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.

Relationship between obesity indicators and hypertension-diabetes comorbidity in an elderly population: a retrospective cohort study.

BACKGROUND: The prevalence of obesity, hypertension and diabetes is increasing. Hypertension and diabetes are common complications. Additionally, obesity and hypertension-diabetes comorbidity (HDC) are both closely related to insulin resistance. The aim of this study was to determine the association of obesity indicators with HDC in elderly individuals. METHODS: This retrospective cohort study included 74,955 subjects aged ≥ 60 years living in Xinzheng, Henan Province, from January 2011 to December 2019. The data were collected from the annual health examination dataset. Cox proportional hazard regression models and competing-risk survival regression models were used to examine the relationships between the three indicators and HDC risk. RESULTS: After 346,504 person-years of follow-up, HDC developed in 9,647 subjects. After further adjustments for confounders and death competing risks, compared with a body mass index (BMI) of 18.5-23.9 kg/m2, the fully adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of BMI < 18.5, 24-27.9 and ≥ 28 kg/m2 for HDC morbidity were 0.651(0.538,0.788),1.00,1.396(1.336,1.459) and 1.769(1.666,1.878), respectively. Moreover, participants with abdominal obesity measured via waist circumference (WC) or waist-to-height ratio (WtHR) had a higher risk of HDC (HR:1.513; 95% CI: 1.45,1.578 and HR:1.412;95% CI: 1.353,1.473), respectively, than participants with low WC or with low WtHR. In the joint analyses, the highest risk was observed in participants who were overweight and who had central obesity (HR: 1.721; 95% CI: 1.635, 1.811) compared with the nonoverweight and noncentral obesity groups. CONCLUSIONS: Increased BMI, WC and WtHR were associated with an increased risk of HDC. There was an additive interaction between general body adiposity (as measured via BMI) and central obesity (as measured via WC and WtHR) for HDC. Therefore, reasonable control of BMI, WC and WtHR may be an effective measure to prevent HDC among elderly individuals.

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.

Relationship Between Six Insulin Resistance Surrogates and Nonalcoholic Fatty Liver Disease Among Older Adults: A Cross-Sectional Study.

Background: Non-alcoholic fatty liver disease (NAFLD) represents a large and growing public health problem. Insulin resistance (IR) plays a crucial role in the pathogenesis of NAFLD. The aim of this study was to determine the association of triglyceride-glucose (TyG) index, TyG index with body mass index (TyG-BMI), lipid accumulation product (LAP), visceral adiposity index (VAI), triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-c) and metabolic score for IR (METS-IR) with NAFLD in older adults and to compare the discriminatory abilities of these six IR surrogates for NAFLD. Methods: This cross-sectional study included 72,225 subjects aged ≥60 years living in Xinzheng, Henan Province, from January 2021 to December 2021. The data were collected from the annual health examination dataset. Logistic regression models were used to examine the relationships between the six indicators and NAFLD risk. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different IR surrogates for NAFLD under the influence of potential risk factors. Results: After adjusting for multiple covariates, compared with the first quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) of the highest quintiles of TyG-BMI were the most obvious (OR:43.02, 95% CI:38.89-47.72), followed by the METS-IR (OR:34.49, 95% CI:31.41-37.95). Restricted cubic spline analysis reported that there were non-linear positive association and dose-response relationship between 6 IR surrogates and NAFLD risk. Compared with other IR-related indicators (LAP, TyG, TG/HDL-c and VAI), TyG-BMI showed the highest AUC (AUC:0.8059;95% CI:0.8025-0.8094). Additionally, METS-IR also had a high predictive performance for NAFLD, and the AUC was greater than 0.75 (AUC:0.7959;95% CI:0.7923-0.7994). Conclusion: TyG-BMI and METS-IR had pronounced discrimination ability to NAFLD, which are recommended as complementary markers for the assessment of NAFLD risk both in clinic and in future epidemiological studies.

Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study.

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