Associations between different triglyceride glucose index-related obesity indices and periodontitis: results from NHANES 2009-2014.

BACKGROUND: This study aimed to explore the associations between triglyceride glucose (TyG) index-related obesity indices and periodontitis within the American population. METHODS: This cross-sectional investigation utilized data from the National Health and Nutrition Examination Survey (NHANES) for 2009-2014. The association between the TyG-waist-to-height ratio (TyG-WHtR), TyG-weight-adjusted-waist index (TyG-WWI), TyG-waist circumference (TyG-WC), or TyG-body mass index (TyG-BMI) and periodontitis was investigated utilizing multivariable logistic regression model, subgroup, and dose-response curve analyses. RESULTS: This study enrolled 4,808 adult participants. Except for TyG-BMI, which did not exhibit a relationship with periodontitis, TyG-WHtR, [odds ratio (OR) (95% confidence interval (CI))] = 2.83 [1.58-5.10], P = 0.002], TyG-WWI [OR (95% CI) = 7.50 (3.06-18.34), P < 0.001], and TyG-WC [OR (95% CI) = 2.12 (1.23-3.64), P = 0.011] were all associated with periodontitis. Participants in the highest quartile displayed an elevated risk of periodontitis relative to their counterparts in the lowest quartile, as evidenced for TyG-WWI [OR (95% CI) = 1.72 (1.26-2.33), P = 0.001] and TyG-WC [OR (95% CI) = 1.50 (1.13-1.99), P = 0.009] in the full adjustment model. Subgroup analyses suggested more pronounced positive associations between these indices and periodontitis in participants who were < 60 years old, had a BMI ≥ 25, and did not have diabetes. The dose-response curve indicated linear responses in these associations. CONCLUSIONS: This investigation identified a significant and stable association between TyG-WHtR, TyG-WWI, or TyG-WC and periodontitis, which implies a robust correlation between high insulin resistance and susceptibility to periodontitis in the American population.

Associations between new obesity indices and abnormal bone density in type 2 diabetes mellitus patients.

The clinical data analysis found that, compared with the traditional obesity index, the waist-weight ratio (WWR) has more advantages in predicting abnormal bone mineral density in subjects with type 2 diabetes. WWR may serve as a new predictive indicator for osteoporosis in T2DM patients. PURPOSE: This study was designed to explore the correlation between obesity-related indices and bone mineral density (BMD) and its influencing factors in type 2 diabetes mellitus (T2DM) patients. METHODS: A total of 528 patients with type 2 diabetes were recruited. Glucose tolerance, insulin stimulation, and blood biochemical tests were conducted on all participants. All subjects underwent dual-energy X-ray bone density testing and were grouped based on the bone density results. RESULTS: Compared with those in the normal BMD group, the waist-to-body weight ratio (WWR) and weight-adjusted-waist index (WWI) in the osteopenia and osteoporosis groups were significantly greater, while body mass index (BMI) was significantly lower (P < 0.05). The logistic regression results showed that the WWR, WWI, and BMI were independently correlated with abnormal BMD in T2DM patients (P < 0.05). WWR and the WWI were negatively correlated with the T-value of bone density in various parts of the body, while BMI was positively correlated with the T-value of bone density (P < 0.05). The area under the working characteristic curve (AUC) for T2DM patients with abnormal bone mass predicted by the WWR [0.806, 95% CI = (0.770-0.843), P < 0.001] was greater than that for patients with other obesity indicators, such as the WWI and BMI. CONCLUSION: We found a positive correlation between the WWR and bone density in T2DM patients. Compared with other obesity indicators, such as BMI and WWI, the WWR has a stronger discriminative ability for T2DM patients with abnormal bone density. Therefore, more attention should be given to the WWR in T2DM patients.

Characteristics of Different Obesity Metabolic Indexes and their Correlation with Insulin Resistance in Patients with Polycystic Ovary Syndrome.

This study is aimed to investigate the characteristics of different obesity metabolic indexes [body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), and lipid aggregation products (LAP)] and their correlation with insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS). The study was conducted on 140 subjects with PCOS and 133 control subjects aged 18-44 years. According to insulin resistance index (HOMA-IR) ≥ 2.69 and HOMA-IR < 2.69, PCOS group members were divided into insulin resistance group and non-insulin resistance group. Anthropometric and serological characteristics of the population with PCOS focused on calculating different obesity metabolic indexes and HOMA-IR. BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher in PCOS patients than in the control group, and the differences were all statistically significant (P < 0.05); In the insulin resistance group of PCOS patients, BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher than in the non-insulin resistance group (P < 0.05). In PCOS patients, BMI (r = 0.658, P < 0.001), WC (r = 0.0.662, P < 0.001), WHR (r = 0.377, P < 0.001), WHtR (r = 0.660, P < 0.001), CMI (r = 0.698, P < 0.001), BRI (r = 0.757, P < 0.001), VAI (r = 0.640, P < 0.001), and LAP (r = 0.767, P < 0.001) were positively correlated with IR. Obesity metabolic indexes associated with PCOS were elevated in the PCOS group compared to the control group, and in the PCOS insulin-resistant group compared to the non-insulin resistant group. Novel obesity metabolic indexes, especially CMI, BRI and LAP, might be more appropriate for evaluating the risk of concurrent IR in PCOS.

Associations between abdominal obesity indices with hypertension in type 2 diabetes mellitus: Chinese visceral adiposity index.

PURPOSE: This research was performed to evaluate the relationship between hypertension (HTN) and abdominal obesity index in patients with type 2 diabetes mellitus (T2DM). METHODS: Totally 1657 participants with T2DM (mean age 54 ± 12 years; 38.02% female) were enrolled. They were divided into the groups of HTN (n = 775) and non-HTN (n = 882). Anthropometric and biochemical indicators were measured and collected. A bioelectrical impedance analyzer was used to measure visceral and subcutaneous fat areas. RESULTS: Compared with the HTN group, the non-HTN group had a lower level of Chinese visceral adiposity index (CVAI) (p < 0.001). Meanwhile, among tertiles of CVAI, as CVAI increased, the proportion of patients with HTN increased, which was 33.51%, 44.30%, and 62.50%, respectively. CVAI was shown to have a significant positive correlation with HTN. (r = 0.258, p < 0.001). CVAI was independently related to an elevated risk of HTN by binary logistic regression analyses, and the OR was (95% CI) 1.013 (1.010-1.016, p < 0.001) after adjustment. The area under the receiver operating characteristic curve (AUC) of CVAI predicted HTN in T2DM patients was greater than those of other abdominal obesity indices (p < 0.001). CONCLUSION: We found that CVAI was highly positively correlated with HTN in T2DM. Compared with other indices of abdominal obesity, such as WC, BMI, WHR, VAI, and LAP, the CVAI showed superior discriminative ability in T2DM complicated with HTN. Therefore, more attention should be paid to CVAI in T2DM.

Association between visceral obesity and 10-year risk of first atherosclerotic cardiovascular diseases events among American adults: National Health and Nutrition Examination Survey.

Background: In the United States, the relationship between visceral obesity and the risk of developing atherosclerosis cardiovascular disease (ASCVD) for the first time in 10 years is unclear. Methods: Data for this cross-sectional study came from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020. We collected variable information related to 10-year ASCVD risk and visceral obesity reliable indicators [Visceral obesity index (VAI) and Lipid accumulation product (LAP)]. And we used multiple logistic regression to analyze the correlation of visceral obesity indicators (VAI and LAP) with 10-year ASCVD risk. In addition, we assessed the linear relationship between VAI or LAP and 10-year ASCVD risk by smoothing curve fitting. Finally, we conducted subgroup analysis and sensitivity analysis after excluding participants with extreme VAI and LAP values to ensure that we obtained accurate and reliable results. Results: Our study included a total of 1,547 participants (mean age: 56.5 ± 10.1, 60% of males). The results of the multiple logistic regression showed that compared with participants with the lowest VAI in the 1st Quartile (≤0.79), the adjusted OR values for VAI and elevated 10-year ASCVD risk in Q3 (1.30-2.14), and Q4 (≥2.15) were 2.58 (95% CI: 1.24-5.36, P = 0.011), 15.14 (95% CI: 6.93-33.05, P < 0.001), respectively. Compared with participants with the lowest LAP in the 1st Quartile (≤28.29), the adjusted OR values for VAI and elevated 10-year ASCVD risk in Q3 (46.52-77.00), and Q4 (≥77.01) were 4.63 (95% CI: 2.18-9.82, P < 0.001), 16.94 (95% CI: 6.74-42.57, P < 0.001), respectively. Stratified analysis showed that the association between VAI or LAP and the first ASCVD event was more pronounced in males. Conclusion: Higher VAI or LAP scores are significantly associated with elevated 10-year ASCVD risk in adults aged 40 to 79 in the USA, which suggested that monitoring visceral obesity is crucial to reduce the risk of a first ASCVD event.

Management of children with obesity at local hospital and impact of COVID-19 pandemic.

This study investigated the status of children with obesity before and after the COVID-19 pandemic, and the effects of lifestyle guidance on weight loss among children in Japan. We analysed the data of patients who visited our hospital after check-ups for obesity and evaluated the efficacy of lifestyle guidance. The patients were divided into groups A, B, and C (year 2011, 2019, and 2021, respectively). There were no differences in body weight, obesity index (OI), blood pressure, or alanine transaminase (ALT) levels between the groups; however, aspartate transaminase (AST) level was the highest in Group C. In Group C, only OI increased between the primary and secondary screenings; however, OI and body mass index (BMI) improved during the second screening and more children in the weight loss group followed lifestyle guidance. OI/BMI did not change over the past decade; however, short-term weight gain was significant owing to the COVID-19 pandemic, and simple guidance was effective in reducing weight. Future challenges include identifying methods to achieve long-term weight loss.

Correlation analysis of anthropometric indices and type 2 diabetes mellitus in residents aged 60 years and older.

Background and purpose: In recent years, the incidence of obesity in people aged 60 and over has increased significantly, and abdominal obesity has been recognized as an independent risk factor for diabetes. Aging causes physiologic decline in multiple body systems, leading to changes in obesity indicators such as BMI. At present, the relationship between abdominal obesity markers and Diabetes mellitus (DM) in people aged 60 years and older remains unclear. Therefore, it is necessary to study the correlation between anthropometric indices and diabetes and explore potential predictors. Methods: The basic demographic information of participants aged 60 and above in Zhongshan City in 2020 was collected. Physical parameters, blood glucose and other biochemical indices were measured comprehensively. Binary logistic regression analysis was used to explore the relationship between abdominal obesity indicators [Waist circumference, Neck Circumference, Waist-to-hip ratio, Chinese Visceral Obesity Index (CVAI), and visceral obesity index] and diabetes mellitus. ROC characteristic curve was used to analyze the predictive ability of abdominal obesity indicators to DM, and the non-restrictive cubic spline graph was used to visualize the screened obesity indicators and diabetes risk. Results: Among 9,519 participants, the prevalence of diabetes was 15.5%. Compared with low CVAI, High CVAI level was significantly associated with increased prevalence of DM in males and females (all p < 0.05), in males (OR, 2.226; 95%CI: 1.128-4.395), females (OR, 1.645; 95%CI: 1.013-2.669). After adjusting for potential confounding factors, there were gender differences between neck circumference and the prevalence of DM, and above-normal neck circumference in males was significantly associated with increased prevalence of DM (OR, 1.381; 95% CI: 1.091-1.747) (p < 0.05). Conclusion: Among these anthropometric indices, CVAI is consistent with the features of fat distribution in older individuals and shows superior discriminative power as a potential predictor of DM, compared to traditional anthropometric parameters.

A novel clinical diagnostic marker predicting the relationship between visceral adiposity and renal function evaluated by estimated glomerular filtration rate (eGFR) in the Chinese physical examination population.

BACKGROUND AND AIMS: The effect of body fat deposition on the kidney has received increasing attention. The Chinese visceral adiposity index (CVAI) is an important indicator of recent research. The purpose of this study was to explore the predictive value of CVAI and other organ obesity indicators in predicting CKD in Chinese residents. METHODS: A retrospective cross-sectional study of 5355 subjects was performed. First, the study utilized locally estimated scatterplot smoothing to describe the dose-response relationship between the estimated glomerular filtration rate (eGFR) and CVAI. The L1-penalized least absolute shrinkage and selection operator (LASSO) regression algorithm was used for covariation screening, and the correlation between CVAI and eGFR was quantified using multiple logistic regression. At the same time, the diagnostic efficiency of CVAI and other obesity indicators was evaluated by ROC curve analysis. RESULTS: CVAI and eGFR were negatively correlated. Using group one as the control, an odds ratio (OR) was calculated to quantify CVAI quartiles (ORs of Q2, Q3, and Q4 were 2.21, 2.99, and 4.42, respectively; P for trend < 0.001). CVAI had the maximum area under the ROC curve compared with other obesity indicators, especially in the female population (AUC: 0.74, 95% CI: 0.71-0.76). CONCLUSIONS: CVAI is closely linked to renal function decline and has certain reference value for the screening of CKD patients, particularly in women.

Comparison of the predictive value of anthropometric indicators for the risk of benign prostatic hyperplasia in southern China / 亚洲男科学杂志(英文版)

This study aimed to compare the predictive value of six selected anthropometric indicators for benign prostatic hyperplasia (BPH). Males over 50 years of age who underwent health examinations at the Health Management Center of the Second Xiangya Hospital, Central South University (Changsha, China) from June to December 2020 were enrolled in this study. The characteristic data were collected, including basic anthropometric indices, lipid parameters, six anthropometric indicators, prostate-specific antigen, and total prostate volume. The odds ratios (ORs) with 95% confidence intervals (95% CIs) for all anthropometric parameters and BPH were calculated using binary logistic regression. To assess the diagnostic capability of each indicator for BPH and identify the appropriate cutoff values, receiver operating characteristic (ROC) curves and the related areas under the curves (AUCs) were utilized. All six indicators had diagnostic value for BPH (all P ≤ 0.001). The visceral adiposity index (VAI; AUC: 0.797, 95% CI: 0.759-0.834) had the highest AUC and therefore the highest diagnostic value. This was followed by the cardiometabolic index (CMI; AUC: 0.792, 95% CI: 0.753-0.831), lipid accumulation product (LAP; AUC: 0.766, 95% CI: 0.723-0.809), waist-to-hip ratio (WHR; AUC: 0.660, 95% CI: 0.609-0.712), waist-to-height ratio (WHtR; AUC: 0.639, 95% CI: 0.587-0.691), and body mass index (BMI; AUC: 0.592, 95% CI: 0.540-0.643). The sensitivity of CMI was the highest (92.1%), and WHtR had the highest specificity of 94.1%. CMI consistently showed the highest OR in the binary logistic regression analysis. BMI, WHtR, WHR, VAI, CMI, and LAP all influence the occurrence of BPH in middle-aged and older men (all P ≤ 0.001), and CMI is the best predictor of BPH.

Association between obesity indicators and hyperuricemia in Chinese adults / 公共卫生与预防医学

Objective The study aims to find a suitable obesity index for predicting hyperuricemia (HUA)in Chinese adults. Methods The obesity indexes of 8133 subjects in China Health and Nutrition Survey in 2009 were calculated, and the basic situation of them was analyzed descriptively. χ2 test and t test were used to test the differences of categorical variables and continuous variables between the HUA group and the non-HUA group. The area under the curve (AUC) and receiver operating characteristic (ROC) curves were used to analyze the predictive value of these indices for HUA. Binary logistic regression was used to analyze the relationship between obesity and HUA. Results Demographic covariates, prevalence and Body Mass Index (BMI) all have impacts on the prevalence of HUA. Obesity indexes have a good predictive effect on HUA, and the Lipid Accumulation Product (LAP) is the best (AUC=0.77 (95% CI [0.75, 0.78]). Obesity indexes all have a significant correlation with HUA. When covariates were not adjusted, LAP had the highest OR value (OR=5.87, 95% CI [5.08, 6.77]). Conclusion LAP index is significantly related to HUA, and it can be used as an emerging index to assess the prevalence of HUA in Chinese adults.

Comparison of the predictive value of anthropometric indicators for the risk of benign prostatic hyperplasia in southern China.

This study aimed to compare the predictive value of six selected anthropometric indicators for benign prostatic hyperplasia (BPH). Males over 50 years of age who underwent health examinations at the Health Management Center of the Second Xiangya Hospital, Central South University (Changsha, China) from June to December 2020 were enrolled in this study. The characteristic data were collected, including basic anthropometric indices, lipid parameters, six anthropometric indicators, prostate-specific antigen, and total prostate volume. The odds ratios (ORs) with 95% confidence intervals (95% CIs) for all anthropometric parameters and BPH were calculated using binary logistic regression. To assess the diagnostic capability of each indicator for BPH and identify the appropriate cutoff values, receiver operating characteristic (ROC) curves and the related areas under the curves (AUCs) were utilized. All six indicators had diagnostic value for BPH (all P ≤ 0.001). The visceral adiposity index (VAI; AUC: 0.797, 95% CI: 0.759-0.834) had the highest AUC and therefore the highest diagnostic value. This was followed by the cardiometabolic index (CMI; AUC: 0.792, 95% CI: 0.753-0.831), lipid accumulation product (LAP; AUC: 0.766, 95% CI: 0.723-0.809), waist-to-hip ratio (WHR; AUC: 0.660, 95% CI: 0.609-0.712), waist-to-height ratio (WHtR; AUC: 0.639, 95% CI: 0.587-0.691), and body mass index (BMI; AUC: 0.592, 95% CI: 0.540-0.643). The sensitivity of CMI was the highest (92.1%), and WHtR had the highest specificity of 94.1%. CMI consistently showed the highest OR in the binary logistic regression analysis. BMI, WHtR, WHR, VAI, CMI, and LAP all influence the occurrence of BPH in middle-aged and older men (all P ≤ 0.001), and CMI is the best predictor of BPH.

A Body Shape Index (ABSI) as a Variant of Conicity Index Not Affected by the Obesity Paradox: A Cross-Sectional Study Using Arterial Stiffness Parameter.

A body shape index (ABSI) is an abdominal obesity index developed based on epidemiological statistics and designed to correlate minimally with body mass index (BMI). We examined the approximation between ABSI and other abdominal obesity indices based on biophysical concepts. The cross-sectional data from 62,514 Japanese urban residents were analyzed. Body adiposity indices comprising BMI, waist circumference (WC), ABSI, conicity index (CI), waist-to-height ratio (WHtR), and WC/BMI ratio were examined. ABSI and CI more strongly correlated with age and arterial stiffness assessed by cardio-ankle vascular index (CAVI) compared to the other indices. The discriminative power for high CAVI (≥9.0) was the strongest for ABSI followed by CI and other indices, in that order. The range and distribution of WC corresponding to the cutoff of ABSI (0.0801), or CI (1.23) seemed reasonable. The correlation between ABSI and CI was the strongest compared to any other combination of indices. CI correlated moderately with BMI, whereas ABSI correlated minimally with BMI. ABSI correlates strongly and approximates closely with CI. Hence, ABSI may be considered to reflect the degree of body shape change from cylindricity to conicity and is currently the only abdominal obesity index not affected by the obesity paradox.

Effects of Konjaku Flour on the Gut Microbiota of Obese Patients.

Objective: Gut microbiota have been thought to play a role in the emergence of obesity and metabolic disorders, thus dietary fiber may be an effective strategy for the management of obesity by modulating the gut microbiota. The aim of the present study was to investigate the effects of konjaku flour (KF) supplementation on treating obesity and regulating intestinal microbiota in obese adults. Methods: In a 5-week, randomized, double-blind, place-controlled trial, sixty-nine obese volunteers aged 25 to 35 with body mass index ≥28 kg/m2 were randomly assigned to receive KF or placebo (lotus root starch). Obesity index, blood parameters, and gut microbiota were analyzed. Results: KF remarkably reduced the body mass index (BMI), fat mass, percentage body fat (PBF), serum triglyceride (TG), glycated hemoglobin A1c (HbA1c), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels in the patients (p <0.05 or p <0.01). Meanwhile, high-throughput sequencing and bioinformatics analysis showed that the konjac flour treatment notably increased the α-diversity and changed the ß-diversity of intestinal microflora in patients (p <0.01). Moreover, konjac flour could also evidently increase the abundance of some of the beneficial microorganisms related to obesity of patients, such as Lachnospiraceae, Roseburia, Solobacterium, R. inulinivorans, Clostridium perfringens, and Intestinimonas butyriciproducens, and reduce the abundance of the harmful microorganisms, such as Lactococcus, Bacteroides fragilis, Lactococcus garvieae, B. coprophilus, B. ovatus, and B. thetaiotaomicron (p <0.01). Specifically, C. perfringens was significantly negatively correlated with serum total cholesterol (TC) (p <0.01). Conclusion: These results suggested that KF can achieve positive effects on treating obesity, which manifest on reducing BMI, fat mass, blood glucose, and blood lipid, improving hepatic function, and also regulating intestinal microfloral structure. Therefore, changes in gut microbiota may explain in part the effects of KF.

Gender Differences in the Association Between Obesity Indices and Chronic Kidney Disease Among Middle-Aged and Elderly Taiwanese Population: A Community-Based Cross-Sectional Study.

Background: Traditional risk factors for chronic kidney disease (CKD) include diabetes mellitus (DM), hypertension (HTN), and metabolic syndrome, which are health conditions related to obesity. We aimed to investigate which of the three obesity indices has the strongest association with CKD and to explore whether there are gender differences in these relationships in the middle-aged and elderly Taiwanese population. Methods: This was a cross-sectional, community-based study. It included 400 residents (141 males and 259 females, age 50-90 years) residing in a community in northern Taiwan. Each participant was asked to fill a questionnaire that collected personal information, medical history, medication use, and anthropometric measurements. The laboratory data were obtained by testing the blood and urine samples. The baseline characteristics were compared, and the obesity indices included body mass index (BMI), waist circumference (WC), and visceral adiposity index (VAI). CKD was defined as the presence of renal dysfunction (urine albumin-creatinine ratio ≥ 30 mg/g) or estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m2. We used a multiple logistic regression model to evaluate the association between each obesity index and CKD for both genders. Further, we used the area under the receiver operating characteristic (ROC) curve (AUC) to examine the best obesity indices to predict CKD in different genders. Results: The average age of the subjects was 64.47 ± 8.45 years, and men were significantly older. CKD was found in 31 (22.0%) males and 50 (19.3%) females. In men, there was no significant difference between the CKD and non-CKD groups among the three obesity indices. However, in women, only VAI was significantly higher in subjects with CKD (1.9 [1.1, 3.4]) than in subjects without CKD (1.5 [1.0, 2.2]) (p-value = 0.03). The multivariate logistic regression revealed that even after adjusting for possible confounding factors, VAI was found to be an independent risk factor for CKD in women (OR: 1.32, 95% CI: 1.04-1.69, p = 0.02), but not in men (OR: 1.20, 95% CI: 0.85-1.69, p = 0.30). The AUC of VAI had a significant ability to predict CKD in women but not in men. Conclusion: Our results showed that among the three obesity indices, VAI had the strongest association with CKD compared to BMI and WC in women. In addition, VAI in women should be given more importance in the screening for CKD among the middle-aged and elderly Taiwanese population.

Birth Weight and Adult Obesity Index in Relation to the Risk of Hypertension: A Prospective Cohort Study in the UK Biobank.

Objectives: To investigate the association between birth weight and the risk of hypertension, and to examine the interaction between birth weight and the adult obesity index. Methods: We included 199,893 participants who had birth weight data and no history of hypertension at baseline (2006-2010) from the UK Biobank. A multivariate cubic regression spline was used to visually explore the dose-response relationship. Multivariate Cox proportional hazard regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: We observed a nonlinear inverse association between birth weight and hypertension. The risk for hypertension decreased as birth weight increased up to approximately 3.80 kg. Compared with the participants with the fourth quintile of birth weight (3.43-3.80 kg), those with the first quartile of birth weight (<2.88 kg) were associated with a 25% higher risk of hypertension [HR 1.25; 95% CI (1.18-1.32)]. In addition, the participants with birth weight <2.88 kg and body mass index ≥30 kg/m2 had the highest risk [HR 3.54; 95% CI (3.16-3.97); p for interaction <0.0001], as compared with those with birth weight between 3.43-3.80 kg and body mass index between 18.5-25.0 kg/m2. These associations were largely consistent in the stratified and sensitivity analyses. Conclusion: Our findings indicate that lower birth weight is nonlinearly correlated with higher risk of hypertension, and birth weight between 3.43-3.80 kg might represent an intervention threshold. Moreover, lower birth weight may interact with adult obesity to significantly increase hypertension risk.

Association Among Lipid Accumulation Product, Chinese Visceral Obesity Index and Diabetic Retinopathy in Patients with Type 2 Diabetes: A Cross-Sectional Study.

BACKGROUND AND AIM: Obesity often coexists with diabetes, especially abdominal obesity, recognized as a risk factor for diabetic complications. Diabetic retinopathy (DR), as one of the most common microvascular complications of diabetes, may be associated with these indices. Lipid accumulation product (LAP) and Chinese visceral obesity index (CVAI) are novel visceral obesity indicators, which have been proven to be an influential factor predicting type 2 diabetes (T2DM). However, the correlation among LAP, CVAI, and DR still lacks systematic research in T2DM. The study aimed to explore the relationship among LAP, CVAI levels in different DR stages of T2DM patients and the diagnostic efficacy of LAP and CVAI for DR. METHODS: A total of 263 participants were recruited in this cross-sectional study. We enrolled 169 patients with T2DM, divided into the non-DR group (NDR, n = 61), non-proliferative DR group (NPDR, n = 55), and proliferative DR group (PDR, n = 53). And we also enrolled 94 healthy control participants. We collected demographic, anthropometric, and biochemical data on each subject. LAP and CVAI are calculated according to different formulas for men and women. RESULTS: Compared with the control group, LAP and CVAI were significantly higher (P < 0.05). After adjusting for confounding factors, LAP (OR: 1.029, 95CI%: 1.010-1.049, P < 0.05), WC (OR: 1.073, 95CI%: 1.009-1.141, P < 0.05) and CVAI (OR: 1.017, 95CI%: 1.000-1.033, P < 0.05) were all associated with an increased risk of DR. Furthermore, increased LAP (OR: 1.020, 95% CI: 0.100-0.290) is associated with DR severity (P < 0.001). Moreover, the LAP had the most significant area under the receiver operating characteristics (ROC) curve (AUC) (AUC = 0.728, 95% CI: 0.653-0.804). CONCLUSION: A high LAP is associated with an increased risk of DR in T2DM patients, and the LAP index appears to be a good predictor of DR risk and severity in patients with T2DM, compared with BMI, WC, and CVAI.

Relationship between obesity indices and hypertension among middle-aged and elderly populations in Taiwan: a community-based, cross-sectional study.

OBJECTIVE: Obesity and hypertension (HTN) have become increasingly prevalent in Taiwan. People with obesity are more likely to have HTN. In this study, we evaluated several anthropometric measurements for the prediction of HTN in middle-aged and elderly populations in Taiwan. DESIGN: Cross-sectional observational study. SETTING: Community-based investigation in Guishan Township of northern Taiwan. PARTICIPANTS: A total of 396 people were recruited from a northern Taiwan community for a cross-sectional study. Anthropometrics and blood pressure were measured at the annual health exam. The obesity indices included body mass index (BMI), body fat (BF) percentage and waist circumference (WC). OUTCOME MEASURES: Statistical analyses, including Pearson's correlation, multiple logistic regression and the area under ROC curves (AUCs) between HTN and anthropometric measurements, were used in this study. RESULTS: Of the 396 people recruited, 200 had HTN. The age-adjusted Pearson's coefficients of BMI, BF percentage and WC were 0.23 (p<0.001), 0.14 (p=0.01) and 0.26 (p<0.001), respectively. Multiple logistic regression of the HTN-related obesity indices showed that the ORs of BMI, BF percentage and WC were 1.15 (95% CI 1.08 to 1.23, p<0.001), 1.07 (95% CI 1.03 to 1.11, p<0.001) and 1.06 (95% CI 1.03 to 1.08, p<0.001), respectively. The AUCs of BMI, BF percentage and WC were 0.626 (95% CI 0.572 to 0.681, p<0.001), 0.556 (95% CI 0.500 to 0.613, p=0.052) and 0.640 (95% CI 0.586 to 0.694, p<0.001), respectively. CONCLUSIONS: WC is a more reliable predictor of HTN than BMI or BF percentage. The effect of abdominal fat distribution on blood pressure is greater than that of total BF amount.

The association between obesity indices and hypertension: Which index is the most notable indicator of hypertension in different age groups stratified by sex?

OBJECTIVE: This study aimed to investigate the most notable obesity index and its optimal cut-off point of hypertension in different age groups stratified by sexes among community residents in southern China. METHODS: In this cross-sectional study, 620 men and 631 women aged 18-59 years were enrolled. The independent-samples t-test and chi-square test were conducted to analyze continuous and categorical variables, respectively. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis assessed the association between the obesity indices and hypertension risk. RESULTS: Waist-stature ratio (WSR) and waist-hip ratio (WHR) were the most notable risk factors for hypertension in young men and women, respectively. The odds ratios (ORs) of hypertension risk increased with per standard deviation (SD) in WSR and WHR (WSR: OR = 2.877, 95% confidence interval [CI] = 1.602 to 5.167; WHR: OR = 10.683, 95%CI = 2.179 to 52.376). In the middle-aged group of both sexes, body mass index (BMI) was the most distinctive risk factor for hypertension, the ORs of hypertension risk increased with per SD in BMI (men: OR = 2.297, 95%CI = 1.683 to 3.136; women: OR = 1.810, 95%CI = 1.338 to 2.450). ROC curve analysis demonstrated WSR and PI were better indicators than other indices among young men, and WSR was the best marker among young women. However, BMI and WC were the most sensitive markers in middle-aged men and women, respectively. CONCLUSIONS: In this Chinese population, the association of obesity indices and hypertension is inconsistent in different age groups and sexes. It is important to choose appropriate indicators for specific groups of people.

[Association of obesity indexes with hypertension and dyslipidemia in Chinese adults].

OBJECTIVE: To explore the association of obesity indicators with hypertension and dyslipidemia in adults. METHODS: The study used anthropometric data of 1022 adults aged 18-69 years in Liaoning, Henan and Hunan Provinces in 2012 to describe the overweight and obesity rate of body mass index( BMI), waist circumference( WC), waist to height ratio( WHtR), waist hip ratio( WHR) and body fat percentage( BF%). The ability of indicators to predict the risk of hypertension and dyslipidemia was evaluated by receiver operating characteristic( ROC) curve analysis. RESULTS: In comparison of anthropometric measurements, male WC was significantly higher than female, thigh circumference( ThC) was no gender differences and thigh height ratio( THtR) lower in men than in women. The obesity index was used to determine the overweight and obesity rate of Chinese adults: WHtR > WHR > BMI > BF% > WC was58. 7%, 50. 4%, 49. 1%, 35. 7% and 35. 3%, respectively. The obesity rate of BMI was13. 2%, significantly lower than other indicators. The ROC curve illustrated area under curve( AUC) of WHtR was the largest in predicting the risk of hypertension, and the cutoff values were 0. 53 and 0. 56 in male and female. AUC of WHR were the largest with hypercholesterolemia as dependent variables in male and female and as the only significant indicator in men. The value of BMI, WC, WHtR, WHR and BF% to predict the risk of hypertriglyceridemia was similar. ThC and THtR had a better prognosis value than BMI, WC, WHtR and other common indicators in low high-density lipoprotein cholesterolemia, especially in male residents. The cut-off values of ThC were 52. 50 and 55. 40, and the cut-off values of THtR were 0. 31 and 0. 35 in male and female. CONCLUSION: Men are more likely to hoard fat in the abdomen, female fat easily in the thigh accumulation. WHtR is the best index in predicting the risk of hypertension. The association between obesity indexes and different clinical classification of dyslipidemia are not the same: WHR shows the best effect in predicting the risk of hypercholesterolemia, BMI, WC, WHtR, WHR and BF% have the same value in predicting the risk of hypertriglyceridemia, ThC and THtR are better than BMI, WC, WHtR and other common indicators in predicting the risk of low high-density lipoprotein cholesterolemia, especially in male residents.

Identification of an obesity index for predicting metabolic syndrome by gender: the rural Chinese cohort study.

BACKGROUND: To compare the accuracy of different obesity indexes, including waist circumference (WC), weight-to-height ratio (WHtR), body mass index (BMI), and lipid accumulation product (LAP), in predicting metabolic syndrome (MetS) and to estimate the optimal cutoffs of these indexes in a rural Chinese adult population. METHODS: This prospective cohort involved 8468 participants who were followed up for 6 years. MetS was defined by the International Diabetes Federation, American Heart Association, and National Heart, Lung, and Blood Institute criteria. The power of the 4 indexes for predicting MetS was estimated by receiver operating characteristic (ROC) curve analysis and optimal cutoffs were determined by the maximum of Youden's index. RESULTS: As compared with WHtR, BMI, and LAP, WC had the largest area under the ROC curve (AUC) for predicting MetS after adjusting for age, smoking, drinking, physical activity, and education level. The AUCs (95% CIs) for WC, WHtR, BMI, and LAP for men and women were 0.862 (0.851-0.873) and 0.806 (0.794-0.817), 0.832 (0.820-0.843) and 0.789 (0.777-0.801), 0.824 (0.812-0.835) and 0.790 (0.778-0.802), and 0.798 (0.785-0.810) and 0.771 (0.759-0.784), respectively. The optimal cutoffs of WC for men and women were 83.30 and 76.80 cm. Those of WHtR, BMI, and LAP were approximately 0.51 and 0.50, 23.90 and 23.00 kg/m2, and 19.23 and 20.48 cm.mmol/L, respectively. CONCLUSIONS: WC as a preferred index over WHtR, BMI, and LAP for predicting MetS in rural Chinese adults of both genders; the optimal cutoffs for men and women were 83.30 and 76.80 cm.