代谢相关脂肪性肝病及其心脏代谢风险指标异常与不良妊娠结局的相关性

doi:10.19723/j.issn.1671-167X.2025.03.012

摘要/Abstract

摘要：

目的: 探讨代谢相关脂肪性肝病(metabolic dysfunction-associated steatotic liver disease, MASLD)与不良妊娠结局的相关性, 并分析心脏代谢风险指标(cardiometabolic risk factor, CMRF)异常的种类及其严重程度对该相关性的影响。方法: 采用回顾性队列研究, 选择2020年3月10日至2022年12月31日在首都医科大学附属北京友谊医院产科建档的单胎初产孕妇, 共纳入2 623名孕妇。记录基本信息和分娩结局, 并进行肝脏超声检查及相关产前检查, 对不良妊娠结局进行诊断。采用修正Poisson回归方法分析MASLD及其不同CMRF异常种类与不良妊娠结局的相关性, 并探究MASLD的CMRF异常程度变化与不良妊娠结局发生风险的相关性。结果: 调整年龄、孕期增重水平和受教育水平等协变量后, MASLD与剖宫产(RR=1.531, 95%CI：1.304~1.799, P < 0.001)、妊娠期糖尿病(RR=2.409, 95%CI：1.948~2.979, P < 0.001)、妊娠相关高血压(RR=3.062, 95%CI: 2.069~4.533, P < 0.001)、早产(RR=2.145, 95%CI: 1.342~3.429, P=0.001)和大于胎龄儿(RR=2.224, 95%CI: 1.599~3.095, P < 0.001)的风险升高相关。在控制其他种类CMRF异常的影响后, 不同CMRF异常MASLD孕妇的不良妊娠结局风险存在差异, 体重指数异常组的剖宫产、妊娠期糖尿病、妊娠相关高血压、早产和大于胎龄儿风险升高；血糖异常组的妊娠期糖尿病风险升高；血压异常组的妊娠相关高血压风险升高；高密度脂蛋白胆固醇异常组的剖宫产、妊娠期糖尿病和妊娠相关高血压风险升高；甘油三酯异常组的妊娠期糖尿病和早产风险升高。随着CMRF异常程度的加重, MASLD孕妇的剖宫产、妊娠期糖尿病、妊娠相关高血压、早产和大于胎龄儿风险持续升高(P均 < 0.05)。结论: 妊娠期MASLD与多种不良妊娠结局风险升高相关, 且MASLD的CMRF异常种类及严重程度对该相关性存在影响, 这提示在诊断MASLD时关注CMRF异常的具体情况, 有助于实施针对性干预并降低不良妊娠结局的发生风险。

关键词: 心脏代谢风险指标, 妊娠结局, 肝脏疾病, 代谢相关脂肪性肝病, 不良妊娠结局

Abstract:

Objective: To investigate the association between metabolic dysfunction-associated steatotic liver disease (MASLD) and the risk of adverse pregnancy outcomes, and to analyze the impact of the type and severity of cardiometabolic risk factor (CMRF) abnormalities on this association. Methods: A retrospective cohort study was conducted among primiparous women with singleton pregnancies who had registered at Beijing Friendship Hospital from March 10, 2020, to December 31, 2022. A total of 2 623 women were included. Basic characteristics and delivery outcomes were documented, liver ultrasound and relevant prenatal examinations were performed, and adverse pregnancy outcomes were diagnosed. Modified Poisson regression models were used to analyze the association between MASLD and adverse pregnancy outcomes. The relationship between the type or severity of CMRF abnormalities in MASLD and the risk of adverse pregnancy outcomes was also explored. Results: After adjusting for confounding factors including age, gestational weight gain, and education level, MASLD was associated with an increased risk of cesarean section (RR=1.531, 95%CI: 1.304-1.799, P < 0.001), gestational diabetes mellitus (GDM; RR=2.409, 95%CI: 1.948-2.979, P < 0.001), pregnancy-associated hypertension (PAH; RR=3.062, 95%CI: 2.069-4.533, P < 0.001), preterm birth (RR=2.145, 95%CI: 1.342-3.429, P=0.001), and large for gestational age (LGA; 2.224, 95%CI: 1.599-3.095, P < 0.001). However, no significant associations were found for small for gestational age or postpartum hemorrhage. After adjusting for other CMRF abnormalities, the risk of adverse pregnancy outcomes varied among MASLD pregnant women with different CMRF abnormalities: the body mass index abnormal group had higher risks of cesarean section, GDM, PAH, preterm birth, and LGA; the glucose abnormal group had an increased risk of GDM; the blood pressure abnormal group had a higher risk of PAH; the high density lipoprotein cholesterol abnormal group had higher risks of cesarean section, GDM, and PAH; and the triglyceride abnormal group was associated with higher risks of GDM and preterm birth. Additional, as the severity of CMRF abnormalities increased, the risks of cesarean section (RR=1.199, 95%CI: 1.112-1.292, P < 0.001), GDM (RR=1.478, 95%CI: 1.345-1.624, P < 0.001), PAH (RR=1.626, 95%CI: 1.367-1.934, P < 0.001), preterm birth (RR=1.384, 95%CI: 1.120-1.710, P=0.003), and LGA (RR=1.422, 95%CI: 1.224-1.650, P < 0.001) continued to rise. Conclusion: MASLD during pregnancy is associated with an increased risk of multiple adverse pregnancy outcomes, and the type and severity of CMRF abnormalities significantly influence this association. These results suggest that attention should be paid to the specific CMRF abnormalities when diagnosed MASLD, as this may help to facilitate targeted interventions and reduce the risk of adverse pregnancy outcomes.

Key words: Cardiometabolic risk factor, Pregnancy outcome, Liver disease, Metabolic dysfunction-associated steatotic liver disease, Adverse pregnancy outcome

中图分类号:

R714.25

杨树涵, 李奕昕, 崔浩亮, 王佑新, 吴玉莹, 王明月, 杨依凡, 恩卡尔·努尔, 杨磊, 王辉. 代谢相关脂肪性肝病及其心脏代谢风险指标异常与不良妊娠结局的相关性[J]. 北京大学学报（医学版）, 2025, 57(3): 487-495.

Shuhan YANG, Yixin LI, Haoliang CUI, Youxin WANG, Yuying WU, Mingyue WANG, Yifan YANG, Nur Enkar, Lei YANG, Hui WANG. Associations of metabolic dysfunction-associated steatotic liver disease and cardiometabolic risk factor abnormalities with adverse pregnancy outcomes[J]. Journal of Peking University (Health Sciences), 2025, 57(3): 487-495.

图/表 6

表1

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表3

不同CMRF异常MASLD与不良妊娠结局的相关性分析"

Adverse pregnancy outcome	Control group	BMI abnormal group		Glucose abnormal group		Blood pressure abnormal group		HDL-C abnormal group		TG abnormal group
Adverse pregnancy outcome	Control group	RR (95% CI)	P	RR (95% CI)	P	RR (95% CI)	P	RR (95% CI)	P	RR (95% CI)	P
Cesarean section
Model 1	1.000	1.670(1.414, 1.972)	< 0.001	1.992 (1.414, 2.807)	< 0.001	1.752 (1.186, 2.588)	0.005	1.677(1.366, 2.059)	< 0.001	1.559 (1.166, 2.085)	0.003
Model 2	1.000	1.498(1.264, 1.776)	< 0.001	1.617 (1.139, 2.298)	0.007	1.509 (1.017, 2.240)	0.041	1.518(1.232, 1.869)	< 0.001	1.363 (1.015, 1.830)	0.040
Model 3	1.000	1.572(1.224, 2.018)	< 0.001	2.779 (0.796, 9.705)	0.109	3.206 (0.714, 14.395)	0.128	1.971(1.226, 3.170)	0.005	1.371 (0.641, 2.934)	0.416
Gestational diabetes mellitus
Model 1	1.000	2.560(2.063, 3.176)	< 0.001	4.600 (3.221, 6.569)	< 0.001	3.046 (1.920, 4.831)	< 0.001	2.502(1.918, 3.264)	< 0.001	2.85 8 (2.03 8, 4.009)	< 0.001
Model 2	1.000	2.411(1.930, 3.012)	< 0.001	3.825 (2.628, 5.567)	< 0.001	2.548 (1.591, 4.081)	< 0.001	2.284(1.741, 2.997)	< 0.001	2.506 (1.773, 3.544)	< 0.001
Model 3	1.000	2.308 (1.665, 3.198)	< 0.001	6.734 (1.934, 23.444)	0.003	2.174 (0.267, 17.688)	0.468	2.098(1.067, 4.126)	0.032	2.862 (1.314, 6.235)	0.008
Pregnancy-associated hypertension
Model 1	1.000	3.444(2.328, 5.096)	< 0.001	2.867 (1.164, 7.059)	0.022	2.638 (0.968, 7.184)	0.058	3.377(2.098, 5.436)	< 0.001	3.178 (1.652, 6.112)	< 0.001
Model 2	1.000	3.161(2.113, 4.728)	< 0.001	2.3 89 (0.944, 6.049)	0.066	2.526 (0.913, 6.987)	0.074	3.221(1.981, 5.239)	< 0.001	2.793 (1.427, 5.467)	0.003
Model 3	1.000	3.288(1.859, 5.814)	< 0.001	6.097 (0.372, 100.030)	0.205	15.649 (1.194, 205.006)	0.036	3.764(1.172, 12.091)	0.026	2.372 (0.319, 17.662)	0.399
Preterm birth
Model 1	1.000	2.218(1.373, 3.582)	0.001	2.461 (0.902, 6.715)	0.079	3.538 (1.434, 8.727)	0.006	1.726(0.895, 3.328)	0.103	2.728 (1.320, 5.638)	0.007
Model 2	1.000	2.185(1.333, 3.582)	0.002	2.055 (0.728, 5.800)	0.174	2.932 (1.161, 7.407)	0.023	1.650(0.846, 3.217)	0.142	2.408 (1.146, 5.062)	0.020
Model 3	1.000	2.459(1.231, 4.913)	0.011	1.239 (0.191, 8.030)	0.823	-	-	1.333(0.182, 9.738)	0.777	4.285 (1.031, 17.810)	0.045
Large for gestational age
Model 1	1.000	2.410(1.725, 3.366)	< 0.001	3.510 (1.905, 6.467)	< 0.001	2.935 (1.443, 5.972)	0.003	1.969(1.260, 3.076)	0.003	3.183 (1.955, 5.183)	< 0.001
Model 2	1.000	2.249(1.595, 3.171)	< 0.001	3.270 (1.732, 6.174)	< 0.001	2.844 (1.382, 5.852)	0.005	1.832(1.164, 2.884)	0.009	3.019 (1.832, 4.976)	< 0.001
Model 3	1.000	2.266(1.388, 3.697)	0.001	4.962 (0.485, 50.773)	0.177	-	-	1.376(0.416, 4.549)	0.601	3.223 (0.980, 10.593)	0.054
Small for gestational age
Model 1	1.000	0.876(0.615, 1.246)	0.460	0.750 (0.310, 1.814)	0.523	1.208 (0.571, 2.553)	0.621	0.884(0.569, 1.373)	0.583	0.915 (0.502, 1.668)	0.771
Model 2	1.000	0.916(0.641, 1.310)	0.631	0.785 (0.322, 1.916)	0.596	1.227 (0.577, 2.606)	0.595	0.909(0.583, 1.419)	0.676	0.949 (0.519, 1.738)	0.867
Model 3	1.000	0.925(0.536, 1.594)	0.778	4.515 (0.564, 36.128)	0.155	-	-	1.265(0.467, 3.432)	0.644	1.132 (0.275, 4.656)	0.863
Postpartum hemorrhage
Model 1	1.000	0.697(0.387, 1.256)	0.230	1.355 (0.502, 3.657)	0.549	0.389 (0.054, 2.783)	0.347	0.855(0.436, 1.675)	0.648	1.126 (0.498, 2.547)	0.776
Model 2	1.000	0.668(0.369, 1.212)	0.185	1.205 (0.439, 3.313)	0.717	0.349 (0.049, 2.508)	0.296	0.806(0.409, 1.589)	0.533	1.014 (0.445, 2.313)	0.974
Model 3	1.000	0.487(0.167, 1.420)	0.188	2.519 (0.134, 47.306)	0.537	-	-	0.503(0.065, 3.890)	0.510	2.517 (0.628, 10.086)	0. 192

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参考文献 33

1	Wu T , Ye J , Mo S , et al. Impact of nomenclature as metabolic associated steatotic liver disease on steatotic liver disease prevalence and screening: A prospective population survey in Asians[J]. J Gastroenterol Hepatol, 2024, 39 (8): 1636- 1647. doi: 10.1111/jgh.16554
2	Sarkar M , Grab J , Dodge JL , et al. Non-alcoholic fatty liver disease in pregnancy is associated with adverse maternal and perinatal outcomes[J]. J Hepatol, 2020, 73 (3): 516- 522. doi: 10.1016/j.jhep.2020.03.049
3	窦紫岩, 钱文红, 孔邻润, 等. 非酒精性脂肪性肝病检出率现状及其影响因素: 基于北京市32万人群数据[J]. 中国全科医学, 2024, 27 (2): 144-149, 155.
4	Shulman GI . Ectopic fat in insulin resistance, dyslipidemia, and cardiometabolic disease[J]. N Engl J Med, 2014, 371 (12): 1131- 1141. doi: 10.1056/NEJMra1011035
5	Melchiorre K , Sharma R , Khalil A , et al. Maternal cardiovascular function in normal pregnancy: Evidence of maladaptation to chronic volume overload[J]. Hypertension, 2016, 67 (4): 754- 762. doi: 10.1161/HYPERTENSIONAHA.115.06667
6	Targher G , Byrne CD , Lonardo A , et al. Non-alcoholic fatty liver disease and risk of incident cardiovascular disease: A meta-analysis[J]. J Hepatol, 2016, 65 (3): 589- 600. doi: 10.1016/j.jhep.2016.05.013
7	中华医学会肝病学分会. 代谢相关(非酒精性)脂肪性肝病防治指南(2024年版)[J]. 中华肝脏病杂志, 2024, 32 (5): 418- 434.
8	Rinella ME , Lazarus JV , Ratziu V , et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature[J]. Hepatology, 2023, 78 (6): 1966- 1986. doi: 10.1097/HEP.0000000000000520
9	Niu C , Zhang J , Khalid N , et al. Cardiovascular complications during delivery hospitalizations in patients with nonalcoholic fatty liver disease in pregnancy[J]. Eur J Gastroenterol Hepatol, 2024, 36 (9): 1141- 1148. doi: 10.1097/MEG.0000000000002802
10	Catalano PM , Shankar K . Obesity and pregnancy: Mechanisms of short term and long term adverse consequences for mother and child[J]. BMJ, 2017, 356, j1.
11	Woollett LA , Catov JM , Jones HN . Roles of maternal HDL during pregnancy[J]. Biochim Biophys Acta Mol Cell Biol Lipids, 2022, 1867 (3): 159106.
12	Tomiyama H . Vascular function: A key player in hypertension[J]. Hypertens Res, 2023, 46 (9): 2145- 2158. doi: 10.1038/s41440-023-01354-3
13	中华人民共和国国家卫生和计划生育委员会. 成人体重判定[S]. 北京: 中国标准出版社, 2013.
14	中华人民共和国国家卫生健康委员会. 妊娠期妇女体重增长推荐值标准[S]. 北京: 中国标准出版社, 2022.
15	中华医学会肝病学分会脂肪肝和酒精性肝病学组, 中国医师协会脂肪性肝病专家委员会. 非酒精性脂肪性肝病防治指南(2018更新版)[J]. 中华肝脏病杂志, 2018, 26 (3): 195- 203.
16	Metzger BE , Gabbe SG , Persson B , et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy[J]. Diabetes Care, 2010, 33 (3): 676- 682. doi: 10.2337/dc09-1848
17	Hypertension in pregnancy: Executive summary [J]. Obstet Gynecol, 2013, 122(5): 1122-1131.
18	American College of Obstetricians and Gynecologists' Committee on Practice Bulletins-Obstetrics . Practice bulletin No. 171: Management of preterm labor[J]. Obstet Gynecol, 2016, 128 (4): e155- e164. doi: 10.1097/AOG.0000000000001711
19	Marsál K , Persson PH , Larsen T , et al. Intrauterine growth curves based on ultrasonically estimated foetal weights[J]. Acta Paediatr, 1996, 85 (7): 843- 848. doi: 10.1111/j.1651-2227.1996.tb14164.x
20	中华人民共和国国家卫生健康委员会. 不同胎龄新生儿出生时生长评价标准[S]. 北京: 中国标准出版社, 2022.
21	谢幸, 孔北华, 段涛, 等. 妇产科学[M]. 9版北京: 人民卫生出版社, 2018: 204.
22	Qian Y , Zhang Y , Fan X , et al. Nonalcoholic fatty liver disease and adverse pregnancy outcomes in women with normal prepregnant weight[J]. J Clin Endocrinol Metab, 2023, 108 (2): 463- 471. doi: 10.1210/clinem/dgac567
23	Monteiro R , Azevedo I . Chronic inflammation in obesity and the metabolic syndrome[J]. Mediators Inflamm, 2010, 2010, 289645.
24	Shan D , Wang A , Yi K . Lipids, apolipoproteins and gestational diabetes mellitus: A Mendelian randomization study[J]. BMC Pregnancy Childbirth, 2024, 24 (1): 347. doi: 10.1186/s12884-024-06556-2
25	Coates D , Homer C , Wilson A , et al. Indications for, and timing of, planned caesarean section: A systematic analysis of clinical guidelines[J]. Women Birth, 2020, 33 (1): 22- 34. doi: 10.1016/j.wombi.2019.06.011
26	Nasioudis D , Doulaveris G , Kanninen TT . Dyslipidemia in pregnancy and maternal-fetal outcome[J]. Minerva Ginecol, 2019, 71 (2): 155- 162.
27	Brereton MF , Rohm M , Shimomura K , et al. Hyperglycaemia induces metabolic dysfunction and glycogen accumulation in pancreatic β-cells[J]. Nat Commun, 2016, 7, 13496. doi: 10.1038/ncomms13496
28	Tomasi M , Cherubini A , Pelusi S , et al. Circulating interlukin-32 and altered blood pressure control in individuals with metabolic dysfunction[J]. Int J Mol Sci, 2023, 24 (8): 7465. doi: 10.3390/ijms24087465
29	Mottillo S , Filion KB , Genest J , et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis[J]. J Am Coll Cardiol, 2010, 56 (14): 1113- 1132. doi: 10.1016/j.jacc.2010.05.034
30	Metzger BE , Coustan DR , Trimble ER . Hyperglycemia and adverse pregnancy outcomes[J]. Clin Chem, 2019, 65 (7): 937- 938. doi: 10.1373/clinchem.2019.303990
31	Litwin M , Kułaga Z . Obesity, metabolic syndrome, and primary hypertension[J]. Pediatr Nephrol, 2021, 36 (4): 825- 837. doi: 10.1007/s00467-020-04579-3
32	Hilton C , Sabaratnam R , Drakesmith H , et al. Iron, glucose and fat metabolism and obesity: An intertwined relationship[J]. Int J Obes (Lond), 2023, 47 (7): 554- 563. doi: 10.1038/s41366-023-01299-0
33	Malaza N , Masete M , Adam S , et al. A systematic review to compare adverse pregnancy outcomes in women with pregestational diabetes and gestational diabetes[J]. Int J Environ Res Public Health, 2022, 19 (17): 10846. doi: 10.3390/ijerph191710846

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Variables	Control group(n=2 321)	MASLD group(n=302)	χ²/t	P
Maternal age/years	31.20 ± 3.12	32.57 ± 3.64	6.23	< 0.001
< 35	2 075 (89.4)	226 (74.8)	51.31	< 0.001
≥35	246 (10.6)	76 (25.2)
Height/cm	162.86±5.10	162.79±5.42	0.22	0.824
Pre-pregnancy weight/kg	53.98±5.61	74.54±11.88	29.64	< 0.001
Pre-pregnancy BMI/(kg/m²)	20.34±1.75	28.07±3.85	34.46	< 0.001
Underweight	329 (14.2)	0 (0.0)	2 294.87	< 0.001
Normal weight	1 992 (85.8)	34 (11.3)
Overweight	0 (0.0)	131 (43.4)
Obese	0 (0.0)	137 (45.4)
Weight before delivery/kg	67.78±7.58	84.46±12.88	22.01	< 0.001
Gestational weight gain/kg	13.81±4.92	9.92±6.41	10.16	< 0.001
Insufficient	263 (11.3)	79 (26.2)	61.10	< 0.001
Adequate	1 096 (47.3)	93 (30.8)
Excessive	959 (41.4)	130 (43.0)
Systolic blood pressure/mmHg	111.61±9.95	122.41±11.65	15.39	< 0.001
Diastolic blood pressure/mmHg	66.02±7.91	73.97±9.26	14.27	< 0.001
Education level
Below bachelor’s degree	439 (18.9)	86 (28.5)	14.67	< 0.001
Bachelor’s degree or higher	1 882 (81.1)	216 (71.5)
Primiparous	2 263 (97.5)	295 (97.7)	< 0.001	1.000
Chronic hypertension history	0 (0.0)	27 (8.9)	200.98	< 0.001
Type 2 diabetes mellitus history	0 (0.0)	25 (8.3)	185.32	< 0.001
Adverse pregnancy outcome
Cesarean section	861 (37.1)	190 (62.9)	73.11	< 0.001
Gestational diabetes mellitus	362 (15.6)	121 (40.1)	104.88	< 0.001
Pregnancy-associated hypertension	88 (3.8)	38 (12.6)	43.26	< 0.001
Preterm birth	82 (3.5)	24 (7.9)	12.31	< 0.001
Large for gestational age	158 (6.8)	49 (16.2)	31.26	< 0.001
Small for gestational age	336 (14.5)	39 (12.9)	0.42	0.517
Postpartum hemorrhage	149 (6.4)	15 (5.0)	0.73	0.393

Adverse pregnancy outcome	BMI abnormal group (n=268)	Glucose abnormal group (n=46)	Blood pressure abnormal group (n=40)	HDL-C abnormal group (n=164)	TG abnormal group (n=83)	χ²	P
Cesarean section	166 (61.94)	34 (73.91)	26 (65.00)	102 (62.20)	48 (57.83)	3.48	0.481
Gestational diabetes mellitus	107 (39.93)	33 (71.74)	19 (47.50)	64 (39.02)	37 (44.58)	17.96	0.001
Pregnancy associated hypertension	35 (13.06)	5 (10.87)	4 (10.00)	21 (12.80)	10 (12.05)	0.45	0.978
Preterm birth	21 (7.84)	4 (8.70)	5 (12.50)	10 (6.10)	8 (9.64)	2.25	0.689
Large for gestational age	44 (16.42)	11 (23.91)	8 (20.00)	22 (13.41)	18 (21.69)	4.63	0.328
Small for gestational age	34 (12.69)	5 (10.87)	7 (17.50)	21 (12.80)	11 (13.25)	0.94	0.919
Postpartum hemorrhage	12 (4.48)	4 (8.70)	1 (2.50)	9 (5.49)	6 (7.23)	2.66	0.617

Adverse pregnancy outcome	Control group (n=2 321)	Mild CMRF abnormality group (n=104)	Moderate CMRF abnormality group (n=125)	Severe CMRF abnormality group (n=73)	χ²	P
Cesarean section	861 (37.1)	65 (62.50)	78 (62.40)	47 (64.38)	74.26	< 0.001
Gestational diabetes mellitus	362 (15.6)	36 (34.62)	48 (38.40)	37 (50.68)	114.27	< 0.001
Pregnancy-associated hypertension	88 (3.8)	10 (9.62)	19 (15.20)	9 (12.33)	49.05	< 0.001
Preterm birth	82 (3.5)	7 (6.73)	11 (8.80)	6 (8.22)	14.07	0.003
Large for gestational age	158 (6.8)	19 (18.27)	13 (10.40)	17 (23.29)	43.97	< 0.001
Small for gestational age	336 (14.5)	11 (10.58)	19 (15.20)	9 (12.33)	1.56	0.669
Postpartum hemorrhage	149 (6.4)	3 (2.88)	8 (6.40)	4 (5.48)	2.20	0.532

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