 0.614) in both age groups of men. However, WHtR (OR = 2.366, AUC = 0.771) and BMI (OR = 1.596, AUC = 0.647) were the optimal criteria for predicting T2DM among females in the 18–59 and ≥ 60 years age groups, respectively.

Conclusions

This study suggests that there is a positive association between obesity-related anthropometric indices and T2DM in different sex and age groups. WC appears to be the optimal anthropometric index for predicting T2DM in men. The optimal obesity indices related to T2DM were WHtR and BMI for women aged 18–59 and ≥ 60 years, respectively.

Accuracy of obesity indices alone or in combination for prediction of diabetes: A novel risk score by linear combination of general and abdominal measures of obesity

Background

The predictive power of obesity measures varies according to the presence of coexistent measures. The present study aimed to determine the predictive power of combinations of obesity measures for diabetes by calculation of a linear risk score.

Methods

Data from a population-based cross-sectional study of 994 representative samples of Iranian adults in Babol, Iran were analyzed. Measures of obesity including waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), and waist to hip ratio (WHR) were calculated, and diabetes was diagnosed by fasting blood sugar >126 mg/dl or taking antidiabetic medication. Multiple logistic regression model was used to develop a logit risk score based on BMI, WC, WHtR, and WHR. The ROC analysis was applied to determine the priority of every single index and combined logit score for the prediction of diabetes.

Results

All four measures of general and abdominal obesity were predictors of diabetes individually in both sexes (P=0.0001). Calculation of risk score for a combination of all measures use full model improved predictive power. Adjustment for age resulted in further improvement in diagnostic power and combined novel risk score differentiated individuals with and without diabetes with an accuracy of 0.747 (95%CI: 0.690-0.808) in men and 0.789 (95%CI: 0.740, 0.837) in women.

Conclusion

These findings indicate that the simultaneous calculation of age-adjusted risk score for all measures provides stronger diagnostic accuracy in both sexes. This issue suggests the calculation of combined risk scores for all obesity indices especially in a population at borderline risk.

Evaluation of the Association between Obesity Markers and Type 2 Diabetes: A Cohort Study Based on a Physical Examination Population

PURPOSE

To evaluate the predictive effect of different obesity markers on the risk of developing type 2 diabetes in a population of healthy individuals who underwent physical examination and to provide a reference for the early detection of individuals at risk of diabetes.

METHODS

This retrospective cohort study included 15206 healthy subjects who underwent a physical examination (8307 men and 6899 women). Information on the study population was obtained from the Dryad Digital Repository. Cox proportional risk models were used to calculate the hazard ratio (HR) and 95% confidence interval (CI) of different obesity markers, including the lipid accumulation index (LAP), body mass index (BMI), waist-to-height ratio (WHtR), visceral adiposity index (VAI), and body roundness index (BRI) on the development of type 2 diabetes. The effectiveness of each obesity marker in predicting the risk of developing type 2 diabetes was analyzed using the receiver operating characteristic curve (ROC curve) and the area under the curve (AUC).

RESULTS

After a mean follow-up of 5.4 years, there were 372 new cases of type 2 diabetes. After correcting for confounding factors such as age, sex, smoking, alcohol consumption, exercise, and blood pressure, Cox proportional risk model analysis showed that elevations in BMI, LAP, WHtR, VAI, and BRI increased the risk of developing type 2 diabetes. The ROC curve results showed that LAP was the best predictor of the risk of developing diabetes, with an AUC (95% CI) of 0.759 (0.752-0.766), an optimal cutoff value of 16.04, a sensitivity of 0.72, and a specificity of 0.69.

CONCLUSION

An increase in the BMI, LAP, WHtR, VAI, and BRI can increase the risk of developing type 2 diabetes, with LAP being the best predictor of this risk.

Body Roundness Index Is a Superior Obesity Index in Predicting Diabetes Risk Among Hypertensive Patients: A Prospective Cohort Study in China

Objective: Individuals with both hypertension and diabetes have been confirmed to significantly increase the risk of cardiovascular disease morbidity and mortality compared with those with only hypertension or diabetes. This study aimed to evaluate the potential of different anthropometric indices for predicting diabetes risk among hypertensive patients.

Methods: The study group consisted of 6,990 hypertensive adults without diabetes who were recruited in China. Demographic and clinical assessment, physical examinations, laboratory tests, and anthropometric measurements, including body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and novel indices (ABSI, AVI, BAI, BRI, CI, WWI, and WHHR), were performed at baseline and during the (median) 3-year follow-up. Cox regression analyses were conducted to estimate effects from these indices for the onset of diabetes. Receiver operator characteristic (ROC) analyses were conducted to assess the predictive capacities of the anthropometric indices and determine the optimal cut-points.

Results: A total of 816 (11.7%) developed diabetes during our prospective study. Multivariate Cox regression analyses revealed weight, WC, WHR, WHtR, BAI, BRI, and WWI as the independent risk factor for diabetes among hypertensive patients, regardless of whether it was treated as a continuous or categorical variable (P < 0.05). Further Cox analyses combining BMI and different central obesity indices showed that elevated WC, WHR, WHtR, AVI, BRI, CI, regardless of the general obesity status, were found to be each independently associated with increased diabetes risk (P < 0.05). Dynamic increases of BRI < 5.24 to BRI ≥ 5.24 were associated with increased risk (HR = 1.29; 95% CI, 1.02, 1.64), and its reversal was associated with reduced risk (HR = 1.56; 95% CI, 1.23, 1.98) compared with the others (HR = 1.95; 95% CI, 1.63, 2.32). ROC analysis indicated that the areas under the ROC curves (AUC) of the anthropometric indices ranged from 0.531 to 0.63, with BRI (cut-off value = 4.62) and WHtR having the largest area.

Conclusions: Based on this novel study, BRI was the most superior predictor and independent determinant for diabetes onset among the hypertensive population. Hypertensive patients with BRI > 4.62, regardless of general obesity status, were at high risk of diabetes. Thus, the prompt screening and diagnosis of diabetes should be carried out among these patients for timely integrated intervention.

Associations of body mass index, waist circumference and waist-to-height ratio with cognitive impairment among Chinese older adults: Based on the CLHLS

BACKGROUND

Few studies have been conducted on the associations of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) with cognitive impairment among Chinese older adults through a prospective design.

OBJECTIVE

This study was aimed to evaluate the associations of BMI, WC, and WHtR with cognitive impairment.

METHODS

We included participants aged 65 years and older in 2014 at baseline and 2018 follow-up surveys of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). BMI, WC, and WHtR were calculated from measured weight, height, and waist circumference. Mini-Mental State Examination was utilized to assess cognitive impairment. Modified Poisson regression was used for calculating prevalence ratios, risk ratios, and 95% confidence intervals.

RESULTS

A total of 5156 participants were included in 2014 at baseline. The prevalence of cognitive impairment was 42.5%, 26.7%, and 21.2% in underweight, normal-weight, and overweight/obesity participants defined by BMI categories, respectively, and 24.1% and 26.8% in central obesity participants defined by WC and WHtR cutoffs, respectively. Prospectively, participants with underweight were more likely to suffer from cognitive impairment (RR = 1.258, 95% CI: [1.016, 1.559]), but no risk was found among participants with overweight/obesity after adjustment. Regardless of whether covariates were adjusted or not, no effect on cognitive impairment was found in participants with WC and WHtR groups in the follow-up survey.

CONCLUSIONS

Underweight may be a significant risk factor for the cognitive impairment of Chinese older adults. Weight management programs targeting older adults should attach importance to achieving and maintaining optimal body weight and improving cognitive function.

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.

Strong Association of Waist Circumference (WC), Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), and Waist-to-Hip Ratio (WHR) with Diabetes: A Population-Based Cross-Sectional Study in Jilin Province, China

BACKGROUNDS

The prevalence of diabetes has increased with the increase of obesity, and finding indicators to predict diabetes risk has become an urgent need. The purpose of this study is to compare the correlation between four anthropometric indices and the prevalence of diabetes.

METHODS

A total of 4052 participants aged 40 years and above were selected in Dehui City, Jilin Province, using a multistage stratified whole group sampling method. Face-to-face interviews and physical examinations were conducted. Multivariate logistic analysis was used. The values of BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were divided into quartiles (Q1: <25%; Q2: ~25%; Q3: ~50%; and Q4: ~75%). The median of each quartile was used for a linear trend test.

RESULTS

For all four body fat-measuring indices of body mass index (adjusted OR: 3.300, 95% CI: 2.370, 4.595), WC (adjusted OR: 5.131, 95% CI: 3.433, 7.669), WHR (adjusted OR: 3.327, 95% CI: 2.386, 4.638), and WHtR (adjusted OR: 5.959, 95% CI: 3.922, 9.054), patients in the highest quartile were more likely to have diabetes than those in the lowest quartile. The areas under the curve of WHtR, WC, WHR, and BMI for diabetes were 0.683, 0.669, 0.654, and 0.629, respectively. In female participants, the areas under the curve of the waist-height ratio and WC were 0.710 (95% CI: 0.679-0.741) and 0.701 (95% CI: 0.670-0.732), respectively.

CONCLUSIONS

The WC and WHtR were more closely related to diabetes than BMI and WHR among study participants ≥ 40 years of age, especially in females.

Relationship between Body Roundness Index and Risk of Type 2 Diabetes in Japanese Men and Women: A Reanalysis of a Cohort Study

PURPOSE

The purpose of this study was to investigate the association between body roundness index (BRI) and type 2 diabetes (T2DM) in each sex, explore the dose-response relationship between them, and evaluate the predictive value of BRI for T2DM.

MATERIALS AND METHODS

A retrospective cohort study was performed on 15,464 Japanese patients at the Murakami Memorial Hospital. Data on anthropometric indices and biochemical parameters were obtained. Multivariate Cox regression models were used to estimate the hazard ratios (HRs) of incident T2DM associated with BRI. Dose-response relationships were evaluated using a smoothing function analysis and the threshold effect. Receiver operating characteristic curves were used to evaluate and compare the predictive values of BRI, body mass index (BMI), and waist circumference (WC) for T2DM.

RESULTS

During a median 5.4-year follow-up period, 373 subjects were diagnosed with T2DM. After adjusting for age, alcohol intake, smoking status, fatty liver, systolic blood pressure, fasting plasma glucose, glycated hemoglobin, high-density lipoprotein cholesterol, triglycerides, and total cholesterol, the relationship between BRI and T2DM was linear in women (HR (95% CI) for BRI Z score = 1.48 (1.26,1.74)) and curvilinear in men (HR (95% CI) on the left and right of the inflection point = 0.70 (0.44, 1.10) and 1.46 (1.27, 1.67), respectively). Compared with BMI (area under the curve (AUC) = 0.684; p < 0.001) and WC (AUC = 0.700; p=0.007), BRI was the strongest predictor of T2DM in men (AUC = 0.715). Similarly, the AUC of BRI was larger than that of BMI (AUC = 0.757; p=0.966) and WC (AUC = 0.733; p=0.015) in women.

CONCLUSIONS

BRI was positively linearly associated with an elevated risk of incident T2DM in women. In men, the relationship between BRI and T2DM was J-shaped. BRI is an effective indicator of predicting T2DM. Its discriminatory power was higher than that of BMI and WC in both sexes.

Obesity markers for the prediction of incident type 2 diabetes mellitus in resource-poor settings: The CRONICAS Cohort Study

AIMS

To determine the predictive performance of well-known obesity markers: body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR), and total body fat percentage (TBF%), to identify incident cases of type 2 diabetes mellitus T2DM.

METHODS

Secondary data analysis of the CRONICAS Cohort Study, conducted in 3 regions of Peru. Participants without T2DM at baseline were selected for analyses. The obesity markers were evaluated at the beginning of the study, and the development of T2DM was determined at 30 months of follow-up. The predictive performance of the markers was calculated using areas under the curve (AUC), and sensitivity and specificity of the best cutoff points were estimated.

RESULTS

A total of 2510 participants with no diabetes at baseline, median age 54.1 years (inter-quartile range: 44.6 to 63.5), were included in the analysis. The cumulative incidence of T2DM at 30 months of follow-up was 4.7%. All the AUC studied for obesity markers and TBF% were poor.

CONCLUSIONS

We found that obesity markers had a poor predictive performance (AUC) for the incidence of T2DM when used alone. The BMI, WC and WHtR had better performance for the incidence of T2DM relative to the WHR among women, and no differences in performance between obesity markers were found among men.

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta-analysis

Body roundness index (BRI) is a new anthropometric index developed to predict both body fat and the percentage of visceral adipose tissue. Our aim was to investigate whether BRI is superior to traditional anthropometric indices in predicting metabolic syndrome (MetS). This systematic review and meta-analysis was conducted using Pubmed, Scopus and Web of Sciences databases. The estimated pooled areas under curve (AUCs) for BRI predicting MetS was higher than body mass index (BMI), waist-to-hip ratio (WHR), body shape index (ABSI) and body adiposity index (BAI), similar to waist circumference (WC) and lower than waist-to-height ratio (WHtR). However, the difference between BRI and BMI, WC and WHtR predicting MetS was statistically non-significant. Similar results were found with the summary receiver operating characteristic curve (AUC-SROC). In addition, the non-Chinese population had pooled AUCs greater than the Chinese population for all indices. Pooled ORs showed that BRI is associated with an increased MetS risk. In conclusion, BRI had good discriminatory power for MetS in adults of both sexes from diverse populations (AUC > 0.7; AUC-SROC>0.7). However, WC and WHtR offer the best performance when screening for MetS, and non-significant differences were found with BRI. In contrast, BRI was superior to BMI, WHR, ABSI and BAI in predicting MetS.

Association of two novel adiposity indicators with visceral fat area in type 2 diabetic patients: Novel adiposity indexes for type 2 diabetes

The present study evaluated the performance of 2 novel adiposity indicators, body shape index (ABSI), and body roundness index (BRI), to determine the accumulation of visceral fat in type 2 diabetic patients.A cross-sectional study was performed on 233 type 2 diabetic patients from Qinhuangdao, China. Visceral fat area (VFA) was measured using bioelectrical impedance. Accumulation of visceral fat was defined as VFA ≥ 100 cm.In diabetic males, the area under the curve (AUC) values were 0.904 for waist circumference (WC), 0.923 for BRI, and 0.788 for ABSI. In diabetic females, the AUC values were 0.894 for WC, 0.915 for BRI, and 0.668 for ABSI. The AUCs were similar between BRI and WC (P > .05). The AUC for ABSI was lower compared to WC and BRI (P < .05). The optimal cut-off for BRI was 4.25 for diabetic males (sensitivity = 87.8% and specificity = 81.1%) and 4.75 for diabetic females (sensitivity = 80.8% and specificity = 88.1%).BRI was an effective indicator for determining the accumulation of visceral fat in type 2 diabetic patients, however, it was not better compared to WC.

Effectiveness of Anthropometric Measurements for Identifying Diabetes and Prediabetes among Civil Servants in a Regional City of Northern Ethiopia: A Cross-Sectional Study

Methods

The study involved a cross-sectional survey carried out from October 2015 to February 2016 among 1504 subjects aged from 18 to 75 years of age. Receiver operating characteristic (ROC) was used to select the most effective anthropometric cut-off point among waist circumference, waist-to-hip ratio, waist-to-height ratio, and BMI for identifying prediabetic and diabetes. Statistical significance was declared at p value of ≤0.05.

Results

Waist circumference was found better for identifying diabetes (AUC = 0.69) and prediabetes (AUC = 0.63) in women, respectively. Waist-to-hip ratio was better identifying diabetes (AUC = 0.67) while waist circumference-to-height ratio was better identifying prediabetes (AUC = 0.63) in men compared to body mass index. The optimal cut-off point with maximum sensitivity and specificity of waist circumference for identifying diabetes and prediabetes was 83.5 cm and 82.9 cm in women, respectively. The optimal ut-off point with maximum sensitivity and specificity of waist-to-hip ratio for identifying diabetes and prediabetes was 0.97 and 0.82 in men, respectively.

Conclusion

Waist circumference and waist-to-hip ratio exhibited better discriminate performance than BMI for identifying prediabetes and diabetes in women and men, respectively.

A composite of BMI and waist circumference may be a better obesity metric in Indians with high risk for type 2 diabetes: An analysis of NMB-2017, a nationwide cross-sectional study

AIMS

Obesity measurement is a vital component of most type 2 diabetes screening tests; while studies had shown that waist circumference (WC) is a better predictor in South Asians, there is evidence that BMI is also effective. Our objective was to evaluate the efficacy of BMI_WC, a composite measure, against BMI and WC.

METHODS

Using data from a nationwide randomized cluster sample survey (NMB-2017), we analyzed 7496 adults at high risk for type 2 diabetes. WC, BMI, and BMI_WC were evaluated using Odds Ratio (OR), and Classification scores (Sensitivity, Specificity, and Accuracy). These were validated using Indian Diabetes Risk Score (IDRS) by replacing WC with BMI and BMI_WC, and calculating Sensitivity, Specificity, and Accuracy.

RESULTS

BMI_WC had higher OR (2·300) compared to WC (1·87) and BMI (2·26). WC, BMI, and BMI_WC were all highly Sensitive (0·75, 0·81, 0·70 resp.). But BMI_WC had significantly higher Specificity (0.36) when compared to WC and BMI (0.27 each). IDRS_WC, IDRS_BMI, and IDRS_BMIWC were all highly Sensitive (0·87, 0·88, 0·82 resp.). But IDRS_BMIWC had significantly higher Specificity (0·39) compared to IDRS_WC and IDRS_BMI (0·30, 0·31 resp.).

CONCLUSIONS

Both WC and BMI are good predictors of risk for T2DM, but BMI_WC is a better predictor, with higher Specificity; this may indicate that Indians with high values of both central (high WC) and general (BMI > 23) obesity carry higher risk for type 2 diabetes than either one in isolation. Using BMI_WC in IDRS improves its performance on Accuracy and Specificity.

Capacity of different anthropometric measures to predict diabetes in a Chinese population in southwest China: a 15-year prospective study

AIM

To investigate whether conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product compared with waist circumference could predict future diabetes in a 15-year prospective study.

METHODS

The data were collected in 1992 and recollected in 2007 from the same group of 687 individuals. Anthropometric indices and biochemical data were obtained. Cox's proportional hazards regression models were used to estimate the hazard ratios of anthropometric measures. The discriminatory power of anthropometric measures for incident diabetes were assessed by Harrell's C-statistic.

RESULTS

During follow-up, 74 participants were newly diagnosed with diabetes. In multivariable Cox regression analysis after adjusting potential for confounders, log₁₀ -conicity index [HR: 1.67 (95% CI: 1.31-2.11) per sd; P < 0.0001], log₁₀ -abdominal volume index [HR: 1.95 (95% CI: 1.50-2.55) per sd; P < 0.0001], log₁₀ -body adiposity index [HR: 1.82 (95% CI: 1.33-2.50) per sd; P < 0.0001], log₁₀ -body roundness index [HR: 2.16 (95% CI: 1.63-2.88) per sd; P < 0.0001], log₁₀ -cardiometabolic index [HR: 1.70 (95% CI: 1.39-2.09) per sd; P < 0.0001], log₁₀ -lipid accumulation product [HR: 2.06 (95% CI: 1.56-2.73) per sd; P < 0.0001] and log₁₀ -waist circumference [HR: 1.99 (95% CI: 1.51-2.46) per sd; P < 0.0001] were significantly associated with incident diabetes. Additionally, lipid accumulation product had the highest Harrell's C-statistic at 0.715 (95% CI: 0.656-0.775), followed by body roundness index at 0.714 (95% CI: 0.658-0.770) and cardiometabolic index at 0.704 (95% CI: 0.643-0.764) then by waist circumference at 0.701 (95% CI: 0.644-0.759).

CONCLUSIONS

Conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product were independent predictors of future diabetes. The discriminatory power of body roundness index, cardiometabolic index and lipid accumulation product for diabetes prediction were higher than that of waist circumference.

Visceral adiposity index outperforms common anthropometric indices in predicting 10-year diabetes risk: Results from the ATTICA study

BACKGROUND

Visceral adiposity index (VAI) is a novel marker of visceral adipose tissue accumulation and dysfunction. The study aim was to explore the association of VAI with the 10-year type 2 diabetes mellitus (T2DM) incidence in apparently healthy individuals and compare its T2DM predictive ability against common anthropometric indices.

METHODS

In 2001 to 2002, the ATTICA study (Greece) recruited a random sample of 1514 and 1528 CVD-free men (18-87 years old) and women (18-89 years old), respectively. Sociodemographic, lifestyle, clinical, and biochemical characteristics of participants were measured at baseline, and the 10-year follow-up was performed during 2011 to 2012. After excluding participants with diabetes at baseline and participants without complete follow-up information regarding diabetes status and/or baseline VAI values, the working sample consisted of 1049 participants. In this sample, the predictive value of baseline VAI value was studied in relation to 10-year diabetes incidence.

RESULTS

One hundred thirty-three incident cases of diabetes were documented (10-year incidence: 12.7%). In the fully adjusted model, VAI significantly increased diabetes risk by 22% (OR per 1-unit increase =1.22; 95%CI, 1.09-1.37). Markers of oxidative stress and inflammation were found to, at least partly, mediate this relationship. Also, a moderating effect of menstruation status was revealed among women. VAI showed the highest predictive ability and contributed the most, along with waist-to-height ratio, to the correct classification of participants who developed diabetes.

CONCLUSIONS

The present findings suggest that VAI may be a useful index for predicting long-term diabetes development and may exhibit better predictive ability to commonly used anthropometric indices.

Relationship between body-roundness index and metabolic syndrome in type 2 diabetes

Background: The present study evaluated the relationship between body-roundness index (BRI) and metabolic syndrome (MetS) in type 2 diabetes. Methods: A cross-sectional study was conducted on 585 type 2 diabetes in Qinhuangdao. MetS was defined as per the Chinese Diabetes Society. Results: The BRI was strongly associated with the odds of having MetS in both males and females after adjustment for age, history of diabetes, and body-mass index (P<0.05). AUC of the BRI were 0.824 for males and 0.775 for females (P<0.001). The optimal cutoff points for the BRI were 3.85 in males (sensitivity 76.5%, specificity 82.1%) and 4.05 in females (sensitivity 76.4%, specificity 70.3%). Conclusion: The BRI was correlated with MetS and was an effective indicator for the screening of MetS in type 2 diabetes.

Body Adiposity Index and Body Roundness Index in Identifying Insulin Resistance Among Adults Without Diabetes

BACKGROUND

Body adiposity index (BAI) and body roundness index (BRI), initially developed to assess obesity, were evaluated here to detect insulin resistance in comparison with traditional anthropometric indices of body mass index (BMI), waist circumference (WC), weight-to-height ratio (WHtR), visceral adiposity index (VAI) and abdominal volume index (AVI).

METHODS

In this cross-sectional study, 570 Chinese individuals without diabetes were evaluated.

RESULTS

The Spearman rank test showed that insulin resistance correlated most strongly with WC and AVI in men and BMI in women, and most weakly with BAI in men and VAI in women. The prevalence of insulin resistance increased per quartile for all 7 anthropometric indices. Multivariate logistic regression identified BAI as the weakest predictor of insulin resistance in both genders (men, odds ratio [OR] 3.34, 95% confidence interval [CI] 1.09-10.18; women, OR 4.90, 95% CI 1.89-12.69), AVI as the strongest predictor in men (OR 19.73, 95% CI 2.51-155.04) and BMI as the strongest predictor in women (OR 15.55, 95% CI 4.71-51.28). The area under the receiver operating characteristic curve (AUC) showed that BAI exhibited the lowest AUCs for men (0.653, 95% CI 0.574-0.731) and women (0.701, 95% CI 0.627-0.774). BRI showed significantly higher AUCs for men (0.769, 95% CI 0.699-0.838) and women (0.763, 95% CI 0.699-0.827), and WHtR showed equal AUCs to BRI.

CONCLUSIONS

Neither BAI nor BRI were superior to BMI, WC, WHtR, VAI or AVI for predicting insulin resistance. BAI showed the weakest predictive ability, while BRI showed reasonable potential to serve as an alternative anthropometric index to detect insulin resistance.