中国医科大学学报  2019, Vol. 48 Issue (8): 738-742

文章信息

张强, 郑海明, 郑锐
ZHANG Qiang, ZHENG Haiming, ZHENG Rui
慢性阻塞性肺疾病急性加重患者体质量指数与病情的相关分析
Correlation Analysis between Body Mass Index and Disease Status in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease
中国医科大学学报, 2019, 48(8): 738-742
Journal of China Medical University, 2019, 48(8): 738-742

文章历史

收稿日期:2019-02-15
网络出版时间:2019-07-15 15:58
慢性阻塞性肺疾病急性加重患者体质量指数与病情的相关分析
张强 , 郑海明 , 郑锐     
中国医科大学附属盛京医院第二呼吸内科, 沈阳 110022
摘要目的 根据慢性阻塞性肺疾病急性加重(AECOPD)患者体质量指数(BMI)对患者进行分层,探讨BMI与患者急性发作期病情的相关性。方法 回顾分析我院596例AECOPD患者临床资料,根据BMI指数将患者分成低体质量、正常体质量、超重、肥胖4组,分析患者各项临床指标(年龄、性别、吸烟、生化指标、肺功能、有创呼吸机使用率、病死率、住院时间、住院费用等)与BMI的关系。结果 BMI与患者年龄呈负相关(P=0.04);BMI越低,吸烟患者比例越高,吸烟量越大。logistic回归分析表明,BMI低是患者C反应蛋白水平、FEV1/FVC、住院时间及住院费用的影响因素(均P < 0.05)。结论 AECOPD患者中超重和肥胖比例低于正常人群。BMI低的AECOPD患者病情较重。
Correlation Analysis between Body Mass Index and Disease Status in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease
Department of the Second Respiratory, Shengjing Hospital, China Medical University, Shenyang 110022, China
Abstract: Objective Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) were stratified according to body mass index (BMI), and the correlation between BMI and the patients condition was investigated. Methods A total of 596 patients were retrospectively analyzed. BMI was calculated, and the patients were divided into four groups according to BMI as follows:underweight, normal weight, overweight, and obesity. The relationship of the patients BMI with age, sex, smoking condition, laboratory parameters, lung function, invasive ventilator use rate, mortality, hospitalization time, and hospitalization expenses of the four groups were analyzed. Results The underweight, normal weight, overweight, and obesity groups accounted for 19.6%, 47.1%, 23.2%, and 9.9% of the patients, respectively. BMI negatively correlated with patient age (P=0.05). The lower the BMI, the higher the proportion of smokers and the greater the amount of smoking in the patients. In a logistic analysis, we found that lower BMI is an important influencing factor of C reactive protein level, forced expiratory volume in 1 s to forced vital capacity, hospitalization time, and hospitalization expense (P < 0.05). Conclusion The proportions of subjects who are overweight and obese among the AECOPD patients are lower than those among the healthy population. The patients with lower BMI have significantly more severe COPD.

慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)是常见的呼吸系统疾病,以气道和肺泡异常引起的持续呼吸道症状及气流受限为主要特征。COPD全球患病率达10.7%[1-2]。中国40岁以上人群患病率达13.7%[3]。随着生活条件改善,肥胖也逐渐成为了全球性人类健康威胁之一。预计到2035年,全球肥胖人口将达到30亿[4]。荟萃分析结果证实,肥胖与全因病死率有关[5]。在呼吸系统疾病方面,肥胖对于哮喘及睡眠呼吸暂停等疾病的危害目前已经达成了共识[6-7],但体质量指数(body mass index,BMI)对于COPD患者急性发作期病情的影响尚有争议[8-10]。本研究根据BMI对慢性阻塞性肺疾病急性加重(acute exacerbations of chronic obstructive pulmonary disease,AECOPD)患者进行分组,探讨BMI对AECOPD患者病情的影响。

1 材料与方法 1.1 临床资料

收集2018年1月至2018年12月我院呼吸与重症监护病房住院治疗的AECOPD患者的临床资料,包括年龄、性别、身高、体质量、吸烟,生化指标[白细胞(white blood cell,WBC)、C反应蛋白(C reaction protein,CRP)],肺功能、呼吸机辅助通气率,病死率、住院时间、住院费用等。患者COPD诊断标准按照GOLD标准[1]执行。COPD急性发作定义:呼吸道症状急性恶化,导致患者需要新增治疗措施。纳入标准:(1)GOLDⅠ~Ⅳ期;(2)年龄≥40岁;(3)中~重度急性发作,需要抗生素、支气管扩张剂、激素,甚至急救治疗;(4)家属及患者同意必要时使用呼吸机辅助通气。排除标准:(1)患有肺癌、结核等导致呼吸受限的其他慢性呼吸系统疾病。(2)年龄 < 40岁。(3)家属及患者依从性差或治疗中途退院。

1.2 分组

计算患者BMI [BMI(kg/m2)=体质量/身高2]。按照中国肥胖问题工作组织2002年提出的中国成年人体质量评价体系[11]分为4组:低体质量组,BMI < 18.5 kg/m2;正常体质量组,18.5 kg/m2≤BMI < 24 kg/m2;超重组,24 kg/m2≤BMI < 28 kg/m2;肥胖组,BMI > 28 kg/m2

1.3 统计学分析

所有分析采用SPSS 23.0软件完成。计量资料若符合正态分布,以x±s表示,组间比较采用单因素方差分析;若不符合正态分布,以中位数(四分位间距)表示,组间比较采用Kruskal-Wallis H检验;计数资料以频率表示,组间比较采用χ2检验。校正年龄、性别、吸烟和吸烟量进入方程。BMI对病情(计量资料)影响采用多元线性回归分析;对于病情(计数资料)影响采用logistic回归分析,y发生为1,未发生为0。P < 0.05为差异有统计学意义。

2 结果 2.1 各组患者基线特征比较

共纳入596例患者,其中低体质量组117例(19.6%),正常体质量组281例(47.1%),超重组139例(23.3%),肥胖组59例(9.9%)。由于部分AECOPD患者病情较重,不能耐受肺功能检查,所以只有一部分患者进行了肺功能检查,在低体质量、正常体质量、超重和肥胖4组中分别占44.4%、60.9%、66.9%、64.4%。结果显示,4组患者年龄、吸烟情况、WBC、CRP、FEV1%、FEV1/FVC、住院费用、病死率比较存在统计学差异(均P < 0.05)。见表 1

表 1 各组患者临床指标比较 Tab.1 Comparison of clinical data among the four groups
Item Underweight group Normal weight group Overweight group Obesity group P
Age(year) 74.37±10.58 72.19±10.26 70.21±9.65 69.75±11.42 0.004
Female [n(%)] 51(43.6) 102(36.3) 61(43.9) 28(47.5) 0.225
Smoker [n(%)] 79(67.5) 159(56.6) 72(51.8) 25(42.4) 0.008
Smoking-index(package per year) 25(0,47.5) 9(0,34.8) 5(0,36.0) 0(0,30.0) 0.002
WBC(×106 7.82±3.45 7.55±3.21 7.44±2.68 7.68±2.75 0.784
CRP(mg/L) 17.70(3.65,73.85) 10.70(3.13,32.65) 7.66(3.38,22.70) 8.64(3.12,48.85) 0.037
FEV1% 50.26±10.94 52.44±12.49 54.18±12.00 59.91±9.66 0.008
FEV1/FVC 41.69±13.74 49.03±17.87 52.14±17.97 50.86±13.49 0.005
Hospital stay(d) 14.02±8.53 12.27±5.59 12.14±5.82 12.37±7.25 0.070
Hospital costs(CNY) 15 526(11 289,23 689) 13 650(9 612,19 377) 13 670(9 567,19 687) 15 543(10 778,210 578) 0.002
Invasive ventilator usage [n(%)] 10(8.5) 11(3.9) 4(2.9) 3(5.1) 0.190
Mortality [n(%)] 7(6.0) 3(1.1) 2(1.4) 0(0.0) 0.016

2.2 BMI对AECOPD病情的影响

为了研究BMI对各指标的影响,将患者年龄、性别、吸烟、吸烟量混杂因素调整后对WBC、CRP、FEV1%、FEV1/FVC、住院时间及住院费用进行了线性回归分析,对呼吸机辅助通气率及病死率进行了logistic回归分析,结果显示,去除混杂因素后,低体质量组CRP高、肺功能差、住院时间长、住院费用高、病死率高(均P < 0.05)。而肥胖组表现为肺功能好,但住院费用却高。见表 2表 3

表 2 BMI与患者其他指标的线性回归分析 Tab.2 Linear regression analysis of body mass index grades and influencing factors
Item n β SE 95% CI for β P
WBC 596
    Normal weight group 281 ref.
    Underweight group 117 0.156 0.344 (-0.520,0.831) 0.651
    Overweight group 139 -0.028 0.321 (-0.658,0.602) 0.930
    Obesity group 59 0.273 0.443 (-0.598,1.144) 0.538
CRP 596
    Normal weight group 281 ref.
    Underweight group 117 0.169 0.069 (0.033,0.305) 0.015
    Overweight group 139 -0.047 0.065 (-0.174,0.081) 0.474
    Obesity group 59 0.060 0.088 (-0.113,0.233) 0.494
FEV1% 353
    Normal weight group 170 ref.
    Underweight group 52 -2.107 1.896 (-5.837,1.624) 0.267
    Overweight group 93 1.062 1.538 (-1.964,4.087) 0.490
    Obesity group 38 6.975 2.566 (1.926,12.023) 0.007
FEVI/FVC 353
    Normal weight group 170 ref.
    Underweight group 52 -6.780 2.755 (-12.199,1.362) 0.014
    Overweight group 93 1.983 2.234 (-2.412,6.378) 0.375
    Obesity group 38 3.355 3.728 (-3.979,10.689) 0.369
Hospital stay 596
    Normal weight group 281 ref.
    Underweight group 117 1.588 0.724 (0.166,3.010) 0.029
    Overweight group 139 0.025 0.675 (-1.302,1.351) 0.971
    Obesity group 59 0.358 0.934 (-1.476,2.191) 0.702
Hospital costs 596
    Normal weight group 281 ref.
    Underweight group 117 0.068 0.029 (0.011,0.125) 0.019
    Overweight group 139 0.009 0.027 (-0.044,0.062) 0.743
    Obesity group 59 0.086 0.037 (0.013,0.160) 0.021
Adjustment factors include age,gender,smoking,and smoking-index.

表 3 BMI与患者呼吸机辅助通气率及病死率logistic回归分析 Tab.3 Logistic regression analysis of body mass index grades and invasive ventilator use and mortality
Item n β OR 95% CI for OR P
Invasive ventilator usage 596        
    Normal weight group 281   ref.    
    Underweight group 117 -0.900 2.460 (0.990,6.113) 0.053
    Overweight group 139 -0.247 0.781 (0.242,2.526) 0.680
    Obesity group 59 0.338 1.402 (0.372,5.278) 0.617
Mortality 596        
    Normal weight group 281   ref.    
    Underweight group 117 1.740 5.695 (1.389,23.352) 0.016
    Overweight group 139 0.294 1.341 (0.217,8.289) 0.752
    Obesity group 59 -16.692 - - 0.997
Adjustment factors including age,gender,smoking,and smoking-index.

3 讨论

COPD是一种具有异质性的多组分疾病,其核心症状由慢性气流阻塞导致,其他症状的存在也影响着疾病的严重程度,同时也使住院和死亡风险增加[12]。本研究结果发现,年龄增长和吸烟都与BMI降低相关。BMI用于COPD病情评价,尤其是在病死率预测方面的价值很早就受到了广泛关注[13-14]。研究[15]发现,较高BMI可以独立预测更好的长期生存率,肥胖COPD患者预后更好,这和心血管疾病中肥胖症的预后相反。根据研究[16]数据显示,2015年我国超重率为30%,肥胖率为15%。而本研究结果显示,AECOPD患者超重率和肥胖率均低于平均水平。这说明AECOPD患者患病后营养状态会逐步恶化,BMI逐渐降低。

本研究结果发现患者各组WBC比较没有统计学差异,而CRP水平在低体质量、正常体质量、超重3组中随BMI升高而降低,而在肥胖组中随BMI升高而升高。可见,CRP是一个比较灵敏的炎症指标,是评估COPD患者全身炎症水平的重要指标[17-19]。另外,目前研究[20]也证实了肥胖、代谢综合征与CRP之间的关系。对于肺功能分析可以发现,FEV1%、FEV1/FVC与患者BMI水平正相关,与以往研究[21]结果相似。这说明低体质量患者在急性发作期表现出更差的肺功能及更严重的气道阻塞。这可能是由于低体质量患者存在营养风险,包括呼吸肌在内的肌肉量不足和日常活动量不足。而这也导致了低体质量患者较高的死亡风险,以及更长的住院时间和较高的费用。但本研究发现肥胖患者中似乎存在一个悖论,尽管高BMI患者表现更好的肺功能,但住院费用却高于正常体质量患者。这可能与高BMI患者更容易合并内分泌系统疾病、心脑血管疾病有关,是这些合并症导致了更大的疾病负担。

本研究中高BMI患者肺功能较好,这一结果与LAMBERT等[10]研究结果不太一致。分析原因可能是LAMBERT等[10]的研究针对美国人群,COPD患者中肥胖率高达34%,而在本研究中仅为9.9%。由于肥胖人群数量较少,因此对于肥胖COPD人群预后的判断可能存在偏差。另外,也可能因为BMI是最容易获得的指标,但却可能并不是最准确的预测指标。近年来,一些研究提出了新的指标(营养风险筛查[22]、骨骼肌质量指数[23]、生物电阻抗分析[24]等)对COPD患者预后进行预测,认为这些指标与BMI比较具有更准确的预测价值。但BMI具有简便易行的优点,仍然是其他指标不能取代的。因此,建议对入院的AECOPD患者首先进行BMI评估,并对低BMI患者加强营养治疗。

参考文献
[1]
Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD).Global strategy for the diagnosis, management, and prevention of COPD (GOLD) 2019[R/OL].[2019-05-23]. http://www.goldcopd.org.
[2]
ADELOYE D, CHUA S, LEE C, et al. Global and regional estimates of COPD prevalence:systematic review and meta-analysis[J]. J Glob Heal, 2015, 5(2): 020415. DOI:10.7189/jogh.05.020415
[3]
WANG C, XU JY, YANG L, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health[CPH] study):a national cross-sectional study[J]. Lancet, 2018, 391(10131): 1706-1717. DOI:10.1016/S0140-6736(18)30841-9
[4]
MÜLLER TD, CLEMMENSEN C, FINAN B, et al. Anti-obesity therapy:from rainbow pills to polyagonists[J]. Pharmacol Rev, 2018, 70(4): 712-746. DOI:10.1124/pr.117.014803
[5]
FLEGAL KM, KIT BK, ORPANA H, et al. Association of all-cause mortality with overweight and obesity using standard body mass index categories:a systematic review and meta-analysis[J]. JAMA, 2013, 309(1): 71-82. DOI:10.1001/jama.2012.113905
[6]
PETERS U, DIXON AE, FORNO E. Obesity and asthma[J]. J Allergy Clin Immunol, 2018, 141(4): 1169-1179. DOI:10.1016/j.jaci.2018.02.004
[7]
SENARATNA CV, PERRET JL, LODGE CJ, et al. Prevalence of obstructive sleep apnea in the general population:a systematic review[J]. Sleep Med Rev, 2017, 34: 70-81. DOI:10.1016/j.smrv.2016.07.002
[8]
KIVIMÄKI M, SHIPLEY MJ, BELL JA, et al. Underweight as a risk factor for respiratory death in the Whitehall cohort study:exploring reverse causality using a 45-year follow-up[J]. Thorax, 2016, 71(1): 84-85. DOI:10.1136/thoraxjnl-2015-207449
[9]
STOLL P, FOERSTER S, VIRCHOW JC, et al. Overweight is a predictor of long-term survival in hospitalised patients with exacerbations of COPD[J]. Respir Med, 2016, 116: 59-62. DOI:10.1016/j.rmed.2016.05.016
[10]
LAMBERT AA, PUTCHA N, DRUMMOND MB, et al. Obesity is associated with increased morbidity in moderate to severe COPD[J]. Chest, 2017, 151(1): 68-77. DOI:10.1016/j.chest.2016.08.1432
[11]
中国肥胖问题工作组数据汇总分析协作组. 我国成人体重指数和腰围对相关疾病危险因素异常的预测价值:适宜体重指数和腰围切点的研究[J]. 中华流行病学杂志, 2002, 23(1): 5-10. DOI:10.3760/j.issn:0254-6450.2002.01.003
[12]
VOGELMEIER CF, CRINER GJ, MARTINEZ FJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary[J]. Am J Respir Crit Care Med, 2017, 195(5): 557-582. DOI:10.1164/rccm.201701-0218PP
[13]
GRAY-DONALD K, GIBBONS L, SHAPIRO SH, et al. Nutritional status and mortality in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 1996, 153(3): 961-966. DOI:10.1164/ajrccm.153.3.8630580
[14]
LANDBO C, PRESCOTT E, LANGE P, et al. Prognostic value of nutritional status in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 1999, 160(6): 1856-1861. DOI:10.1164/ajrccm.160.6.9902115
[15]
LAINSCAK M, VON HAEHLING S, DOEHNER W, et al. Body mass index and prognosis in patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease[J]. J Cachexia Sarcopenia Muscle, 2011, 2(2): 81-86. DOI:10.1007/s13539-011-0023-9
[16]
中国肥胖问题工作组. 中国成人超重与肥胖症预防与控制指南(节录)[J]. 营养学报, 2004, 26(1): 1-4. DOI:10.3321/j.issn:0512-7955.2004.01.001
[17]
HUERTA A, CRISAFULLI E, MENÉNDEZ R, et al. Pneumonic and nonpneumonic exacerbations of COPD:inflammatory response and clinical characteristics[J]. Chest, 2013, 144(4): 1134-1142. DOI:10.1378/chest.13-0488
[18]
MOY ML, TEYLAN M, WESTON NA, et al. Daily step count is associated with plasma C-reactive protein and IL-6 in a US cohort with COPD[J]. Chest, 2014, 145(3): 542-550. DOI:10.1378/chest.13-1052
[19]
FERMONT JM, MASCONI KL, JENSEN MT, et al. Biomarkers and clinical outcomes in COPD:a systematic review and meta-analysis[J]. Thorax, 2019, 74(5): 439-446. DOI:10.1136/thoraxjnl-2018-211855
[20]
DEN ENGELSEN C, KOEKKOEK PS, GORTER KJ, et al. High-sensitivity C-reactive protein to detect metabolic syndrome in a centrally obese population:a cross-sectional analysis[J]. Cardiovasc Diabetol, 2012, 11: 25. DOI:10.1186/1475-2840-11-25
[21]
ODONNELL DE, DEESOMCHOK A, LAM YM, et al. Effects of BMI on static lung volumes in patients with airway obstruction[J]. Chest, 2011, 140(2): 461-468. DOI:10.1378/chest.10-2582
[22]
CHEN RQ, XING L, YOU C, et al. Prediction of prognosis in chronic obstructive pulmonary disease patients with respiratory failure:a comparison of three nutritional assessment methods[J]. Eur J Intern Med, 2018, 57: 70-75. DOI:10.1016/j.ejim.2018.06.006
[23]
MUNHOZ DA ROCHA LEMOS COSTA T, COSTA FM, JONASSON TH, et al. Body composition and sarcopenia in patients with chronic obstructive pulmonary disease[J]. Endocrine, 2018, 60(1): 95-102. DOI:10.1007/s12020-018-1533-4
[24]
DE BLASIO F, SCALFI L, DI GREGORIO A, et al. Raw bioelectrical impedance analysis variables are independent predictors of early all-cause mortality in patients with COPD[J]. Chest, 2019. DOI:10.1016/j.chest.2019.01.001