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.
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.
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.
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.
The WC and WHtR were more closely related to diabetes than BMI and WHR among study participants ≥ 40 years of age, especially in females.
Zhang FL
，Ren JX
，Zhang P
，Jin H
，Qu Y
，Yu Y
，Guo ZN
，Yang Y
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Weight-adjusted waist index as a practical predictor for diabetes, cardiovascular disease, and non-accidental mortality risk.
Identifying a more suitable marker among various measures of adiposity, demonstrating strong associations and predictive ability for clinical use, remains a topic of debate. Weight-adjusted waist index (WWI) has been proposed as a novel index of adiposity, yet its exploration is limited, especially in Chinese populations. This study seeks to examine the associations between body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), weight-adjusted waist index (WWI), waist circumference divided by body mass to the power of 0.333 (WC/M0.333), visceral adiposity index (VAI), lipid accumulation product (LAP), and the incidence of diabetes, cardiovascular disease, and non-accidental mortality in Chinese populations. Furthermore, our goal is to compare the respective predictive values of these measures for these health outcomes.
This prospective cohort study included 21,750 subjects with a 9-year follow-up period. Cox proportional hazard models were used to investigate the relationship between eight anthropometric indexes and the incidence of diabetes, cardiovascular disease, and non-accidental mortality. The predictive value of these eight indexes was compared using the area under the curve metric. Significant positive associations were found between WWI and the risk of diabetes. Using the first quartile (Q1) of WWI as the reference group, hazard ratios with 95% confidence intervals for the risk of diabetes were 1.58 (0.98-2.55) for Q2, 2.18 (1.34-3.35) for Q3, and 2.27 (1.41-3.67) for Q4. Significant associations were observed with the highest quartile of WWI for the risk of cardiovascular disease [Q2: HR 1.45 (95% CI 1.06-1.98); Q3: 1.33 (0.97-1.83); Q4: 1.55 (1.13-2.14)] and risk of non-accidental mortality [Q2: 0.94 (0.80-1.11); Q3: 1.24 (1.04-1.48); Q4: 1.44 (1.16-1.79)]. Receiver operating characteristic analysis revealed that WWI exhibited superior discrimination and accuracy in predicting cardiovascular disease and non-accidental mortality compared to other adiposity indexes (BMI, WC, WHR, WHTR, WC/M0.333, VAI, and LAP).
WWI exhibited the most robust and consistent association with the incidence of cardiovascular disease and non-accidental mortality. Given its simplicity and widespread use, WWI emerges as a novel and practical predictor of diabetes, cardiovascular disease, and non-accidental mortality among the eight adiposity indexes investigated in this study.
Liu S
，Yu J
，Wang L
，Zhang X
，Wang F
，Zhu Y
... -
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Determining the best method for evaluating obesity and the risk for non-communicable diseases in women of childbearing age by measuring the body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, A Body Shape Index, and hip index.
Non-communicable diseases (NCDs) are linked to excessive adiposity and anthropometric indices can be used to identify those at risk. The aim of this study was to evaluate the precision of anthropometric indices in identifying obesity and risk factors for NCDs and to investigate the emergence of obesity-related NCDs in young women in Sri Lanka.
We recruited 282 women 18 to 35 y of age from suburban and rural areas in Sri Lanka. We measured the women's height, weight, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), A Body Shape Index(ABSI), hip circumference (HC), hip index (HI), anthropometric risk index (ARI), fasting serum glucose, fasting serum insulin, homeostatic model assessment for insulin resistance, cholesterol, high-density lipoprotein, low-density lipoprotein, triacylglycerols, and ovulatory gonadal hormones (progesterone, testosterone). Comparisons were made between women with normal BMI and those who were overweight or obese using anthropometric and biochemical characteristics.
The prevalence of obesity was highest in WC and in receiver operating characteristic analysis, BMI, WC, and WHtR showed higher sensitivity and lower 1-specificity as indicators of obesity. BMI had an area under the curve (AUC) of 1.000 with 100% sensitivity and 0% 1-specificity. WC had an AUC of 0.941 with 80% sensitivity and 13.4% 1-specificity. Additionally, WHtR showed a 0.974 AUC, 92.1% sensitivity, and 4.9% 1-specificity. The correlations between body size and shapes were assessed among the study participants using Pearson's correlation. More than other measures, WC and WHtR showed a significant correlation with BMI with P < 0.05 (r = 0.888 and 0.737, respectively). Although ABSI and BMI showed only a weak correlation (P = 0.006, r = 0.162), WHR and BMI showed a moderate correlation (P = 0.001, r = 0.477). Although HI demonstrated a negative association with BMI (P = 0.618, r = -0.030), HC exhibited a strong association (P = 0.001, r = 0.749). A significant association with higher odds ratios was found for obesity-related NCD risk factors such as hypertension, homeostatic model assessment for insulin resistance, hypercholesterolemia, altered ovulatory hormones with these (BMI, WC, WHR, WHtR, ABSI, HI) obesity-assessing criteria (P < 0.05). A significant correlation between WC and hypertriacylglycerolmia (P = 0.001, r = 0.781, odds ratio, >16) was identified. A positive correlation was observed between all MS components and ARI, indicating that ARI may serve as a potential indicator of cardiometabolic risk.
BMI, WC, WHtR, and HC are intercorrelated anthropometric measurements that can be used either alone or in combination to define obesity and detect the risk for NCDs, including diabetes mellitus, cardiovascular disease, and infertility. On the other hand, BMI, ABSI, and HI are designed to be mutually independent indices and have the advantage of combining the separate risks to generate an overall ARI. Furthermore, ARI appears to be a highly effective predictor of cardiovascular disease.
Hewage N
，Wijesekara U
，Perera R
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ResearchGate
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