Independent impact of body mass index and metabolic syndrome on the risk of type 2 diabetes in koreans

Abstract Background: Although obesity and metabolic syndrome have been associated with the risk of type 2 diabetes mellitus (T2DM), it is unclear whether obese or overweight people without metabolic syndrome are at increased risk for T2DM. Methods: Clinical and laboratory data were assessed in 8,748 subjects without diabetes (5,707 men, 3,041 women; age 20-79 years) who underwent voluntary medical check-ups at a 5-year interval. The subjects were categorized by body mass index (BMI) and metabolic syndrome status at baseline, and the incidence of diabetes over 5 years was assessed. Results: Of the 8,748 subjects, 308 (3.5%) developed T2DM over 5 years. Compared with normal weight (BMI <25.0?kg/m(2)) individuals without metabolic syndrome, the adjusted odds ratios (ORs) were 1.61 (1.13-2.29) and 4.93 (1.90-12.79) for overweight (BMI 25.0-29.9?kg/m(2)) and obese (BMI ≥30.0?kg/m(2)) individuals without metabolic syndrome, respectively, and 6.94 (5.08-9.47) and 10.61 (5.59-20.14) for overweight and obese individuals with metabolic syndrome, respectively. Using the lower BMI cutoff points for Asian populations, compared with subjects with BMI <23?kg/m(2) without metabolic syndrome, the adjusted ORs for subjects with BMI 23-27.4?kg/m(2) and BMI ≥27.5?kg/m(2) without metabolic syndrome were 2.64 (1.74-4.00) and 4.31 (2.36-7.86), respectively, and 10.11 (6.53-15.67) and 16.69 (10.40-26.77), respectively, for those with metabolic syndrome. Conclusions: Overweight/obesity and metabolic syndrome both are significant risk factors for development of T2DM in Koreans, and overweight or obesity without metabolic syndrome should not be considered a harmless condition. The lower BMI cutoffs for Asian populations can be useful in predicting risk of T2DM in Koreans.     

Type 2 diabetes mellitus in midlife estimated from the Cambridge Risk Score and body mass index

BACKGROUND: The Cambridge Risk Score (CRS) was developed to screen for type 2 diabetes mellitus risk. We assessed the ability of the CRS to predict glycosylated hemoglobin (HbA(1c)) levels and determined whether the CRS was better than body mass index (BMI) at predicting HbA(1c) levels in midlife. METHODS: We included 7452 participants without known diabetes in a biomedical survey of the 1958 British Birth Cohort at 45 years of age. Receiver operator characteristic curves were used to compare the ability of the CRS and BMI to identify individuals with elevated HbA(1c) levels using thresholds of 7.0% or more, 6.0% or more, and 5.5% or more. RESULTS: Of the total sample, 0.9% (95% confidence interval [CI], 0.7%-1.1%) had HbA(1c) levels of 7.0% or more; 3.8% (95% CI, 3.2%-4.5%), 6.0% or more; and 24.4% (95% CI, 23.1%-25.9%), 5.5% or more. The CRS detected individuals with elevated HbA(1c) levels with reasonable accuracy (area under the curve, 0.84 for HbA(1c) level >or=7.0%; 0.76 for HbA(1c) level >or=6.0%). Similar area under the curve values were obtained using BMI alone (0.84 for HbA(1c) level >or=7.0%; 0.79 for HbA(1c) level >or=6.0%). When tested using the lower HbA(1c) threshold of 5.5% or more, the CRS and BMI did not perform well (areas under the curve, 0.65 and 0.63 for CRS and BMI, respectively). Both measures indicated that approximately 20% of the cohort were at increased risk of diabetes. Owing to the low prevalence of diabetes at 45 years of age, only 2% to 3% of those considered at risk had elevated HbA(1c) levels. CONCLUSIONS: For a population in mid-adult life, the CRS identified individuals with elevated HbA(1c) levels reasonably well. However, the CRS had no advantage compared with BMI alone in identifying diabetes risk.     

Increase in body mass index during pregnancy and risk of gestational diabetes

We recorded gestational weight gain (GWG) and change in body mass index (BMI) at 28 weeks gestation in 343 vs. 339 women with and without gestational diabetes (GDM). GDM was associated with a greater increment in BMI, but not with increased GWG in kilograms.     

A comparison of body mass index and percent body fat as predictors of cardiovascular risk factors

BackgroundCardiovascular disease (CVD) is an important cause of global mortality and morbidity. Body mass index (BMI) is the measure of adiposity that is used most frequently in CVD risk algorithms.AimsWe aimed to assess the relationship between several CVD risk factors (RFs) and percent body fat (PBF), and to compare the predictive values obtained using PBF for these cardiovascular RFs with the values obtained using BMI. The CVD RFs included, hypertension (HTN), diabetes mellitus (DM) and the presence of dyslipidemia (DLP).Methods and materialsThe data were derived from the MASHAD study, a cohort study of 9704 volunteers, aged 35–65 years and living in the city of Mashhad. Based on BMI and PBF values, subjects were classified into 4 groups; group 1 (low or normal BMI and PBF, N = 1670), group 2 (low or normal BMI but high PBF, N = 992), group 3 (high BMI and low or normal PBF, N = 837), and group 4 (high BMI and PBF, N = 6245). Chi-square, covariance and logistic regression were used to analyze the data at a significance level of 0.05.ResultsThere was an increasing trend from group 1 to group 4 for the mean values of all CVD RFs and their prevalence. There were significant differences in the frequency of a low HDL-C, this was substantially higher in Group 3 (38.6% in Group 3 versus 12.2% in Group 2); the frequency of a high serum TG (24% in Group 3 versus 9.9% in Group 2) and the frequency of dyslipidemia overall (56.2% in Group 3 and 28.8% in Group 2) (P-value<0.001 for all comparisons). The frequency of hypertension (22.9% in Group 3 versus 16.2% in Group 2) and IFG (8.5% in Group 3 versus 5.0% in Group 2) were also substantially higher in Group 3 compared to Group 2 (P-value<0.001 for both comparisons). All the mean values for the RFs were higher in group 3 from group 2 except HDL-C. When Group 1 was used as a reference and calculated OR of any RF for any group 2–4 rather than group 1, OR for all RF in group 3 was higher from group 2.ConclusionThe differences in frequency, means and OR of RFs between Groups 2 and 3 showed a differential impact of a high BMI or high PBF. Compared to PBF, BMI may be a better predictor for several RFs for CVD.     

Impact of body mass index for patients undergoing pancreaticoduodenectomy

AIM: To evaluate the impact of body mass index (BMI) on short and long term results after pancreaticoduodenectomies (PD).METHODS: A consecutive series of PDs performed at the Karolinska University Hospital from 2004 till 2010 were retrieved from our prospective database. The patients were divided by BMI into overweight/obese (O; BMI ≥ 25 kg/m²) and controls (C; BMI < 25 kg/m²). Demographics, peri-operative data, morbidity, mortality, pancreatic fistula (PF) rate, length of stay (LOS), hospital costs, histology, and survival were analyzed. An additional sub analysis of survival was performed in patients with a diagnosis of pancreatic ductal adenocarcinoma (PDAC) and divided in underweight, normal-weight, overweight and obese.RESULTS: A total of 367 PDs were included (O = 141/C = 226). No differences were found between O and C regarding demographics, peri-operative data, costs, morbidity or mortality. O was associated with higher intra-operative blood loss (1392 ± 115 mL vs 1121 ± 83 mL; P = 0.01), rate of PF (20% vs 9.5%; P = 0.006) and marginally longer LOS (18 ± 0.9 d vs 15 ± 1.1 d; P = 0.05). An increasing risk for PF was observed with increasing BMI. The 1, 3 and 5 years survival rate was similar in O and C in PDAC (68.7%, 26.4% and 8.8% vs 66.1%, 30.9% and 17.9% respectively; P = 0.9). When the survival was analyzed using 4 different categories of BMI (underweight, normal, overweight and obese), a trend was seen toward a difference in survival, with a worse prognosis for the underweight and obese patients compared to normal weight and overweight patients.CONCLUSION: Overweight increases the risk for intra-operative bleeding and PF, but do not otherwise alter short or long term outcome after PD for pancreatic cancer.     

Impact of body mass on autonomic function in persons with type 2 diabetes

The aim of this study was to investigate the influence of body mass on autonomic nerve function in persons with type 2 diabetes. Towards this aim we studied two groups of diabetic persons. Group 1: n = 30 lean (mean age 57.2+/-12.5 years, body mass index (BMI) 22.5+/-1.8 kg/m2]. Group 2: n = 35 overweight and obese (age 52.3+/-10.3 years, BMI 28.8 + 3.2 kg/m2). Autonomic neuropathy (DAN) was assessed using the battery of the five classical tests. DAN was diagnosed when at least two of the five tests were abnormal. Abnormalities of the heart rate based tests were considered as indication of parasympathetic and of blood pressure changes as indication of sympathetic dysfunction. The prevalence rates of DAN were not different between group 2 and group 1 (54.2 and 53.3%, respectively, P = 0.54). The same was valid for the rates of parasympathetic and sympathetic dysfunction in the studied groups (51.4 and 53.3% (P = 0.87) in group 2 and 34.2 and 33.3% (P = 0.93) in group 1, respectively). When the values of the arithmetic expression of each single autonomic function test were compared, no significant difference could be shown between the studied groups. In addition, no significant correlation was found between BMI and indices of DAN. These data indicate that moderate increase of body mass does not affect autonomic function in persons with type 2 diabetes.     

Effects of fat mass and body fat distribution on resting metabolic rate in the elderly

The aim of the present study was to investigate the relationship between resting metabolic rate (RMR) and fat-free mass, fat mass, and body fat distribution in 164 women (age 60 to 85 years; body mass index [BMI], 18.5 to 35.6 kg/m(2)) and 98 men (age 60 to 85 years; BMI, 18.3 to 36.5 kg/m(2)). After an overnight fast, RMR was assessed by indirect calorimetry and body composition by bioelectrical impedance analysis. Waist-to-hip ratio (WHR) was used to determine fat distribution. Results from linear regression analysis showed that most of the variance in RMR could be attributed to fat-free mass in women (R(2) = 0.54) and men (R(2) = 0.44), respectively. Fat mass explained an additional 3% and 2% of the variability in RMR in women and men, respectively. In stepwise multiple regression analysis, considering body composition and fat distribution, only fat-free mass and WHR were significant predictors of RMR in both sexes. In addition to fat-free mass, in women 6% and in men 8% of the variability in RMR was attributable to WHR. Grouping subjects according to their WHR, RMR, and RMR adjusted for fat-free mass and fat mass showed a significant increase with increasing WHR in both sexes. Results indicate that RMR not only depends on fat-free mass but also is influenced by fat mass, especially by fat distribution. These findings support our hypothesis of an elevated RMR with increasing abdominal body fat as a direct consequence of its greater metabolic activity.     

The estimation of cardiovascular risk factors by body mass index and body fat percentage in Korean male adults

The aim of the study was to assess cardiovascular risk in men with high body fat percentage (BF%) and normal body mass index (BMI) and men with normal BF% and high BMI. This study was a cross-sectional study using data on 5534 Korean male adults. Body mass index, BF%, and waist circumference were measured as adiposity indices. Bioelectrical impedance analysis was used for measuring BF%. Blood pressure, fasting plasma glucose, total cholesterol, triglyceride, and high-density lipoprotein cholesterol were measured routinely. Information regarding alcohol consumption, smoking, exercise, and past/current medical history was obtained by structured questionnaires. Subjects were categorized into 4 groups by means of BMI and BF% (group 1, BMI <25 kg/m² and BF% <25%; group 2, BMI <25 kg/m² and BF% ≥25%; group 3, BMI ≥25 kg/m² and BF% <25%; group 4, BMI ≥25 kg/m² and BF% ≥25%). Cardiovascular risk factors (CVRFs) such as high blood pressure, hyperglycemia, and dyslipidemia were estimated in each group. As might be expected, the prevalences of high blood pressure, hyperglycemia, and dyslipidemia were lowest in group 1 and were highest in group 4. Multivariate analyses showed that subjects in group 2 or group 4 had a 1.8 times increased risk of clustering of 2 or more CVRFs compared with subjects in group 1 (P < .001). The adjusted odds ratio (1.15; 95% confidence interval, 0.94-1.40) of subjects in group 3 on clustering of 2 or CVRFs was not significantly increased (P = .180). High BF% was related to increase of cardiovascular risk regardless of the level of BMI in Korean men. However, cardiovascular risk of men with high BMI without high BF% was not significantly increased.     

Impact of body mass index and waist circumference on the long-term risk of diabetes mellitus, hypertension, and cardiac organ damage

Obesity is associated with a higher risk of developing diabetes mellitus (DM), hypertension (HT), and left ventricular hypertrophy (LVH). The present study assessed in the general population the impact of body weight and visceral obesity on the development of alterations in glucose metabolism and cardiac structure, as well as of elevation in blood pressure. In 1412 subjects randomly selected and representative of the general population of Monza, we assessed twice (in 1990/1991 and 2000/2001) body mass index (BMI); waist circumference; office, home, and 24-hour ambulatory (24-hour) blood pressure, fasting glycemia, and left ventricular mass (echocardiography). New-onset high-risk conditions were DM; impaired fasting glucose; office, home, and 24-hour HT; and LVH. The incidence of new-onset DM; impaired fasting glucose; office, home, and 24-hour HT; and LVH increased progressively from the quintile with the lowest to the quintile with the highest BMI values. Adjusting for confounders, the risk of developing new-onset DM; impaired fasting glucose; office, home, and 24-hour HT; and LVH increased significantly for an increase of 1 kg/m(2) of BMI and 1 cm of waist circumference (respectively, 8.4% [P<0.01], 9.5% [P<0.0001], 4.2% [P<0.0001], 3.9% [P<0.001], 2.5% [P<0.05], and 5.1% [P<0.001] for BMI and 3.2% [P<0.001], 3.5% [P<0.0001], 1.8% [P<0.0001], 1.5% [P<0.0001], 1.4% [P<0.001], and 2.6% [P<0.0001]). These data provide evidence that an increase in BMI and waist circumference is associated with a linearly increased adjusted risk of developing conditions with high cardiovascular risk, such as DM, impaired fasting glucose, in- and out-of-office HT, and LVH.     

A high lean body mass is not protecting from type 2 diabetes in the presence of a high body fat mass

AimMost studies examining the associations between body composition and type 2 diabetes have been cross-sectional with prevalent diabetes diagnosis or they have analyzed only fat or lean body mass. Hence, the combined effect of fat and lean body mass on the risk of developing type 2 diabetes remains unclear. We investigated whether baseline lean and fat body mass taken simultaneously into account are associated with incidence of type 2 diabetes over a 15-year follow-up in older adults.MethodsWe studied 704 men (n = 297) and women (n = 407) from the Helsinki Birth Cohort Study (mean age 61 years at baseline) without diabetes at baseline. Bioelectrical impedance analysis was used to derive baseline fat mass index (FMI, fat mass/height²) and lean mass index (LMI, lean mass/height²), dichotomized at sex-specific medians. Incident diabetes was defined as the composite of fasting plasma glucose (FPG) ≥ 7.0 mmol/l, haemoglobin A_1c (HbA_1C) ≥ 6.5% (48 mmol/mol) or physician-based diagnosis.ResultsAfter a median 14.8 (range 12.5–16.8) years of follow-up, 110 incident diabetes cases occurred (15.6%). Participants with high FMI and LMI at baseline had higher composite incidence of type 2 diabetes (P < 0.001), and significantly increased risk of type 2 diabetes after adjustment for potential confounding factors (sex, physical activity, education and body mass index) compared to the other participants.ConclusionContrary to a general belief greater muscle mass is not protective against type 2 diabetes. High LMI accompanied with high FMI seem to predict subsequent development of type 2 diabetes.     

Impact of fat obesity on laparoscopic total mesorectal excision: more reliable indicator than body mass index

Background  

The aim of this study was to evaluate the impact of visceral fat obesity (VFO) on early surgical and oncologic outcomes of laparoscopic total mesorectal excision (LTME) for rectal cancer.     

男性2型糖尿病患者体脂分布与心血管危险因素的关系

目的探讨男性2型糖尿病患者体脂分布特点及其与心血管危险因素的关系。方法横断面研究,用CT测量91例男性T2DM患者腹壁皮下脂肪面积（SA）及腹腔脏器脂肪面积（VA）,计算VA／SA（VSR）以及腹部总体脂量（TAF）,同时检测代谢参数,计算BMI;对体脂参数与代谢危险因素行peanson相关分析、偏相关分析及多元逐步回归分析。结果（1）相关分析结果显示,体脂分布与年龄无相关关系;无论BMI高低,其VSR均明显高于欧美肥胖人群和我国肥胖人群;内脏型肥胖的HbA1 c、TG、FFA水平高于皮下型肥胖组,FIns、FPG水平低于皮下型肥胖组,差异有统计学意义（P〈0．05）;（2）在校正年龄、糖尿病病程和BMI后,VA、SA和TAF均与FFA呈正相关,VSR与HbA1c呈正相关;（3）BMI为影响DBP、UA、Fins的独立危险因素,影响SBP、TG、HDL-C的重要因素;TAF是影响2hFFA的独立危险因素;VA为影响FFA的独立危险因素;SA是影响FPG的独立危险因素;VSR是影响HbA1 c的独立危险因素。结论男性T2DM患者体脂分布以中心性肥胖、尤其是腹部内脏脂肪增加为特点;其心血管危险因素不仅与总体脂有关,更与体脂分布（腹型肥胖）有关。     

The impact of body build on the relationship between body mass index and percent body fat.

OBJECTIVE: The objective of the study was to test the hypothesis that differences in the relationship between percent body fat (%BF) and body mass index (BMI) between populations can be explained (in part) by differences in body build. DESIGN: Cross-sectional, comparative study. SUBJECTS: 120 age, gender and BMI matched Singapore Chinese, Beijing Chinese and Dutch (Wageningen) Caucasians. MEASUREMENTS: From body weight and body height, BMI was calculated. Relative sitting height (sitting height/height) was used as a measure of relative leg length. Body fat was determined using densitometry (underwater weighing) in Beijing and Wageningen and using a three-compartment model based on densitometry and hydrometry in Singapore. Wrist and knee widths were measured as indicators for frame size and skeletal mass was calculated based on height, wrist and knee width. In addition, a slenderness index (height/sum of wrist and knee width) was calculated. RESULTS: For the same BMI, Singapore Chinese had the highest %BF followed by Beijing Chinese and the Dutch Caucasians. Singaporean Chinese had a more slender frame than Beijing Chinese and Dutch Caucasians. Predicted %BF from BMI, using a Caucasian prediction formula, was not different from measured %BF in Wageningen and in Beijing, but in Singapore the formula underpredicted %BF by 4.0 +/- 0.8% (mean +/- s.e.m.) compared to Wageningen. The difference between measured and predicted %BF (bias) was related to the level of %BF and with measures of body build, especially slenderness. Correction for differences in %BF, slenderness and relative sitting height, decreased the differences between measured and predicted values compared to the Dutch group from 1.4 +/- 0.8 (not statistically significant, NS) to -0.2 +/- 0.5 (NS) in Beijing and from 4.0 +/- 0.8 (P < 0.05) to 0.3 +/- 0.5 (NS) in Singapore (all values mean +/- s.e.m.). CONCLUSIONS: The study results confirm the hypothesis that differences in body build are at least partly responsible for a different relationship between BMI and %BF among different (ethnic) groups.     

Increases in body mass index, even within non-obese levels, raise the risk for Type 2 diabetes mellitus: a follow-up study in a Japanese population.

AIMS: Obesity, the strongest risk factor for Type 2 diabetes mellitus, is less prevalent in Japanese than in other populations. We investigated the effects of body mass index (BMI, kg/m(2)) on the incidence of diabetes mellitus in a Japanese population. METHODS: A follow-up study in 16 829 men and 8370 women who were apparently healthy at baseline (age 30-59 years, BMI 14.9-43.2 kg/m(2)). Incident diabetes mellitus was identified by 'fasting serum glucose > or = 7.00 mmol/l (126 mg/dl)' and/or 'under medical treatment for diabetes mellitus'. Hazard ratio, as an index for risk ratio, for incident diabetes mellitus according to BMI was estimated using Cox's proportional hazard models. Baseline age, smoking, drinking, exercise and education were computed as confounders. RESULTS: During mean follow-up periods of 7.4 years for men and 7.1 years for women, 869 men and 224 women had incident diabetes mellitus. Although the subjects were averagely non-obese [mean (sd) BMI 23.1 (2.6) kg/m(2) for men, 22.3 (2.7) kg/m(2) for women], hazard ratio for incident diabetes mellitus increased in parallel with increases in BMI. Multivariate-adjusted hazard ratios (95% confidence intervals) for increases in BMI of 1 kg/m(2) were 1.26 (1.24, 1.29) for men and 1.24 (1.20, 1.29) for women. CONCLUSION: BMI, even within the non-obese level, is a dose-dependent risk factor for diabetes mellitus in middle-aged Japanese. Increases in BMI of 1 kg/m(2) (= body-weight gain of 2.4-2.9 kg) may raise the risk by about 25%.     

Impact of combined systolic blood pressure and body mass index on the risk of new-onset atrial fibrillation

<正>Objective To observe the impact of combined systolic blood pressure and body mass index(BMI)on the risk of new-onset atrial fibrillation.Methods The participants who participated the health examination between July 2006 and October 2007 at Kailuan medical group and had no history of atrial fibrillation were selected as the observation cohort.The second,the third and the     

血浆瘦素与体重指数和脂肪分布的关系

目的探讨血浆瘦素水平与体重指数和脂肪分布的关系。方法对100例肥胖者(男性52例,女性48例)和71非肥胖者(男性38例,女性33例)用免疫放射法测定血浆瘦素水平,测量身高、体重,计算体重指数(BMI)。对其中19例肥胖者(男12例,女7例),15例非肥胖者(男6例,女9例)经CT扫描测量腹部内脏和皮下脂肪面积,分析瘦素与肥胖程度和脂肪分布的关系。结果血浆瘦素水平性别差异显著(P<0.001),女性是男性的2～3倍;瘦素与体重指数呈正相关(男r=0.6772,P<0.01;女r=0.7191,P<0.01)。经CT扫描测量皮下和内脏脂肪面积,瘦素水平与皮下脂肪面积的正相关(r=0.8238,P<0.01),与腹部内脏脂肪面积无明显相关性(r=0.2118,P>0.05)。结论肥胖者血浆瘦素升高,瘦素水平不仅与肥胖程度有关,还与脂肪分布有关。     

Impact of body mass index on outcomes following critical care

STUDY OBJECTIVES: To determine the impact of body mass index (BMI) on outcomes in critically ill patients. DESIGN: Retrospective analysis of a large multi-institutional ICU database. MEASUREMENTS: The influence of BMI classification (underweight, < 20 kg/m(2); normal [control subjects], 20 to 25 kg/m(2); overweight, 25 to 30 kg/m(2); obese, 30 to 40 kg/m(2); severe obesity, > 40 kg/m(2)) on hospital survival, functional status at hospital discharge, and ICU/hospital length of stay (LOS) was analyzed via multivariate analysis, adjusting for age, gender, type of hospital admission, and severity score (ie, simplified acute physiologic score [SAPS] II and mortality prediction model [MPM] at time zero). Univariate analysis also was performed according to the quartile of the severity score. All comparisons were to the normal BMI group. RESULTS: Of 63,646 patient datasets, 41,011 were complete for height, weight, and at least one of the two severity scores. We found increased mortality in underweight patients (odds ratio [OR] of death: SAPS group, 1.19; MPM group, 1.26) but not in overweight, obese, or severely obese patients. ICU and hospital LOS were increased in both the severely obese (OR of discharge: ICU, 0.81 and 0.84, respectively; hospital, 0.83 and 0.87, respectively) and underweight groups (OR of discharge: ICU, 0.96 and 0.94, respectively; hospital, 0.91 and 0.90, respectively). Only in the SAPS group did the obese group have increased ICU LOS (OR, 0.96) and hospital LOS (OR, 0.96). Functional status at discharge was impaired in underweight patients (OR of disability: ICU, 1.11; hospital, 1.19). Overweight patients had decreased discharge disability (OR of disability: SAPS, 0.93; MPM, 0.94), while the results in the obese group were discordant between the two severity score groups (SAPS, not significant; MPM, 0.91; p < 0.05 for all ORs). CONCLUSIONS: Low BMI, but not high BMI, is associated with increased mortality and worsened hospital discharge functional status. LOS is increased in severely obese patients and, to a lesser extent, in underweight patients. Patients in the overweight and obese BMI groups may have improved mortality and discharge functional status.