基于内蒙古地区的非传统脂质参数与脑卒中的关联性研究

刘敏; 包含; 徐肖倩; 闫涛; 朱浩; 张楠; 赵羽芊; 田梓璇; 毕艳青; 闫文艳; 张星光

doi:10.16462/j.cnki.zhjbkz.2022.02.003

基于内蒙古地区的非传统脂质参数与脑卒中的关联性研究

doi: 10.16462/j.cnki.zhjbkz.2022.02.003

1.
010110 呼和浩特，内蒙古医科大学公共卫生学院卫生统计学教研室
2.
010110 呼和浩特，内蒙古医科大学公共卫生学院环境与职业卫生学教研室
3.
010110 呼和浩特，内蒙古医科大学公共卫生学院卫生毒理学教研室

基金项目:

内蒙古自治区自然科学基金项目 2020MS08048

详细信息

通讯作者:
张星光，E-mail: zxg311@126.com

中图分类号: R743.3
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- 被引次数: 0
出版历程
- 收稿日期: 2020-11-02
- 修回日期: 2021-01-12
- 网络出版日期: 2022-02-10
- 刊出日期: 2022-02-10

The associations of Non-traditional lipid profiles with stroke: based on Inner Mongolia population

1.
Department of Statistics, School of Public Health, Inner Mongolia Medical University, Huhhot 010110, China
2.
Department of Environment and Occupational Hygiene, School of Public Health, Inner Mongolia Medical University, Huhhot 010110, China
3.
Department of Toxicology, School of Public Health, Inner Mongolia Medical University, Huhhot 010110, China

Funds:

Inner Mongolia Natural Science Foundation 2020MS08048

More Information

Corresponding author: ZHANG Xing-guang, E-mail: zxg311@126.com

摘要

摘要: 目的非传统脂质参数已被证实与心血管疾病有关，而内蒙古地区作为脑卒中高发和特定的血脂特征地区，非传统脂质参数与脑卒中风险的关联性研究较少。本研究利用内蒙古地区“心血管病高危人群早期筛查与综合干预项目”探索内蒙古地区非传统脂质参数与脑卒中的关联。方法 2015―2017年，收集中国北部内蒙古地区35~75岁常住人群的人口学基本信息及各项血脂指标，最终纳入32 518人参与本项研究。将各脂质参数分为四分位，以第1四分位为参照，采用多因素Logistic回归分析模型探索非传统脂质参数与脑卒中的OR值及95% CI值。结果本研究含脑卒中患者1 949人，以脑卒中为因变量，调整相关因素后的Logistic回归分析模型结果表明，以各非传统脂质参数第1四分位为参照，第4四分位的TC/HDL-C、LDL-C/HDL-C、TG/HDL-C与脑卒中有关，其对应OR值分别为1.390(95% CI: 1.206~1.601)、1.380(95% CI: 1.201~1.585)及1.473(95% CI: 1.276~1.699)；且随着各脂质参数水平的升高，脑卒中风险增加(均有P < 0.001)。在不同性别、年龄中除非高密度脂蛋白胆固醇(Non-high density lipoprotein-cholesterol, Non-HDL-C)外，TC/HDL-C、LDL-C/HDL-C及TG/HDL-C与脑卒中风险相关。结论 TC/HDL-C、LDL-C/HDL-C及TG/HDL-C为脑卒中的危险因素，相比于传统脂质参数，非传统脂质参数与脑卒中的关联更强，其可作为脑卒中风险分层及一级预防的新指标。
- 非传统脂质参数 /
- 脑卒中 /
- 内蒙古
Abstract: Objective Non-traditional lipid profiles are recognized as predictors for cardiovascular disease, but there are few researches on the association between non-traditional lipid profiles and stroke risk in Inner Mongolia. The purpose of this study was to explore the association between non-traditional lipid profiles and stroke in Inner Mongolia through the Program of Screening and Intervention Subjects with High-Risk Cardiovascular Diseases Survey. Methods From 2015 to 2017, demographic basic information and various blood lipid indicators were collected from permanent residents aged 35-75 in Inner Mongolia, North China. A total of 32 518 people was finally included in this study. We categorized plasma lipid measurements into quartile and calculated odds ratios (ORs) and their 95% confidence intervals (CIs) using adjusted Multivariate Logistic regression models. Results The study included 1 949 stroke patients. Comparing with the lowest quarter, the OR of stroke risk in the highest were 1.390 (95% CI: 1.206-1.601) for total cholesterol/ high-density lipoprotein-cholesterol(TC/HDL-C), 1.380 (95% CI: 1.201-1.585) for low-density lipoprotein-cholesterol/ high-density lipoprotein-cholesterol(LDL-C/HDL-C), and 1.473 (95% CI: 1.276-1.699) for triglycerides/ high-density lipoprotein-cholesterol(TG/HDL-C), respectively. Higher lipid profiles related to an increased risk for stroke (all P < 0.001). The TC/HDL-C, LDL-C/HDL-C and TG/HDL-C were still associated with the risk of stroke in different genders and age groups except for Non-high-density lipoprotein cholesterol (Non-HDL-C). Conclusions We found that TC/HDL-C, LDL-C/HDL-C and TG/HDL-C were associated with an increased risk of stroke. Compared with traditional lipid parameters, non-traditional lipids are more strongly associated with stroke, which can be used as a new indicator for risk stratification and primary prevention of stroke.
- Non-traditional lipids /
- Stroke /
- Inner mongolia

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图 1 不同性别中非传统脂质参数与脑卒中的多因素Logistic回归分析

注：Q1、Q2、Q3及Q4分别为第1四分位、第2四分位、第3四分位、第4四分位，多因素Logistic回归分析模型调整因素含性别、年龄、民族、BMI、是否吸烟、是否饮酒、目前是否患有高血压、目前是否患有糖尿病、是否服用调脂药物及脑卒中家族史情况，以各非传统脂质参数的第1四分位为参照。

Figure 1. Logistic regression analysis of the non-traditional lipids and stroke in different genders

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图 2 不同年龄组非传统脂质参数与脑卒中的多因素Logistic回归分析

Figure 2. Logistic regression analysis of the non-traditional lipids and stroke in different age groups

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表 1 调查人群基本特征[n(%)]

Table 1. Baseline characteristics of the population [n(%)]

变量	脑卒中	非脑卒中	合计	χ²/Z值	P值
年龄(岁)				363.562	< 0.001 ^ac
＜55	569(29.19)	15 733(51.47)	16 302(50.13)
≥55	1 380(70.81)	14 836(48.53)	16 216(49.87)
性别				27.159	< 0.001 ^ac
女性	1 017(52.18)	17 789(58.19)	18 806(57.83)
男性	932(47.82)	12 780(41.81)	13 712(42.17)
民族				6.826	0.009 ^ac
汉族	1 820(93.38)	28 034(91.71)	29 854(91.81)
蒙古族	129(6.62)	2 535(8.29)	2 664(8.19)
BMI [M(P₂₅, P₇₅), kg/m²]	25.86(23.63, 28.28)	25.95(23.65, 28.27)	25.94(23.65, 28.27)	-0.694	0.488 ^b
吸烟	479(24.58)	8 159(26.69)	8 638(26.56)	4.196	0.041 ^ac
饮酒	572(29.35)	9 734(31.84)	10 306(31.69)	5.266	0.022 ^ac
高血压病史	1 086(55.72)	11 929(39.02)	13 015(40.02)	212.806	< 0.001 ^ac
糖尿病病史	252(12.93)	2 886(9.44)	3 138(9.65)	25.577	< 0.001 ^ac
传统脂质参数[M(P₂₅, P₇₅), mmol/L]
TC	4.55(3.84, 5.22)	4.53(3.92, 5.23)	4.53(3.91, 5.23)	-1.372	0.170 ^b
TG	1.40(1.04, 2.03)	1.37(1.00, 1.94)	1.37(1.00, 1.94)	-3.495	< 0.001 ^bc
HDL-C	1.30(1.07, 1.56)	1.36(1.11, 1.65)	1.36(1.11, 1.65)	-6.585	< 0.001 ^bc
LDL-C	2.47(1.94, 3.08)	2.43(1.92, 3.02)	2.44(1.92, 3.02)	-1.026	0.305 ^b
血压参数[M(P₂₅, P₇₅), mm Hg]
SBP	147.00(132.50, 161.00)	145.00(128.50, 163.50)	145.00(129.00, 163.00)	-3.021	0.003 ^bc
DBP	86.50(78.50, 94.25)	86.50(78.50, 96.50)	86.50(78.50, 96.50)	-2.191	0.028 ^bc
非传统脂质参数[M(P₂₅, P₇₅), mmol/L]
Non-HDL-C	3.20(2.58, 3.85)	3.14(2.55, 3.80)	3.15(2.55, 3.80)	-1.298	0.194 ^b
TC/HDL-C	3.45(2.85, 4.20)	3.35(2.73, 4.12)	3.35(2.74, 4.12)	-4.278	< 0.001 ^bc
LDL-C/HDL-C	1.91(1.42, 2.46)	1.81(1.33, 2.40)	1.81(1.34, 2.40)	-4.497	< 0.001 ^bc
TG/HDL-C	1.12(0.73, 1.74)	1.01(0.66, 1.61)	1.02(0.66, 1.62)	-5.905	< 0.001 ^bc
注：^a表示采用χ²检验进行检验；^b表示采用Mann-Whitney U检验；^c表示与0.05相比，差异有统计学意义。

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表 2 非传统脂质参数与脑卒中的多因素Logistic回归分析模型[OR (95% CI)值]

Table 2. Logistic regression analysis of the non-traditional lipids and stroke [OR (95% CI)值]

脂质参数(mmol/L)	第1四分位组	第2四分位组	第3四分位组	第4四分位组	P_趋势值
Non-HDL-C	< 2.550	2.550~ < 3.150	3.150~ < 3.800	≥3.800
模型1	1.000	0.951(0.832~1.087)	1.039(0.912~1.185)	1.024(0.897~1.168)	0.455
模型2	1.000	1.001(0.874~1.147)	1.117(0.977~1.278)	1.127(0.985~1.291)	0.032
TC/HDL-C	< 2.736	2.736~ < 3.352	3.352~ < 4.121	≥4.121
模型1	1.000	1.225(1.069~1.404) ^a	1.296(1.133~1.482) ^a	1.272(1.112~1.456) ^a	< 0.001
模型2	1.000	1.271(1.106~1.460) ^a	1.370(1.192~1.575) ^a	1.390(1.206~1.601) ^a	< 0.001
LDL-C/HDL-C	< 1.339	1.339~ < 1.815	1.815~ < 2.400	≥2.400
模型1	1.000	1.121(0.977~1.286)	1.277(1.119~1.458) ^a	1.233(1.079~1.410) ^a	< 0.001
模型2	1.000	1.183(1.029~1.360) ^a	1.388(1.211~1.590) ^a	1.380(1.201~1.585) ^a	< 0.001
TG/HDL-C	< 0.662	0.662~ < 1.016	1.016~ < 1.622	≥1.622
模型1	1.000	1.174(1.022~1.349) ^a	1.323(1.155~1.516) ^a	1.463(1.279~1.673) ^a	< 0.001
模型2	1.000	1.166(1.012~1.343) ^a	1.312(1.138~1.511) ^a	1.473(1.276~1.699) ^a	< 0.001
TC	< 3.910	3.910~ < 4.530	4.530~ < 5.230	≥5.230
模型1	1.000	0.791(0.693~0.903) ^a	0.908(0.798~1.033)	0.838(0.733~0.957) ^a	0.063
模型2	1.000	0.848(0.742~0.970) ^a	0.994(0.871~1.133)	0.926(0.808~1.060)	0.709
TG	< 1.000	1.000~ < 1.370	1.370~ < 1.940	≥1.940
模型1	1.000	1.112(0.973~1.271)	1.100(0.962~1.258)	1.244(1.091~1.420) ^a	0.002
模型2	1.000	1.113(0.971~1.274)	1.077(0.937~1.237)	1.218(1.061~1.399) ^a	0.012
HDL-C	< 1.110	1.110~ < 1.360	1.360~ < 1.650	≥1.650
模型1	1.000	0.815(0.719~0.924) ^a	0.772(0.679~0.878) ^a	0.622(0.542~0.713) ^a	< 0.001
模型2	1.000	0.796(0.701~0.904) ^a	0.749(0.656~0.855) ^a	0.604(0.523~0.698) ^a	< 0.001
LDL-C	< 1.920	1.920~ < 2.440	2.440~ < 3.020	≥3.020
模型1	1.000	0.964(0.844~1.101)	1.002(0.878~1.143)	1.019(0.893~1.161)	0.652
模型2	1.000	1.040(0.909~1.190)	1.107(0.968~1.266)	1.146(1.002~1.310) ^a	0.030
注：模型1：调整因素含性别、年龄；模型2：调整因素含性别、年龄、民族、BMI、是否吸烟、是否饮酒、目前是否患有高血压、目前是否患有糖尿病、是否服用调脂药物及脑卒中家族史情况；以各非传统脂质参数第1四分位为参照，^a表示以第1四分位为参照，P < 0.05。

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