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A Linear Relationship Between a Body Shape Index and Risk of Incident Type 2 Diabetes: A Secondary Analysis Based on a Retrospective Cohort Study in Japan.

ABSTRACT: Purpose:This study aimed to evaluate the association between a body shape index (ABSI) and incident type 2 diabetes and to explore the shape of their relationship in a cohort of Japanese adults. Patients and Methods:Data from 15,462 Japanese adults aged 18-79 years attending the NAGALA study (NAfld in the Gifu Area, Longitudinal Analysis) were used. Body weight, height, and waist circumference were measured. Blood samples were measured for serum lipid, glucose, and HbA1c. The risk of incident type 2 diabetes according to ABSI was estimated using multivariate Cox regression models. We examined a potential nonlinear relationship using a smoothing function analysis. Subgroup analyses were conducted according to age, gender, smoking status, alcohol intake, fatty liver, and BMI. Results:After adjusting for potential confounding factors (age, gender, smoking status, alcohol intake, fatty liver, systolic blood pressure, BMI, fasting plasma glucose, HbA1c, HDL-cholesterol, triglycerides), a linear relationship was observed between ABSI and risk of type 2 diabetes. The hazard ratio (HR) and 95% confidence intervals (95% CI) for incident type 2 diabetes with ABSI (10-2 m11/6kg-2/3) were 1.51 (1.13, 2.01) (p=0.005). When ABSI was handled as categorical variable, the HRs and 95% CIs in the quartile 2 to 4 versus the quartile 1 were 0.97 (0.67, 1.41), 1.21 (0.85, 1.72) and 1.30 (0.92, 1.83), respectively (P for trend = 0.046). Subgroup analyses showed that the association stably existed in different subgroups including gender, age, smoking status, alcohol intake, fatty liver, and BMI. Conclusion:ABSI was linearly associated with an elevated risk of incident type 2 diabetes across the full range of ABSI, independent of gender, age, smoking status, alcohol intake, fatty liver, SBP, BMI, FPG, HbA1c, HDL-cholesterol, and triglycerides.

SUBMITTER: Zhao W

PROVIDER: S-EPMC7319528 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Linear Relationship Between a Body Shape Index and Risk of Incident Type 2 Diabetes: A Secondary Analysis Based on a Retrospective Cohort Study in Japan.

Zhao Wei W Tong Jing-Jing JJ Cao Yong-Tong YT Li Jing-Hua JH

Diabetes, metabolic syndrome and obesity : targets and therapy 20200622

<h4>Purpose</h4>This study aimed to evaluate the association between a body shape index (ABSI) and incident type 2 diabetes and to explore the shape of their relationship in a cohort of Japanese adults.<h4>Patients and methods</h4>Data from 15,462 Japanese adults aged 18-79 years attending the NAGALA study (NAfld in the Gifu Area, Longitudinal Analysis) were used. Body weight, height, and waist circumference were measured. Blood samples were measured for serum lipid, glucose, and HbA1c. The risk ...[more]

PMID: 32606872

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Project description:BackgroundObesity is known to be related to the development of type 2 diabetes mellitus (T2D). The most commonly used anthropometric indicator (body mass index [BMI]) presents several limitations such as the lack of possibility to distinguish adipose tissue distribution. Thus, this study examines the suitability of a body shape index (ABSI) for prediction of body composition and sarcopenic obesity in obese or overweight T2D subjects.MethodsCross-sectional study in 199 overweight/obese T2D adults. Anthropometric (BMI, ABSI) and body composition (fat mass [FM], fat-free mass [FFM], fat mass index [FMI] and fat-free mass index, and the ratio FM/FFM as an index of sarcopenic obesity) data was collected, as well as metabolic parameters (glycated haemoglobin [HbA1c], mean blood glucose, fasting plasma glucose [FPG], high-density-lipoprotein cholesterol [HDL], low-density-lipoprotein cholesterol, total cholesterol, and triglycerides [TG] levels; the ratio TG/HDL was also calculated as a surrogate marker for insulin resistance).ResultsABSI was significantly associated with age and waist circumference. It showed a statistically significant correlation with BMI exclusively in women. Regarding body composition, in men, ABSI was associated with FM (%), while in women it was associated with both FM and FFM. Both males and females groups with high ABSI scores were significantly older (men: 59.3 ± 10.8 vs 54.6 ± 10.1, p ≤ 0.05; women: 65.1 ± 9.8 vs 58.1 ± 13.3, p ≤ 0.005) and showed lower FFM values (men: 62.3 ± 9.0 vs 66.2 ± 9.3, p ≤ 0.05; women: 48.7 ± 5.6 vs 54.5 ± 8.9, p ≤ 0.001) compared with low-ABSI groups. Multiple linear regression revealed that ABSI independently predict FMI and the FM/FFM ratio in women. Sarcopenic obesity was identified in 70 (36.5%) individuals according to the FM/FFM ratio. The AUROC of ABSI was 63.1% (95% CI 54.6-71.6%; p = 0.003) and an ABSI value of 0.083 m11/6 kg-2/3 was the optimal threshold in discriminating patients with sarcopenic obesity (sensitivity: 48%, specificity: 73%). Moreover, a significant association between ABSI and FPG was found in men.ConclusionsABSI could be useful to identify visceral and sarcopenic obesity in overweight/obese adults with T2D, adding some relevant clinical information to traditional anthropometric measures.

Project description:ObjectivesPrevious studies reported that overweight older adults had a lower mortality after cardiovascular diseases attack, indicating being thinner might not always be better. However, there is an ongoing debate about what is the optimal range of body mass index (BMI) for the aged population. We aimed to evaluate the value of BMI for the prediction of incident diabetes mellitus (DM) in the Chinese elderly population.MethodsA total number of 6,911 Chinese elderly people (4,110 men and 2,801 women, aged 71 ± 6.0 years) were included in this cohort study. BMI was measured at baseline (Jan 1, 2014, to Dec 31, 2014). All the participants were further classified into six groups: <18.5 kg/m2, 18.5 to <22.5 kg/m2, 22.5 to <25.0 kg/m2, 25.0 to <27.5 kg/m2, 27.5 to <30.0 kg/m2, and ≥30.0 kg/m2. Fasting blood glucose (FBG) and glycated hemoglobin A1c (HbA1c) were annually measured during follow-up (Jan 1, 2015-May 31, 2019). DM was confirmed if either FBG ≥ 7.0 mmol/L or HbA1c ≥ 6.5%. We used the Cox proportional hazard regression model to evaluate the association between BMI and the prediction of incident DM.ResultsComparing individuals with a BMI range of 18.5 to <22.5 kg/m2 (reference), the hazard ratio for incident DM was 2.13 (95% CI: 1.54~2.95), 2.14 (95% CI: 1.53~3.00), 3.17 (95% CI: 2.19~4.59), 3.15 (95% CI: 1.94~5.09), and 3.14 (95% CI: 1.94~5.09) for the group with a BMI range of 22.5 to <25.0 kg/m2, 25.0 to <27.5 kg/m2, 27.5 to <30.0 kg/m2, and ≥30.0 kg/m2 after adjusting for baseline age, sex, blood pressure, lipid profiles, and eGFR (P trend < 0.001), after adjusting for the abovementioned confounders. The association tended to be closer in men and young participants, compared with their counterparts.ConclusionsHigh BMI was associated with a high risk of developing DM in the Chinese aged population. Thus, it is optimal for the aged population to maintain their body weight within a reasonable range to prevent chronic diseases.

Project description:AimsThere are limited data examining whether body mass index (BMI) influences the association between cardiovascular biomarkers and incident heart failure (HF).Methods and resultsThirteen biomarkers representing key HF domains were measured: N-terminal pro-B-type natriuretic peptide (NT-proBNP), mid-regional pro-A-type natriuretic peptide (MR-proANP), cardiac troponin T (cTnT), C-reactive protein, procalcitonin, galectin-3, C-terminal pro-endothelin-1 (CT-proET-1), mid-regional pro-adrenomedullin, plasminogen activator inhibitor-1, copeptin, renin, aldosterone, and cystatin-C. Associations of biomarkers with BMI were examined using linear regression models, and with incident HF using Cox regression models. We selected biomarkers significantly associated with incident HF, and evaluated whether BMI modified these associations. Among 8202 individuals, 41% were overweight (BMI 25-30 kg/m2 ), and 16% were obese (BMI ≥30 kg/m2 ). Mean age of the cohort was 49 years (range 28-75), and 50% were women. All biomarkers except renin were associated with BMI: inverse associations were observed with NT-proBNP, MR-proANP, CT-proET-1 and aldosterone whereas positive associations were observed with the remaining biomarkers (all P ≤ 0.001). During 11.3 ± 3.1 years of follow-up, 357 HF events were recorded. Only NT-proBNP, MR-proANP and cTnT remained associated with incident HF (P < 0.001), and a significant biomarker*BMI interaction was not observed (interaction P > 0.1). Combined NT-proBNP and cTnT measurements modestly improved performance metrics of the clinical HF model in overweight (ΔC-statistic = 0.024; likelihood ratio χ2 = 38; P < 0.001) and obese (ΔC-statistic = 0.020; likelihood ratio χ2 = 32; P < 0.001) individuals.ConclusionsPlasma concentrations of several cardiovascular biomarkers are influenced by obesity. Only NT-proBNP, MR-proANP and cTnT were associated with incident HF, and BMI did not modify these associations. A combination of NT-proBNP and cTnT improves HF risk prediction in overweight and obese individuals.

Project description:BackgroundObesity is a global public health challenge. In the US, for instance, obesity prevalence remains high at more than one-third of the adult population, while over two-thirds are obese or overweight. Obesity is associated with various health problems, such as diabetes, cardiovascular diseases (CVDs), depression, some forms of cancer, sleep apnea, osteoarthritis, among others. The body mass index (BMI) is one of the best known measures of obesity. The BMI, however, has serious limitations, for instance, its inability to capture the distribution of lean mass and adipose tissue, which is a better predictor of diabetes and CVDs, and its curved ("U-shaped") relationship with mortality hazard. Other anthropometric measures and their relation to obesity have been studied, each with its advantages and limitations. In this work, we introduce a new anthropometric measure (called Surface-based Body Shape Index, SBSI) that accounts for both body shape and body size, and evaluate its performance as a predictor of all-cause mortality.Methods and findingsWe analyzed data on 11,808 subjects (ages 18-85), from the National Health and Human Nutrition Examination Survey (NHANES) 1999-2004, with 8-year mortality follow up. Based on the analysis, we introduce a new body shape index constructed from four important anthropometric determinants of body shape and body size: body surface area (BSA), vertical trunk circumference (VTC), height (H) and waist circumference (WC). The surface-based body shape index (SBSI) is defined as follows: SBSI = ((H(7/4))(WC(5/6)))/(BSA VTC) (1) SBSI has negative correlation with BMI and weight respectively, no correlation with WC, and shows a generally linear relationship with age. Results on mortality hazard prediction using both the Cox proportionality model, and Kaplan-Meier curves each show that SBSI outperforms currently popular body shape indices (e.g., BMI, WC, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), A Body Shape Index (ABSI)) in predicting all-cause mortality.ConclusionsWe combine measures of both body shape and body size to construct a novel anthropometric measure, the surface-based body shape index (SBSI). SBSI is generally linear with age, and increases with increasing mortality, when compared with other popular anthropometric indices of body shape.

Project description:BackgroundRecent studies have suggested the triglyceride-glucose index (TyG index) may serve as a suitable substitute for insulin resistance. However, evidence for the relationship between TyG index and risk of diabetes remains limited. This study sought to explore the association of baseline TyG index with risk of developing diabetes in Chinese adults.MethodsThis retrospective cohort study was conducted using data from the health screening program in China. A total of 201,298 non-diabetic individuals were included. TyG index was calculated as Ln [fasting plasma glucose (mg/dL) × fasting triglyceride level (mg/dL) / 2]. Diabetes was defined as fasting plasma glucose ≥126 mg/dL and/or self-reported diabetes. Cox proportion-hazard model was employed to evaluate the independent impact of baseline TyG index on future diabetes risk. Sensitivity and subgroup analyses were implemented to verify the reliability of results. Notably, data were downloaded from the DATADRYAD website, and used only for secondary analyses.ResultsDuring an average follow-up of 3.12 years, among 201,298 individuals aged ≥20 years, 3389 subjects developed diabetes. After adjusting for potential confounders, elevated TyG index were independently correlated with greater risk of incident diabetes (hazard ratio (HR), 3.34; 95% confidence interval (CI), 3.11-3.60). Compared with the lowest quartile (Q1), increasing TyG index (Q2, Q3, and Q4) was related to increased HR estimates of incident diabetes [HR (95% CI), 1.83 (1.49-2.26); 3.29 (2.70-4.01), and 6.26 (5.15-7.60), respectively]. Moreover, a nonlinear relationship was observed between TyG index and risk of diabetes and the slope of the curve increased accompanying the rise of TyG index. Subgroup analysis revealed the positive association was stronger among subjects with age < 40 years, body mass index ≥18.5 kg/m2 and < 24 kg/m2, or systolic blood pressure < 140 mmHg, or in females.ConclusionsElevated TyG index is independently correlated with increased risk of incident diabetes in Chinese adults, indicating it may represent a reliable predictor of diabetes in high-risk populations.

Project description:BackgroundThe relation between body weight and mortality among persons with type 2 diabetes remains unresolved, with some studies suggesting decreased mortality among overweight or obese persons as compared with normal-weight persons (an "obesity paradox").MethodsWe studied participants with incident diabetes from the Nurses' Health Study (8970 participants) and Health Professionals Follow-up Study (2457 participants) who were free of cardiovascular disease and cancer at the time of a diagnosis of diabetes. Body weight shortly before diagnosis and height were used to calculate the body-mass index (BMI, the weight in kilograms divided by the square of the height in meters). Multivariable Cox models were used to estimate the hazard ratios and 95% confidence intervals for mortality across BMI categories.ResultsThere were 3083 deaths during a mean period of 15.8 years of follow-up. A J-shaped association was observed across BMI categories (18.5 to 22.4, 22.5 to 24.9 [reference], 25.0 to 27.4, 27.5 to 29.9, 30.0 to 34.9, and ≥35.0) for all-cause mortality (hazard ratio, 1.29 [95% confidence interval {CI}, 1.05 to 1.59]; 1.00; 1.12 [95% CI, 0.98 to 1.29]; 1.09 [95% CI, 0.94 to 1.26]; 1.24 [95% CI, 1.08 to 1.42]; and 1.33 [95% CI, 1.14 to 1.55], respectively). This relationship was linear among participants who had never smoked (hazard ratios across BMI categories: 1.12, 1.00, 1.16, 1.21, 1.36, and 1.56, respectively) but was nonlinear among participants who had ever smoked (hazard ratios across BMI categories: 1.32, 1.00, 1.09, 1.04, 1.14, and 1.21) (P=0.04 for interaction). A direct linear trend was observed among participants younger than 65 years of age at the time of a diabetes diagnosis but not among those 65 years of age or older at the time of diagnosis (P<0.001 for interaction).ConclusionsWe observed a J-shaped association between BMI and mortality among all participants and among those who had ever smoked and a direct linear relationship among those who had never smoked. We found no evidence of lower mortality among patients with diabetes who were overweight or obese at diagnosis, as compared with their normal-weight counterparts, or of an obesity paradox. (Funded by the National Institutes of Health and the American Diabetes Association.).

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A Linear Relationship Between a Body Shape Index and Risk of Incident Type 2 Diabetes: A Secondary Analysis Based on a Retrospective Cohort Study in Japan.

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A Linear Relationship Between a Body Shape Index and Risk of Incident Type 2 Diabetes: A Secondary Analysis Based on a Retrospective Cohort Study in Japan.

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