甲状腺功能正常人群中甲状腺激素敏感性与肥胖表型的关系

目的在一般体检人群中探索甲状腺激素敏感性与肥胖表型的关系。方法本回顾性研究纳入2017年1月至2018年12月在中国医科大学附属第一医院健康管理科进行体检的6 155名甲状腺功能正常人群。根据体重指数和代谢情况分为4种肥胖表型。通过甲状腺反馈分位数指数(TFQI)、参数化TFQI、游离三碘甲状腺原氨酸与游离甲状腺素比值(FT3/FT4)和外周脱碘酶活性总和(SPINA-GD)评估甲状腺激素敏感性。结果与代谢健康型非肥胖(MHNO)组相比, 代谢健康型肥胖(MHO)和代谢异常型肥胖(MUO)组FT3/FT4比值更高;代谢异常型非肥胖(MUNO)和MUO组TFQI更低。调整混杂因素后, FT3/FT4比值与MHO和MUO风险正相关, OR为1.18(95%CI 1.11～1.26)和1.28(95%CI 1.19～1.39);TFQI与MUNO负相关(OR为0.77, 95%CI 0.64～0.94)。参数化TFQI和SPINA-GD的结果分别与TFQI和FT3/FT4比值一致。结论甲状腺功能正常人群中, 甲状腺激素敏感性增加与不健康的肥胖表型风险升高相关。     

新疆地区居民代谢健康型肥胖的患病率及影响因素

目的探讨新疆地区居民代谢健康型肥胖(MHO)的患病率及影响因素。方法 2015年至2016年期间,采用分层多阶段随机抽样,选取新疆地区35~80岁调查对象4627人,有效数据3456(74.69%)人。肥胖和代谢状态分类基于体质指数(BMI)和代谢异常组分的数量。结果调查人群中MHO患病率为16.09%,肥胖人群MHO患病率为59.15%。女性中MHO比例随着年龄增加而下降(P0.01),男性中未见该趋势(P0.05)。农村居民MHO比例显著高于城市(64.75%vs.43.27%,P0.01)。汉族(OR=0.33,95%CI:0.23~0.45)、腰围(WC)增加(每5cm)(OR=0.80,95%CI:0.73~0.88)与MHO患病风险下降相关,中度职业体力劳动(OR=2.92,95%CI:1.75~4.88)与MHO患病风险增加相关。调整内脏脂肪指数(VFI)模型中,VFI升高(OR=0.80,95%CI:0.73~0.88)与MHO患病风险下降相关。结论新疆地区35~80岁居民MHO患病率较高。年龄、民族、中度职业劳动强度、WC和VFI与肥胖人群的代谢状态有关。     

湖南地区中青年人群正常体质代谢异常和代谢正常肥胖表型的流行病学及生活方式危险因素研究

目的确定中青年人群中各种体质量代谢表型的患病率,尤其是正常体质代谢异常(MONW)和代谢正常肥胖(MHO)这两种特殊表型,并调查各表型相关的人口统计学和行为学因素。方法以中南大学湘雅三医院健康管理中心44 551例中青年(30～59岁)体检人群为研究对象,根据体质量和代谢状态将人群分为四种表型:正常体质代谢正常(MHNW)、正常体质代谢异常(MONW)、代谢正常肥胖(MHO)和代谢异常肥胖(MAO)。收集一般资料,进行体格检查及生化指标检测;采用Logistic回归分析评估生活方式因素与正常体质代谢异常和代谢正常肥胖表型的相关性。结果正常体质代谢正常、正常体质代谢异常、代谢正常肥胖、代谢异常肥胖表型在中青年人群中的患病率分别为58.0%、6.4%(占正常体质人群的10.0%)、18.0%和17.6%。多元Logistic回归分析结果显示,在校正了年龄、文化程度后,男性正常体质代谢异常表型与吸烟(OR=1.12,95%CI:1.02～1.24)、饮酒(OR=1.22,95%CI:1.11～1.35)呈正相关,与健康的饮食习惯(OR=0.88,95%CI:0.80～0.98)呈负相关。而女性正常体质代谢异常表型与中高度体育锻炼(OR=0.83,95%CI:0.73～0.93)和健康饮食习惯(OR=0.80,95%CI:0.71～0.90)呈负相关。结论在中青年人群中,正常体质代谢异常表型患病率为6.4%,约占正常体质人群的10.0%,代谢正常肥胖表型患病率为18.0%,约占肥胖人群的一半。代谢表型在不同性别的中青年人群之间具有不同的临床特征。为了预防体质量正常人群出现代谢异常,应多锻炼身体,健康饮食,尤其是男性还应该戒烟、戒酒。     

北京某医院体检人群代谢综合征与高尿酸血症的相关性调查

目的探讨体检人群代谢综合征(MS)各组分与高尿酸血症的相关性。方法收集2015年在北京电力医院行健康体检的年龄大于18岁的人群资料,并采用多因素Logistic回归分析MS各组分与高尿酸血症的相关性。结果本研究共入选12 335例调查对象,其中男性7 681例,女性4 654例,平均年龄(45.5±14.2)岁。高尿酸血症的患病率为18.30%(2 257/12 335),MS人群高尿酸血症的患病率高于非MS人群(P<0.001)。MS各组分中,超重(OR=2.310,95%CI:2.054~2.598)、肥胖(OR=3.920,95%CI:3.413~4.502)、血压升高(OR=1.660,95%CI:1.505~1.831)、空腹血糖升高(OR=1.445,95%CI:1.292~1.617)、三酰甘油升高(OR=2.935,95%CI:2.660~3.237)和高密度脂蛋白胆固醇降低(OR=2.009,95%CI:1.815~2.224)与高尿酸血症的患病有显著相关性(均为P<0.05)。结论体检人群中MS各组分与高尿酸血症的发生具有一定关联。     

代谢正常肥胖亚群研究的重要性

肥胖与代谢异常密切相关，更是动脉粥样硬化、2型糖尿病、心血管疾病、肿瘤、非酒精性脂肪肝等多种疾病的易感因素。然而，肥胖人群并不是一个单一的群体。20世纪80年代至今，对于肥胖亚群的研究日益增多，出现了代谢正常肥胖（metabolically healthy but obese，MHO）的概念。MHO亚群以肥胖但胰岛素敏感为特征，似乎存在某些代谢保护机制，无论在体脂分布、代谢及炎症谱还是减重疗效上均与代谢异常的“高危”肥胖（at-riskobese）明显不同，因此在科学研究和临床实践中应区别对待。     

贵阳城区40岁及以上代谢健康型肥胖人群代谢异常及心血管疾病发生风险的3年随访研究

目的通过随访代谢健康型肥胖(MHO)表型人群发生代谢综合征(MS)及其组分和心血管疾病的发生率, 探索MHO是否为真正稳定的健康状态。方法 2011年采用整群抽样的方法选取贵阳城区40～79岁居民10 140人, 通过检测空腹血糖(FPG)、血脂、血压评定代谢状态, 测量身高、体重, 计算体重指数判定肥胖程度, 其中1 299人代谢健康, 根据体重指数分为3组, 即代谢健康型非肥胖组(MHNW)、代谢健康型超重组(MHOW)、MHO组, 于2014年对基线代谢健康人群进行随访, 最终共有966名基线及随访资料完整者被纳入本研究分析对象中, 随访3年后比较3组人群MS及其组分、心脑血管事件发病率的关系。结果 (1)平均随访3年后, MHO人群中有47.77%转变为代谢不健康状态。3组间MS组分发生率差异无统计学意义(P>0.05), 但MS发生率有显著性差异(P<0.05);(2)随访3年后3组人群心脑血管事件发病率无显著性差异(P>0.05), 采用logistic回归分析3组人群心脑血管事件的危险因素, 以MHNW组为对照组, 经校正年龄、性别、FPG、血脂、血压后...     

老年人脉压和脉压指数与代谢综合征的相关性和剂量反应关系

目的探讨老年人脉压和脉压指数与代谢综合征及其组分的相关性和剂量反应关系。方法横断面研究,选择2019年武进区65岁及以上健康体检老年人114212例,代谢综合征患者40388(35.4%)。调查内容包括问卷调查、体格检查和实验室检查。采用Logistic回归和限制性立方样条分析脉压和脉压指数与代谢综合征患病的相关性和剂量反应关系。结果随脉压水平和脉压指数的增加,代谢综合征及其各组分的患病率逐渐增加(P<0.01)。调整混杂因素后,代谢综合征的OR值随脉压和脉压指数的增加逐渐升高,与最低四分位比较,脉压在第二、三和四组相关(OR=1.52,95%CI:1.47~1.58;OR=1.89,95%CI:1.82~1.96;OR=2.15,95%CI:2.07~2.23);脉压指数与第二、三和四组相关(OR=1.22,95%CI:1.18~1.26;OR=1.36,95%CI:1.31~1.41;OR=1.47,95%CI:1.42~1.53)。限制性立方样条分析结果显示,脉压和脉压指数与代谢综合征呈非线性剂量反应关系(χ2值分别为309.23和57.14,均P<0.01)。结论脉压和脉压指数与老年人代谢综合征及其组分相关,且呈现非线性剂量反应关系。     

成人肥胖测量指标与高血压患病关系

目的探讨成人肥胖测量指标与高血压患病的关系。方法利用江苏省2010年成人慢性病及其危险因素监测数据,描述新发现高血压患者在不同人群中的分布差异;运用双变量相关和非条件Logistic回归方法,分析体质量指数(BMI)、腰围、腰身比和体脂百分比等肥胖测量指标与血压及高血压患病的关系。结果江苏省成人新发现高血压患病率为35.3%,男性高于女性,患病率随年龄增长呈上升趋势(P0.05)。双变量相关分析结果表明,BMI、腰围、腰身比和体脂百分比等肥胖测量指标与收缩压和舒张压均成正相关。多因素非条件Logistic回归分析结果显示,肥胖(χ2=129.67,P0.05)、中心型肥胖(χ2=157.05,P0.05)、BMI(χ2=176.21,P0.05)、腰围(χ2=187.73,P0.05)、腰身比(χ2=221.49,P0.05)和体脂百分比(χ2=155.22,P0.05)均与高血压患病显著相关;BMI、腰围、腰身比和体脂百分比每增加1个标准差(SD),高血压患病风险分别增加59%(OR=1.59,95%CI:1.50~1.70)、60%(OR=1.61,95%CI:1.50~1.71)、68%(OR=1.68,95%CI:1.57~1.79)和149%(OR=2.49,95%CI:2.21~2.80)。BMI、腰围、腰身比和体脂百分比等肥胖测量指标对高血压患病风险的影响依次升高。结论 BMI、腰围、腰身比和体脂百分比与高血压患病相关,高血压患病风险随肥胖程度的增加而升高。     

福建沿海地区超重及肥胖人群血压、血脂现状分析

目的:调查福建沿海地区人群超重和肥胖的现状及其与血压、血脂的相关性。方法:通过横断面调查方法,纳入福建省沿海地区30岁以上人群3343例,进行身高、体质量、血压、腰围、血糖、血脂等指标检测,采用统计学方法分析BMI与血压、血脂的相关性。结果:调查地区超重及肥胖检出率为34.6%和10.0%,男性超重率显著高于女性(40.4%比30.7%,P0.05);超重和肥胖人群比例在70岁以前均随年龄增加而逐渐显著增高,70岁以后有下降趋势。与年龄匹配的正常体重人群比较,青年(40岁)超重和肥胖人群血压、腰围显著升高(P均0.01);中老年(40岁)超重和肥胖人群血压、腰围、TC、LDL-C水平显著升高,而HDL-C水平显著降低(P0.05或0.01)。偏相关分析显示BMI与腰围、收缩压、舒张压、TC、LDL-C和HbA1c水平呈显著正相关(r=0.701,0.218,0.238,0.068,0.120,0.135,P均0.01),与TG和HDL-C水平呈显著负相关(r均=-0.069,P均0.01)。多元线性回归分析显示BMI与腰围、性别、年龄、DBP、HDL-C、FBG显著相关。控制年龄、性别、血糖等混杂因素后,二元Logistic回归分析显示:超重(OR=2.283,95%CI 1.915~2.721)和肥胖(OR=4.419,95%CI 3.329~5.865)是高血压、血脂异常的危险因素[超重(OR=1.356,95%CI 1.160~1.584),肥胖(OR=1.691,95%CI 1.319~2.167)],P均0.01。结论:福建沿海地区人群超重/肥胖率较高,超重、肥胖人群中高血压、血脂异常、糖尿病、心血管危险因素聚集比例显著增高,控制体重对高血压、血脂异常及糖尿病等慢性病的防治具有重要意义。     

急性心肌梗死患者非手术相关性急性肾损伤

目的:探讨急性心肌梗死(AMI)非手术相关性急性肾损伤(AKI)的危险因素。方法:回顾性分析2008-12-01~2012-12-31在苏州大学附属第三医院诊断AMI后未行手术治疗发生AKI的患者及对照组人群资料共计656例,根据KDIGO指南推荐的标准定义AKI。结果:AMI后非手术(包括冠脉造影术、冠脉搭桥术)治疗后发生的AKI共计228例(34.8%),其病死率显著高于对照组(P0.001)。多因素Logistic回归分析结果 :基线e GFR下降(OR=2.049,95%CI 1.246~3.370)、空腹血糖(FBG)升高(OR=1.070,95%CI 1.018~1.124)、利尿剂(OR=1.867,95%CI 1.220~2.856)和心肌梗死KillipⅣ级(OR=1.362,95%CI 1.059~3.170)是AKI患病的独立危险因素(P0.05),入院时舒张压(DBP)增高(OR=0.986,95%CI 0.974~0.998)是AKI患病的保护性因素(P0.05)。结论:住院AMI非手术治疗患者发生AKI的患病率、病死率较高。基础肾功能减退、空腹血糖增加、心功能下降及利尿剂为该人群患病的独立危险因素,基础舒张压水平升高为保护性因素。     

Association of obesity phenotypes with electrocardiographic left ventricular hypertrophy in the general population

Objective

Increasing evidence doubts the benign nature of metabolically healthy obesity (MHO). An investigation of the association of MHO and other obesity phenotypes with electrocardiographic left ventricular hypertrophy (ECG-LVH), a risk factor for cardiovascular disease (CVD), can give insight into the pathophysiological basis for increased risk of CVD linked to these phenotypes.

Obesity is more closely related with hepatic steatosis and fibrosis measured by transient elastography than metabolic health status

ObjectiveThe pathogenesis of non-alcoholic fatty liver disease (NAFLD) involves multiple concomitant events induced by obesity and metabolic health condition. This study aimed to assess the risk of NAFLD according to metabolic health and obesity status using transient elastography (TE).Materials and MethodsA total of 2198 asymptomatic adults without chronic liver disease and who underwent a medical health check-up were recruited. Subjects were categorized into four groups according to metabolic health and obesity statuses: metabolically healthy non-obese (MHNO); metabolically unhealthy non-obese (MUNO); metabolically healthy obese (MHO); and metabolically unhealthy obese (MUO). Hepatic steatosis was defined as controlled attenuation parameter (CAP) ≥ 238 dB/m, and significant liver fibrosis was defined as liver stiffness measurement (LSM) > 7.0 kPa, as defined by TE.ResultsCompared with MHNO group, the odds ratios (ORs) [95% confidence interval (CI)] for hepatic steatosis were 2.94 [2.32–3.71], 4.62 [3.52–6.07], and 12.02 [9.08–15.92] in the MUNO, MHO, and MUO groups, respectively (P < 0.001) in crude model. Regarding liver fibrosis, there was no significant difference in the ORs in MUNO group (ORs: 0.95 [95% CI, 0.33–2.78], P value = 0.929), whereas there was a significant increase in the ORs in MHO group compared with MHNO group (ORs: 4.32 [95% CI, 1.73–10.76], P = 0.002) in the fully adjusted model.ConclusionOur results show that MHO was associated with both liver steatosis and fibrosis assessed by transient elastography. Our results suggest that a healthy metabolic profile does not protect obese adults from hepatic steatosis or fibrosis, indicating that obesity itself might contribute to liver fibrosis.     

Incidence of type 2 diabetes,hypertension, and dyslipidemia in metabolically healthy obese and non-obese

Background and aims

Metabolically healthy obese (MHO) individuals are devoid of many metabolic abnormalities, but how this condition is maintained over time remains debated. We assessed the prevalence of MHO over time and the incidence of hypertension (HTN), dyslipidemia, and type 2 diabetes mellitus (T2DM) in MHO as compared with metabolically healthy non obese (MHNO).

Association of metabolic health phenotypes,obesity, and hepatocellular carcinoma risk

BackgroundThe obesity and hepatocellular carcinoma (HCC) risk association may differ by individuals’ metabolic health status.AimTo investigate the association between obesity categories and HCC risk among individuals with different metabolic health phenotypes.MethodsA case-control study among 518 HCC cases and 1,036 frequency-matched controls was conducted. Body mass index (BMI) was assessed before diagnosis. Pre-diagnosis data on dyslipidemia, hypertension, and diabetes were used to categorize participants as metabolically healthy or metabolically unhealthy. Participants were further categorized into metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and metabolically unhealthy obese (MHO). We used logistic regression to calculate multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs).ResultsBeing overweight (OR=1.68, 95%CI=1.21–2.34) or obese (OR=1.49, 95%CI=1.11–1.89) was associated with higher HCC risk. Among metabolically healthy participants, no association was found between being overweight or obese and HCC risk. However, among the metabolically unhealthy participants, being overweight (OR=1.89, 95%CI=1.31–2.72) or obese (OR=1.50, 95%CI=1.07–2.09) was associated with higher HCC risk. Compared to the MHNW phenotype, no association was found between the MHOW and MHO phenotypes and HCC risk, but the MUNW (OR=1.94, 95%CI=1.09–3.43), MUOW (OR=3.78, 95%CI=2.15–6.65), and MUO (OR=2.93, 95%CI=1.70–5.05) phenotypes were associated with higher HCC risk.ConclusionThe association between BMI and HCC appears to be restricted to individuals with underlying metabolic abnormalities.     

Metabolic abnormalities,but not obesity per se,associated with chronic kidney disease in a Taiwanese population

Background and aimsIt is inconclusive whether obesity itself or metabolic abnormalities are linked to chronic kidney disease (CKD). The aim of this study was to examine the association between different subtypes of obesity and metabolic abnormalities with CKD in adults.Methods and resultsThis study enrolled 14,983 eligible subjects stratified into metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and metabolically unhealthy obesity (MUO) according to body mass index and metabolic syndrome status (ATP-III criteria). The metabolic healthy phenotype was defined as the absence of both metabolic syndrome and any known diabetes, coronary artery disease, stroke, hypertension or dyslipidemia. Early and advanced CKD were defined as eGFR<60, proteinuria, or structural abnormalities as detected by renal sonography. The prevalence of CKD was 2.5, 3.0, 4.0, 10.6, 9.5, and 10.5% in subjects with MHNW, MHOW, MHO, MUNW, MUOW, and MUO, respectively. In the multivariate analysis, the MUNW (OR:2.22, P < 0.001), MUOW (OR:2.22, P < 0.001), and MUO (OR:2.45, P < 0.001) groups were associated with early CKD. For advanced CKD, the OR was 2.56 (P < 0.001), 2.31 (P < 0.001), and 3.49 (P < 0.001) in the MUNW, MUOW, and MUO groups, respectively. The associated risks of early and advanced CKD were not significant in the MHOW and MHO group. MUOW and MUO were associated with higher risk of CKD compared with MHOW and MHO after adjusting other variables.ConclusionsMetabolic abnormalities, but neither overweight nor obesity, were associated with a higher risk of CKD in adults.     

Metabolically healthy obese subjects are at risk of fatty liver but not of pre-clinical atherosclerosis

Backgrounds and aimsWhether obesity increases risk of cardiovascular disease (CVD) and fatty liver because of the co-existence of other risk factors is uncertain. We investigated odds ratios (ORs) for: a) a measure of pre-clinical atherosclerosis and b) fatty liver, in metabolically healthy obese (MHO) subjects, metabolically abnormal obese (MAO) subjects and metabolically abnormal non obese subjects (MANO), using a metabolically healthy non obese (MHNO) group as the reference.Methods and results14,384 South Koreans from an occupational cohort underwent cardiac computed tomography (CT) estimation of CAC score, liver ultrasound determination of fatty liver, and measurement of cardiovascular risk factors. Pre-clinical atherosclerosis was defined by a CAC score >0. We used logistic regression to determine ORs for CAC >0, and fatty liver in MHO, MAO and MANO subjects (reference group MHNO). There was no increase in OR for CAC score >0 (OR = 0.93, [95% CIs 0.67,1.31], p = 0.68), in the MHO group, whereas there was an increase in the ORs for CAC score >0 in the MAO, and MANO groups (OR = 1.64 [95% CI 1.36,1.98], p < 0.001) and (OR = 1.38 [95% CI 1.17,1.64], p < 0.001), respectively. In contrast, for fatty liver, there was an increase in OR in each group (OR = 3.63 [95% CI 3.06, 4.31] p < 0.001); (OR = 5.89 [5.18,6.70] p < 0.001); and (OR = 1.83 [95% CI 1.69,2.08]) in the MHO, MAO group and MANO groups respectively.ConclusionMHO subjects are at risk of fatty liver but attenuated risk of pre-clinical atherosclerosis. Both MAO and MANO subjects are at risk of fatty liver and pre-clinical atherosclerosis.     

Epidemiology and pathophysiology of the association between NAFLD and metabolically healthy or metabolically unhealthy obesity

The prevalence of nonalcoholic fatty liver disease (NAFLD) is continuing to rise in many countries, paralleling the epidemic of obesity worldwide. In the last years, the concept of metabolically healthy obesity [MHO, generally defined as obesity without metabolic syndrome (MetS)] has raised considerable scientific interest. MHO is a complex phenotype with risks intermediate between metabolically healthy individuals with normal-weight (NWMH) and patients who are obese and metabolically unhealthy (MUO, i.e. obesity with MetS). In this review we aimed to examine the association and pathophysiological link of NAFLD with MHO and MUO. Compared to NWMH individuals, patients with obesity, regardless of the presence of MetS features, are at higher risk of all-cause mortality and cardiovascular events. Moreover, MHO patients have a greater risk of NAFLD development and progression compared to NWMH individuals. However, this risk is generally lower than that of MUO patients, suggesting a stronger adverse effect of coexisting MetS disorders than obesity per se on the severity of NAFLD. Nevertheless, since MHO is a dynamic state (with a significant proportion of MHO subjects progressing to MUO over time) and NAFLD itself may predict the transition from MHO to MUO, we believe that any effort should be made to identify NAFLD in all obese individuals, although they appear to be “metabolically healthy”. Future research is needed to better understand the role of NAFLD and other pathogenic factors potentially involved in the transition from MHO to MUO and to elucidate how this transition may affect the presence and severity of NAFLD.     

Association of childhood obesity phenotypes with early adulthood Carotid Intima-Media Thickness (CIMT): Tehran lipid and glucose study

Background and aimsOver the past few years, obesity and metabolic syndrome prevalence among children and adolescence have an increasing trend. This study aims to investigate the association of obesity phenotypes during childhood and adolescence with early adulthood carotid intima-media thickness (CIMT).Methods and resultsParticipants were divided into four obesity phenotypes: Metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Participants were followed for 18 years. Multivariate-adjusted Risk Ratios (RRs) were calculated for high CIMT (≥95% percentile) incidence.In this cohort study 1220 children and adolescents with the average age of 10.9 ± 4.0 years were included. CIMT values had a significantly increasing trend from MHNW to MUO group (p for trend<0.001). Individuals with normal weight status, even with an unhealthy metabolic profile did not have higher risk of high CIMT. Similarly, Children with obesity but healthy metabolic status was not at higher risk. On the other hand, MUO phenotype during childhood was associated with increased risk of high CIMT in early adulthood (RR = 2.13, 95%CI (1.02–4.48)). This association became insignificant for all obesity phenotypes after adjusting for adulthood BMI.ConclusionAdulthood CIMT has an increasing trend based on childhood and adolescence obesity phenotypes from MHNW to MUO. Children with MUO phenotype was the only ones that had an increased risk of high CIMT incidence in early adulthood.     

Evaluating the risk of hypertension according to the metabolic health status stratified by degree of obesity

Despite the accumulated evidence showing the significant association between hypertension and obesity, it remains unclear how metabolic healthy status of obesity have an impact on the development of hypertension. Thus, this study was to investigate the risk of hypertension according to the metabolic healthy status stratified by the degree of obesity. A cohort of 25,442 Korean men without hypertension at baseline was followed-up from 2005 to 2010. They were divided into the following 6 phenotypes according to their baseline metabolic health and obesity status: metabolically healthy normal weight (MH-NW), metabolically healthy overweight (MH-OW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MU-NW), metabolically unhealthy overweight (MU-OW), and metabolically unhealthy obese (MUO). Cox proportional hazard model was used to evaluate the risk for hypertension according to the metabolically healthy status stratified by degree of obesity. During 91,256.4 person-years of follow-up, 4633 participants (18.2%) developed hypertension. The adjusted hazard ratios (95% confidence intervals) for hypertension in MH-OW, MHO, MU-NW, MU-OW, and MUO phenotypes compared with MH-NW phenotype were 1.13 (1.04–1.23), 1.43 (1.15–1.69), 1.17 (1.02–1.34), 1.49 (1.27–1.72), and 1.54 (1.36–1.88), respectively. The interaction between metabolically healthy status and degree of obesity was not significant (P for interaction = .29). Compared with MH-NW, both the obese phenotype and metabolically unhealthy phenotype independently had an increased risk for hypertension. These results imply that both metabolic health status and obesity status play important roles independently in the risk of hypertension in Korean men.     

Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians

Background

We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians.

Method

Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m², based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram.

Results

Metabolically obese nonobese was defined as nonobese subjects (BMI < 25 kg/m²) with MS, MOO as obesity (BMI ≥ 25 kg/m²) with MS, MHO as obese subjects (BMI ≥ 25 kg/m²) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706–2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852–3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250–2.130, p = .564) groups compared to MHNO, perhaps due to small numbers.

Conclusion

Metabolic obesity may have different clinical implications than phenotypic obesity.