Department of Neurology, University of Michigan, Ann Arbor.
School of Public Health, University of Michigan, Ann Arbor.
JAMA Neurol. 2016 Dec 1;73(12):1468-1476. doi: 10.1001/jamaneurol.2016.3745.
Past studies have shown an association between metabolic syndrome and polyneuropathy, but the precise components that drive this association remain unclear.
To determine the prevalence of polyneuropathy stratified by glycemic status in well-characterized obese and lean participants and investigate the association of specific components of metabolic syndrome with polyneuropathy.
DESIGN, SETTING, AND PARTICIPANTS: We performed a cross-sectional, observational study from November 1, 2010, to December 31, 2014, in obese participants (body mass index [calculated as weight in kilograms divided by height in meters squared] of 35 or more with no comorbid conditions or 32 or more with at least 1 comorbid condition) from a weight management program and lean controls from a research website. The prevalence of neuropathy, stratified by glycemic status, was determined, and a Mantel-Haenszel χ2 test was used to investigate for a trend. Logistic regression was used to model the primary outcome of polyneuropathy as a function of the components of metabolic syndrome after adjusting for demographic factors. Participants also completed quantitative sudomotor axon reflex testing, quantitative sensory testing, the neuropathy-specific Quality of Life in Neurological Disorders instrument, and the short-form McGill Pain Questionnaire.
Components of metabolic syndrome (as defined by the National Cholesterol Education Program Adult Treatment Panel III), including glycemic status (as defined by the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus).
Toronto consensus definition of probable polyneuropathy. Secondary outcomes included intraepidermal nerve fiber density and nerve conduction study parameters.
We enrolled 102 obese participants (mean [SD] age, 52.9 [10.2] years; 48 men and 54 women; 45 with normoglycemia [44.1%], 31 with prediabetes [30.4%], and 26 with type 2 diabetes [25.5%]) and 53 lean controls (mean [SD] age, 48.5 [9.9] years; 16 men and 37 women). The prevalence of polyneuropathy was 3.8% in lean controls (n = 2), 11.1% in the obese participants with normoglycemia (n = 5), 29% in the obese participants with prediabetes (n = 9), and 34.6% in the obese participants with diabetes (n = 9) (P < .01 for trend). Age (odds ratio, 1.09; 95% CI, 1.02-1.16), diabetes (odds ratio, 4.90; 95% CI, 1.06-22.63), and waist circumference (odds ratio, 1.24; 95% CI, 1.00-1.55) were significantly associated with neuropathy in multivariable models. Prediabetes (odds ratio, 3.82; 95% CI, 0.95-15.41) was not significantly associated with neuropathy.
The prevalence of polyneuropathy is high in obese individuals, even those with normoglycemia. Diabetes, prediabetes, and obesity are the likely metabolic drivers of this neuropathy.
clinicaltrials.gov Identifier: NCT02689661.
过去的研究表明代谢综合征与多发性神经病之间存在关联,但导致这种关联的确切因素仍不清楚。
在特征明确的肥胖和瘦参与者中,根据血糖状态确定多发性神经病的患病率,并研究代谢综合征的特定成分与多发性神经病的关系。
设计、地点和参与者:我们进行了一项横断面、观察性研究,参与者为 2010 年 11 月 1 日至 2014 年 12 月 31 日期间来自体重管理计划的肥胖参与者(体重指数[按体重公斤数除以身高米数的平方计算]为 35 或更高,无合并症或 32 或更高,至少有 1 种合并症)和来自研究网站的瘦对照者。根据血糖状态确定多发性神经病的患病率,并使用 Mantel-Haenszel χ2 检验调查趋势。使用 logistic 回归模型,在调整人口统计学因素后,将多发性神经病的主要结局作为代谢综合征成分的函数进行建模。参与者还完成了定量汗反射神经轴索测试、定量感觉测试、神经病特异性生活质量在神经疾病工具和简短形式的麦吉尔疼痛问卷。
代谢综合征的组成部分(按国家胆固醇教育计划成人治疗专家组 III 定义),包括血糖状态(按专家委员会对糖尿病的诊断和分类定义)。
多伦多共识定义的可能多发性神经病。次要结局包括表皮内神经纤维密度和神经传导研究参数。
我们纳入了 102 名肥胖参与者(平均[标准差]年龄 52.9[10.2]岁;48 名男性和 54 名女性;45 名血糖正常[44.1%]、31 名前驱糖尿病[30.4%]和 26 名 2 型糖尿病[25.5%])和 53 名瘦对照者(平均[标准差]年龄 48.5[9.9]岁;16 名男性和 37 名女性)。瘦对照组的多发性神经病患病率为 3.8%(n=2),血糖正常的肥胖参与者为 11.1%(n=5),前驱糖尿病的肥胖参与者为 29%(n=9),糖尿病的肥胖参与者为 34.6%(n=9)(趋势 P<0.01)。年龄(比值比,1.09;95%置信区间,1.02-1.16)、糖尿病(比值比,4.90;95%置信区间,1.06-22.63)和腰围(比值比,1.24;95%置信区间,1.00-1.55)在多变量模型中与神经病显著相关。前驱糖尿病(比值比,3.82;95%置信区间,0.95-15.41)与神经病无显著相关性。
肥胖个体,甚至血糖正常的个体,多发性神经病的患病率也很高。糖尿病、前驱糖尿病和肥胖是导致这种神经病的可能代谢驱动因素。
clinicaltrials.gov 标识符:NCT02689661。