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1990—2019年中国卒中危险因素的归因负担及变化趋势

吴琼,  王晨冉,  赵燕,  韩丽媛,  刘世炜

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文章导航 > 中华疾病控制杂志  > 2022 >  26(1): 28-33, 79
吴琼, 王晨冉, 赵燕, 韩丽媛, 刘世炜. 1990—2019年中国卒中危险因素的归因负担及变化趋势[J]. 中华疾病控制杂志, 2022, 26(1): 28-33, 79. doi: 10.16462/j.cnki.zhjbkz.2022.01.005
引用本文: 吴琼, 王晨冉, 赵燕, 韩丽媛, 刘世炜. 1990—2019年中国卒中危险因素的归因负担及变化趋势[J]. 中华疾病控制杂志, 2022, 26(1): 28-33, 79. doi: 10.16462/j.cnki.zhjbkz.2022.01.005
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WU Qiong, WANG Chen-ran, ZHAO Yan, Han Li-yuan, LIU Shi-wei. The burden of stroke attributable to risk factors and their trends from 1990 to 2019 in China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(1): 28-33, 79. doi: 10.16462/j.cnki.zhjbkz.2022.01.005
Citation: WU Qiong, WANG Chen-ran, ZHAO Yan, Han Li-yuan, LIU Shi-wei. The burden of stroke attributable to risk factors and their trends from 1990 to 2019 in China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2022, 26(1): 28-33, 79. doi: 10.16462/j.cnki.zhjbkz.2022.01.005
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1990—2019年中国卒中危险因素的归因负担及变化趋势

doi: 10.16462/j.cnki.zhjbkz.2022.01.005
  • 1.

    315010 宁波，中国科学院大学宁波华美医院

  • 2.

    010059 呼和浩特，内蒙古医科大学公共卫生学院

  • 3.

    100081 北京，中国疾病预防控制中心妇幼保健中心

  • 4.

    100050 北京，中国疾病预防控制中心控烟办公室

基金项目: 

国家自然科学基金 81872721

国家自然科学基金 82173648

国家重点研发计划 2017YFC1310902

详细信息
    通讯作者:

    刘世炜，E-mail: shiwei_liu@aliyun.com

    韩丽媛，E-mail: hanliyuan@ucas.ac.cn

  • 中图分类号: R181.2; R743.3

The burden of stroke attributable to risk factors and their trends from 1990 to 2019 in China

  • 1.

    HwaMei Hospital, University of Chinese Academy of Sciences, Nibo 315010, China

  • 2.

    School of Public Health, Inner Mongolia Medical University, Huhehoot 010059, China

  • 3.

    National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China

  • 4.

    Tobacco Control Office, Chinese Center for Disease Control and Prevention, Beijing 100050, China

Funds: 

National Natural Science Foundation of China 81872721

National Natural Science Foundation of China 82173648

National Key Research and Development Program of China 2017YFC1310902

More Information

    摘要
  • 摘要:   目的  分析1990—2019年中国卒中及其亚型的危险因素归因负担与变化趋势。  方法  利用2019年全球疾病负担研究开放数据，用人群归因分值(population attributable fraction, PAF)和伤残调整生命年(disability-adjusted life years, DALYs)探讨1990—2019年中国卒中及其亚型的危险因素归因负担及变化趋势。  结果  卒中危险因素主要包括环境、行为和代谢三大类，因其亚型不同而有所不同。与蛛网膜下腔出血(subarachnoid hemorrhage, SAH)的15种危险因素(室外空气污染、高温、低温、铅暴露、室内空气污染、红肉摄入过多、高钠饮食、吸烟、吸二手烟、蔬菜摄入不足、水果摄入不足、纤维摄入不足、高BMI、高SBP、高FPG)相比，颅内出血(intracerebral hemorrhage, ICH)、缺血性卒中(ischemic stroke, IS)的危险因素还包括饮酒与肾功能不全，IS的危险因素还有低体力活动、全谷物摄入不足、高LDL-C。2019年，由IS、ICH、SAH导致的1 861.91、1 989.18、204.29万人年DALYs中，分别有68.91%、68.83%、66.35%归因于代谢因素，IS危险因素主要是高SBP(50.94%)、室外空气污染(26.81%)、高LDL-C(20.69%)；ICH、SAH危险因素主要是高SBP(58.18%、58.01%)、室外空气污染(28.82%、30.09%)、高钠饮食(24.40%、25.11%)。1990—2019年，室外空气污染、高BMI、饮酒、红肉摄入过多导致的IS和ICH DALYs增幅较大，分别为410.46%、320.48%、277.03%、245.41%和168.93%、132.07%、60.01%、84.58%，而SAH仅因室外空气污染增加4.47%。   结论  导致卒中疾病负担的危险因素大多是可防可控的，因其亚型不同而有所不同，建议在考虑成本效益的情况下采取有针对性的干预措施。
    Abstract:   Objective  To investigate the burden of stroke and its subtypes attributable to risk factors, and their trends from 1990 to 2019 in China.  Methods  Based on the open access data from the 2019 global burden of disease study, we used population attributable-faction (PAF) and disability-adjusted life years (DALYs) to explore the burden of stroke and its subtypes attributable to risk factors, and the changes from 1990 to 2019.  Results  In general, the risk factors of stroke can be classified as environmental, behavioral and metabolic factors, which vary in subtypes of stroke for specific factors. Compared with the 15 risk factors of subarachnoid hemorrhage (SAH) (ambient particulate matter pollution, high temperature, low temperature, lead exposure, household air pollution from solid fuels, diet high in red meat, diet high in sodium, smoking, secondhand smoke, diet low in vegetables, diet low in fruits, diet low in fiber, high BMI, high systolic blood pressure, and high fasting plasma glucose), the factors of alcohol use and kidney dysfunction were also included in intracerebral hemorrhage (ICH) and ischemic stroke (IS), and low physical activity, diet low in whole grains, and high LDL-C in IS. In 2019, 68.91%, 68.83% and 66.35% of the 18.62, 19.89 and 2.04 million person years DALYs caused by IS, ICH and SAH were attributed to metabolic factors. The burden of IS was mainly attributed to high systolic blood pressure (50.94%), ambient particulate matter pollution (26.81%), high LDL-C (20.69%); The burden of ICH and SAH were mainly attributed to high systolic blood pressure (58.18% and 58.01%), ambient particulate matter pollution (28.82% and 30.09%), and diet high in sodium (24.40% and 25.11%). From 1990 to 2019, the DALYs of IS and ICH attributable to ambient particulate matter pollution, high BMI, alcohol use and diet high in red meat significantly increased by 410.46%, 320.48%, 277.03%, 245.41% and 168.93%, 132.07%, 60.01%, 84.58%, respectively, and only ambient particulate matter pollution increased by 4.47% for the DALYs of SAH.  Conclusion  Most of the risk factors of stroke are preventable and controllable, and vary considerably in subtypes of stroke, suggesting tailored measures of preventive interventions with consideration of cost-effectiveness.
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  • 表  1  1990—2019年中国缺血性卒中PAF值和归因DALYs变化

    Table  1.   The changes on the PAF and the DALYs attributable to risk factors for IS in China from 1990 to 2019

    变量 PAF值(%) DALYs(万人年) DALYs率(/10万)
    1990年 2019年 变化率(%) 1990年 2019年 变化率(%) 1990年 2019年 变化率(%)
    环境因素 48.53 41.58 -14.32 435.10 889.61 104.46 367.58 625.45 70.15
      室外空气污染 12.54(7) 26.81(2) 113.80(1) 112.40(7) 573.78(2) 410.48(1) 94.96(7) 403.40(2) 324.81(1)
      高温 0.06(20) 0.08(20) 33.33(5) 0.56(20) 1.68(20) 200.00(5) 0.47(20) 1.18(20) 151.06(5)
      低温 8.34(9) 7.66(10) -8.15(12) 74.80(9) 163.78(10) 118.96(12) 63.19(9) 115.15(10) 82.23(12)
      铅暴露 5.87(13) 5.32(12) -9.37(14) 52.69(13) 113.68(12) 115.75(14) 44.52(13) 79.93(12) 79.54(14)
      室内空气污染 27.94(2) 6.34(11) -77.33(19) 250.53(2) 135.43(11) -45.94(19) 211.65(2) 95.21(11) -55.02(19)
    行为因素 53.44 50.06 -6.32 479.16 1 071.18 123.55 404.80 753.10 86.04
      饮酒 2.08(19) 3.30(16) 58.65(3) 18.66(19) 70.54(16) 278.03(3) 15.76(19) 49.59(16) 214.66(3)
      红肉摄入过多 6.38(11) 9.23(8) 44.67(4) 57.21(11) 197.61(8) 245.41(4) 48.33(11) 138.94(8) 187.48(4)
      低体力活动 2.96(17) 3.07(17) 3.72(8) 26.56(17) 65.59(17) 146.95(8) 22.44(17) 46.11(17) 105.48(8)
      全谷物摄入不足 5.43(14) 4.95(13) -8.84(13) 48.64(14) 106.11(13) 118.15(13) 41.09(14) 74.60(13) 81.55(13)
      高钠饮食 21.10(4) 18.61(5) -11.80(15) 189.25(4) 397.93(5) 110.27(15) 159.88(4) 279.77(5) 74.99(15)
      吸二手烟 4.70(15) 3.79(15) -19.36(16) 42.10(15) 80.98(15) 92.35(16) 35.57(15) 56.93(15) 60.05(16)
      水果摄入不足 6.34(12) 3.91(14) -38.33(17) 56.88(12) 83.83(14) 47.38(17) 48.06(12) 58.94(14) 22.64(17)
      纤维摄入不足 4.35(16) 1.74(18) -60.00(18) 39.03(16) 37.10(18) -4.94(18) 32.97(16) 26.09(18) -20.87(18)
      蔬菜摄入不足 2.48(18) 0.26(19) -89.52(20) 22.23(18) 5.65(19) -74.58(20) 18.78(18) 3.97(19) -78.86(20)
      吸烟 19.63(5) 19.49(4) -0.71(10) 176.08(5) 417.25(4) 136.97(10) 148.76(5) 293.36(4) 97.20(10)
    代谢因素 62.88 68.91 9.59 563.87 1 474.18 161.44 476.37 1 036.44 117.57
      高BMI 7.22(10) 12.73(7) 76.32(2) 64.75(10) 272.26(7) 320.48(2) 54.70(10) 191.42(7) 249.95(2)
      高SBP 42.55(1) 50.94(1) 19.72(6) 381.60(1) 1 089.68(1) 185.56(6) 322.38(1) 766.11(1) 137.64(6)
      高FPG 15.06(6) 17.13(6) 13.75(7) 135.26(6) 366.73(6) 171.13(7) 114.27(6) 257.83(6) 125.63(7)
      肾功能不全 8.56(8) 8.62(9) 0.70(9) 76.77(8) 184.60(9) 140.46(9) 64.86(8) 129.79(9) 100.11(9)
      高LDL-C 21.73(3) 20.69(3) -4.79(11) 194.75(3) 442.77(3) 127.35(11) 164.53(3) 311.29(3) 89.20(11)
    合计 86.05 87.03 1.14 771.52 1 861.91 141.33 651.80 1 309.04 100.83
    注：括号内数字为排序。
    下载: 导出CSV

    表  2  1990—2019年中国颅内出血PAF值和归因DALYs变化

    Table  2.   The changes on the PAF and the DALYs attributable to risk factors for ICH in China from 1990 to 2019

    变量 PAF值(%) DALYs(万人年) DALYs率(/10万)
    1990年 2019年 变化率(%) 1990年 2019年 变化率(%) 1990年 2019年 变化率(%)
    环境因素 51.88 46.23 -10.89 982.45 1 026.92 4.53 829.99 721.99 -13.01
      室外空气污染 12.58(6) 28.82(2) 129.09(1) 238.12(6) 640.39(2) 168.93(1) 201.17(6) 450.23(2) 123.81(1)
      高温 0.08(17) 0.10(17) 25.00(5) 1.51(17) 2.34(17) 54.97(5) 1.28(17) 1.64(17) 28.13(5)
      低温 9.78(10) 9.63(9) -1.53(10) 185.17(10) 213.92(9) 15.53(10) 156.43(10) 150.40(9) -3.85(10)
      铅暴露 7.38(13) 6.20(13) -15.99(13) 139.96(13) 137.70(13) -1.61(13) 118.24(13) 96.81(13) -18.12(13)
      室内空气污染 30.09(2) 7.68(11) -74.48(16) 569.76(2) 170.55(11) -70.07(16) 481.34(2) 119.91(11) -75.09(16)
    行为因素 59.71 59.61 -0.17 1 130.95 1 324.57 17.12 955.45 931.25 -2.53
      红肉摄入过多 7.63(12) 11.99(8) 57.13(3) 144.27(12) 266.29(8) 84.58(3) 121.88(12) 187.22(8) 53.61(3)
      饮酒 10.04(9) 13.69(7) 36.35(4) 190.24(9) 304.40(7) 60.01(4) 160.72(9) 214.01(7) 33.16(4)
      吸烟 21.94(4) 24.21(4) 10.35(8) 415.76(4) 538.40(4) 29.50(8) 351.25(4) 378.53(4) 7.77(8)
      高钠饮食 25.53(3) 24.40(3) -4.43(11) 483.77(3) 542.13(3) 12.06(11) 408.70(3) 381.15(3) -6.74(11)
      吸二手烟 5.41(14) 4.61(14) -14.78(12) 102.44(14) 102.29(14) -0.15(12) 86.55(14) 71.92(14) -16.90(12)
      水果摄入不足 10.85(8) 7.12(12) -34.38(14) 205.84(8) 158.39(12) -23.05(14) 173.90(8) 111.36(12) -35.96(14)
      纤维摄入不足 4.91(15) 2.22(15) -54.79(15) 93.08(15) 49.41(15) -46.92(15) 78.64(15) 34.74(15) -55.82(15)
      蔬菜摄入不足 3.85(16) 0.27(16) -92.99(17) 72.81(16) 6.12(16) -91.59(17) 61.51(16) 4.30(16) -93.01(17)
    代谢因素 57.30 68.83 20.12 1 085.56 1 528.42 40.80 917.10 1 074.58 17.17
      高BMI 11.10(7) 21.96(5) 97.84(2) 210.21(7) 487.83(5) 132.07(2) 177.59(7) 342.97(5) 93.12(2)
      高SBP 46.58(1) 58.18(1) 24.90(6) 882.71(1) 1 291.90(1) 46.36(6) 745.73(1) 908.28(1) 21.80(6)
      高FPG 13.24(5) 15.79(6) 19.26(7) 250.48(5) 350.66(6) 40.00(7) 211.61(5) 246.54(6) 16.51(7)
      肾功能受损 7.85(11) 8.22(10) 4.71(9) 148.58(11) 182.67(10) 22.94(9) 125.53(11) 128.43(10) 2.31(9)
    合计 86.01 89.56 4.13 1 628.71 1 989.18 22.13 1 375.97 1 398.52 1.64
    注：括号内数字为排序。
    下载: 导出CSV

    表  3  1990—2019年中国蛛网膜下腔出血PAF值和归因DALYs变化

    Table  3.   The changes on the PAF and the DALYs attributable to risk factors for SAH in China from 1990 to 2019

    变量 PAF值(%) DALYs(万人年) DALYs率(/10万)
    1990年 2019年 变化率(%) 1990年 2019年 变化率(%) 1990年 2019年 变化率(%)
    环境因素 50.90 46.92 -7.82 291.53 110.06 -62.25 246.29 77.38 -68.58
      室外空气污染 11.78(6) 30.09(2) 155.43(1) 67.54(6) 70.56(2) 4.47(1) 57.06(6) 49.61(2) -13.06(1)
      高温 0.07(15) 0.08(15) 14.29(7) 0.42(15) 0.19(15) -54.76(7) 0.35(15) 0.13(15) -62.86(7)
      低温 9.74(9) 8.88(8) -8.83(9) 55.84(9) 20.86(8) -62.64(9) 47.17(9) 14.67(8) -68.90(9)
      铅暴露 7.23(11) 5.81(11) -19.64(11) 41.53(11) 13.65(11) -67.13(11) 35.08(11) 9.59(11) -72.66(11)
      室内空气污染 29.96(2) 8.03(9) -73.20(14) 171.46(2) 18.83(9) -89.02(14) 144.85(2) 13.24(9) -90.86(14)
    行为因素 53.73 55.23 2.79 308.30 129.67 -57.94 260.46 91.16 -65.00
      红肉摄入过多 7.45(10) 12.89(7) 73.02(3) 42.68(10) 30.23(7) -29.17(3) 36.06(10) 21.26(7) -41.04(3)
      吸烟 19.41(4) 23.07(5) 18.86(6) 112.56(4) 54.28(5) -51.78(6) 95.09(4) 38.16(5) -59.87(6)
      高钠饮食 24.15(3) 25.11(3) 3.98(8) 138.52(3) 58.96(3) -57.44(8) 117.03(3) 41.46(3) -64.57(8)
      吸二手烟 5.61(12) 4.92(12) -12.30(10) 31.90(12) 11.53(12) -63.86(10) 26.95(12) 8.11(12) -69.91(10)
      水果摄入不足 10.83(8) 7.60(10) -29.82(12) 61.86(8) 17.84(10) -71.16(12) 52.26(8) 12.54(10) -76.00(12)
      纤维摄入不足 5.02(13) 2.59(13) -48.41(13) 28.67(13) 6.05(13) -78.90(13) 24.22(13) 4.26(13) -82.41(13)
      蔬菜摄入不足 3.83(14) 0.27(14) -92.95(15) 21.94(14) 0.63(14) -97.13(15) 18.54(14) 0.44(14) -97.63(15)
    代谢因素 51.61 66.35 28.56 295.61 155.60 -47.36 249.74 109.39 -56.20
      高BMI 10.99(7) 25.05(4) 127.93(2) 62.68(7) 58.74(4) -6.29(2) 52.95(7) 41.30(4) -22.00(2)
      高SBP 44.45(1) 58.01(1) 30.51(4) 254.67(1) 136.05(1) -46.58(4) 215.15(1) 95.65(1) -55.54(4)
      高FPG 12.45(5) 15.31(6) 22.97(5) 71.32(5) 35.93(6) -49.62(5) 60.25(5) 25.26(6) -58.07(5)
    合计 81.13 87.10 7.36 464.72 204.29 -56.04 392.60 143.63 -63.42
    注：括号内数字为排序。
    下载: 导出CSV
    • 参考文献(24)
  • [1] GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet, 2020, 396(10258): 1204-1222. DOI: 10.1016/S0140-6736(20)30925-9.
    [2] 《中国脑卒中防治报告》编写组. 《中国脑卒中防治报告2019》概要[J]. 中国脑血管病杂志, 2020, 17(5): 272-281. DOI: 10.3969/j.issn.1672-5921.2020.05.008.

    Report on Stroke Prevention and Treatment in China Writing Group. Brief report on stroke prevention and treatment in China, 2019[J]. Chin J Cerebrovasc Dis, 2020, 17(5): 272-281. DOI: 10.3969/j.issn.1672-5921.2020.05.008.
    [3] Hachinski V, Azarpazhooh MR. Stroke is a burdensome but preventable brain disorder[J]. Lancet Neurol, 2016, 15(9): 892-893. DOI: 10.1016/S1474-4422(16)30120-X.
    [4] GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet, 2020, 396(10258): 1223-1249. DOI: 10.1016/S0140-6736(20)30752-2.
    [5] 宁佩珊, 胡国清. 有害饮酒所致疾病负担的归因方法综述[J]. 中华疾病控制杂志, 2015, 19(10): 1047-1050. DOI: 10.16462/j.cnki.zhjbkz.2015.10.019.

    Ning PS, Hu GQ. Review on the methods of alcohol-attributable burden of diseases[J]. Chin J Dis Control Prev 2015, 19(10): 1047-1050. DOI: 10.16462/j.cnki.zhjbkz.2015.10.019.
    [6] 徐晓慧, 杨静, 王黎君, 等. 2017年中国人群高血清低密度脂蛋白胆固醇归因疾病负担研究[J]. 中华流行病学杂志, 2020, 41(6): 839-844. DOI: 10.3760/cma.j.cn112338-20191205-00861.

    Xu XH, Yang J, Wang LJ, et al. Burden of disease attributed to high level serum low-density lipoprotein cholesterol in China in 2017[J]. Chin J Epidemiol, 2020, 41(6): 839-844. DOI: 10.3760/cma.j.cn112338-20191205-00861.
    [7] Virani SS, Alonso A, Aparicio HJ, et al. Heart disease and stroke statistics-2021 update: a report from the American Heart Association[J]. Circulation, 2021, 143(8): e254-e743. DOI: 10.1161/cir.0000000000000950.
    [8] Ban J, Wang Q, Ma R, et al. Associations between short-term exposure to PM2.5 and stroke incidence and mortality in China: a case-crossover study and estimation of the burden[J]. Environ Pollut, 2021, 268(Pt A): 115743. DOI: 10.1016/j.envpol.2020.115743.
    [9] Puddey IB, Mori TA, Barden AE, et al. Alcohol and hypertension-new insights and lingering controversies[J]. Curr Hypertens Rep, 2019, 21(10): 79. DOI: 10.1007/s11906-019-0984-1.
    [10] 陈晶晶, 徐格林. 吸烟与卒中[J]. 医学研究生学报, 2020, 33(5): 454-459. DOI: 10.16571/j.cnki.1008-8199.2020.05.002.

    Chen JJ, Xu GL. Smoking and stroke[J]. J Med Postgraduates, 2020, 33(5): 454-459. DOI: 10.16571/j.cnki.1008-8199.2020.05.002.
    [11] Wang L, Du J, Cao W, et al. Trends of stroke attributable to high sodium intake at the global, regional, and national levels from 1990 to 2019: a population-based study[J]. Neurol Res, 2020, 43(6): 474-481. DOI: 10.1080/01616412.2020.1867950.
    [12] 刘娅飞. 基于孟德尔随机化探索代谢综合征相关指标间因果关系的研究[D]. 济南: 山东大学, 2018.

    Liu YF. Causality of metabolic syndrome related biomarkers based on mendelian randomization[D]. Jinan: Shandong University, 2018.
    [13] Spence JD. Diet for stroke prevention[J]. Stroke Vasc Neurol, 2018, 3(2): 44-50. DOI: 10.1136/svn-2017-000130.
    [14] 孟祥燕. 夏季高温对主要心脑血管疾病患病人数及相关理化指标影响研究[D]. 兰州: 兰州大学, 2020.

    Meng XY. The effect of high temperature in summer on the number of patients with major cardiovascular and cerebrovascular disease and related physicochemical indexes[D]. Lanzhou: Lanzhou University, 2020.
    [15] Tsai CF, Jeng JS, Anderson N, et al. Comparisons of risk factors for intracerebral hemorrhage versus ischemic stroke in Chinese patients[J]. Neuroepidemiology, 2017, 48(1-2): 72-78. DOI: 10.1159/000475667.
    [16] Tuttolomondo A, Puleo MG, Velardo MC, et al. Molecular biology of atherosclerotic ischemic strokes[J]. Int J Mol Sci, 2020, 21(24): 9372. DOI: 10.3390/ijms21249372.
    [17] 吴兴辰, 宋伟娜. 自发性脑出血和动脉瘤性蛛网膜下腔出血的常见因素[J]. 国外医学(脑血管疾病分册), 1997, 5(4): 243-244. https://www.cnki.com.cn/Article/CJFDTOTAL-NXGF199704031.htm

    Wu XC, Song WN. Common factors of spontaneous intracerebral hemorrhage and aneurysmal subarachnoid hemorrhage[J]. Cerebrovasc Dis Foreign Med Sci, 1997, 5(4): 243-244. https://www.cnki.com.cn/Article/CJFDTOTAL-NXGF199704031.htm
    [18] 张艳天. 我国大气污染的成因与防治[J]. 科技风, 2021, (3): 114-115. DOI:10.19392/j.cn-ki.1671-7341.202103055.

    Zhang YT. Cause and prevention of air pollution in China[J]. Technology Wind, 2021, (3): 114-115. DOI: 10.19392/j.cnki.1671-7341.202103055.
    [19] 柳海英. 缺血性脑卒中和出血性脑卒中患者发病前后的血压变化研究[J]. 中外医疗, 2015, 34(33): 103-104. DOI: 10.16662/j.cnki.1674-0742.2015.33.103.

    Liu HY. Changes of patient's blood pressure before and after ischemic and hemor-rhagic stroke[J]. China Foreign Med Treat, 2015, 34(33): 103-104. DOI: 10.16662/j.cnki.1674-0742.2015.33.103.
    [20] Li Z, Jiang Y, Li H, et al. China's response to the rising stroke burden[J]. BMJ, 2019, 364: l879. DOI: 10.1136/bmj.l879.
    [21] Luo L, Jiang J, Zhang G, et al. Stroke mortality attributable to ambient particulate matter pollution from 1990 to 2015 in China: an age-period-cohort and spatial autocorrelation analysis[J]. Int J Environ Res Public Health, 2017, 14(7): 772. DOI: 10.3390/ijerph14070772.
    [22] Yin P, Brauer M, Cohen AJ, et al. The effect of air pollution on deaths, disease burden, and life expectancy across China and its provinces, 1990-2017: an analysis for the Global Burden of Disease Study 2017[J]. Lancet Planet Health, 2020, 4(9): e386-e398. DOI: 10.1016/S2542-5196(20)30161-3.
    [23] 李娟娟, 靳荣荣, 张娟, 等. 国家慢性病综合防控示范区居民蔬菜水果摄入情况及影响因素分析[J]. 中华流行病学杂志, 2018, 39(4): 412-416. DOI: 10.3760/cma.j.issn.0254-6450.2018.04.005.

    Li JJ, Jin RR, Zhang J, et al. Study on consumption of vegetables and fruits and related influencing factors among residents from the national demonstration areas for comprehensive prevention and control of non-communicable diseases[J]. Chin J Epidemiol, 2018, 39(4): 412-416. DOI: 10.3760/cma.j.issn.0254-6450.2018.04.005.
    [24] 李丽, 欧阳一非, 王惠君, 等. 中国15省儿童青少年蔬菜和水果摄入状况[J]. 中国健康教育, 2020, 36(1): 3-7. DOI: 10.16168/j.cnki.issn.1002-9982.2020.01.001.

    Li L, Ouyang YF, Wang HJ, et al. Status of fruit and vegetable intake among children and adolescents in 15 provinces of China[J]. Chin J Heal Educ, 2020, 36(1): 3-7. DOI: 10.16168/j.cnki.issn.1002-9982.2020.01.001.
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