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WANG Jing Yu, WANG Yan, LIANG Xiao Hua, HUANG Ke Yong, LIU Fang Chao, CHEN Shu Feng, LU Xiang Feng, LI Jian Xin. Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China[J]. Biomedical and Environmental Sciences. doi: 10.3967/bes2024.083
Citation: WANG Jing Yu, WANG Yan, LIANG Xiao Hua, HUANG Ke Yong, LIU Fang Chao, CHEN Shu Feng, LU Xiang Feng, LI Jian Xin. Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China[J]. Biomedical and Environmental Sciences. doi: 10.3967/bes2024.083

Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China

doi: 10.3967/bes2024.083
Funds:  This research was supported by National Key Research and Development Program of China (2018YFE0115300, 2022YFC3600800, 2017YFC0211706), Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2021-I2M-1-010), National Natural Science Foundation of China (82073658, 82070473), National High Level Hospital Clinical Research Funding (2022-GSP-GG-1, 2022-GSP-GG-2), Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, CAMS (2019RU038), National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, CAMS (NCRC2020006).
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  • Author Bio:

    WANG Jing Yu, male, born in 1998, MD, majoring in cardiovascular epidemiology

    WANG Yan, female, born in 1985, MD, majoring in cardiovascular epidemiology

    LIANG Xiao Hua, female, born in 1982, PhD, majoring in etiology and prevention measures of cardiovascular diseases

  • Corresponding author: Correspondence should be addressed to LI Jian Xin, E-mail: leeljx@126.com, Tel: 86-10-60866572
  • WANG Jing Yu: Methodology, Formal analysis, Visualization, Writing-original draft, Writing- review & editing. WANG Yan: Methodology, Software, Writing-original draft, Writing- review & editing. LIANG Xiao Hua: Methodology, Software, Writing-original draft, Writing- review & editing. HUANG Ke Yong: Writing- review & editing. LIU Fang Chao: Funding acquisition, Writing- review & editing. CHEN Shu Feng: Funding acquisition, Writing- review & editing. LU Xiang Feng: Funding acquisition, Writing- review & editing. LI Jian Xin: Conceptualization, Funding acquisition, Writing- review & editing.
  • The authors have no competing interests to declare that are relevant to the content of this article.
  • &These authors contributed equally to this work.
  • Received Date: 2023-10-27
  • Accepted Date: 2024-04-10
  •   Objective  In recent decades, China has implemented a series of policies to address air pollution. We aimed to assess the health effects of these policies on stroke burden attributable to ambient fine particulate matter (PM2.5).  Methods  Joinpoint regression was applied to explore the temporal tendency of stroke burden based on data from the Global Burden of Disease 2019 study.  Results  The age-standardized rates of disability-adjusted life year (DALY) for stroke attributable to ambient PM2.5 in China, increased dramatically during 1990−2012, subsequently decreased at an annual percentage change (APC) of −1.98 (95% confidence interval [CI]: −2.26, −1.71) during 2012−2019. For ischemic stroke (IS), the age-standardized DALY rates doubled from 1990 to 2014, and decreased at an APC of −0.83 (95% CI: −1.33, −0.33) during 2014−2019. Intracerebral hemorrhage (ICH) showed a substantial increase in age-standardized DALY rates from 1990 to 2003, followed by declining trends, with APCs of −1.46 (95% CI: −2.74, −0.16) during 2003−2007 and −3.33 (95% CI: −3.61, −3.06) during 2011−2019, respectively. Conversely, the age-standardized DALY rates for subarachnoid hemorrhage (SAH) generally declined during 1990−2019.   Conclusion  Our results clarified the dynamic changes of the ambient PM2.5−attributable stroke burden in China during 1990−2019, highlighting the health effects of air quality improvement policies.
  • WANG Jing Yu: Methodology, Formal analysis, Visualization, Writing-original draft, Writing- review & editing. WANG Yan: Methodology, Software, Writing-original draft, Writing- review & editing. LIANG Xiao Hua: Methodology, Software, Writing-original draft, Writing- review & editing. HUANG Ke Yong: Writing- review & editing. LIU Fang Chao: Funding acquisition, Writing- review & editing. CHEN Shu Feng: Funding acquisition, Writing- review & editing. LU Xiang Feng: Funding acquisition, Writing- review & editing. LI Jian Xin: Conceptualization, Funding acquisition, Writing- review & editing.
    The authors have no competing interests to declare that are relevant to the content of this article.
    &These authors contributed equally to this work.
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Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China

doi: 10.3967/bes2024.083
Funds:  This research was supported by National Key Research and Development Program of China (2018YFE0115300, 2022YFC3600800, 2017YFC0211706), Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2021-I2M-1-010), National Natural Science Foundation of China (82073658, 82070473), National High Level Hospital Clinical Research Funding (2022-GSP-GG-1, 2022-GSP-GG-2), Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, CAMS (2019RU038), National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, CAMS (NCRC2020006).
  • Author Bio:

  • Corresponding author: Correspondence should be addressed to LI Jian Xin, E-mail: leeljx@126.com, Tel: 86-10-60866572
  • WANG Jing Yu: Methodology, Formal analysis, Visualization, Writing-original draft, Writing- review & editing. WANG Yan: Methodology, Software, Writing-original draft, Writing- review & editing. LIANG Xiao Hua: Methodology, Software, Writing-original draft, Writing- review & editing. HUANG Ke Yong: Writing- review & editing. LIU Fang Chao: Funding acquisition, Writing- review & editing. CHEN Shu Feng: Funding acquisition, Writing- review & editing. LU Xiang Feng: Funding acquisition, Writing- review & editing. LI Jian Xin: Conceptualization, Funding acquisition, Writing- review & editing.
  • The authors have no competing interests to declare that are relevant to the content of this article.
  • &These authors contributed equally to this work.

Abstract:   Objective  In recent decades, China has implemented a series of policies to address air pollution. We aimed to assess the health effects of these policies on stroke burden attributable to ambient fine particulate matter (PM2.5).  Methods  Joinpoint regression was applied to explore the temporal tendency of stroke burden based on data from the Global Burden of Disease 2019 study.  Results  The age-standardized rates of disability-adjusted life year (DALY) for stroke attributable to ambient PM2.5 in China, increased dramatically during 1990−2012, subsequently decreased at an annual percentage change (APC) of −1.98 (95% confidence interval [CI]: −2.26, −1.71) during 2012−2019. For ischemic stroke (IS), the age-standardized DALY rates doubled from 1990 to 2014, and decreased at an APC of −0.83 (95% CI: −1.33, −0.33) during 2014−2019. Intracerebral hemorrhage (ICH) showed a substantial increase in age-standardized DALY rates from 1990 to 2003, followed by declining trends, with APCs of −1.46 (95% CI: −2.74, −0.16) during 2003−2007 and −3.33 (95% CI: −3.61, −3.06) during 2011−2019, respectively. Conversely, the age-standardized DALY rates for subarachnoid hemorrhage (SAH) generally declined during 1990−2019.   Conclusion  Our results clarified the dynamic changes of the ambient PM2.5−attributable stroke burden in China during 1990−2019, highlighting the health effects of air quality improvement policies.

WANG Jing Yu: Methodology, Formal analysis, Visualization, Writing-original draft, Writing- review & editing. WANG Yan: Methodology, Software, Writing-original draft, Writing- review & editing. LIANG Xiao Hua: Methodology, Software, Writing-original draft, Writing- review & editing. HUANG Ke Yong: Writing- review & editing. LIU Fang Chao: Funding acquisition, Writing- review & editing. CHEN Shu Feng: Funding acquisition, Writing- review & editing. LU Xiang Feng: Funding acquisition, Writing- review & editing. LI Jian Xin: Conceptualization, Funding acquisition, Writing- review & editing.
The authors have no competing interests to declare that are relevant to the content of this article.
&These authors contributed equally to this work.
WANG Jing Yu, WANG Yan, LIANG Xiao Hua, HUANG Ke Yong, LIU Fang Chao, CHEN Shu Feng, LU Xiang Feng, LI Jian Xin. Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China[J]. Biomedical and Environmental Sciences. doi: 10.3967/bes2024.083
Citation: WANG Jing Yu, WANG Yan, LIANG Xiao Hua, HUANG Ke Yong, LIU Fang Chao, CHEN Shu Feng, LU Xiang Feng, LI Jian Xin. Changes on Stroke Burden Attributable to Ambient Fine Particulate Matter in China[J]. Biomedical and Environmental Sciences. doi: 10.3967/bes2024.083
    • Stroke is the third leading cause of disability-adjusted life years (DALYs), and is a major public health issue worldwide[1]. According to the Global Burden of Disease 2019 (GBD 2019) study , the incident cases, deaths and DALYs of stroke have increased sharply in the past three decades, reaching 12.2 million, 6.55 million and 143 million in 2019, respectively[2]. The burden of stroke is more pronounced in developing countries such as China[3]. A remarkable increase of stroke burden occurred in China during 1990-2019. It is estimated that 3.94 million new stroke cases, 13 million patients, 2.19 million deaths, and 45.9 million DALYs occurred in China in 2019[4-6].

      Ambient fine particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5) has been proved to be one of the leading environmental risk factors for population health in many countries[7-9], and it has presented a stronger effect on stroke compared to others pollutants, such as PM10 and NO2[10,11]. As the largest developing country, China has experienced severe air pollution in recent decades[12]. Previous studies in China have showed that a 10 μg/m3 increment in PM2.5 can lead to a 0.34% increase in hospital admission of ischemic stroke for short-term exposure[13], and a 13% higher risk of incident stroke for long-term exposure[14]. Air pollution has caused widespread concern in China, and a series of governance policies have been implemented in recent years[15]. Subsequently, the national PM2.5 concentration in China has gradually decreased since 2011[16]. Improvements in air quality can lead to significant public health benefits. Understanding the temporal patterns of the PM2.5-attributable stroke burden is essential for developing tailored strategies for stroke prevention[17]. Thus, previous studies explored the trends in stroke burden attributable to PM2.5 using the GBD 2019 study[18,19]. However, they simply focused on the general increasing trends since 1990, without a comprehensive analysis of the change patterns in different periods, especially the trends after the implementation of policies on air quality improvement in recent decades. Moreover, PM2.5 has different effects on stroke subtypes[14]. Therefore, the dynamic trends in the burden of stroke and its subtypes attributable to ambient PM2.5 in China, remain unclear. There is an urgent need to further evaluate the temporal trends for stroke and its subtypes.

      Based on the GBD 2019 study, we aimed to comprehensively elaborate on the changing patterns in the disease burden of stroke and its subtypes attributable to ambient PM2.5 at different stages across the past three decades in China.

    • We obtained age-standardized rates, percents and numbers of DALY, death, year lived with disability (YLD), and year of life lost (YLL) for stroke and its subtypes attributable to ambient PM2.5 in China during 1990-2019 from the GBD 2019 study. Age-standardized rates were computed using the 2019 Global Standard Population (Supplementary Table S1, available in www.besjournal.com)[20]. DALY indicates health loss from both non-fatal and fatal outcomes, and is calculated as the sum of YLL and YLD[4]. YLL is the loss of life due to premature death, and is computed as the number of stroke deaths multiplied by the standard remaining life expectancy at the time of death[4]. YLD is the loss of a healthy life caused by disability, and is calculated using stroke prevalence multiplied by the corresponding disability weights, representing the extent of health loss related to a particular health outcome[4]. These metrics can help policymakers better understand the disease burden caused by PM2.5, improve air quality, and further contribute to stroke prevention and control. The prevalence estimates of stroke in China were based on systematic reviews of current Chinese researches, using a Bayesian meta-regression tool[4,21]. Stroke deaths in the GBD 2019 study were estimated using the Cause of Death Ensemble modelling method based on data mainly from surveillance systems, surveys, and the Center for Disease Control and Prevention in China[4,21].

      Age group (yeas) Percent of population (%)
      < 1 2.03
      1 to 4 7.91
      5 to 9 9.57
      10 to 14 8.99
      15 to 19 8.32
      20 to 24 7.87
      25 to 29 7.63
      30 to 34 7.33
      35 to 39 6.81
      40 to 44 6.14
      45 to 49 5.51
      50 to 54 4.92
      55 to 59 4.35
      60 to 64 3.68
      65 to 69 2.99
      70 to 74 2.27
      75 to 79 1.61
      80 to 84 1.11
      85 to 89 0.62
      90 to 94 0.26
      95 plus 0.08
        Note. In GBD 2019, the age standardized rates were calculated with a global age structure called the GBD world population age standard, which had been updated in 2019. The standard was developed based on the non-weighted mean of the age-specific proportional distributions for national locations with populations greater than 5 million in 2019.

      Table S1.  2019 GBD world population age standard

    • In the GBD 2019 study, stroke was identified as a rapidly progressing clinical sign of disturbance of cerebral function lasting more than 24 h or resulting in death according to the World Health Organization clinical criteria[21]. Stroke was classified as ischemic stroke (IS), intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH). IS was defined as an episode of neurological dysfunction triggered by focal cerebral, spinal, or retinal infarction; ICH was diagnosed as a non-traumatic hemorrhagic stroke with focal accumulation of blood in the brain; SAH was identified as a non-traumatic stroke caused by bleeding into the subarachnoid space in the brain. The International Classification of Diseases codes for stroke and its subtypes are listed in Supplementary Table S2 (available in www.besjournal.com)[4].

      Stroke Category ICD-9 Codes ICD-10 Codes
      Ischemic Stroke 433-435.9, 437.0-437.1, 437.5-437.8
      G45-G46.8, I63-I63.9, I65-I66.9, I67.2-I67.3, I67.5-I67.6, I69.3
      Intracerebral Hemorrhage 430.1, 430.3-432.9, 437.2 I61-I62.9, I67.0-I67.1, I68.1-I68.2, I69.0-I69.2
      Subarachnoid Hemorrhage 430.2 I60
        Note. ICD, International Classification of Diseases.

      Table S2.  ICD codes for stroke categories

    • The exposure levels of ambient PM2.5 in the GBD 2019 study were estimated by an improved rigorous modelling approach called the Data Integration Model for Air Quality, using multiple data sources, including satellite observations of aerosols in the atmosphere, PM2.5 ground measurements, population data and chemical transport model simulations[7]. Notably, the GBD 2019 study made important changes to revise the relationship between PM2.5 and stroke, including recruiting recent Chinese studies on PM2.5, and using flexible splines to fit the risk data[7]. The ambient PM2.5-attributable disease burden of stroke and its subtypes was evaluated by comparing the distribution of exposure to ambient PM2.5 with exposure-risk estimates at each exposure level[21].

    • Joinpoint regression was used to analyze the changing patterns of the burden of ambient PM2.5-attributable stroke and its subtypes during 1990–2019. Grid search algorithm was selected to identify the optimal number and position of joinpoints, which were then verified using the Bayesian Information Criterion test. The maximum number of joinpoints in the Joinpoint regression model was set to five. The annual percentage change (APC) of each slope segment and the average annual percentage change (AAPC) from 1990 to 2019 showed the average degree of change in stroke burden over a specific period, and their 95% confidence intervals (CI) were calculated based on the t-distribution[22]. To compare the stroke burden in China with that globally, a z-test was applied[23]. All statistical tests were 2-sided and P < 0.05 was considered as statistically significant. Additionally, we calculated the contributions of YLLs and YLDs to DALYs for stroke attributable to PM2.5 in China during 1990-2019. We further described the sex- and age-specific changing patterns of PM2.5-attributable stroke burden.

      The GBD Data Tool repository (http://ghdx.healthdata.org/gbd-results-tool) was used to obtain the available stroke burden data, and all analyses were performed using Joinpoint software, version 4.9.0.1, National Cancer Institute.

    • The global ambient PM2.5-attributable age-standardized DALY rates for stroke have fluctuated slightly over the past three decades, with values of 348.06, 146.16, 174.82 and 27.08 per 100,000 in 2019 for stroke, IS, ICH and SAH, respectively (Supplementary Figure S1, available in www.besjournal.com). Notably, China had much higher rates than the global level for most years (Supplementary Tables S3-S6, available in www.besjournal.com). As shown in Figure 1A and Table 1, the age-standardized DALY rates per 100,000 for stroke in China increased dramatically from 490.54 in 1990 to 727.08 in 2012, thereafter it decreased consistently with an APC of −1.98 (95% CI: −2.26, −1.71) during 2012−2019. It is worth noting that a brief decline was observed during 2004−2007, showing an APC of −1.31 (95% CI: −3.37, 0.79). Distinct trends were observed for different stroke subtypes. The age-standardized DALY rates per 100,000 for IS climbed from 141.06 to 303.55 during 1990−2014, then persistently decreased with an APC of −0.83 (95% CI: −1.33, −0.33) during 2014−2019, demonstrating a noticeable decline in most age groups among people aged 45 years or above (Figure 2A). For ICH, the DALY rates per 100,000 increased substantially from 273.64 in 1990 to 426.36 in 2003, and presented downward trends subsequently, with APCs of −1.46 (95% CI: −2.74, −0.16) during 2003−2007 and −3.33 (95% CI: −3.61, −3.06) during 2011−2019, respectively. We observed significant decreases of DALY rates for ICH during 2003−2019 among population aged ≥40 years (Figure 2B). In contrast, the DALY rates for SAH showed a general downward trend over the past three decades, with an AAPC of −2.64 (95% CI: −2.92, −2.37). Among the stroke subtypes, ICH had the highest PM2.5-attributable age-standardized DALY rates, followed by IS. However, the gaps between ICH and IS have attenuated in recent decades. The trends in age-standardized DALY rates for stroke and its subtypes related to ambient PM2.5 in males were similar to those in females, while males had much higher rates than females (Figure 1B and Supplementary Table S7, available in www.besjournal.com).

      Figure 1.  Age-standardized Rates and Numbers of DALY for Stroke Attributable to PM2.5 in China from 1990 to 2019. (A) Age-standardized DALY rates in total population; (B) Age-standardized DALY rates in males and females, respectively; (C) Numbers of DALY in total population; (D) Numbers of DALY in males and females, respectively. DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

      Variables Age-standardized DALY Rates Numbers of DALY
      Segments Period APC (95% CI) P value Period APC (95% CI) P value
      Stroke 1 1990−1995 2.18 (1.70, 2.66) <0.001 1990−1995 5.00 (4.52, 5.47) <0.001
      2 1995−2001 3.99 (3.50, 4.48) <0.001 1995−2001 7.03 (6.54, 7.51) <0.001
      3 2001−2004 1.88 (−0.25, 4.05) 0.079 2001−2004 4.67 (2.57, 6.81) <0.001
      4 2004−2007 −1.31 (−3.37, 0.79) 0.199 2004−2007 1.69 (−0.35, 3.77) 0.097
      5 2007−2012 1.08 (0.41, 1.76) 0.004 2007−2012 4.15 (3.48, 4.81) <0.001
      6 2012−2019 −1.98 (−2.26, −1.71) <0.001 2012−2019 1.12 (0.85, 1.39) <0.001
      AAPC (95%CI) 1990−2019 0.94 (0.61, 1.27) <0.001 1990−2019 3.94 (3.61, 4.26) <0.001
      IS 1 1990−1995 3.15 (2.63, 3.67) <0.001 1990−1997 6.34 (6.09, 6.59) <0.001
      2 1995−2004 4.92 (4.66, 5.18) <0.001 1997−2000 9.30 (7.42, 11.22) <0.001
      3 2004−2007 −0.16 (−2.39, 2.12) 0.881 2000−2004 7.36 (6.43, 8.30) <0.001
      4 2007−2011 3.55 (2.39, 4.73) <0.001 2004−2007 3.31 (1.53, 5.12) 0.001
      5 2011−2014 1.58 (−0.69, 3.90) 0.158 2007−2013 6.49 (6.08, 6.91) <0.001
      6 2014−2019 −0.83 (−1.33, −0.33) 0.004 2013−2019 2.96 (2.66, 3.27) <0.001
      AAPC (95%CI) 1990−2019 2.54 (2.17, 2.91) <0.001 1990−2019 5.79 (5.50, 6.08) <0.001
      ICH 1 1990−1995 1.77 (1.18, 2.37) <0.001 1990−1995 4.49 (3.88, 5.10) <0.001
      2 1995−2003 4.99 (4.62, 5.36) <0.001 1995−2001 8.38 (7.75, 9.02) <0.001
      3 2003−2007 −1.46 (−2.74, −0.16) 0.030 2001−2004 5.77 (3.03, 8.58) <0.001
      4 2007−2011 −0.13 (−1.43, 1.18) 0.832 2004−2007 1.04 (−1.58, 3.72) 0.410
      5 2011−2019 −3.33 (−3.61, −3.06) <0.001 2007−2011 3.04 (1.70, 4.40) <0.001
      6 2011−2019 −0.48 (−0.76, −0.19) 0.003
      AAPC (95%CI) 1990-2019 0.49 (0.21, 0.77) 0.001 1990-2019 3.45 (3.02, 3.88) <0.001
      SAH 1 1990-1996 1.77 (1.42, 2.11) <0.001 1990-1996 4.63 (4.27, 4.99) <0.001
      2 1996-2000 −3.82 (−4.77, −2.86) <0.001 1996-2000 −0.81 (−1.81, 0.21) 0.109
      3 2000-2004 −13.68 (−14.54, −12.82) <0.001 2000-2004 −10.77 (−11.67, −9.86) <0.001
      4 2004-2007 −6.24 (−8.09, −4.36) <0.001 2004-2007 −3.34 (−5.29, −1.36) 0.003
      5 2007-2014 1.88 (1.54, 2.22) <0.001 2007-2014 4.56 (4.20, 4.92) <0.001
      6 2014-2019 −1.49 (−1.92, −1.05) <0.001 2014-2019 0.89 (0.43, 1.35) 0.001
      AAPC (95%CI) 1990-2019 −2.64 (−2.92, −2.37) <0.001 1990-2019 0.13 (−0.16, 0.42) 0.379
        Note. DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table 1.  The Trends in age-standardized rates and numbers of DALY for stroke attributable to Ambient PM2.5 in China during 1990−2019 using Join-Point regression.

      Figure 2.  Average Annual Percentage Change of DALY Rates for Stroke Attributable to PM2.5 in China. (A) Average annual percentage change of DALY rates for IS during 2014-2019; (B) Average annual percentage change of DALY rates for ICH during 2003-2019. DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage.

      Figure S1.  Age-standardized Rates of DALY and Mortality for Stroke Attributable to PM2.5 From 1990 to 2019 Globally. (A) Age-standardized DALY rates in total population; (B) Age-standardized mortality in total population. DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

      Year Age-standardized DALY rate for stroke (95% CI) P-value
      Global China
      1990 319.34 (219.46, 433.52) 490.54 (231.12, 832.24) 0.293
      1991 319.70 (220.57, 429.91) 496.64 (242.61, 816.42) 0.256
      1992 323.03 (224.97, 428.21) 507.67 (254.89, 815.97) 0.225
      1993 330.08 (231.51, 437.22) 521.41 (266.31, 824.00) 0.207
      1994 334.68 (235.39, 442.02) 532.17 (283.45, 840.87) 0.193
      1995 335.99 (238.71, 442.40) 547.48 (294.24, 838.56) 0.154
      1996 337.33 (238.81, 436.70) 566.04 (315.03, 849.87) 0.116
      1997 340.25 (244.15, 440.26) 584.45 (337.86, 855.05) 0.084
      1998 343.63 (249.49, 440.95) 607.10 (362.37, 873.20) 0.058
      1999 350.66 (259.30, 448.59) 634.62 (398.11, 902.02) 0.039
      2000 357.21 (261.28, 451.72) 667.22 (420.74, 925.66) 0.024
      2001 359.92 (266.75, 452.11) 684.72 (445.93, 932.95) 0.015
      2002 363.71 (268.51, 454.27) 703.40 (463.93, 940.04) 0.009
      2003 364.33 (271.87, 455.74) 713.74 (488.38, 944.41) 0.005
      2004 362.62 (268.66, 448.21) 726.17 (498.61, 937.17) 0.003
      2005 361.52 (269.28, 445.26) 720.96 (498.16, 933.87) 0.003
      2006 355.44 (268.82, 431.59) 699.78 (506.75, 871.31) <0.001
      2007 355.40 (272.48, 429.80) 696.28 (510.25, 861.19) <0.001
      2008 359.71 (279.55, 432.60) 706.65 (538.57, 857.47) <0.001
      2009 361.66 (284.53, 430.63) 718.94 (550.96, 866.33) <0.001
      2010 364.26 (288.42, 434.02) 729.51 (559.72, 866.96) <0.001
      2011 364.23 (289.53, 434.60) 731.53 (577.11, 873.19) <0.001
      2012 364.48 (292.78, 429.67) 727.08 (579.63, 859.85) <0.001
      2013 363.73 (289.29, 428.62) 721.62 (573.14, 852.03) <0.001
      2014 361.68 (292.64, 423.64) 712.49 (577.01, 840.95) <0.001
      2015 359.45 (287.64, 416.52) 698.51 (561.12, 821.39) <0.001
      2016 352.87 (284.60, 413.35) 681.39 (550.14, 799.00) <0.001
      2017 345.24 (278.75, 404.15) 659.52 (531.04, 777.30) <0.001
      2018 344.23 (280.67, 401.24) 648.46 (518.63, 768.28) <0.001
      2019 348.06 (283.29, 404.35) 647.63 (525.39, 772.78) <0.001
        Note. DALY, disability-adjusted life year; CI, confidence interval; P-value: z test.

      Table S3.  The global and Chinese age-standardized rates for stroke during 1990−2019

      Year Age-standardized DALY rate for SAH (95% CI) P-value
      Global China
      1990 36.32 (22.06, 54.88) 75.85 (31.51, 135.05) 0.154
      1991 36.58 (22.17, 55.36) 77.37 (32.95, 133.25) 0.130
      1992 36.87 (22.41, 53.42) 78.57 (34.79, 130.93) 0.106
      1993 37.43 (23.18, 53.89) 80.72 (37.77, 135.48) 0.097
      1994 37.83 (23.60, 54.65) 82.19 (38.37, 135.47) 0.088
      1995 38.14 (24.05, 54.56) 83.75 (39.21, 133.79) 0.072
      1996 37.89 (24.02, 53.39) 82.81 (40.62, 129.65) 0.060
      1997 37.53 (24.57, 51.99) 80.96 (41.61, 124.67) 0.052
      1998 37.23 (24.69, 50.59) 79.31 (41.35, 120.37) 0.047
      1999 36.88 (25.11, 50.00) 76.39 (42.06, 114.17) 0.042
      2000 35.75 (24.61, 48.10) 70.85 (39.84, 104.02) 0.044
      2001 33.80 (23.57, 44.79) 62.54 (37.35, 89.32) 0.045
      2002 31.83 (22.28, 42.14) 54.26 (34.37, 75.79) 0.056
      2003 29.85 (21.20, 39.77) 46.32 (30.05, 63.30) 0.090
      2004 28.29 (20.42, 37.24) 40.62 (26.86, 54.25) 0.133
      2005 27.44 (19.93, 35.94) 37.21 (24.92, 49.59) 0.193
      2006 26.88 (19.55, 35.25) 34.91 (24.23, 45.00) 0.227
      2007 26.71 (19.60, 34.86) 33.81 (24.07, 42.77) 0.249
      2008 26.84 (19.90, 34.74) 33.77 (25.06, 42.12) 0.230
      2009 26.86 (20.23, 34.43) 34.15 (25.67, 42.54) 0.195
      2010 27.09 (20.58, 34.52) 34.72 (26.31, 43.17) 0.172
      2011 27.34 (20.94, 34.50) 35.45 (27.14, 43.74) 0.138
      2012 27.52 (21.32, 34.61) 36.38 (27.95, 44.47) 0.101
      2013 27.77 (21.40, 34.75) 37.04 (28.23, 45.03) 0.090
      2014 27.90 (21.58, 34.66) 37.56 (29.09, 45.59) 0.072
      2015 27.92 (21.72, 34.46) 37.48 (28.25, 45.07) 0.076
      2016 27.54 (21.53, 34.10) 37.11 (27.95, 45.29) 0.080
      2017 26.94 (21.31, 32.89) 35.81 (27.16, 44.01) 0.089
      2018 26.82 (21.20, 32.78) 35.13 (26.25, 43.82) 0.122
      2019 27.08 (21.35, 32.74) 35.18 (26.18, 44.60) 0.143
        Note. DALY, disability-adjusted life year; SAH, subarachnoid hemorrhage; CI, confidence interval; P-value: z test.

      Table S6.  The global and Chinese age-standardized rates for SAH during 1990−2019

    • As shown in Supplementary Figure S2 and Supplementary Table S8 (available in www.besjournal.com), the age-standardized percents of stroke burden attributable to ambient PM2.5 increased with an AAPC of 2.86 (95%CI: 2.69, 3.03) during 1990−2019 in China, with a significant decline occurring after 2014. This phenomenon was also observed for ICH, IS and SAH. We found similar declining trends in both males and females, with males showing a greater decline than females.

      Figure S2.  Age-standardized Percents of DALY Attributable to Ambient PM2.5-related Stroke in China From 1990 to 2019 Globally. Age-standardized percents of DALY in total population; (B) Age-standardized percents of DALY in males and females, respectively. Percent, the age-standardized proportion of stroke burden attributable to ambient PM2.5 within the total stroke burden; DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

      Variables Total population Males Females
      Segments Period APC (95% CI) P value Period APC (95% CI) P value Period APC (95% CI) P value
      Stroke 1 1990−1995 3.78 (3.50, 4.06) <0.001 1990−1995 3.39 (3.15, 3.62) <0.001 1990−1995 4.13 (3.83, 4.43) <0.001
      2 1995−1999 4.89 (4.27, 5.52) <0.001 1995−1999 4.52 (3.98, 5.05) <0.001 1995−1999 5.34 (4.66, 6.02) <0.001
      3 1999−2014 3.09 (3.03, 3.15) <0.001 1999−2014 2.73 (2.68, 2.78) <0.001 1999−2014 3.43 (3.37, 3.49) <0.001
      4 2014−2017 −0.82 (−1.99, 0.37) <0.001 2014−2017 −0.83 (−1.83, 0.19) 0.104 2014−2017 −0.73 (−2.01, 0.56) 0.246
      5 2017−2019 0.50 (−0.69, 1.70) <0.001 2017−2019 0.33 (−0.69, 1.35) 0.509 2017−2019 1.01 (−0.29, 2.32) 0.120
      6
      AAPC
      (95%CI)
      1990−2019 2.86 (2.69, 3.03) <0.001 1990−2019 2.54 (2.40, 2.69) <0.001 1990−2019 3.20 (3.02, 3.39) <0.001
      IS 1 1990−1995 3.58 (3.45, 3.7) <0.001 1990−1995 3.25 (3.10, 3.39) <0.001 1990−1995 3.93 (3.77, 4.09) <0.001
      2 1995−1999 4.59 (4.31, 4.88) <0.001 1995-2000 4.02 (3.81, 4.23) <0.001 1995−1999 5.08 (4.71, 5.45) <0.001
      3 1999−2009 3.05 (3.00, 3.11) <0.001 2000−2014 2.50 (2.47, 2.53) <0.001 1999−2009 3.49 (3.42, 3.55) <0.001
      4 2009−2014 2.74 (2.56, 2.91) <0.001 2014−2017 −0.95 (−1.58, −0.32) 0.006 2009−2014 2.97 (2.74, 3.20) <0.001
      5 2014−2017 −0.79 (−1.33, −0.24) 0.008 2017−2019 0.26 (−0.37, 0.90) 0.396 2014−2017 −0.60 (−1.30, 0.10) 0.085
      6 2017−2019 0.37 (−0.18, 0.93) 0.165 2017−2019 0.78 (0.07, 1.49) 0.033
      AAPC
      (95%CI)
      1990−2019 2.71 (2.63, 2.79) <0.001 1990−2019 2.37 (2.28, 2.46) <0.001 1990−2019 3.07 (2.97, 3.18) <0.001
      ICH 1 1990−1993 3.53 (2.85, 4.22) <0.001 1990−1994 3.41 (3.03, 3.79) <0.001 1990−1993 3.90 (3.09, 4.71) <0.001
      2 1993−2000 4.62 (4.39, 4.86) <0.001 1994−2000 4.30 (4.03, 4.57) <0.001 1993−2000 5.00 (4.73, 5.28) <0.001
      3 2000−2005 2.55 (2.12, 2.98) <0.001 2000−2005 2.27 (1.89, 2.64) <0.001 2000−2005 2.88 (2.38, 3.39) <0.001
      4 2005−2009 3.75 (3.06, 4.43) <0.001 2005−2009 3.33 (2.73, 3.93) <0.001 2005−2009 4.10 (3.29, 4.92) <0.001
      5 2009−2014 2.97 (2.54, 3.40) <0.001 2009−2014 2.68 (2.30, 3.06) <0.001 2009−2014 3.15 (2.64, 3.66) <0.001
      6 2014−2019 −0.12 (−0.41, 0.18) 0.404 2014−2019 −0.20 (−0.46, 0.06) 0.125 2014−2019 0.17 (−0.18, 0.52) 0.319
      AAPC
      (95%CI)
      1990−2019 2.92 (2.76, 3.08) <0.001 1990−2019 2.63 (2.49, 2.77) <0.001 1990−2019 3.23 (3.05, 3.42) <0.001
      SAH 1 1990−1994 3.67 (3.45, 3.88) <0.001 1990−1994 3.28 (3.06, 3.50) <0.001 1990−1995 4.10 (3.90, 4.31) <0.001
      2 1994−2000 4.56 (4.41, 4.72) <0.001 1994−2000 4.01 (3.85, 4.17) <0.001 1995−1999 5.23 (4.77, 5.70) <0.001
      3 2000−2010 3.89 (3.82, 3.95) <0.001 2000−2010 3.43 (3.37, 3.50) <0.001 1999−2010 4.35 (4.28, 4.42) <0.001
      4 2010−2014 2.93 (2.59, 3.27) <0.001 2010−2014 2.71 (2.36, 3.06) <0.001 2010−2014 3.13 (2.68, 3.58) <0.001
      5 2014−2017 −0.19 (−0.84, 0.47) 0.550 2014−2017 −0.28 (−0.96, 0.40) 0.389 2014−2017 0.01 (−0.87, 0.89) 0.985
      6 2017−2019 0.98 (0.31, 1.65) 0.007 2017−2019 0.72 (0.04, 1.41) 0.040 2017−2019 1.49 (0.61, 2.39) 0.003
      AAPC
      (95%CI)
      1990−2019 3.23 (3.13, 3.33) <0.001 1990−2019 2.85 (2.75, 2.95) <0.001 1990−2019 3.60 (3.47, 3.74) <0.001
        Note. Percent, the age-standardized proportion of stroke burden attributable to ambient PM2.5 within the total stroke burden; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table S8.  The trends in age-standardized percents of DALY attributable to ambient PM2.5-related stroke in China during 1990−2019 using Join-Point regression.

    • The numbers of DALY for stroke attributable to ambient PM2.5 in China presented an upward trend over the past three decades, which increased consistently from 4.18 million in 1990 to 12.85 million in 2019, with an AAPC of 3.94 (95% CI: 3.61, 4.26) (Figure 1C and Table 1). The similar upward trend occurred in DALYs for IS, with an AAPC of 5.79 (95% CI: 5.50, 6.08). For ICH, the DALYs increased rapidly from 2.38 million in 1990 to 6.48 million in 2011, and then presented an obvious downward trend during 2011−2019, with an APC of −0.48 (95% CI: −0.76, −0.19). For SAH, DALYs fluctuated at a relatively low level over the entire period. Among the stroke subtypes, ICH dominated more than half of the stroke DALYs attributable to PM2.5 in China each year from 1990 to 2019. By contrast, contribution of IS on stroke DALYs rose dramatically from 26.89% to 44.66% during 1990−2019, while contribution of SAH declined from 16.16% to 5.49%. We found that males and females shared similar trends in DALYs for stroke and its subtypes, whereas males had much higher DALYs than females (Figure 1D and Supplementary Table S9, available in www.besjournal.com).

      Variables Males Females
      Segments Period APC (95% CI) P value Period APC (95% CI) P value
      Stroke 1 1990−1994 4.73 (3.99, 5.48) <0.001 1990−1996 5.04 (4.63, 5.45) <0.001
      2 1994−2001 6.94 (6.53, 7.34) <0.001 1996−2001 7.19 (6.41, 7.97) <0.001
      3 2001−2004 4.76 (2.44, 7.13) 0.001 2001−2004 4.57 (2.18, 7.01) 0.001
      4 2004−2007 1.83 (−0.42, 4.14) 0.104 2004−2007 1.30 (−1.01, 3.67) 0.248
      5 2007−2012 4.72 (3.98, 5.46) <0.001 2007−2011 3.55 (2.36, 4.75) <0.001
      6 2012−2019 0.78 (0.48, 1.08) <0.001 2011−2019 1.77 (1.52, 2.03) <0.001
      AAPC (95%CI) 1990−2019 3.98 (3.63, 4.34) <0.001 1990−2019 3.85 (3.46, 4.23) <0.001
      IS 1 1990−1995 6.06 (5.54, 6.59) <0.001 1990−1997 6.33 (6.03, 6.64) <0.001
      2 1995−2004 7.66 (7.40, 7.92) <0.001 1997−2000 10.08 (7.75, 12.46) <0.001
      3 2004−2007 2.88 (0.61, 5.20) 0.016 2000−2004 7.79 (6.64, 8.95) <0.001
      4 2007−2011 7.38 (6.18, 8.58) <0.001 2004−2007 3.27 (1.09, 5.51) 0.006
      5 2011−2014 5.61 (3.28, 7.99) <0.001 2007−2013 5.72 (5.22, 6.23) <0.001
      6 2014−2019 2.27 (1.76, 2.78) <0.001 2013−2019 3.52 (3.14, 3.89) <0.001
      AAPC (95%CI) 1990−2019 5.69 (5.32, 6.06) <0.001 1990−2019 5.88 (5.52, 6.24) <0.001
      ICH 1 1990−1995 4.60 (3.84, 5.36) <0.001 1990−1995 4.42 (3.85, 5.00) <0.001
      2 1995−2002 8.58 (7.99, 9.18) <0.001 1995−2003 7.75 (7.40, 8.11) <0.001
      3 2002−2012 2.90 (2.59, 3.20) <0.001 2003−2011 1.36 (1.02, 1.69) <0.001
      4 2012−2019 −0.84 (−1.27, −0.41) 0.001 2011−2017 −0.72 (−1.27, −0.18) 0.013
      5 2017−2019 2.20 (−0.29, 4.74) 0.080
      6
      AAPC (95%CI) 1990−2019 3.61 (3.38, 3.84) <0.001 1990−2019 3.23 (2.98, 3.48) <0.001
      SAH 1 1990−1996 4.97 (4.59, 5.34) <0.001 1990−1995 4.78 (4.27, 5.30) <0.001
      2 1996−2000 −0.68 (−1.72, 0.37) 0.186 1995−2000 −0.27 (−0.96, 0.43) 0.425
      3 2000−2004 −10.78 (−11.71, −9.83) <0.001 2000−2004 −10.95 (−11.93, −9.96) <0.001
      4 2004−2007 −3.18 (−5.19, −1.12) 0.006 2004−2007 −3.52 (−5.63, −1.36) 0.004
      5 2007−2014 5.07 (4.70, 5.44) <0.001 2007−2014 3.77 (3.38, 4.16) <0.001
      6 2014−2019 0.44 (−0.03, 0.92) 0.064 2014−2019 1.60 (1.10, 2.10) <0.001
      AAPC (95%CI) 1990−2019 0.27 (−0.03, 0.57) 0.075 1990−2019 −0.04 (−0.35, 0.26) 0.778
        Note. DALY, disability-adjusted life year; IS ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table S9.  The trends in numbers of DALY for stroke attributable to ambient PM2.5 for males and females in China during 1990−2019 using Join-Point regression

    • Considering that the DALY comprises YLL and YLD, we further elaborated on their trends, separately (Figure 3). The age-standardized YLL rates for stroke and its subtypes attributable to ambient PM2.5 in China were much higher than those in YLD. Age-standardized YLL rates showed similar trends to DALY regardless of stroke subtype and sex. In comparison, the age-standardized YLD rates for stroke and its subtypes showed upward trends, especially for IS, which sharply increased from 22.34 to 68.92 per 10,000 during 1990-2019. The age-standardized rates of YLD for IS ranked first across the past 30 years, which was even 5-fold and 14-fold higher than those for ICH and SAH in 2019, respectively. Additionally, we found that the age-standardized YLD rates for stroke and its subtypes were higher in females than males except for ICH, with the greatest difference observed for IS.

      Figure 3.  Age-standardized Rates of YLL and YLD for Stroke Attributable to PM2.5 in China from 1990 to 2019. (A) Age-standardized YLL rates in total population; (B) Age-standardized YLL rates in males and females, respectively; (C) Age-standardized YLD rates in total population; (D) Age-standardized YLD rates in males and females, respectively. YLL, year of life lost; YLD, year lived with disability; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

    • We further evaluated the trends in the numbers of YLL and YLD (Figure 4). The DALYs of stroke arose mostly from the YLLs every year over the entire period. Therefore, the YLLs showed trends similar to those of the DALYs. The YLDs for stroke increased dramatically from 1990 to 2019, particularly for IS, which climbed from 0.20 million to 1.38 million. Moreover, we observed that females had noticeably higher YLDs for IS than males. As for the contribution of YLL to DALY, we noticed that the proportion obviously decreased from 81.89% in 2004 to 76.01% in 2019 for IS, and from 96.09% in 1990 to 86.12% in 2019 for SAH (Supplementary Figure S3, available in www.besjournal.com).

      Figure 4.  Numbers of YLL and YLD for Stroke Attributable to PM2.5 in China from 1990 to 2019. (A) Numbers of YLL in total population; (B) Numbers of YLL in males and females, respectively; (C) Numbers of YLD in total population; (D) Numbers of YLD in males and females, respectively. YLL, year of life lost; YLD, year lived with disability; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

    • We also estimated trends in the age-standardized rates and numbers of mortality for stroke and its subtypes attributable to ambient PM2.5. We found that the mortality of stroke and its subtypes shared similar trends with DALY (Supplementary Figure S4, Supplementary Table S10 and Supplementary Table S11, available in www.besjournal.com).

      Figure S4.  Age-standardized Rates and Numbers of Death for Stroke Attributable to PM2.5 in China From 1990 to 2019. (A) Age-standardized mortality in total population; Age-standardized mortality in males and females, respectively; Numbers of death in total population; (D) Numbers of death in males and females, respectively. IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

      Variables Total population Males Females
      Segments Period APC (95% CI) P value Period APC (95% CI) P value Period APC (95% CI) P value
      Stroke 1 1990−1996 2.59 (2.17, 3.01) <0.001 1990−1994 2.23 (1.38, 3.07) <0.001 1990−1996 2.20 (1.82, 2.59) <0.001
      2 1996−2001 4.48 (3.68, 5.28) <0.001 1994−2001 4.11 (3.65, 4.57) <0.001 1996−2003 4.20 (3.81, 4.60) <0.001
      3 2001−2004 2.18 (−0.26, 4.67) 0.076 2001−2004 2.07 (−0.57, 4.77) 0.114 2003−2007 −1.35
      (−2.44, −0.24)
      0.021
      4 2004−2007 −1.66 (−4.01, 0.74) 0.158 2004−2007 −1.16 (−3.71, 1.46) 0.353 2007−2011 0.48 (−0.63, 1.61) 0.366
      5 2007−2011 1.65 (0.44, 2.89) 0.012 2007−2012 2.04 (1.20, 2.89) <0.001 2011−2017 −2.80
      (−3.28, −2.32)
      <0.001
      6 2011−2019 −2.31
      (−2.57, −2.06)
      <0.001 2012−2019 −2.73
      (−3.07, −2.39)
      <0.001 2017−2019 −0.53 (−2.72, 1.71) 0.618
      AAPC (95%CI) 1990−2019 0.92 (0.53, 1.31) <0.001 1990−2019 1.05 (0.65, 1.46) <0.001 1990−2019 0.70 (0.42, 0.98) <0.001
      IS 1 1990−1995 3.32 (2.66, 3.98) <0.001 1990−1994 3.07 (2.18, 3.96) <0.001 1990−1997 3.50 (3.12, 3.89) <0.001
      2 1995−2004 5.27 (4.94, 5.60) <0.001 1994−2004 4.71 (4.45, 4.97) <0.001 1997−2001 7.11 (5.63, 8.61) <0.001
      3 2004−2007 −0.52 (−3.33, 2.38) 0.703 2004−2007 0.02 (−2.67, 2.78) 0.989 2001−2004 4.75 (1.88, 7.71) 0.003
      4 2007−2011 3.78 (2.30, 5.27) <0.001 2007−2011 4.83 (3.41, 6.26) <0.001 2004−2007 −0.49 (−3.22, 2.32) 0.708
      5 2011−2014 0.65 (−2.20, 3.57) 0.636 2011−2014 1.84 (−0.90, 4.65) 0.172 2007−2011 2.72 (1.30, 4.16) 0.001
      6 2014−2019 −1.45
      (−2.08, −0.82)
      <0.001 2014−2019 −2.15 (−2.75, −1.56) <0.001 2011−2019 −0.85
      (−1.15, −0.55)
      <0.001
      AAPC (95%CI) 1990−2019 2.46 (2.00, 2.92) <0.001 1990−2019 2.50 (2.06, 2.94) <0.001 1990−2019 2.37 (1.90, 2.84) <0.001
      ICH 1 1990−1995 1.96 (1.09, 2.84) <0.001 1990−1995 2.03 (1.39, 2.67) <0.001 1990−1996 1.89 (1.41, 2.36) <0.001
      2 1995−2003 5.16 (4.63, 5.70) <0.001 1995−2001 5.55 (4.90, 6.22) <0.001 1996−2003 5.46 (4.97, 5.95) <0.001
      3 2003−2011 −0.87
      (−1.38, −0.36)
      0.002 2001−2004 3.08 (0.24, 6.00) 0.035 2003−2011 −1.41
      (−1.78, −1.05)
      <0.001
      4 2011−2019 −3.70
      (−4.10, −3.30)
      <0.001 2004−2007 −1.98 (−4.68, 0.80) 0.146 2011−2017 −4.51
      (−5.10, −3.92)
      <0.001
      5 2007−2011 0.80 (−0.60, 2.21) 0.241 2017−2019 −0.88 (−3.59, 1.91) 0.510
      6 2011−2019 −3.85
      (−4.14, −3.55)
      <0.001
      AAPC (95%CI) 1990−2019 0.44 (0.18, 0.70) 0.001 1990−2019 0.60 (0.16, 1.05) 0.008 1990−2019 0.26 (−0.01, 0.53) 0.059
      SAH 1 1990−1996 1.94 (1.53, 2.35) <0.001 1990−1996 2.47 (2.02, 2.91) <0.001 1990−1995 1.97 (1.39, 2.55) <0.001
      2 1996−2000 −4.47
      (−5.59, −3.33)
      <0.001 1996−2000 −4.05
      (−5.28, −2.81)
      <0.001 1995−2000 −4.23
      (−5.00, −3.45)
      <0.001
      3 2000−2004 −15.59
      (−16.58, −14.59)
      <0.001 2000−2004 −15.49
      (−16.57, −14.39)
      <0.001 2000−2004 −15.89
      (−16.95, −14.81)
      <0.001
      4 2004−2007 −7.79
      (−9.94, −5.59)
      <0.001 2004−2007 −6.93
      (−9.30, −4.51)
      <0.001 2004−2007 −8.49
      (−10.79, −6.13)
      <0.001
      5 2007−2014 1.74 (1.33, 2.15) <0.001 2007−2015 1.84 (1.49, 2.19) <0.001 2007−2014 1.10 (0.67, 1.54) <0.001
      6 2014−2019 −2.01
      (−2.53, −1.49)
      <0.001 2015−2019 −3.33
      (−4.12, −2.54)
      <0.001 2014−2019 −1.65
      (−2.20, −1.08)
      <0.001
      AAPC (95%CI) 1990−2019 −3.29
      (−3.61, −2.96)
      <0.001 1990−2019 −3.05
      (−3.40, −2.69)
      <0.001 1990−2019 −3.67
      (−4.00, −3.33)
      <0.001
        Note. IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table S10.  The trends in age-standardized mortality of stroke attributable to ambient PM2.5 in China during 1990−2019 using Join-Point regression

      Variables Total population Males Females
      Segments Period APC
      (95% CI)
      P value Period APC
      (95% CI)
      P value Period APC
      (95% CI)
      P value
      Stroke 0 1990−1996 5.46 (5.04, 5.88) <0.001 1990-1994 5.10 (4.25, 5.96) <0.001 1990−1996 5.01 (4.64, 5.38) <0.001
      1 1996−2001 7.81 (7.01, 8.61) <0.001 1994−2001 7.42 (6.95, 7.88) <0.001 1996−2003 7.57 (7.19, 7.95) <0.001
      2 2001−2004 5.52 (3.07, 8.03) <0.001 2001−2004 5.49 (2.81, 8.24) 0.001 2003−2007 1.84 (0.78, 2.90) 0.002
      3 2004−2007 1.45 (−0.91, 3.86) 0.209 2004−2007 1.79 (−0.79, 4.44) 0.160 2007−2011 3.90 (2.83, 4.99) <0.001
      4 2007−2011 5.01 (3.78, 6.25) <0.001 2007−2012 5.06 (4.21, 5.92) <0.001 2011−2017 1.14 (0.67, 1.61) <0.001
      5 2011−2019 1.39 (1.13, 1.65) <0.001 2012−2019 0.97 (0.62, 1.31) <0.001 2017−2019 3.58 (1.45, 5.77) 0.003
      AAPC (95%CI) 1990−2019 4.24 (3.85, 4.64) <0.001 1990−2019 4.32 (3.91, 4.74) <0.001 1990−2019 4.11 (3.84, 4.38) <0.001
      IS 0 1990−1996 6.51 (6.04, 6.98) <0.001 1990−1995 6.41 (5.81, 7.02) <0.001 1990−1997 6.40 (6.01, 6.79) <0.001
      1 1996−2004 8.98 (8.60, 9.36) <0.001 1995−2004 8.37 (8.08, 8.67) <0.001 1997−2001 10.92
      (9.43, 12.45)
      <0.001
      2 2004−2007 2.59 (−0.05, 5.30) 0.054 2004−2007 2.81 (0.25, 5.44) 0.034 2001−2004 8.49 (5.57, 11.48) <0.001
      3 2007−2011 7.38 (5.99, 8.79) <0.001 2007−2010 8.55 (5.84, 11.33) <0.001 2004−2007 2.75 (−0.01, 5.59) 0.051
      4 2011−2014 4.68 (1.99, 7.45) 0.002 2010−2014 5.93 (4.60, 7.28) <0.001 2007−2011 6.32 (4.89, 7.78) <0.001
      5 2014−2019 2.69 (2.09, 3.29) <0.001 2014−2019 2.18 (1.60, 2.76) <0.001 2011−2019 3.41 (3.10, 3.71) <0.001
      AAPC (95%CI) 1990−2019 6.03 (5.59, 6.47) <0.001 1990−2019 6.04 (5.62, 6.47) <0.001 1990−2019 5.99 (5.52, 6.47) <0.001
      ICH 0 1990−1995 4.77 (3.90, 5.64) <0.001 1990−1995 4.93 (4.28, 5.58) <0.001 1990−1996 4.76 (4.27, 5.25) <0.001
      1 1995−2003 8.53 (8.00, 9.07) <0.001 1995−2001 9.00 (8.33, 9.68) <0.001 1996−2003 8.86 (8.35, 9.36) <0.001
      2 2003−2011 2.45 (1.94, 2.96) <0.001 2001−2004 6.56 (3.65, 9.55) <0.001 2003−2011 1.88 (1.51, 2.26) <0.001
      3 2011−2019 −0.14
      (−0.55, 0.26)
      0.471 2004−2007 1.14 (−1.62, 3.98) 0.392 2011−2017 −0.66
      (−1.27, −0.05)
      0.036
      4 2007−2011 3.96 (2.53, 5.40) <0.001 2017−2019 2.95 (0.16, 5.83) 0.040
      5 2011−2019 −0.38
      (−0.68, −0.08)
      0.017
      AAPC (95%CI) 1990−2019 3.76 (3.50, 4.02) <0.001 1990−2019 3.89 (3.44, 4.35) <0.001 1990−2019 3.65 (3.38, 3.93) <0.001
      SAH 0 1990−1996 4.84 (4.42, 5.26) <0.001 1990−1996 5.46 (5.03, 5.89) <0.001 1990−1995 4.76 (4.16, 5.38) <0.001
      1 1996−2000 −1.30
      (−2.47, −0.13)
      0.033 1996−2000 −0.87
      (−2.06, 0.33)
      0.141 1995−2000 −1.08
      (−1.89, −0.26)
      0.014
      2 2000−2004 −12.52 (−13.55, −11.47) <0.001 2000−2004 −12.36
      (−13.41, −11.29)
      <0.001 2000−2004 −12.96
      (−14.09, −11.82)
      <0.001
      3 2004−2007 −4.62
      (−6.86, −2.33)
      0.001 2004−2007 −4.08
      (−6.37, −1.74)
      0.002 2004−2007 −5.34
      (−7.77, −2.84)
      0.001
      4 2007−2014 5.06 (4.64, 5.48) <0.001 2007−2014 5.46 (5.03, 5.89) <0.001 2007−2014 4.44 (3.98, 4.90) <0.001
      5 2014−2019 1.24 (0.71, 1.78) <0.001 2014−2019 0.81 (0.26, 1.35) 0.007 2014−2019 1.93 (1.34, 2.53) <0.001
      AAPC (95%CI) 1990−2019 −0.13
      (−0.47, 0.21)
      0.442 1990−2019 0.15 (−0.19, 0.50) 0.386 1990−2019 −0.49
      (−0.84, −0.13)
      0.007
        Note. IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table S11.  The trends in numbers of death for stroke attributable to ambient PM2.5 in China during 1990−2019 using Join-Point regression

    • Based on the GBD 2019 study, we found that China has much higher age-standardized DALY rates for stroke than the global level. A declining trend has been observed for age-standardized DALY rates of stroke in recent years, although there was a general upward trend in China from 1990 to 2019. However, we did not find a downward trend in the numbers of DALY. Among the stroke subtypes, the age-standardized DALY rates for ICH ranked first and then decreased from 2003, thereafter the numbers of DALY declined from 2011. Although the age-standardized DALY rates for IS have decreased since 2014, the downward trend in the ratio of YLL to DALY started as early as 2004. Conversely, the SAH burden showed a successive downward trend over the past three decades. We found that YLLs contributed most of the DALYs for stroke and subtypes attributable to PM2.5 throughout the study period. In addition, males had higher DALYs and YLLs for PM2.5-attributable stroke and its subtypes than females. However, females had higher YLDs for stroke, IS and SAH than males did.

      The age-standardized rates, percents and numbers of DALY for stroke attributable to PM2.5 in China all increased dramatically during 1990-2004, which could be explained by the increasing emission of ambient particulate matter due to rapid economic growth and growing energy consumption over the past decades[12,24]. Since the early 2000s, China has been actively addressing air pollution and its adverse health effects, implementing policies aimed at improving air quality and reducing the disease burden. A slight decrease in the PM2.5-attributable age-standardized rates of DALY for stroke existed during 2004-2007, especially for ICH during 2003-2007, which may be related to stricter emission standards of particulate matter for power plants in 2003 and the subsequent implementation of energy-conservation and emission-reduction policies[15]. In addition, stringent emission controls on regional air quality in preparation for the 2008 Beijing Olympic Games could partially contribute to the slight decrease in stroke burden[25]. Although no apparent decrease in PM2.5 occurred during this period, these policies might have led to changes in the chemical composition and sources of ambient PM2.5, especially the decrease in fossil fuels and industrial sources, and further influenced its pathogenic and lethal effects on stroke[16,26,27]. The influence of these policies was not strong enough to reduce the DALY rates for IS in the early stages, but it evidently decreased the proportion of YLL to DALY, implying a weakened lethal effect of PM2.5. Since 2011, China has paid more attention to PM2.5, promulgated brand-new national ambient air quality standard, issued new air quality assessment indicators, optimized the national air monitoring system, promoted the enforcement of the first National Action Plan on Air Pollution Prevention and Control, and developed the air pollution and health effects monitoring system[15,28-30]. Consequently, population-weighted mean geophysical PM2.5 concentrations in China have shown an apparent downward trend since 2011[16]. This was consistent with the markedly declining trends in the age-standardized rates and percents of DALY for stroke attributable to PM2.5 after 2012 and 2014, respectively. It also reduced the numbers of DALY for ICH considerably at the same time, which indicates the effectiveness of the policies for improving air quality in public health. Additionally, in recent years, policies focusing on desulfurization and denitrification have greatly contributed to reducing the precursors of PM2.5, playing an important role in the decline of stroke burden[31,32]. In summary, our study suggests that remarkable public health benefits can be obtained through policies that control air pollution.

      This study identified different changing patterns in the burden of stroke subtypes attributable to ambient PM2.5. The declining trend in PM2.5-related age-standardized DALY rates for ICH occurred earlier and more substantially than that for IS. This suggests that the reduction in PM2.5, with the implementation of the policies, could yield more health benefits for ICH. This may be explained by the fact that PM2.5 is more relevant to ICH than IS[33]. Additionally, it may be related to the fact that PM2.5 could trigger an increase of blood pressure which has twice the effect on ICH compared to IS, and the fatality rate of ICH is triple that of IS in China[34-37]. In contrast, the SAH burden attributed to ambient PM2.5 remained at a lower level and showed a general downtrend during 1990-2019. This may be more attributable to the substantial improvement in diagnosis and treatment, but less so for PM2.5. For example, more non-fatal non-aneurysmal SAH cases have been identified due to improvements in imaging technology, whereas case fatality has decreased because of advances in surgical and medical management[38].

      Our study also showed sex differences in the stroke burden attributable to ambient PM2.5. The PM2.5-related stroke burden was much higher in males than females, particularly the fatal stroke burden (YLL). This phenomenon may be explained by the higher probability of ambient PM2.5 exposure in males due to a higher proportion of outdoor work[39,40], and the higher prevalence of risk factors for stroke in males, including hypertension, diabetes, tobacco use, and alcohol consumption[41-44]. In addition, it may be related to the different pathophysiological functions of cerebral circulation between males and females related to sex hormones[45]. Therefore, strategies for reducing PM2.5-related stroke burden should be given more attention to males, and provide more protection in high PM2.5-pollution settings. However, it is worth noting that females had higher levels of YLD for stroke than males, particularly for IS, implying females have a greater non-fatal stroke burden. This may be explained by the protective effect of estrogen, which makes females less likely to die from stroke[45].

      This study has some limitations. First, the stroke burden attributed to ambient PM2.5 in the GBD 2019 study is not directly observed data, but estimated data generated through mathematical conversion. Therefore, caution should be exercised when interpreting these results. Second, our study is a population-based analysis of trends in stroke burden, which may be inapplicable at the individual level due to potential ecological fallacy and regression dilution bias[46,47]. Third, the stroke burden at the provincial level in China was not analyzed, because of the lack of relevant data in the GBD 2019 study. Forth, toxic chemicals bounded to PM2.5, like heavy metals and organic matters, can accumulate in blood and organs, leading to inflammation and further increasing the risk of stroke[48,49]. Moreover, other determinants, such as ambient temperature, relative humidity, and other pollutants (SO2, NO2, CO, O3 and PM10), also affect stroke[11,50]. They could confound the association between PM2.5 and stroke, which requires further research in the future.

    • Our results illustrate different changing patterns of disease burden for stroke subtypes attributable to ambient PM2.5 in China from 1990 to 2019, reflecting the health effects of the policies on improving air quality. Moreover, our results suggest that effective policies should be implemented persistently, and more attention should be paid to males.

    • Year Age-standardized DALY rate for IS (95% CI) P-value
      Global China
      1990 130.81 (93.18, 169.76) 141.06 (67.56, 238.25) 0.830
      1991 130.46 (93.63, 167.76) 144.85 (71.38, 236.53) 0.755
      1992 131.35 (95.59, 168.61) 150.06 (77.38, 241.97) 0.684
      1993 134.60 (98.62, 172.10) 155.81 (80.70, 247.05) 0.648
      1994 135.95 (99.86, 174.25) 159.58 (86.07, 249.25) 0.606
      1995 135.15 (99.11, 172.77) 164.92 (89.06, 252.42) 0.515
      1996 134.06 (99.18, 169.53) 172.47 (96.79, 256.18) 0.387
      1997 133.63 (99.50, 167.89) 179.56 (103.79, 259.74) 0.290
      1998 133.55 (99.59, 166.50) 188.20 (113.32, 270.07) 0.209
      1999 135.46 (102.41, 168.85) 199.18 (126.47, 282.61) 0.141
      2000 137.33 (104.40, 170.61) 212.59 (136.21, 294.21) 0.085
      2001 138.49 (105.46, 170.95) 222.27 (146.72, 300.86) 0.049
      2002 139.91 (107.86, 170.86) 231.20 (154.77, 310.75) 0.033
      2003 140.89 (108.34, 172.44) 241.06 (166.64, 317.02) 0.016
      2004 140.51 (108.68, 171.43) 250.83 (175.67, 321.93) 0.007
      2005 140.86 (109.24, 170.88) 254.25 (178.73, 325.10) 0.005
      2006 138.69 (109.39, 166.64) 251.04 (183.50, 312.89) 0.002
      2007 138.86 (110.21, 167.10) 253.23 (187.52, 312.23) 0.001
      2008 140.99 (113.02, 168.01) 260.86 (200.17, 315.97) <0.001
      2009 142.41 (115.10, 168.67) 270.80 (211.75, 324.26) <0.001
      2010 144.42 (117.19, 170.28) 281.51 (218.68, 334.98) <0.001
      2011 145.13 (117.15, 171.40) 289.36 (228.68, 344.84) <0.001
      2012 145.96 (118.90, 171.63) 294.30 (237.01, 347.05) <0.001
      2013 146.92 (119.21, 172.39) 300.29 (239.87, 354.34) <0.001
      2014 147.34 (120.71, 172.35) 303.55 (246.17, 356.72) <0.001
      2015 147.48 (121.36, 172.16) 303.22 (245.37, 357.34) <0.001
      2016 145.49 (118.54, 170.53) 299.56 (242.11, 352.04) <0.001
      2017 143.49 (117.64, 167.04) 294.61 (238.83, 346.71) <0.001
      2018 144.00 (117.55, 168.91) 292.40 (234.36, 345.35) <0.001
      2019 146.16 (119.78, 171.23) 294.05 (239.00, 352.73) <0.001
        Note. DALY, disability-adjusted life year; IS, ischemic stroke; CI, confidence interval; P-value: z test.

      Table S4.  The global and Chinese age-standardized rates for IS during 1990−2019.

      Year Age-standardized DALY rate for ICH (95% CI) P-value
      Global China
      1990 152.22 (98.85, 215.36) 273.64 (128.05, 466.76) 0.184
      1991 152.66 (99.61, 214.12) 274.42 (131.87, 457.77) 0.167
      1992 154.80 (102.86, 213.47) 279.04 (138.00, 455.76) 0.148
      1993 158.05 (105.33, 216.99) 284.88 (143.97, 459.21) 0.137
      1994 160.91 (108.52, 220.23) 290.39 (151.43, 460.47) 0.122
      1995 162.70 (110.23, 220.15) 298.80 (158.70, 461.82) 0.098
      1996 165.39 (112.20, 224.08) 310.76 (171.89, 467.64) 0.072
      1997 169.10 (117.42, 226.73) 323.93 (186.47, 477.62) 0.051
      1998 172.85 (120.44, 228.46) 339.59 (202.00, 496.04) 0.039
      1999 178.31 (126.20, 235.96) 359.04 (224.12, 510.30) 0.021
      2000 184.13 (130.46, 242.06) 383.78 (241.32, 538.82) 0.014
      2001 187.63 (132.76, 242.40) 399.91 (258.43, 545.74) 0.007
      2002 191.98 (136.48, 246.55) 417.95 (273.52, 566.03) 0.005
      2003 193.58 (138.97, 247.37) 426.36 (286.40, 565.95) 0.002
      2004 193.83 (139.74, 242.68) 434.72 (297.12, 566.20) 0.001
      2005 193.21 (139.72, 243.27) 429.50 (293.38, 557.42) 0.001
      2006 189.87 (141.01, 235.07) 413.83 (301.25, 521.18) <0.001
      2007 189.83 (142.51, 233.70) 409.24 (299.85, 507.05) <0.001
      2008 191.88 (147.21, 233.63) 412.02 (311.44, 502.13) <0.001
      2009 192.39 (147.41, 232.53) 413.99 (313.77, 500.19) <0.001
      2010 192.74 (149.62, 232.46) 413.28 (315.71, 493.65) <0.001
      2011 191.76 (149.46, 231.12) 406.73 (319.03, 486.22) <0.001
      2012 191.00 (151.98, 227.96) 396.40 (311.94, 471.62) <0.001
      2013 189.03 (148.80, 225.51) 384.29 (303.07, 456.72) <0.001
      2014 186.43 (148.17, 219.49) 371.38 (298.00, 441.92) <0.001
      2015 184.05 (145.45, 215.37) 357.81 (285.70, 421.04) <0.001
      2016 179.85 (142.58, 213.49) 344.72 (277.55, 408.95) <0.001
      2017 174.81 (138.17, 206.50) 329.10 (261.82, 391.35) <0.001
      2018 173.41 (140.41, 205.04) 320.93 (253.91, 381.95) <0.001
      2019 174.82 (140.07, 206.00) 318.40 (255.96, 382.95) <0.001
        Note. DALY, disability-adjusted life year; ICH, intracerebral hemorrhage; CI, confidence interval; P-value: z test.

      Table S5.  The global and Chinese age-standardized rates for ICH during 1990−2019

      Variables Males Females
      Segments Period APC (95% CI) P value Period APC (95% CI) P value
      Stroke 1 1990−1994 1.93 (1.21, 2.66) <0.001 1990−1996 2.22 (1.80, 2.64) <0.001
      2 1994−2001 3.92 (3.53, 4.32) <0.001 1996−2003 3.76 (3.33, 4.18) <0.001
      3 2001−2004 1.80 (−0.46, 4.12) 0.110 2003−2007 −1.31 (−2.50, −0.11) 0.034
      4 2004−2007 −1.16 (−3.35, 1.09) 0.283 2007−2011 0.40 (−0.81, 1.62) 0.494
      5 2007−2012 1.85 (1.13, 2.58) <0.001 2011−2019 −1.65 (−1.91, −1.39) <0.001
      6 2012−2019 −2.16 (−2.45, −1.86) <0.001
      AAPC (95%CI) 1990−2019 1.05 (0.70, 1.40) <0.001 1990−2019 0.76 (0.50, 1.02) <0.001
      IS 1 1990−1995 3.12 (2.60, 3.64) <0.001 1990−1997 3.49 (3.16, 3.81) <0.001
      2 1995−2004 4.51 (4.25, 4.77) <0.001 1997−2001 6.45 (5.20, 7.72) <0.001
      3 2004−2007 −0.12 (−2.36, 2.18) 0.914 2001−2004 4.52 (2.08, 7.02) 0.001
      4 2007−2011 4.31 (3.13, 5.50) <0.001 2004−2007 0.40 (−1.95, 2.79) 0.723
      5 2011−2014 2.12 (−0.17, 4.46) 0.067 2007−2013 2.25 (1.71, 2.79) <0.001
      6 2014−2019 −1.33 (−1.83, −0.83) <0.001 2013−2019 −0.31 (−0.71, 0.09) 0.113
      AAPC (95%CI) 1990−2019 2.48 (2.12, 2.85) <0.001 1990−2019 2.62 (2.23, 3.00) <0.001
      ICH 1 1990−1995 1.79 (1.23, 2.36) <0.001 1990−1996 1.88 (1.47, 2.30) <0.001
      2 1995−2001 5.43 (4.85, 6.02) <0.001 1996−2003 4.95 (4.52, 5.37) <0.001
      3 2001−2004 2.85 (0.33, 5.43) 0.029 2003−2011 −1.66 (−1.97, −1.34) <0.001
      4 2004−2007 −1.79 (−4.20, 0.67) 0.139 2011−2017 −4.02 (−4.53, −3.50) <0.001
      5 2007−2011 0.91 (−0.33, 2.17) 0.138 2017−2019 −0.91 (−3.27, 1.50) 0.43
      6 2011−2019 −3.25 (−3.51, −2.99) <0.001
      AAPC (95%CI) 1990−2019 0.72 (0.32, 1.12) <0.001 1990−2019 0.18 (−0.05, 0.42) 0.133
      SAH 1 1990−1996 2.16 (1.79, 2.52) <0.001 1990−1995 1.89 (1.39, 2.39) <0.001
      2 1996−2000 −3.58 (−4.60, −2.56) <0.001 1995−2000 −3.46 (−4.13, −2.79) <0.001
      3 2000−2004 −13.85 (−14.76, −12.93) <0.001 2000−2004 −13.64 (−14.58, −12.68) <0.001
      4 2004−2007 −6.03 (−8.00, −4.02) <0.001 2004−2007 −6.46 (−8.49, −4.38) <0.001
      5 2007−2014 2.43 (2.07, 2.80) <0.001 2007−2014 1.06 (0.68, 1.43) <0.001
      6 2014−2019 −1.79 (−2.25, −1.32) <0.001 2014−2019 −1.10 (−1.59, −0.62) <0.001
      AAPC (95%CI) 1990−2019 −2.46 (−2.75, −2.17) <0.001 1990−2019 −2.89 (−3.18, −2.60) <0.001
        Note. DALY, disability-adjusted life year; IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; APC, annual percent change; AAPC, average annual percent change; CI, confidence interval.

      Table S7.  The trends in age-standardized rates of DALY for stroke attributable to ambient PM2.5 for males and females in China during 1990−2019 using Join-Point regression

      Figure S3.  Contribution of YLL and YLD to DALY for Stroke Attributable to Ambient PM2.5 in China During 1990-2019. Contribution of YLL and YLD for IS; Contribution of YLL and YLD for ICH; (C) Contribution of YLL and YLD for SAH.. YLL, year of life lost; YLD, year lived with disability; DALY, disability-adjusted life year; ICH, intracerebral hemorrhage; IS, ischemic stroke.

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