结核病与糖尿病共病患者营养风险、炎症指标与血糖控制的相关性分析

doi:10.19982/j.issn.1000-6621.20250503

摘要/Abstract

摘要：

目的: 探讨结核病与糖尿病共病(TB-DM)患者营养风险、炎症指标与血糖控制的关系,为优化TB-DM患者的综合管理提供依据。方法: 采用横断面研究设计,纳入2023年1—12月广州市胸科医院收治的264例TB-DM患者。根据营养风险筛查2002(NRS-2002)评分和糖化血红蛋白(HbA1c)水平进行分组比较。收集患者的营养指标[如体质量指数(BMI)、白蛋白(ALB)、预后营养指数(PNI)]、免疫炎症指标[如CD细胞系列、白细胞计数(WBC)、中性粒细胞计数(Neu)、淋巴细胞计数(LYM)、中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)等]及血糖指标(随机血糖和HbA1c)。采用多因素logistic回归分析营养风险与血糖控制不佳的关联,并进一步运用中介效应分析炎症指标在营养风险与血糖控制间的中介作用。结果: 存在营养风险(NRS-2002≥3分)的患者占50.4%(133/264)。与无营养风险组相比,有营养风险组患者的营养及免疫指标均明显降低,如BMI[20.20(18.73,22.95)kg/m²和22.14(20.55,24.22)kg/m²,Z=-4.759,P<0.001]、ALB[(30.93±7.02)g/L和(36.48±7.08) g/L,t=6.393,P<0.001]、CD4⁺ T细胞计数[392(260,560)个/μl和564(394,756)个/μl,Z=-5.108,P<0.001],且痰涂片阳性率更高[60.90%(81/133)和39.69%(52/131),χ²=11.874,P<0.001]。有营养风险组患者炎症水平明显升高,如NLR[5.20(3.54,10.14)和3.64(2.61,5.48),Z=-4.510,P<0.001]、C反应蛋白[22.54(6.36,58.32)mg/L和5.23(1.36,22.12)mg/L,Z=-4.852,P<0.001],但HbA1c水平反而较低[7.50%(6.60%,10.00%)和8.60%(7.35%,10.20%),Z=-2.711,P=0.007]。多因素logistic回归分析结果表明,在校正混杂因素后,营养风险与血糖控制不佳呈独立负向关联(OR=0.357, 95%CI: 0.194~0.656)。中介效应分析显示,炎症指标(WBC、Neu、NLR)是营养风险影响HbA1c水平的显著中介变量,中介效应占比分别为31.29%、50.44%和53.16%。结论: 在TB-DM患者中,存在营养风险者往往伴有更严重的炎症状态和免疫抑制,但其血糖水平可能因机体严重消耗而相对更低。炎症是连接营养风险与血糖控制的关键路径。临床在管理TB-DM患者时,应在积极控制血糖的基础上,高度重视营养评估,并将调控炎症作为综合治疗的重要环节。

关键词: 结核, 糖尿病, 共病现象, 营养状况, 炎症, 血糖

Abstract:

Objective: To investigate the relationship between nutritional risk, inflammatory markers, and glycemic control in patients with tuberculosis and diabetes comorbidity (TB-DM), providing evidence for optimizing the integrated management of TB-DM patients. Methods: A cross-sectional study was conducted, enrolling 264 TB-DM patients admitted to the Guangzhou Chest Hospital from January to December 2023. Patients were grouped and compared based on their Nutritional Risk Screening 2002 (NRS-2002) scores and glycated hemoglobin (HbA1c) levels. Data collected included nutritional indicators such as body mass index (BMI), albumin (ALB), prognostic nutritional index (PNI), immuno-inflammatory indicators such as CD cell subsets, white blood cell count (WBC), neutrophil count (Neu), lymphocyte count (LYM), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and glycemic indicators (random blood glucose and HbA1c). Multivariable logistic regression was used to analyze the association between nutritional risk and poor glycemic control. Mediation analysis was further employed to examine the mediating role of inflammatory markers in the relationship between nutritional risk and glycemic control. Results: Patients with nutritional risk (NRS-2002 ≥3) accounted for 50.4% (133/264). Compared to the no-nutritional-risk group, the nutritional-risk group had significantly lower nutritional and immune indicators: BMI (20.20 (18.73, 22.95) kg/m² vs. 22.14 (20.55, 24.22) kg/m², Z=-4.759, P<0.001), ALB ((30.93±7.02) g/L vs. (36.48±7.08) g/L, t=6.393, P<0.001), CD4⁺ T-cell count (392 (260, 560) cells/μl vs. 564 (394, 756) cells/μl, Z=-5.108, P<0.001), and a higher sputum smear-positive rate (60.90% (81/133) vs. 39.69% (52/131), χ²=11.874, P<0.001). Notably, this group had significantly higher inflammatory levels: NLR (5.20 (3.54, 10.14) vs. 3.64 (2.61, 5.48), Z=-4.510, P<0.001), C-reactive protein (22.54 (6.36, 58.32) mg/L vs. 5.23 (1.36, 22.12) mg/L, Z=-4.852, P<0.001), but lower HbA1c levels (7.50% (6.60%, 10.00%) vs. 8.60% (7.35%, 10.20%), Z=-2.711, P=0.007). Multivariable logistic regression analysis indicated that, after adjusting for confounders, nutritional risk was independently inversely association with poor glycemic control (OR=0.357, 95%CI: 0.194-0.656). Mediation analysis revealed that inflammatory markers (WBC, Neu, NLR) were significant mediators in the effect of nutritional risk on HbA1c levels, accounting for 31.29%, 50.44%, and 53.16% of the total effect, respectively. Conclusion: In TB-DM patients, those with nutritional risk often present with more severe inflammatory status and immunosuppression, but their blood glucose levels may be relatively lower, potentially due to severe bodily catabolism. Inflammation is a key pathway linking nutritional risk to glycemic control. In the clinical management of TB-DM patients, while actively controlling blood glucose, we should attach high importance to nutritional assessment, and regulating inflammation should be considered a crucial component of comprehensive treatment.

Key words: Tuberculosis, Diabetes mellitus, Comorbidity, Nutritional status, Inflammation, Blood glucose

中图分类号:

范佳画, 颜亮, 陈华, 卢春丽, 汪敏, 黄亚玲, 李艳. 结核病与糖尿病共病患者营养风险、炎症指标与血糖控制的相关性分析[J]. 中国防痨杂志, 2026, 48(6): 769-778. doi: 10.19982/j.issn.1000-6621.20250503

Fan Jiahua, Yan Liang, Chen Hua, Lu Chunli, Wang Min, Huang Yaling, Li Yan. Association between nutritional risk, inflammatory indicators, and glycemic control in patients with tuberculosis complicated by diabetes mellitus[J]. Chinese Journal of Antituberculosis, 2026, 48(6): 769-778. doi: 10.19982/j.issn.1000-6621.20250503

图/表 7

表1

不同营养风险分组的研究对象的基本特征

指标	合计 (264例)	无营养风险组 (131例)	有营养风险组 (133例)	统计检验值	P值
年龄(岁,$\overline{x}$±s)	59.30±12.80	57.30±10.80	61.30±14.20	t=-2.593	0.010
TP(g/L,$\overline{x}$±s)	68.94±7.76	70.72±6.37	67.18±8.59	t=3.801	<0.001
ALB(g/L,$\overline{x}$±s)	33.69±7.57	36.48±7.08	30.93±7.02	t=6.393	<0.001
PNI(g/L,$\overline{x}$±s)	40.09±9.02	43.57±8.12	36.66±8.57	t=6.728	<0.001
BMI[kg/m²,M(Q₁,Q₃)]	21.47(19.29,23.72)	22.14(20.55,24.22)	20.20(18.73,22.95)	Z=-4.759	<0.001
随机血糖[mmol/L,M(Q₁,Q₃)]	11.57(7.57,16.26)	11.77(8.52,16.93)	11.07(7.06,15.39)	Z=-2.154	0.031
HbA1c[%,M(Q₁,Q₃)]	8.15(6.80,10.12)	8.60(7.35,10.20)	7.50(6.60,10.00)	Z=-2.711	0.007
CD4⁺ T细胞[个/μl,M(Q₁,Q₃)]	468(314,689)	564(394,756)	392(260,560)	Z=-5.108	<0.001
CD8⁺ T细胞[个/μl,M(Q₁,Q₃)]	259.9(183.8,396.6)	312.1(219.8,469.9)	212.4(143.7,340.1)	Z=-4.866	<0.001
CD3⁺ T细胞[个/μl,M(Q₁,Q₃)]	794(534,1167)	912(702,1290)	640(448,896)	Z=-5.311	<0.001
CD4/CD8 T细胞比值[M(Q₁,Q₃)]	1.78(1.32,2.34)	1.74(1.40,2.37)	1.78(1.26,2.33)	Z=-0.434	0.664
白细胞计数[×10⁹/L,M(Q₁,Q₃)]	7.37(5.87,9.52)	7.18(5.84,9.03)	7.73(5.98,9.95)	Z=-1.399	0.162
淋巴细胞计数[×10⁹/L,M(Q₁,Q₃)]	1.23(0.80,1.64)	1.34(1.10,1.72)	1.01(0.64,1.53)	Z=-4.114	<0.001
中性粒细胞计数[×10⁹/L,M(Q₁,Q₃)]	5.36(3.94,7.33)	5.00(3.71,6.48)	5.70(4.22,7.64)	Z=-2.452	0.014
血小板计数[×10⁹/L,M(Q₁,Q₃)]	260.5(200.8,335.3)	262.0(205.5,321.5)	257.0(197.0,352.0)	Z=-0.150	0.881
CRP[mg/L,M(Q₁,Q₃)]	11.31(2.17,38.79)	5.23(1.36,22.12)	22.54(6.36,58.32)	Z=-4.852	<0.001
NLR[M(Q₁,Q₃)]	4.35(2.85,7.18)	3.64(2.61,5.48)	5.20(3.54,10.14)	Z=-4.510	<0.001
PLR[M(Q₁,Q₃)]	217.9(146.7,349.7)	195.7(131.3,261.6)	257.7(168.0,390.7)	Z=-3.574	<0.001
感染肺野数[个,M(Q₁,Q₃)]	4(2,6)	2(2,6)	6(2,6)	Z=-2.310	0.021
结核病病程[月,M(Q₁,Q₃)]	6(2,21)	6(2,18)	7(3,24)	Z=-1.117	0.264
糖尿病病程[年,M(Q₁,Q₃)]	3.00(1.00,10.00)	3.00(1.00,10.00)	3.00(1.00,8.00)	Z=-0.778	0.440
性别[例(构成比,%)]				χ²=0.607	0.436
女性	43(16.29)	19(14.50)	24(18.05)
男性	221(83.71)	112(85.50)	109(81.95)
免疫功能低下[例(构成比,%)]				χ²=20.860	<0.001
否	118(44.70)	77(58.78)	41(30.83)
是	146(55.30)	54(41.22)	92(69.17)
患者类型[例(构成比,%)]^a				χ²=0.684	0.408
初治	173(69.76)	86(72.27)	87(67.44)
复治	75(30.24)	33(27.73)	42(32.56)
痰涂片情况[例(构成比,%)]				χ²=11.874	<0.001
阳性	133(50.38)	52(39.69)	81(60.90)
阴性	131(49.62)	79(60.31)	52(39.10)
耐药情况[例(构成比,%)]				χ²=0.047	0.829
耐药	85(32.20)	43(32.82)	42(31.58)
敏感	179(67.80)	88(67.18)	91(68.42)
HbA1c≥7.0%[例(构成比,%)]				χ²=14.572	<0.001
否	79(29.92)	25(19.08)	54(40.60)
是	185(70.08)	106(80.92)	79(59.40)

表1

表2

不同血糖控制情况分组研究对象的基本特征比较

指标	合计 (264例)	血糖控制良好组 (79例)	血糖控制不佳组 (185例)	统计检验值	P值
年龄(岁,$\overline{x}$±s)	59.34±12.75	61.28±14.24	58.51±12.00	t=1.515	0.132
TP(g/L,$\overline{x}$±s)	68.94±7.76	68.63±8.16	69.06±7.61	t=-0.411	0.681
ALB(g/L,$\overline{x}$±s)	33.69±7.57	33.97±7.59	33.57±7.58	t=0.394	0.694
PNI(g/L,$\overline{x}$±s)	40.09±9.02	40.10±8.78	40.08±9.15	t=0.017	0.986
BMI[kg/m²,M(Q₁,Q₃)]	21.50(19.30,23.70)	20.80(19.00,23.60)	21.50(19.60,23.70)	Z=-1.425	0.149
随机血糖[mmol/L,M(Q₁,Q₃)]	11.57(7.57,16.26)	7.96(6.14,10.75)	13.01(9.30,17.34)	Z=-6.786	<0.001
HbA1c[%,M(Q₁,Q₃)]	8.15(6.80,10.12)	6.40(6.00,6.70)	9.30(8.00,11.20)	Z=-12.864	<0.001
CD4⁺ T细胞[个/μl,M(Q₁,Q₃)]	468(314,689)	420(294,592)	500(316,748)	Z=-2.214	0.027
CD8⁺ T细胞[个/μl,M(Q₁,Q₃)]	260(184,396)	251(180,358)	264(192,444)	Z=-1.108	0.265
CD3⁺ T细胞[个/μl,M(Q₁,Q₃)]	794(534,1167)	692(524,910)	844(536,1224)	Z=-1.993	0.046
CD4/CD8 T细胞比值[M(Q₁,Q₃)]	1.78(1.32,2.34)	1.73(1.29,2.23)	1.80(1.34,2.39)	Z=-1.151	0.250
白细胞计数[10⁹/L,M(Q₁,Q₃)]	7.37(5.87,9.52)	6.94(5.53,8.71)	7.73(6.05,9.60)	Z=-2.117	0.034
淋巴细胞计数[10⁹/L,M(Q₁,Q₃)]	1.23(0.80,1.64)	1.12(0.76,1.58)	1.27(0.85,1.68)	Z=-1.281	0.200
中性粒细胞[10⁹/L,M(Q₁,Q₃)]	5.36(3.94,7.33)	5.11(3.63,6.65)	5.50(4.09,7.52)	Z=-2.017	0.044
血小板[10⁹/L,M(Q₁,Q₃)]	261(201,335)	228(181,305)	273(213,349)	Z=-2.549	0.011
CRP[mg/L,M(Q₁,Q₃)]	11.31(2.17,38.79)	16.91(1.83,31.55)	9.93(2.21,42.10)	Z=-0.185	0.853
NLR[M(Q₁,Q₃)]	4.35(2.85,7.17)	4.25(2.72,6.88)	4.50(2.88,7.28)	Z=-0.578	0.567
PLR[M(Q₁,Q₃)]	217.9(146.7,349.7)	214.0(144.3,320.6)	219.7(146.9,373.8)	Z=-0.447	0.654
感染肺野数[个,M(Q₁,Q₃)]	4(2,6)	6(2,6)	3(2,6)	Z=-1.438	0.151
结核病病程[月,M(Q₁,Q₃)]	6(2,21)	7(3,12)	6(2,24)	Z=-0.701	0.485
糖尿病病程[年,M(Q₁,Q₃)]	3.00(1.00,10.00)	2.00(0.75,4.00)	3.00(1.00,10.00)	Z=-2.684	<0.001
性别[例(构成比,%)]				χ²=4.982	0.026
女性	43(16.29)	19(24.05)	24(12.97)
男性	221(83.71)	60(75.95)	161(87.03)
免疫功能低下[例(构成比,%)]				χ²=3.906	0.048
否	118(44.70)	28(35.44)	90(48.65)
是	146(55.30)	51(64.56)	95(51.35)
患者类型[例(构成比,%)]^a				χ²=0.262	0.609
初治	173(69.76)	52(67.53)	121(70.76)
复治	75(30.24)	25(32.47)	50(29.24)
痰涂片情况[例(构成比,%)]				χ²=0.566	0.452
阳性	133(50.38)	37(46.84)	96(51.89)
阴性	131(49.62)	42(53.16)	89(48.11)
耐药情况[例(构成比,%)]				χ²=0.544	0.461
耐药	85(32.20)	28(35.44)	57(30.81)
敏感	179(67.80)	51(64.56)	128(69.19)
营养风险[例(构成比,%)]				χ²=14.572	<0.001
无	131(49.62)	25(31.65)	106(57.30)
有	133(50.38)	54(68.35)	79(42.70)

表2

图1

表3

表4

图2

图3

参考文献 25

[1]	World Health Organization.Global tuberculosis report 2024. Geneva: World Health Organization, 2024.
[2]	Xu Y, Lu J, Li M, et al. Diabetes in China part 1: epidemiology and risk factors. Lancet Public Health, 2024, 9(12): e1089-e1097. doi:10.1016/s2468-2667(24)00250-0.
[3]	中华医学会结核病学分会重症专业委员会. 结核病营养治疗专家共识. 中华结核和呼吸杂志, 2020, 43(1): 17-26. doi:10.3760/cma.j.issn.1001-0939.2020.01.006.
[4]	Ashenafi S, Bekele A, Aseffa G, et al. Anemia Is a Strong Predictor of Wasting, Disease Severity, and Progression, in Clinical Tuberculosis (TB). Nutrients, 2022, 14(16): 3318. doi:10.3390/nu14163318.
[5]	Chandrasekaran P, Saravanan N, Bethunaickan R, et al. Malnutrition: Modulator of Immune Responses in Tuberculosis. Front Immunol, 2017, 8: 1316. doi:10.3389/fimmu.2017.01316.
[6]	Uyar S, Gorar S, Kok M, et al. Could Insulin and Hemoglobin A1c Levels be Predictors of Hunger-Related Malnutrition/Undernutrition Without Disease?. Clin Lab, 2018, 64(10): 1635-1640. doi:10.7754/Clin.Lab.2018.180403.
[7]	Vischer UM, Perrenoud L, Genet C, et al. The high prevalence of malnutrition in elderly diabetic patients: implications for anti-diabetic drug treatments. Diabet Med, 2010, 27(8): 918-924. doi:10.1111/j.1464-5491.2010.03047.x.
[8]	中华人民共和国国家卫生和计划生育委员会. WS 288—2017肺结核诊断. 结核与肺部疾病杂志, 2024, 5(4): 376-378. doi:10.19983/j.issn.2096-8493.2024022.
[9]	American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care, 2010, 33 Suppl 1(Suppl 1): S62-S69. doi:10.2337/dc10-S062.
[10]	刘贵, 马皎洁, 李亮. 预后营养指数在结核病中的应用. 中华结核和呼吸杂志, 2024, 47(10): 991-995. doi:10.3760/cma.j.cn112147-20240613-00334.
[11]	Lu C, Xu Y, Li X, et al. Nutritional status affects immune function and exacerbates the severity of pulmonary tuberculosis. Front Immunol, 2024, 15: 1407813. doi:10.3389/fimmu.2024.1407813.
[12]	沈男男, 王伶, 劳国琴, 等. 糖尿病合并肺结核患者营养风险筛查、评估及干预的临床研究. 中华危重症医学杂志(电子版), 2017, 10(6): 374-380. doi:10.3877/cma.j.issn.1674-6880.2017.06.003.
[13]	Palmer BF, Clegg DJ. Starvation Ketosis and the Kidney. Am J Nephrol, 2021, 52(6): 467-478. doi:10.1159/000517305.
[14]	Rosen E, Bakshi N, Watters A, et al. Hepatic Complications of Anorexia Nervosa. Dig Dis Sci, 2017, 62(11): 2977-2981. doi:10.1007/s10620-017-4766-9.
[15]	Glenn TC, Martin NA, Mcarthur DL, et al. Endogenous Nutritive Support after Traumatic Brain Injury: Peripheral Lactate Production for Glucose Supply via Gluconeogenesis. J Neurotrauma, 2015, 32(11): 811-819. doi:10.1089/neu.2014.3482.
[16]	Vidyadharan VA, Betancourt A, Smith C, et al. Maternal Low-Protein Diet Leads to Mitochondrial Dysfunction and Impaired Energy Metabolism in the Skeletal Muscle of Male Rats. Int J Mol Sci, 2024, 25(23):12860. doi:10.3390/ijms252312860.
[17]	Du Y, Zheng R, Yin H, et al. Mycobacterium tuberculosis Rv2653 Protein Promotes Inflammation Response by Enhancing Glycolysis. Jpn J Infect Dis, 2023, 76(6): 343-350. doi:10.7883/yoken.JJID.2022.647.
[18]	Böni-Schnetzler M, Meier DT. Islet inflammation in type 2 diabetes. Semin Immunopathol, 2019, 41(4): 501-513. doi:10.1007/s00281-019-00745-4.
[19]	Eckold C, Kumar V, Weiner J, et al. Impact of Intermediate Hyperglycemia and Diabetes on Immune Dysfunction in Tuberculosis. Clin Infect Dis, 2021, 72(1): 69-78. doi:10.1093/cid/ciaa751.
[20]	Jonkers DM. Microbial perturbations and modulation in conditions associated with malnutrition and malabsorption. Best Pract Res Clin Gastroenterol, 2016, 30(2): 161-172. doi:10.1016/j.bpg.2016.02.006.
[21]	Patterson GT, Osorio EY, Peniche A, et al. Pathologic Inflammation in Malnutrition Is Driven by Proinflammatory Intestinal Microbiota, Large Intestine Barrier Dysfunction, and Translocation of Bacterial Lipopolysaccharide. Front Immunol, 2022, 13: 846155. doi:10.3389/fimmu.2022.846155.
[22]	Khodabandehloo H, Gorgani-Firuzjaee S, Panahi G, et al. Molecular and cellular mechanisms linking inflammation to insulin resistance and β-cell dysfunction. Transl Res, 2016, 167(1): 228-256. doi:10.1016/j.trsl.2015.08.011.
[23]	Alipourfard I, Datukishvili N, Mikeladze D. TNF-α Downregu-lation Modifies Insulin Receptor Substrate 1 (IRS-1) in Metabolic Signaling of Diabetic Insulin-Resistant Hepatocytes. Mediators Inflamm, 2019, 2019:3560819. doi:10.1155/2019/3560819.
[24]	Rehman K, Akash MSH, Liaqat A, et al. Role of Interleukin-6 in Development of Insulin Resistance and Type 2 Diabetes Mellitus. Crit Rev Eukaryot Gene Expr, 2017, 27(3): 229-236. doi:10.1615/CritRevEukaryotGeneExpr.2017019712.
[25]	Sepidarkish M, Akbari-Fakhrabadi M, Daneshzad E, et al. Effect of omega-3 fatty acid plus vitamin E Co-Supplementation on oxidative stress parameters: A systematic review and meta-analysis. Clin Nutr, 2020, 39(4): 1019-1025. doi:10.1016/j.clnu.2019.05.004.

指标	β值	s${}_{\overline{x}}$值	Wald χ²值	P值	OR值	95%CI值
模型1
营养风险	-0.928	0.302	9.456	0.002	0.395	0.219~0.714
男性	0.834	0.368	5.121	0.024	2.302	1.118~4.740
免疫功能低下	-0.354	0.304	1.357	0.244	0.702	0.387~1.273
糖尿病病程	0.086	0.031	4.000	0.006	1.090	1.025~1.159
模型2
营养风险	-1.031	0.311	10.976	<0.001	0.357	0.194~0.656
男性	0.780	0.379	4.248	0.039	2.182	1.039~4.585
免疫功能低下	-0.251	0.311	0.653	0.419	0.778	0.423~1.431
糖尿病病程	0.083	0.032	6.518	0.011	1.086	1.019~1.157
白细胞计数	0.069	0.057	1.471	0.225	1.072	0.958~1.198
血小板计数	0.002	0.002	1.946	0.163	1.002	0.999~1.005